**Genomic Approaches to Developing Molecular Markers Linked to Grey Leaf Spot Resistance Loci in Ryegrasses**

Wataru Takahashi

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/61966

#### **Abstract**

Ryegrass grey leaf spot (GLS), which is also called ryegrass blast, is caused by *Magna‐ porthe oryzae* (anamorph *Pyricularia oryzae*). It is a serious disease in ryegrasses including perennial ryegrass (*Lolium perenne* L.) and Italian ryegrass (*L. multiflorum* Lam.). Heavily infected young seedlings die within days, and grass stands can be seriously damaged by the disease. Thus, the development of GLS-resistant cultivars has become one of the most important objectives in ryegrass breeding. This chapter provides an overview of the cur‐ rent information regarding molecular marker development in the breeding of GLS-resist‐ ant ryegrass cultivars. It focuses on the pathology of GLS, heritability and breeding of GLS resistance, and development of molecular markers linked to a major ryegrass GLS resistance gene.

**Keywords:** Comparative genomics, Forage grasses, *Lolium*, Molecular breeding, Resist‐ ance gene

#### **1. Introduction**

Perennial ryegrass (*Lolium perenne* L.) and Italian ryegrass (*L. multiflorum* Lam.) are taxonom‐ ically related cool-season grasses and are the most cultivated species in the genus *Lolium* in temperate regions. Perennial ryegrass is mainly used as turf and for grazing, whereas Italian ryegrass is primarily grown for hay and silage.

Ryegrass grey leaf spot (GLS), also called ryegrass blast, is a major disease of perennial ryegrass in the United States [1] and Italian ryegrass in Japan [2-4]. Rice blast and ryegrass GLS are caused by a common pathogenic fungal species, *Magnaporthe oryzae* (anamorph *Pyricularia oryzae*) [5]. Severely infected young seedlings die within days, and infected ryegrass stands can cause widespread damage and losses.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Effective GLS management strategies in ryegrass turf include the use of chemical fungicides. However, the high cost of fungicide application is an important limitation for growers managing large turf areas [1]. Additionally, overreliance on fungicides may lead to the development of fungicide-resistant fungal strains [6] and adversely affect nontarget organisms [7], ultimately resulting in adverse ecological consequences. Furthermore, the bioaccumula‐ tion of fungicides in domesticated animals (e.g., cattle) and its possible effects on the safety of dairy products are potential problems associated with fungicide use. There are currently no labeled fungicides effective against GLS in the United States [8] and Japan [3]. Therefore, there are a limited number of disease management options.

In this context, cultural management practices such as minimizing drought stress, reducing leaf wetness, avoiding excessive applications of nitrogen, and soil compaction may help to reduce disease severity [9]. However, these practices often do not work efficiently because the disease develops rapidly in susceptible ryegrass cultivars [1]. Thus, integrated management including the use of GLS-resistant cultivars is necessary to establish productive ryegrass cultural systems.

This chapter focuses on ryegrass breeding for the development of GLS-resistant cultivars. The main topics covered herein include pathology of ryegrass GLS, diversity and conventional breeding of GLS-resistant ryegrasses, and development of molecular markers linked to GLS resistance loci.

#### **2. Pathology of ryegrass GLS**

#### **2.1. Taxonomy**

In 2002, the causal pathogen of GLS of grass species including ryegrasses (*Lolium* species) and rice blast was identified as a new species, *M. oryzae* (anamorph *P. oryzae*). This new species was considered distinct from *Magnaporthe grisea* (anamorph *P. grisea*), which is associated with the grass genus *Digitaria*. The distinction was based on phylogenetic analyses and laboratory mating experiments that showed the two species were not interfertile, although there were no morphological differences between them [5].

In this chapter, the term "*M. oryzae*" is used. However, it is important to note that a formal change from *M. grisea* to *M. oryzae* has not yet occurred. A proposal for changing the name based on the results of [5] is allowed under the International Code of Nomenclature for algae, fungi, and plants (Melbourne Code). A proposal will be submitted to and discussed by the Nomenclature Committee for Fungi of the International Association for Plant Taxonomy [10]. A final decision on a name change will be made during the Nomenclature Session of the International Botanical Congress in 2017 [10].

#### **2.2. Population structure and host specificity**

Analysis of genomic DNA using molecular markers is the most powerful method for deter‐ mining the population structures of the *Magnaporthe* species. Repetitive DNA elements such as transposons and retrotransposons are often used to generate probes for Southern blotting experiments during DNA fingerprinting [11-15]. This is because of the diversity in copy numbers of elements and the richness of polymorphisms around, within, or among the elements, which might be caused by base substitutions or insertions and deletions. The use of internal transcribed spacer regions between ribosomal DNAs as probes for DNA fingerprint‐ ing is also common [12, 13]. Similarly, the internal transcribed spacer regions have been sequenced for population structure analyses [14]. Table 1 lists the repetitive sequences that have been used to analyze the population structure of *Magnaporthe* species associated with grass weeds, turf grasses, and/or forage grasses in addition to major crops such as rice and wheat (*Triticum aestivum*) [11-15].

Effective GLS management strategies in ryegrass turf include the use of chemical fungicides. However, the high cost of fungicide application is an important limitation for growers managing large turf areas [1]. Additionally, overreliance on fungicides may lead to the development of fungicide-resistant fungal strains [6] and adversely affect nontarget organisms [7], ultimately resulting in adverse ecological consequences. Furthermore, the bioaccumula‐ tion of fungicides in domesticated animals (e.g., cattle) and its possible effects on the safety of dairy products are potential problems associated with fungicide use. There are currently no labeled fungicides effective against GLS in the United States [8] and Japan [3]. Therefore, there

In this context, cultural management practices such as minimizing drought stress, reducing leaf wetness, avoiding excessive applications of nitrogen, and soil compaction may help to reduce disease severity [9]. However, these practices often do not work efficiently because the disease develops rapidly in susceptible ryegrass cultivars [1]. Thus, integrated management including the use of GLS-resistant cultivars is necessary to establish productive ryegrass

This chapter focuses on ryegrass breeding for the development of GLS-resistant cultivars. The main topics covered herein include pathology of ryegrass GLS, diversity and conventional breeding of GLS-resistant ryegrasses, and development of molecular markers linked to GLS

In 2002, the causal pathogen of GLS of grass species including ryegrasses (*Lolium* species) and rice blast was identified as a new species, *M. oryzae* (anamorph *P. oryzae*). This new species was considered distinct from *Magnaporthe grisea* (anamorph *P. grisea*), which is associated with the grass genus *Digitaria*. The distinction was based on phylogenetic analyses and laboratory mating experiments that showed the two species were not interfertile, although there were no

In this chapter, the term "*M. oryzae*" is used. However, it is important to note that a formal change from *M. grisea* to *M. oryzae* has not yet occurred. A proposal for changing the name based on the results of [5] is allowed under the International Code of Nomenclature for algae, fungi, and plants (Melbourne Code). A proposal will be submitted to and discussed by the Nomenclature Committee for Fungi of the International Association for Plant Taxonomy [10]. A final decision on a name change will be made during the Nomenclature Session of the

Analysis of genomic DNA using molecular markers is the most powerful method for deter‐ mining the population structures of the *Magnaporthe* species. Repetitive DNA elements such

are a limited number of disease management options.

cultural systems.

146 Plant Genomics

resistance loci.

**2.1. Taxonomy**

**2. Pathology of ryegrass GLS**

morphological differences between them [5].

International Botanical Congress in 2017 [10].

**2.2. Population structure and host specificity**


**Table 1.** Repetitive DNA sequences for DNA fingerprinting of *Magnaporthe* species associated with grass weeds, turf grasses, and/or forage grasses

In some cases, probes derived from these repetitive DNA sequences cannot clearly distinguish between isolates from different hosts. Restriction fragment length polymorphisms (RFLPs) with single-copy probes derived from long insert-cosmid clones (35–40 kb) are appropriate for the initial comparison of poorly characterized isolates from different hosts [12]. In addition to the repetitive DNA sequences, amplified fragment length polymorphisms (AFLPs) can produce many markers and provide a higher resolution for population structure analyses even within the same *Magnaporthe* lineage [25, 26].

Population structures can be determined in dendrograms constructed by analyzing genetic distances among isolates, which are reflected by differences in the banding patterns obtained during molecular marker analyses. Dendrograms of ryegrass isolates have often revealed genetic similarities between ryegrass isolates and isolates from wheat [12-14, 25] and tall fescue (*Schedonorus arundinaceus*) [12, 25].

In artificial inoculation conditions, isolates from ryegrasses, wheat, and tall fescue can cause serious infections in all hosts. Table 2 summarizes the data from six studies on the pathoge‐ nicity of *Magnaporthe* isolates from ryegrasses, tall fescue, wheat, rice, and/or crabgrass [13-15, 25, 27, 28]. The isolates from ryegrasses are generally avirulent, but can be virulent to rice [13, 14]. Conversely, although the rice isolates are thought to be unable to cause serious infections in ryegrasses [13, 14], they are occasionally highly virulent to the plant species [27]. The wheat isolates are avirulent to rice [14, 27], although the rice isolates are virulent to wheat [13, 27]. Some isolates from crabgrass (*Digitariasanguinalis*) are virulent to tall fescue [25] and ryegrasses [25, 28], highly virulent to Italian ryegrass [25] but are avirulent to wheat [14, 25]. Additionally, isolates from perennial ryegrass, wheat, and rice can infect crabgrass, but these are generally not highly virulent to crabgrass [14]. Many isolates from tall fescue are avirulent to crabgrass [25].



a According to [5], the crabgrass isolate might be *M. grisea* and the others might be *M. oryzae*.

14]. Conversely, although the rice isolates are thought to be unable to cause serious infections in ryegrasses [13, 14], they are occasionally highly virulent to the plant species [27]. The wheat isolates are avirulent to rice [14, 27], although the rice isolates are virulent to wheat [13, 27]. Some isolates from crabgrass (*Digitariasanguinalis*) are virulent to tall fescue [25] and ryegrasses [25, 28], highly virulent to Italian ryegrass [25] but are avirulent to wheat [14, 25]. Additionally, isolates from perennial ryegrass, wheat, and rice can infect crabgrass, but these are generally not highly virulent to crabgrass [14]. Many isolates from tall fescue are avirulent to crabgrass

**Original hosta Inoculated hostb Reference**

Perennial ryegrass (PR) ++ ++ ++ - [13]

Italian ryegrass (IR) [13]

Tall fescue (TF) [13]

Wheat (W) [13]

Rice (R) - - + ++ [13]

PR IR TF W R CG

++ ++ +- +- +- [14]

++ ++ ++ [15]

++ ++ ++ ++- - [25]

++ ++ ++ - + [14]

++ ++ ++ ++- - [25] ++ ++ ++ ++ - - [27]

++ [28]

[15] [25] [27] [28]

[14]

[25] [27]

[14] [15]

[27] [28]

[15]

[28]

[25].

148 Plant Genomics

b +: virulent; ++: highly virulent; -: avirulent; +-: virulent but sometimes fails to infect; ++-: highly virulent but sometimes fails to infect.

**Table 2.** Pathogenicity and host specificity of *Magnaporthe* species during artificial inoculations

In addition to the isolates listed in Table 2, during artificial inoculations, ryegrasses are highly susceptible to isolates from weeping lovegrass (*Eragrostis curvula*) [25], and susceptible to isolates from finger millet (*Eleusine coracana*) [14], St. Augstinegrass (*Stenotaphrum secunda‐ tum*) [25, 28], Alexandergrass (*Brachiaria plantaginea*) [27], Pennsylvania smartweed (*Polygonum pensylvanicum*) [28], and soybean (*Glycine max*) [28].

The cross-infections observed during artificial inoculations suggest that "opportunistic" crossinfections may occur in nature [12]. However, population structure analyses based on molecular marker analyses have revealed that although there are genetic differences even in isolates from the same host species, the population structures are generally associated with host differences. This indicates that the host species is a major selective factor for constructing isolate populations, and cross-infections among hosts might not be detectable in nature [25]. Nevertheless, ryegrasses might be infected by tall fescue isolates because these hosts are congeneric [29-31]. Therefore, the isolates from ryegrasses and tall fescue are genetically quite similar [12] or belong to the same lineage in some cases [25]. Additionally, wheat isolates are genetically similar to the ryegrass and tall fescue isolates, and all can cause serious infections in wheat, ryegrass, and tall fescue in artificial inoculation conditions (Table 2). However, the wheat isolates are clearly genetically distinct [12, 25]. This might explain why no epidemics of wheat blast caused by the cross-infection of ryegrass isolates and *vice versa*, have been reported [12]. This may also be the case for weeping lovegrass, in which there are genetic similarities and cross-pathogenicity among hosts [25]. Therefore, isolates from wheat and/or weeping lovegrass may be progenitors of isolates of ryegrasses and tall fescue rather than being directly responsible for GLS in ryegrasses or tall fescue [12, 25].

#### **3. Diversity and conventional breeding of GLS-resistant ryegrasses**

#### **3.1. Heritability and genetic effects of GLS resistance**

To breed for GLS-resistant ryegrasses, genetic material conferring resistance to GLS must be identified. For this purpose, researchers have investigated the diversity among resistant phenotypes [32-37]. Although most commercial cultivars and experimental lines are suscep‐ tible to GLS, some resistant genotypes have been identified in cultivars and experimental lines of Italian ryegrass [32-34] and perennial ryegrass [32, 35, 36]. Perennial ryegrass might be the more GLS-resistant species as resistant phenotypes are more common than in Italian ryegrass [32]. Additionally, in Italian ryegrass, tetraploid lines were slightly more resistant than diploid lines [33]. This is also the case in perennial ryegrass.

The diversity in GLS resistance has encouraged breeders to continue to attempt to generate GLS-resistant cultivars. In outcrossing plants like ryegrasses, a phenotypic recurrent selection is often used to improve important agronomic traits mainly controlled by genes with an additive effect. The effects of recurrent selection have been observed in Italian ryegrass and GLS-resistant experimental lines have been selected [33, 34], indicating that GLS resistance can be conferred using recurrent selection and is possibly controlled by additive gene effects.

Recurrent selection has also been effective in perennial ryegrass [35, 37]. The broad-sense heritability estimates were very high at 0.92 [35] and 0.95 [37] without any interaction between cultivar and environment. These results suggest that GLS resistance is controlled by strong genetic effects [35, 37]. Further, the phenotypic means of populations composed of selected individuals were dramatically shifted toward the selected GLS resistance. Therefore, GLS resistance was thought to be controlled by a few genes and the frequency of the genes in the selected population rapidly increased during selection cycles [35, 37]. However, much of the additive gene effects cannot be obtained with only one cycle of selection. The genetic gain during the second selection cycle was higher than that of the first cycle in the GLS-resistant phenotype [37].

Narrow-sense heritability and the number of genes having additive effects in GLS resistance are among the most important considerations for breeders because the additive gene effects actually reflect the effect of selection. However, these have not been estimated by the studies mentioned above. Diallel cross analysis is a way to determine narrow-sense heritability, number of genes having additive effects, general combining ability (GCA), and specific combining ability (SCA) of parent plants [38-40]. In perennial ryegrass, diallel crosses involv‐ ing six and eight parents have been analyzed to investigate the GCA, SCA, narrow-sense heritability, and the number of genes involved in GLS resistance [36]. The GCA and SCA were highly significant and accounted for 80–86% and 7–17% of the total genotypic variance, respectively [36]. The significant SCA values suggest that dominant genes or those that interact with related genes must have been involved in the parents. The considerably higher GCA values also suggest that GLS resistance is mainly controlled by additive gene effects as previously concluded [35, 37]. The narrow-sense heritability and number of genes having additive effects were estimated to range from 0.57 to 0.76 and 2.1 to 4.4, respectively [36]. Results of the diallel cross analysis were consistent with those of the abovementioned studies [35, 37]. Thus, phenotypic recurrent selection was very effective in improving GLS resistance in ryegrasses. Because of the quantitative additive gene effects, resistant phenotypes in the selected lines would be durable although the possibility that some genes with additive effects might be more important for GLS resistance cannot be ruled out. The gene most responsible for GLS resistance may be inherited by the next generation and act as a quasi-qualitative major partial resistance gene.

#### **3.2. Available GLS-resistant ryegrass cultivars**

lovegrass may be progenitors of isolates of ryegrasses and tall fescue rather than being directly

To breed for GLS-resistant ryegrasses, genetic material conferring resistance to GLS must be identified. For this purpose, researchers have investigated the diversity among resistant phenotypes [32-37]. Although most commercial cultivars and experimental lines are suscep‐ tible to GLS, some resistant genotypes have been identified in cultivars and experimental lines of Italian ryegrass [32-34] and perennial ryegrass [32, 35, 36]. Perennial ryegrass might be the more GLS-resistant species as resistant phenotypes are more common than in Italian ryegrass [32]. Additionally, in Italian ryegrass, tetraploid lines were slightly more resistant than diploid

The diversity in GLS resistance has encouraged breeders to continue to attempt to generate GLS-resistant cultivars. In outcrossing plants like ryegrasses, a phenotypic recurrent selection is often used to improve important agronomic traits mainly controlled by genes with an additive effect. The effects of recurrent selection have been observed in Italian ryegrass and GLS-resistant experimental lines have been selected [33, 34], indicating that GLS resistance can be conferred using recurrent selection and is possibly controlled by additive gene effects.

Recurrent selection has also been effective in perennial ryegrass [35, 37]. The broad-sense heritability estimates were very high at 0.92 [35] and 0.95 [37] without any interaction between cultivar and environment. These results suggest that GLS resistance is controlled by strong genetic effects [35, 37]. Further, the phenotypic means of populations composed of selected individuals were dramatically shifted toward the selected GLS resistance. Therefore, GLS resistance was thought to be controlled by a few genes and the frequency of the genes in the selected population rapidly increased during selection cycles [35, 37]. However, much of the additive gene effects cannot be obtained with only one cycle of selection. The genetic gain during the second selection cycle was higher than that of the first cycle in the GLS-resistant

Narrow-sense heritability and the number of genes having additive effects in GLS resistance are among the most important considerations for breeders because the additive gene effects actually reflect the effect of selection. However, these have not been estimated by the studies mentioned above. Diallel cross analysis is a way to determine narrow-sense heritability, number of genes having additive effects, general combining ability (GCA), and specific combining ability (SCA) of parent plants [38-40]. In perennial ryegrass, diallel crosses involv‐ ing six and eight parents have been analyzed to investigate the GCA, SCA, narrow-sense heritability, and the number of genes involved in GLS resistance [36]. The GCA and SCA were highly significant and accounted for 80–86% and 7–17% of the total genotypic variance, respectively [36]. The significant SCA values suggest that dominant genes or those that interact

**3. Diversity and conventional breeding of GLS-resistant ryegrasses**

responsible for GLS in ryegrasses or tall fescue [12, 25].

**3.1. Heritability and genetic effects of GLS resistance**

lines [33]. This is also the case in perennial ryegrass.

phenotype [37].

150 Plant Genomics

Although almost all of the commercially available cultivars released before 2004 were very susceptible to GLS [9], many GLS-resistant perennial ryegrass cultivars are currently available in the United States [41]. In contrast, GLS-resistant Italian ryegrass cultivars are very rare, but the diploid cultivar "Sachiaoba" [2] in Japan and the tetraploid cultivar "Jumbo" [42] in the United States have been registered as GLS-resistant in 1998 and 2000, respectively. However, an article published in 2010 reported a lack of annual ryegrass cultivars resistant to *P. grisea* in the United States, which led to the belief that GLS resistance in Italian ryegrass was insufficient [8]. All of these resistant cultivars have partial resistance, and no completely resistant perennial ryegrass or Italian ryegrass cultivars have been released. Therefore, continued breeding for GLS resistance is necessary.

#### **4. Development of molecular markers linked to GLS resistance loci**

In addition to conventional breeding, researchers have used molecular breeding techniques involving molecular markers to develop disease-resistant cultivars of major crops. Developing resistance to rice blast is a major focus among plant pathologists, and many molecular markers relevant for the breeding of rice blast-resistant cultivars have been reported [43, 44]. Regarding ryegrasses, research groups in the United States and Japan have found genetic loci for GLS resistance and have identified molecular markers linked to the resistance loci in an Italian × perennial ryegrass hybrid [45-47] and Italian ryegrass [4, 48, 49].

#### **4.1. Molecular marker development for GLS resistance in an Italian × perennial ryegrass hybrid**

#### *4.1.1. Mapping population derived from Italian × perennial ryegrass hybrid parents*

A research group in the United States developed a mapping population consisting of progeny individuals derived from a cross between Italian × perennial ryegrass hybrid heterozygous parental clones MFA and MFB [45, 46]. The parental clones were obtained in separate crosses between two different grandparental clones of the perennial ryegrass cultivar "Manhattan" and two different grandparental clones of the Italian ryegrass cultivar "Floregon" (Figure 1). A second-generation mapping population [47] was then developed. The GLS-resistant MF-8 was selected from the first mapping population and crossed with the GLS-susceptible L4B-5 obtained in a cross between a clonal individual of the forage-type perennial ryegrass cultivar "Linn" and a clonal individual of the turf-type perennial ryegrass cultivar "SR4400" (Figure 1).

The grandparental clones and parents of the mapping populations could be asexually maintained and propagated. However, the grandparental clones of the Italian ryegrass cultivar "Floregon" could not be maintained because of the annuality of this species [46]. Similarly, the two mapping populations exhibited perenniality, with each individual capable of being clonally maintained and propagated to produce clonal replicates for multiple experiments [45-47].

Modified and combined from [45, 47].

**Figure 1.** Diagram of crosses for the development of mapping populations over two generations.

#### *4.1.2. Phenotyping of GLS resistance/susceptibility in an Italian × perennial ryegrass hybrid*

In two previous studies, seven perennial ryegrass isolates obtained from diseased perennial ryegrass fairways and one rice lab strain capable of infecting rice and ryegrass were used in inoculation tests of the parents and grandparents of the first-generation mapping population [45, 46]. Of these, one of the perennial ryegrass isolates, GG9 [45, 46], and the rice lab strain 6082 [46] were chosen and used for quantitative trait locus (QTL) analyses because of their high sporulation capacity in culture and high virulence [46].

between two different grandparental clones of the perennial ryegrass cultivar "Manhattan" and two different grandparental clones of the Italian ryegrass cultivar "Floregon" (Figure 1). A second-generation mapping population [47] was then developed. The GLS-resistant MF-8 was selected from the first mapping population and crossed with the GLS-susceptible L4B-5 obtained in a cross between a clonal individual of the forage-type perennial ryegrass cultivar "Linn" and a clonal individual of the turf-type perennial ryegrass cultivar "SR4400" (Figure 1).

The grandparental clones and parents of the mapping populations could be asexually maintained and propagated. However, the grandparental clones of the Italian ryegrass cultivar "Floregon" could not be maintained because of the annuality of this species [46]. Similarly, the two mapping populations exhibited perenniality, with each individual capable of being clonally maintained and propagated to produce clonal replicates for

multiple experiments [45-47].

152 Plant Genomics

Modified and combined from [45, 47].

**Figure 1.** Diagram of crosses for the development of mapping populations over two generations.

*4.1.2. Phenotyping of GLS resistance/susceptibility in an Italian × perennial ryegrass hybrid*

In two previous studies, seven perennial ryegrass isolates obtained from diseased perennial ryegrass fairways and one rice lab strain capable of infecting rice and ryegrass were used in inoculation tests of the parents and grandparents of the first-generation mapping population Because the mapping population could be asexually propagated, two inoculation experiments were independently conducted with three or four replicates in one study [45] and four inoculation experiments were completed with four replicates in another [46]. The inoculation experiments were conducted in growth chambers or mist chambers. The GLS resistance/ susceptibility phenotypes of the mapping population were scored based on the rating scale provided in Table 3. In one study, lesion numbers and proportions of resistant lesions were recorded because inoculated individuals often had both resistant and susceptible lesions [45]. In another study, the youngest leaves of each plant were used because symptoms were most severe in these leaves when mixed lesion types occurred on the same plant [46].


**Table 3.** Rating scale for grey leaf spot severity in an Italian × perennial ryegrass hybrid

Similar disease reactions and phenotypic segregation patterns were observed in the mapping population inoculated with the perennial ryegrass isolate GG9, but the results were different from those of experiments involving the rice lab strain 6082 [45, 46]. In another study, where the second-generation mapping population was developed, two perennial ryegrass isolates, including GG9, were used. Each isolate was included in two experiments involving four clonal replicates of the mapping population [47]. Similar disease reactions and phenotype segregation patterns were reported for the second-generation mapping population [47]. No symptom-free individuals were observed throughout these studies [45-47]. The results from these three independent studies indicate the existence of different factors regulating the host–pathogen interactions involving perennial ryegrass isolates and a rice lab strain. This is relevant for determining the *Magnaporthe* species population structure based on the host specificities mentioned in Section 2.2.

Similar to the studies mentioned in Section 3.1, the broad-sense heritability for GLS-resistant/ susceptible phenotypes was high in the experiments with the perennial ryegrass isolates with values of 0.895–0.932 [46] and 0.88 [47]. These results indicate that the GLS resistance of the mapping populations was mainly controlled by genetic effects.

#### *4.1.3. Detection and mapping of GLS resistance loci in an Italian × perennial ryegrass hybrid*

Phenotypic data related to GLS resistance/susceptibility have been analyzed to identify GLS resistance loci in mapping populations [45-47]. A genetic linkage map was constructed using RFLP, AFLP, simple sequence repeat (SSR), and random amplified polymorphic DNA markers [45-47]. Isozyme and morphological markers have also been used [47]. The genetic linkage map from [46] was described in detail in another study [50]. Probes for RFLP markers were derived from other well-studied crops such as barley, oat, and rice so that synteny-based comparative studies among different plant species could be conducted with the constructed map [51]. In these studies, two sets of genetic linkage maps composed of seven linkage groups (LGs) derived from both parents were constructed using a two-way pseudo-testcross mapping strategy [52].

In one study, although results were not shown in detail, QTL analysis detected two genomic regions for GLS resistance against the perennial ryegrass isolate GG9 [45]. The identified QTLs were on LG 2 (for proportions of resistant lesions) and LG 4 (for lesion numbers) [45]. The logarithm of odds (LOD) obtained by interval mapping [53] ranged from about 2.0 to 6.0, although the LOD scores were not always significant [45]. In addition to these QTL regions, some regions were noted on LGs 1, 3, and 5, but these were not consistently detected [45].

Isolate GG9 and rice lab strain 6082 were used to inoculate the same population used in [46]. Significant QTLs were detected on LGs 3 and 6 and LGs 2 and 4 for GG9 and 6082, respectively, indicating that GLS resistance against the different isolates was controlled by different genetic effects [46]. Percentages of phenotypic variance explained by the QTLs at the highest LOD scores were 20.1–37.9% for LG 3 and 9.2–10.7% for LG 6 for resistance against GG9, and 8.9– 10.0% for LG 2, and 9.9% for LG 4 for resistance against 6082 [46]. The QTL differences between the two isolates were expected because the disease reaction and phenotype segregation of the mapping population were different between the isolates [46] (see Section 4.1.2). Nevertheless, significant QTLs were detected on LGs 2 and 4 for GLS resistance against GG9 and 6082 [45, 46]. However, the QTL relationships between the two studies cannot be confirmed by their location on genetic linkage maps because no marker information linked to the QTLs was provided in [45]. Additionally, the locations of the QTLs for GLS resistance against GG9 differed between the two studies even though the same mapping population was used. This inconsistency was not explained [46], but differences in the phenotype segregation of the mapping population during the GG9 inoculation experiments may have been a factor. That is, in one study, the phenotypic distribution of the mapping population seemed skewed toward resistance in the first experiment, but there was a trend toward susceptibility in the second experiment [45]. In the other study, the patterns of phenotype segregation in the mapping population were consistent and showed a trend toward susceptibility over three experiments [46]. These differences in the same mapping population may have been caused by unknown environmental factors that affected the expression of certain genes in the plant hosts and/or pathogens. Irrespective of the high broad-sense heritability, the values for the phenotypic variance explained by the QTLs are considered quite low, indicating there might be undetected genetic factors with minor effects on GLS resistance/susceptibility [46].

Although the QTLs for GLS resistance may be unstable and sometimes adversely influenced by environmental factors, the most significant QTL detected on LG 3 [46] might be detectable in the second generation mapping population developed in [47] (Figure 1). The percentage of phenotypic variance explained by the QTL on LG 3 at the highest LOD scores was 9.3–10.8%. Although this is lower than the values reported in [46], it suggests that the QTL is functional in a population with a different genetic background, which is promising for breeding programs focused on developing GLS-resistant ryegrass. However, the nearest RFLP marker (CDO460) closely linked to the major QTL on LG 3 [46] was not mapped in [47]. Therefore, it is necessary to confirm whether the QTL detected in [47] really corresponds to the QTL detected in [46].

#### **4.2. Molecular marker development for GLS resistance in Italian ryegrass**

#### *4.2.1. Mapping population derived from a single cross in Italian ryegrass*

values of 0.895–0.932 [46] and 0.88 [47]. These results indicate that the GLS resistance of the

Phenotypic data related to GLS resistance/susceptibility have been analyzed to identify GLS resistance loci in mapping populations [45-47]. A genetic linkage map was constructed using RFLP, AFLP, simple sequence repeat (SSR), and random amplified polymorphic DNA markers [45-47]. Isozyme and morphological markers have also been used [47]. The genetic linkage map from [46] was described in detail in another study [50]. Probes for RFLP markers were derived from other well-studied crops such as barley, oat, and rice so that synteny-based comparative studies among different plant species could be conducted with the constructed map [51]. In these studies, two sets of genetic linkage maps composed of seven linkage groups (LGs) derived from both parents were constructed using a two-way pseudo-testcross mapping

In one study, although results were not shown in detail, QTL analysis detected two genomic regions for GLS resistance against the perennial ryegrass isolate GG9 [45]. The identified QTLs were on LG 2 (for proportions of resistant lesions) and LG 4 (for lesion numbers) [45]. The logarithm of odds (LOD) obtained by interval mapping [53] ranged from about 2.0 to 6.0, although the LOD scores were not always significant [45]. In addition to these QTL regions, some regions were noted on LGs 1, 3, and 5, but these were not consistently detected [45].

Isolate GG9 and rice lab strain 6082 were used to inoculate the same population used in [46]. Significant QTLs were detected on LGs 3 and 6 and LGs 2 and 4 for GG9 and 6082, respectively, indicating that GLS resistance against the different isolates was controlled by different genetic effects [46]. Percentages of phenotypic variance explained by the QTLs at the highest LOD scores were 20.1–37.9% for LG 3 and 9.2–10.7% for LG 6 for resistance against GG9, and 8.9– 10.0% for LG 2, and 9.9% for LG 4 for resistance against 6082 [46]. The QTL differences between the two isolates were expected because the disease reaction and phenotype segregation of the mapping population were different between the isolates [46] (see Section 4.1.2). Nevertheless, significant QTLs were detected on LGs 2 and 4 for GLS resistance against GG9 and 6082 [45, 46]. However, the QTL relationships between the two studies cannot be confirmed by their location on genetic linkage maps because no marker information linked to the QTLs was provided in [45]. Additionally, the locations of the QTLs for GLS resistance against GG9 differed between the two studies even though the same mapping population was used. This inconsistency was not explained [46], but differences in the phenotype segregation of the mapping population during the GG9 inoculation experiments may have been a factor. That is, in one study, the phenotypic distribution of the mapping population seemed skewed toward resistance in the first experiment, but there was a trend toward susceptibility in the second experiment [45]. In the other study, the patterns of phenotype segregation in the mapping population were consistent and showed a trend toward susceptibility over three experiments [46]. These differences in the same mapping population may have been caused by unknown environmental factors that affected the expression of certain genes in the plant hosts and/or pathogens. Irrespective of the high broad-sense heritability, the values for the phenotypic

*4.1.3. Detection and mapping of GLS resistance loci in an Italian × perennial ryegrass hybrid*

mapping populations was mainly controlled by genetic effects.

strategy [52].

154 Plant Genomics

Marker development studies involving Italian ryegrass have been completed with F1 mapping populations obtained from a single cross between resistant and susceptible genotypes [4, 49]. Annuality is a more common characteristic among grass species than the perenniality of the previously mentioned Italian × perennial ryegrass hybrid (see Section 4.1). Therefore, it might be difficult to maintain and asexually propagate the Italian ryegrass population to produce clonal replicates like those used in the studies of hybrid populations [45-47]. Regardless, GLSresistant genotypes, which can involve a resistant parent of the mapping population, are very rare because most Italian ryegrass commercial cultivars are susceptible to GLS, similar to perennial ryegrass. Thus, it would be ideal if the resistant genotypes could at least be main‐ tained. An *in vitro* preservation method [54] can be used to maintain and clonally propagate rare genotypes [55].

#### *4.2.2. Detection of a GLS resistance locus by bulked segregant analysis in Italian ryegrass*

A major genetic locus in Italian ryegrass for crown rust resistance has been detected using bulked segregant analysis (BSA) [56], and AFLP markers tightly linked to the locus have been developed [57]. Researchers have attempted to detect a GLS resistance locus in Italian ryegrass [4]. An F1 mapping population was generated from a single cross between a resistant individual from cultivar "Sachiaoba" [2] as the female parent and a susceptible individual from cultivar "Minamiaoba" as the male parent. The rating scale used for phenotyping the F1 mapping population is provided in Table 4.

The inoculation test used during phenotyping was completed only once because of the annuality of the plant material. Nevertheless, disease severity in the mapping population segregated in a 1:1 ratio (resistant:susceptible) [4]. This result suggests that resistance is controlled by one genetic locus. Therefore, the resistance locus was considered a suitable target detectable by BSA. As predicted, AFLP markers specific for resistant phenotypes were screened by BSA, and a single genetic linkage map composed of 25 of the screened AFLP


**Table 4.** Rating scale for grey leaf spot severity in Italian ryegrass

markers was constructed [4]. Additionally, the cleaved amplified polymorphic sequence (CAPS) markers derived from Italian ryegrass expressed sequence tags (ESTs) [58] were mapped. The LG associated with the constructed map could be identified because the CAPS markers had already been assigned to seven Italian ryegrass LGs [59]. As a result, the p56 CAPS marker located on LG 5 was mapped, indicating that the resistance locus was on LG 5. Additionally, a significant QTL was detected by interval mapping. The gene at the identified resistance locus was designated *LmPi1* [4]. Although the results of the QTL analysis, including LOD score and phenotypic variance, were not described in the study, the raw data were analyzed for this chapter. The highest LOD score obtained by interval mapping was 7.36, and the percentage of the phenotypic variance explained by the QTL at the highest LOD score was 19.0%. Although broad-sense heritability of the resistance is unknown, the percentage of the phenotypic variance was unexpectedly low because the strong effect of a major gene was expected based on phenotype segregation data. Similar to the results of the Italian × perennial ryegrass hybrid, the low proportion of the phenotypic variance indicates there might be undetected genetic factors in other genomic regions that have a minor effect on GLS resistance/ susceptibility (see Section 4.1.3).

#### *4.2.3. Targeted mapping of rice ESTs to the LmPi1 locus*

The sequenced rice genome [60] and expanded EST datasets in various plant species enable comparative genomics studies of model and nonmodel plants, in which collinearity of molecular markers and genes in syntenic regions can be elucidated. Based on syntenic regions, high-resolution mapping of genetic loci associated with agronomic traits is possible. This is true even for nonmodel crops where EST-derived markers can be used to map landmarks and demonstrate synteny among different species [61-63]. Conserved intron-scanning primers (CISPs) can be easily developed and used to study nonmodel species [64]. For CISP develop‐ ment, polymerase chain reaction (PCR) primers are designed within relatively conserved exons nearby boundaries between an exon and a variation-rich intron. Target segments are generated by PCR where the introns are scanned during the extension step. Polymorphisms in the PCR products are detected as variations in the introns including base substitutions or insertions and deletions.

Synteny among ryegrasses, rice, and other grasses such as oat and Triticeae species has been revealed. Ryegrass LG 5, where the previously mentioned *LmPi1* is located, has been shown to be syntenic to rice chromosome (Chr) 9 [51, 65]. Thus, to enhance the single genetic linkage map of *LmPi1*, targeted mapping of rice ESTs to the *LmPi1* locus has been attempted using the F1 mapping population DNA used to detect the *LmPi1* locus [48]. The CISPs were designed by aligning the rice genome sequence and ESTs on rice Chr 9. Polymorphic PCR products were detected by single-strand conformation polymorphism analysis [48]. Consequently, a single genetic linkage map spanning 66.3 cM composed of 17 CISP markers and the p56 marker tightly linked to *LmPi1* (see Section 4.2.2) was constructed. There was significant collinearity of marker orders between rice Chr 9 and the newly constructed map corresponding to ryegrass LG 5 [48].

Recently, the primer design method involving CISPs has been improved for temperate forage grasses including ryegrasses [66]. Primers were called Conserved Three-prime-End Region (COTER) primers. They were developed from EST sequences of tall fescue and wheat, and eight bases at the 3′ end of each primer were identical to rice orthologues, which provided high transferability in six temperate grasses [66]. The COTER primers have been used for targeted mapping of a locus for brittleness to a single genetic linkage map in a mutant Italian ryegrass line (unpublished data), thereby providing further evidence of the high transferability of these primers.

#### *4.2.4. Detection of a novel major locus for GLS resistance in Italian ryegrass*

markers was constructed [4]. Additionally, the cleaved amplified polymorphic sequence (CAPS) markers derived from Italian ryegrass expressed sequence tags (ESTs) [58] were mapped. The LG associated with the constructed map could be identified because the CAPS markers had already been assigned to seven Italian ryegrass LGs [59]. As a result, the p56 CAPS marker located on LG 5 was mapped, indicating that the resistance locus was on LG 5. Additionally, a significant QTL was detected by interval mapping. The gene at the identified resistance locus was designated *LmPi1* [4]. Although the results of the QTL analysis, including LOD score and phenotypic variance, were not described in the study, the raw data were analyzed for this chapter. The highest LOD score obtained by interval mapping was 7.36, and the percentage of the phenotypic variance explained by the QTL at the highest LOD score was 19.0%. Although broad-sense heritability of the resistance is unknown, the percentage of the phenotypic variance was unexpectedly low because the strong effect of a major gene was expected based on phenotype segregation data. Similar to the results of the Italian × perennial ryegrass hybrid, the low proportion of the phenotypic variance indicates there might be undetected genetic factors in other genomic regions that have a minor effect on GLS resistance/

1 Plants with brown spotted or brown spindle-shaped leaf lesions

The sequenced rice genome [60] and expanded EST datasets in various plant species enable comparative genomics studies of model and nonmodel plants, in which collinearity of molecular markers and genes in syntenic regions can be elucidated. Based on syntenic regions, high-resolution mapping of genetic loci associated with agronomic traits is possible. This is true even for nonmodel crops where EST-derived markers can be used to map landmarks and demonstrate synteny among different species [61-63]. Conserved intron-scanning primers (CISPs) can be easily developed and used to study nonmodel species [64]. For CISP develop‐ ment, polymerase chain reaction (PCR) primers are designed within relatively conserved exons nearby boundaries between an exon and a variation-rich intron. Target segments are generated by PCR where the introns are scanned during the extension step. Polymorphisms in the PCR products are detected as variations in the introns including base substitutions or

susceptibility (see Section 4.1.3).

**Phenotype Score Symptoms**

From [4]

156 Plant Genomics

Resistant 0 Plants with no leaf symptoms

**Table 4.** Rating scale for grey leaf spot severity in Italian ryegrass

Susceptible 2 Plants with a few white or grey leaf lesions

3 Plants with leaves covered in lesions

insertions and deletions.

*4.2.3. Targeted mapping of rice ESTs to the LmPi1 locus*

There has been an attempt to identify a resistance locus using a similar approach to that used to identify *LmPi1* [49]. An F1 mapping population was generated from a single cross between a resistant individual from the commercial cultivar "Surrey" [67] as the female parent and a susceptible individual from the cultivar "Minamiaoba" as the male parent. As described in Section 3.2, the tetraploid cultivar "Jumbo" [42] has been registered as a GLS-resistant cultivar in the United States. The cultivar was developed by doubling the chromosomes of the diploid "Surrey." Thus, it was reasonable to expect that resistance genotypes existed in "Surrey." However, different genetic factors were expected from the resistant parent because the source material was different from that used in the study of *LmPi1*, which explains why "Surrey" was chosen as the resistant female parent.

#### *4.2.4.1. Artificial inoculation method using detached leaves*

A high heritability of target traits enables very precise QTL analyses. However, the severity of GLS symptoms in ryegrasses is influenced by environmental factors such as temperature and humidity [1, 68, 69]. Fluctuations in these factors may prevent accurate phenotyping of GLS resistance/susceptibility of the mapping population, thereby decreasing the heritability of the disease reaction. Accordingly, phenotyping in stable environmental conditions may lead to increased heritability. Additionally, repeated phenotyping in stable environmental conditions can further moderate environmental effects and increase the accuracy of the phenotype evaluation.

Multiple phenotypic evaluations of the Italian ryegrass F1 mapping population infected with GLS has not been conducted because of the annuality of Italian ryegrass and the fact that GLS is highly lethal to infected plants. Thus, a novel inoculation method, the filter-paper method, has been employed for the phenotypic evaluation of F1 mapping populations [70]. This method can overcome the difficulties of working with Italian ryegrass because it only requires detached leaves from young seedlings. The rating scale for this method is provided in Figure 2. The scale is similar to those of other studies [45, 46] (Table 3) but differs because the score is based on lesion type and not size. More recently, the filter-paper method has been shown to be applicable to the evaluation of resistance to rice blast [71].

**Figure 2.** Rating scale for grey leaf spot severity used in the filter-paper method.

#### *4.2.4.2. Detection of the LmPi2 locus*

Based on the filter-paper method, GLS severity was evaluated twice in young, expanding leaves and fully expanded leaves under controlled inoculation conditions [49]. A signifi‐ cant correlation was observed for all GLS severity scores at different leaf ages, but higher correlation coefficients were found between results from the same leaf stage. Additional‐ ly, results of repeated-measures analysis of variance (ANOVA) indicated there were significant differences in GLS severity scores among genotypes for all inoculations, whereas the differences were not significant for inoculated leaves of the same age. This indicated that the results of the filter-paper method were highly reproducible [49]. Because of this method, high broad-sense heritability was determined from the results of the repeatedmeasures ANOVA, with values of 0.701, 0.779, and 0.665 for young leaves, expanded leaves, and all inoculations, respectively [49].

The ratios for phenotype segregation of the mapping population were 1:1 for young leaves and 3:1 for expanded leaves. Therefore, it was concluded that one or two genes controlled GLS resistance in the mapping population [49]. These results and the high broad-sense heritability mentioned earlier encouraged the use of BSA to identify the most important genes. Preliminary analysis with AFLP markers demonstrated that two markers specific to the resistant parent and resistant bulk were genetically linked. Thus, the two markers along with SSR markers from a reference map of Italian ryegrass [72] were further analyzed. Because the two SSR markers were located on LG 3 in the reference map, the resistance locus was predicted to be located on LG 3. A single genetic linkage map was constructed with the AFLP and SSR markers. Further, ESTs from rice Chr 1 were converted to CISP markers because LG 3 was syntenic to rice Chr 1. Grass anchor RFLP probes located on LG 3 [51, 65] were also converted to CISP markers. The enhanced single genetic linkage map covering 133.6 cM showed significant collinearity with rice Chr 1 in their marker orders [49]. A significant QTL was also detected by interval mapping. The highest LOD scores from interval mapping were 13.8, 15.2, and 17.9 for young leaves, expanded leaves, and total data from four inoculation experiments, respectively [49]. Percentages of phenotypic variance explained by the QTL at the highest LOD scores were 61.0, 68.1, and 69.5% for young leaves, expanded leaves, and total data from four inoculation experiments, respectively [49]. The most important point of this study was that, unlike for *LmPi1*, the broad-sense heritability score (0.665) and percentage of phenotypic variance explained by the QTL at the highest LOD score (69.5%) were very similar. In other words, although only a single genetic linkage map of LG 3 was constructed, most of the genetic factors for the GLS resistance phenotype in the mapping population can be explained by the functions of a single gene.

The detected locus is clearly distinguishable from *LmPi1* because it is located on a different LG. Conversely, the QTL detected in [46] with the highest percentages of phenotypic variance explained was located on the same LG as the detected locus. The two resistance loci could not be distinguished because there was no common marker around the locus that could be used as a landmark. However, there were markers close to both loci on LG 3 of the Italian ryegrass reference genetic linkage map [72]. The genetic distance between the two loci was estimated to be over 25 cM, suggesting the detected locus is probably not the QTL detected in [46]. The detected locus was designated *LmPi2* [49], which is the second identified GLS resistance locus in Italian ryegrass.

#### **5. Conclusion**

Multiple phenotypic evaluations of the Italian ryegrass F1 mapping population infected with GLS has not been conducted because of the annuality of Italian ryegrass and the fact that GLS is highly lethal to infected plants. Thus, a novel inoculation method, the filter-paper method, has been employed for the phenotypic evaluation of F1 mapping populations [70]. This method can overcome the difficulties of working with Italian ryegrass because it only requires detached leaves from young seedlings. The rating scale for this method is provided in Figure 2. The scale is similar to those of other studies [45, 46] (Table 3) but differs because the score is based on lesion type and not size. More recently, the filter-paper method has been shown to be applicable

to the evaluation of resistance to rice blast [71].

**Figure 2.** Rating scale for grey leaf spot severity used in the filter-paper method.

Based on the filter-paper method, GLS severity was evaluated twice in young, expanding leaves and fully expanded leaves under controlled inoculation conditions [49]. A signifi‐ cant correlation was observed for all GLS severity scores at different leaf ages, but higher correlation coefficients were found between results from the same leaf stage. Additional‐ ly, results of repeated-measures analysis of variance (ANOVA) indicated there were significant differences in GLS severity scores among genotypes for all inoculations, whereas the differences were not significant for inoculated leaves of the same age. This indicated that the results of the filter-paper method were highly reproducible [49]. Because of this method, high broad-sense heritability was determined from the results of the repeatedmeasures ANOVA, with values of 0.701, 0.779, and 0.665 for young leaves, expanded leaves,

Modified from [70]

158 Plant Genomics

*4.2.4.2. Detection of the LmPi2 locus*

and all inoculations, respectively [49].

This chapter summarized the advances that have been made in the molecular breeding of GLS resistance in ryegrasses. Rice blast and GLS are caused by *M. oryzae*, but rice blast has been studied more extensively because of the importance of this staple food crop. Nevertheless, there are still incidences of rice blast leading to considerable yield losses, and numerous issues regarding this disease require further research. The breeding history of rice-blast-resistant cultivars is a major consideration during breeding of GLS-resistant ryegrasses. The breakdown of resistance regulated by a few genes is one of the most important factors related to the development of rice-blast-resistant cultivars [44]. Similar concerns would apply to the breeding of GLS-resistant ryegrass cultivars if a small number of genes mediated the resistance. Although some genomic regions associated with GLS resistance have been identified, further studies are required in ryegrasses because our knowledge of GLS resistance is more limited than our understanding of rice blast resistance. To establish highly productive cultural system for ryegrasses, synchronized approaches between cultural disease management practices and breeding for GLS resistance, promoted by advances in plant genomics, are necessary.

#### **Acknowledgements**

I thank Dr. T. Tsukiboshi (NARO Institute of Livestock and Grassland Science) for providing meaningful comments on an early draft of this chapter. This work was supported by the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (C) (23580027, 26450026).

#### **Author details**

Wataru Takahashi\*

Address all correspondence to: twataru@affrc.go.jp

Division of Forage Crop Research, Institute of Livestock and Grassland Science, NARO, Tochigi, Japan

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I thank Dr. T. Tsukiboshi (NARO Institute of Livestock and Grassland Science) for providing meaningful comments on an early draft of this chapter. This work was supported by the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (C) (23580027,

Division of Forage Crop Research, Institute of Livestock and Grassland Science, NARO,

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### **Advances in Plant Tolerance to Abiotic Stresses**

#### Geoffrey Onaga and Kerstin Wydra

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64350

#### **Abstract**

During the last 50 years, it has been shown that abiotic stresses influence plant growth and crop production greatly, and crop yields have evidently stagnated or decreased in economically important crops, where only high inputs assure high yields. The recent manifesting effects of climate change are considered to have aggravated the negative ef‐ fects of abiotic stresses on plant productivity. On the other hand, the complexity of plant mechanisms controlling important traits and the limited availability of germplasm for tol‐ erance to certain stresses have restricted genetic advances in major crops for increased yields or for improved other traits. However, some level of success has been achieved in understanding crop tolerance to abiotic stresses; for instance, identification of abscisic acid (ABA) receptors (e.g., ABA-responsive element (ABRE) binding protein/ABRE bind‐ ing factor (AREB/ABF) transcription factors), and other regulons (e.g., *WRKYs*, *MYB/ MYCs*, *NACs*, *HSFs*, *bZIPs* and nuclear factor-Y (NF-Y)), has shown potential promise to improve plant tolerance to abiotic stresses. Apart from these major regulons, studies on the post-transcriptional regulation of stress-responsive genes have provided additional opportunities for addressing the molecular basis of cellular stress responses in plants. This chapter focuses on the progress in the study of plant tolerance to abiotic stresses, and describes the major tolerance pathways and implicated signaling factors that have been identified, so far. To link basic and applied research, genes and proteins that play functional roles in mitigating abiotic stress damage are summarized and discussed.

**Keywords:** abiotic stress, climate change, crop improvement, transcription, regulatory proteins

#### **1. Introduction**

Abiotic stress is defined as the negative impact of non-living factors on living organisms in a specific environment. Abiotic stresses, such as drought, salinity, low or high temperatures and other environmental extremes are the major cause of poor plant growth and reduced crop yields in the world [1]. Drought alone affects 45% of the world's agricultural land, whereas

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

19.5% of irrigated agricultural lands are considered saline [2, 3]. Moreover, 16% of the agricultural rice land of the world suffers from flash flooding [4]. A combination of two or more abiotic stresses, e.g., drought and heat stress also occurs in field situations and causes more severe crop yield reductions than a single stress [5]. With increasing challenges posed by climate change, it is predicted that warming, drought, floods and storm events will become even more frequent and severe, and will further reduce crop yields, especially in the tropics and subtropics.

Abiotic stresses commonly induce overproduction of reactive oxygen species (ROS) causing extensive cellular damage and inhibition of physiological processes in plants. Although antioxidative mechanisms would be an immediate endogenic choice of the plants to counter ROS production, this mechanism can be impaired by abiotic stresses causing a rise in ROS intra‐ cellular concentration and an increase in the damage. To survive under such conditions, plants have evolved intricate mechanisms, allowing optimal responses that enable adaptation or avoidance of the stress. These plant responses are regulated at all levels of organization. At the cellular level, responses include adjustments of the membrane system, modifications of cell wall architecture, changes in cell cycle and cell division, and synthesis of specific endog‐ enous and low-molecular-weight molecules, such as salicylic acid, jasmonic acid, ethylene and abscisic acid [6]. An overview of changes that may occur under different abiotic stress conditions is presented in Figure 1.

At the genomic level, plant responses include the expression of stress-inducible genes involved in direct plant protection against stresses [3, 7, 8]. A broad range of abiotic stress induced genes are divided into two functional categories: and regulatory proteins. The first group consists of genes encoding for membrane proteins, enzymes for osmolyte biosynthesis, detoxification (glutathione S-transferases, superoxide dismutases, dehydrins, dehydroascorbate reductases, quinine reductases and ascorbate peroxidases) and proteins for macromolecular protection (such as LEA protein, anti-freezing proteins, chaperons and mRNA binding protein) [2]. The second group comprises genes encoding for transcription factors (e.g., *DREBPs*), protein kinases (e.g., *SRK2E*), receptor protein kinases, ribosomal-protein kinases and signal trans‐ duction proteinases (such as phosphoesterases and phospholipase C). Alterations in the phenylpropanoid pathway in which lignin biosynthesis intermediates are produced also occur under abiotic stress conditions. Moreover, increased accumulation of wall-linked phenolic compounds, for instance, in maize root elongation zone and the polyphenol content in cotton have been linked to stress response [9]. The same authors have shown the role of flavonoids, isoflavonoids, terpenoid and nitrogen-containing secondary metabolites such as glucosino‐ lates alkaloids in abiotic stress response.

variation exhibited by most crops due to domestication bottlenecks. The recent reports that the cultivated gene pool of major cereal crops, e.g., rice, maize and wheat, has reduced in genetic variation compared to wild relatives [10–12], raises concern, and could probably undermine the current efforts to identify genetic sources of resistance within the cultivated genepools. It is important, therefore, to consider exploring alternative sources of resistance by incorporating modern techniques into traditional breeding strategies to develop stress-

meostasis and in the destruction of functional and structural proteins and membranes, leading to cell death.

**Figure 1.** Abiotic stress response in plants. Primary stresses, including drought, salinity, cold, heat, and submergence, are often interconnected and cause cellular damage and secondary stresses, such as osmotic and oxidative stresses. The initial stress signals (e.g., osmotic and ionic effects or membrane fluidity changes) are perceived by membrane recep‐ tors that transmit the signals downstream to trigger transcription, which is regulated by hormones, transcription factor binding proteins (TFBPs), miRNAs, and transcription factors (TFs) to precisely activate stress responsive mechanisms to re-establish homeostasis and protect and repair damaged proteins and membranes. Inadequate response at one or several steps in the signaling and gene activation levels may ultimately result in irreversible changes of cellular ho‐

Advances in Plant Tolerance to Abiotic Stresses

http://dx.doi.org/10.5772/64350

169

Recently, with the support of genomics, targeted genetic studies involving QTL mapping and validation, identification of key regulatory genes, e.g., genes encoding for ABA receptors, developments in transcriptional and post-transcriptional regulation of stress-responsive genes and studies on hormonal interactions during plant response to stress, have provided oppor‐ tunities for understanding cellular stress responses in plants. Moreover, the emergence of deep sequencing technologies, proteomics, metabolomics and epigenetics, has remarkably provid‐ ed novel possibilities to understand the biology of plants and consequently to precisely develop stress-tolerant crop varieties. Amongst the techniques that are currently being

tolerant crops (Figure 2).

Thus, abiotic stress tolerance in plants is a complex trait, involving many different metabolic pathways and cellular and molecular components.

In the past 100 years, conventional breeding (Figure 2; based on observed variation and controlled mating) approaches have randomly exploited these plant tolerance mechanisms with limited success. Moreover, *in vitro* induced variations have also shown little progress in the improvement of plants against abiotic stresses. These conventional breeding ap‐ proaches are limited by the complexity of stress tolerance traits coupled with less genetic

19.5% of irrigated agricultural lands are considered saline [2, 3]. Moreover, 16% of the agricultural rice land of the world suffers from flash flooding [4]. A combination of two or more abiotic stresses, e.g., drought and heat stress also occurs in field situations and causes more severe crop yield reductions than a single stress [5]. With increasing challenges posed by climate change, it is predicted that warming, drought, floods and storm events will become even more frequent and severe, and will further reduce crop yields, especially in the tropics

Abiotic stresses commonly induce overproduction of reactive oxygen species (ROS) causing extensive cellular damage and inhibition of physiological processes in plants. Although antioxidative mechanisms would be an immediate endogenic choice of the plants to counter ROS production, this mechanism can be impaired by abiotic stresses causing a rise in ROS intra‐ cellular concentration and an increase in the damage. To survive under such conditions, plants have evolved intricate mechanisms, allowing optimal responses that enable adaptation or avoidance of the stress. These plant responses are regulated at all levels of organization. At the cellular level, responses include adjustments of the membrane system, modifications of cell wall architecture, changes in cell cycle and cell division, and synthesis of specific endog‐ enous and low-molecular-weight molecules, such as salicylic acid, jasmonic acid, ethylene and abscisic acid [6]. An overview of changes that may occur under different abiotic stress

At the genomic level, plant responses include the expression of stress-inducible genes involved in direct plant protection against stresses [3, 7, 8]. A broad range of abiotic stress induced genes are divided into two functional categories: and regulatory proteins. The first group consists of genes encoding for membrane proteins, enzymes for osmolyte biosynthesis, detoxification (glutathione S-transferases, superoxide dismutases, dehydrins, dehydroascorbate reductases, quinine reductases and ascorbate peroxidases) and proteins for macromolecular protection (such as LEA protein, anti-freezing proteins, chaperons and mRNA binding protein) [2]. The second group comprises genes encoding for transcription factors (e.g., *DREBPs*), protein kinases (e.g., *SRK2E*), receptor protein kinases, ribosomal-protein kinases and signal trans‐ duction proteinases (such as phosphoesterases and phospholipase C). Alterations in the phenylpropanoid pathway in which lignin biosynthesis intermediates are produced also occur under abiotic stress conditions. Moreover, increased accumulation of wall-linked phenolic compounds, for instance, in maize root elongation zone and the polyphenol content in cotton have been linked to stress response [9]. The same authors have shown the role of flavonoids, isoflavonoids, terpenoid and nitrogen-containing secondary metabolites such as glucosino‐

Thus, abiotic stress tolerance in plants is a complex trait, involving many different metabolic

In the past 100 years, conventional breeding (Figure 2; based on observed variation and controlled mating) approaches have randomly exploited these plant tolerance mechanisms with limited success. Moreover, *in vitro* induced variations have also shown little progress in the improvement of plants against abiotic stresses. These conventional breeding ap‐ proaches are limited by the complexity of stress tolerance traits coupled with less genetic

and subtropics.

168 Plant Genomics

conditions is presented in Figure 1.

lates alkaloids in abiotic stress response.

pathways and cellular and molecular components.

**Figure 1.** Abiotic stress response in plants. Primary stresses, including drought, salinity, cold, heat, and submergence, are often interconnected and cause cellular damage and secondary stresses, such as osmotic and oxidative stresses. The initial stress signals (e.g., osmotic and ionic effects or membrane fluidity changes) are perceived by membrane recep‐ tors that transmit the signals downstream to trigger transcription, which is regulated by hormones, transcription factor binding proteins (TFBPs), miRNAs, and transcription factors (TFs) to precisely activate stress responsive mechanisms to re-establish homeostasis and protect and repair damaged proteins and membranes. Inadequate response at one or several steps in the signaling and gene activation levels may ultimately result in irreversible changes of cellular ho‐ meostasis and in the destruction of functional and structural proteins and membranes, leading to cell death.

variation exhibited by most crops due to domestication bottlenecks. The recent reports that the cultivated gene pool of major cereal crops, e.g., rice, maize and wheat, has reduced in genetic variation compared to wild relatives [10–12], raises concern, and could probably undermine the current efforts to identify genetic sources of resistance within the cultivated genepools. It is important, therefore, to consider exploring alternative sources of resistance by incorporating modern techniques into traditional breeding strategies to develop stresstolerant crops (Figure 2).

Recently, with the support of genomics, targeted genetic studies involving QTL mapping and validation, identification of key regulatory genes, e.g., genes encoding for ABA receptors, developments in transcriptional and post-transcriptional regulation of stress-responsive genes and studies on hormonal interactions during plant response to stress, have provided oppor‐ tunities for understanding cellular stress responses in plants. Moreover, the emergence of deep sequencing technologies, proteomics, metabolomics and epigenetics, has remarkably provid‐ ed novel possibilities to understand the biology of plants and consequently to precisely develop stress-tolerant crop varieties. Amongst the techniques that are currently being

**Figure 2.** Overview of the traditional and modern approaches in plant breeding. In conjunction with the technological advancements, marker-assisted backcrossing (MABC) and marker-assisted recurrent selection (MARS) schemes, which target an individual marker or set of markers showing significant association with QTLs, are progressively evolving into a modification of MAS, permitting the selection of the desirable genotypes on the basis of genome-wide marker information or genomic selection (GS).

exploited to develop stress-tolerant plants, alongside basic molecular biology, there are molecular breeding methods, including development of functional molecular markers to aid in marker-assisted selection, horizontal gene transfer and genome editing tools such as CRISPR/Cas9, to develop genetically modified plants with new or improved characteristics.

In this chapter, we reviewed the plant responses to various abiotic stresses, and focus on genetic and molecular components that function to confer stress tolerance in plants.

#### **2. Advances in plant tolerance to drought**

Drought tolerance in plants is the ability to survive and produce stable yields under water scarcity during various stages of crop growth. Principally, drought stress occurs when the soil water potential falls between −0.5 and −1.5 MPa. This affects plants by decreasing the photo‐ synthetic rate through photo-oxidation and enzyme damage, thereby decreasing the amount of assimilates available for export to the sink organs [13]. Besides this, carbohydrate metabo‐ lism in plants is severely altered, ultimately affecting both biological and economical yield [14]. Evidence from several studies has shown that plants respond to drought, like many other abiotic stresses, by inducing cellular damage and secondary stresses, such as osmotic and oxidative stresses. These secondary stresses induce initial stress signals (e.g., osmotic and ionic effects and membrane fluidity changes) that are perceived by membrane receptors (sensors). The perceived signals are transmitted downstream to trigger transcription, which is regulated by phytohormones, transcription factor binding proteins (TFBPs), *cis*-acting elements and miRNAs. Based on the biological functions, the role of these transcriptional regulators and the regulated genes that encode functional proteins or other products to protect plant cells directly from damage is well described [15].

The phytohormone—abscisic acid—acts as a central regulator in the response and adaptation of plants to drought conditions. The various physiological reactions regulated by ABA, including stomatal closure, accumulation of osmoprotectants, changes in gene expression, and other phytohormones have been characterized at the molecular level [16]. The molecular mechanisms of ABA synthesis, transport and signaling in relation to the plant's response to stress are also reasonably well described [17]. ABA signals are perceived by different cellular receptors. The nucleocytoplasmic receptors *PYR*/*PYL*/*RCARs* (pyrabactin resistance/pyrabac‐ tin resistance-like/regulatory component of ABA receptors) have been suggested to be the primary sensors that bind ABA and inhibit type 2C protein phosphatases (*PP2Cs*) [18]. Inactivation of *PP2Cs* leads to accumulation of active *sucrose non-fermenting-1* (*SNF1*)-related protein kinases (*SnRK2s*), which interacts with ABA-responsive TFs, *ABA-responsive promoter elements* (*ABREs*) and *ABRE*-binding protein/*ABRE*-binding factors (*AREB*/*ABF*) to regulate transcription of downstream target genes and related physiological processes [19]. Drought also induces changes in calcium ion levels, which activates calcium-dependent protein kinases (*CDPKs*) via calmodulin-like domain. The activated *CDPKs*regulate downstream components of calcium signaling. For instance, *OsCPK4* overexpressing rice plants exhibit increased waterholding capacity under drought or salt stress [20]. Genetic manipulation of *RLK* genes, including *OsSIK1* that acts as a positive regulator of drought stress responses, is also well reported [21]. Other secondary signaling molecules, including phosphatases (serine/threonine phosphatases) and phospholipids such as phosphoinositides, nitric oxide, cAMP and sugars, play an important role in signal transduction [22]. Examples of phosphatases include the wheat phosphatase *TaPP2Ac-1* that exhibited less wilting under water-deficit conditions than nontransformed controls [23].

exploited to develop stress-tolerant plants, alongside basic molecular biology, there are molecular breeding methods, including development of functional molecular markers to aid in marker-assisted selection, horizontal gene transfer and genome editing tools such as CRISPR/Cas9, to develop genetically modified plants with new or improved characteristics.

**Figure 2.** Overview of the traditional and modern approaches in plant breeding. In conjunction with the technological advancements, marker-assisted backcrossing (MABC) and marker-assisted recurrent selection (MARS) schemes, which target an individual marker or set of markers showing significant association with QTLs, are progressively evolving into a modification of MAS, permitting the selection of the desirable genotypes on the basis of genome-wide marker

In this chapter, we reviewed the plant responses to various abiotic stresses, and focus on

Drought tolerance in plants is the ability to survive and produce stable yields under water scarcity during various stages of crop growth. Principally, drought stress occurs when the soil water potential falls between −0.5 and −1.5 MPa. This affects plants by decreasing the photo‐ synthetic rate through photo-oxidation and enzyme damage, thereby decreasing the amount of assimilates available for export to the sink organs [13]. Besides this, carbohydrate metabo‐ lism in plants is severely altered, ultimately affecting both biological and economical yield [14].

genetic and molecular components that function to confer stress tolerance in plants.

**2. Advances in plant tolerance to drought**

information or genomic selection (GS).

170 Plant Genomics

Numerous TF families such as myeloblastosis oncogene (*MYB*), dehydration-responsive element binding proteins (*DREB*), basic leucine zipper domain (*bZIP*), *WRKYs* and the *NAC* (*NAM, ATAF* and *CUC*) are directly or indirectly regulated by endogenous ABA signaling during drought stress [24]. Many *MYB* genes involved in plant response to drought stress are functionally characterized, including *AtMYB15,* which was shown to enhance drought tolerance, and sensitivity to ABA [25]. *WRKY* proteins, including ABA-inducible *OsWRKY45*, *OsWRKY11* and *OsWRKY08,* are upregulated by drought stress [26]. *AP2*/*ERF* family is another large group of plant-specific TFs that have been demonstrated to be effective in enhancing drought tolerance in plants. For instance, overexpression of *AP2*/*ERF* genes, e.g., *GmERF3* in soybeans, has been reported to enhance tolerance to drought [27]. In addition, *DREB2s*, e.g., *ZmDREB2.7*, are candidates for drought stress tolerance in maize [28]. The *bZIP* TFs have also been reported to enhance plant tolerance to stress and hormone signal transduction, e.g., *OsbZIP23* in rice [29] and *ZmbZIP72* in maize [30]. Within the *NAC* family, *RD26* (*responsive to dehydration 26*) was the first *NAC* gene identified as a regulator in mediating crosstalk between abscisic acid and jasmonic acid (JA) signaling during drought stress responses in *Arabidopsis* [31]. Overexpression of other *NAC* genes, including *ANAC019*, *ANAC055* and *ANAC072,* has been shown to confer drought tolerance in transgenic *Arabidopsis* [32]. Similarly, overexpres‐ sion of *SNAC1*, *OsNAC10* and *OsNAC5* driven by a root-specific promoter *RCc3* confers increased drought resistance under field conditions [33, 34]. The nuclear factor Y (*NF-Y*) TFs are emerging as important regulators of drought-stress response, particularly with respect to ABA biosynthesis. For instance, ectopic expression of *Amaranthus hypochondriacus NF-YC* gene (*AhNF-YC*) in *Arabidopsis* and overexpression of Bermuda grass *Cdt-NF-YC1* in rice has shown that these genes confer drought tolerance [35, 36]. *Cdt-NF-YC1* induces expression of both ABA-responsive genes (e.g., *OsRAB16A*, *OsLEA3*, *OsP5CS1* and *OsLIP9*) and signaling genes (e.g., *OsABI2* and *OsNCED3*), as well as, ABA independent genes (e.g., *OsDREB1A*, *Os‐ DREB2B* and *OsDREB1B*). In fact there is an increasing evidence that some NAC genes, e.g., *SNAC3*, contribute to drought resistance and osmotic adjustment independent of ABA [37]. *SNAC3* interacts with *phosphoglycerate mutase*, *cytochrome P450 72A1*, *PP2C*, WD domaincontaining protein and *oxidoreductase* to modulate ROS in rice. These findings suggest a complex regulatory mechanisns of drought response and tolerance in plants, involving both ABA and other signaling pathways.

Recent work on inhibitors of phosphoinositide-dependent phospholipases C (*PI-PLCs*) in *Arabidopsis* has also provided considerable insight into the drought-stress-related lipid signaling by identifying links of phosphoinositides to the *DREB2* pathway [38]. Moreover, overexpression of phosphatidylinositol synthase gene *(ZmPIS)* in tobacco plants changed membrane lipids' composition and improved drought stress tolerance [39]. The best charac‐ terized lipid derivative, so far, is inositol 1,4,5-trisphosphate (IP3). IP3 levels have been shown to increase in response to exogenous ABA in *Vicia faba* guard cell protoplasts and in *Arabidop‐ sis* seedlings, for review see [40]. IP3 acts as a second messenger involved in releasing Ca2+ from internal stores such as vacuoles. This pathway has been reported to induce osmotic-stressresponsive genes, as well as ABA stress-responsive genes [40]. Another lipid derivative, phospholipase D (PLD), has been reported by the same authors to be functionally associated with ABA; and the application of phosphatidic acid (PA), a PLD derivative, has been shown to mimic the effect of ABA in inducing stomatal closure [41]. This could probably suggest that lipid signaling is linked to ABA in drought stress response, and it is worthwhile to study how the different lipid derivatives enter in action, either simultaneously or timely synchronized with ABA.

Downstream of the TFs are numerous responsive genes that function either in a constitutive manner (i.e., also expressed under well-watered conditions) or a drought-responsive manner (i.e., expressed only under pronounced water shortage). Amongst them, genes encoding for receptor-like kinases (RLKs) with Ser/Thr kinase domain could play an important role in optimizing plant responses to drought stress [18]. Other genes that have been shown to be upor downregulated by drought stress to enable dehydration avoidance or tolerance in various plant species are documented in several studies [18, 42]. Another process, downstream of transcriptional regulatory networks, is the induction of a large range of genes encoding for enzymes involved in osmotic adjustments, osmoprotection, wax biosynthesis and changes in fatty acid composition (Figure 3). Adjustment of osmotic pressure allows the plant to take up more soil water and maintain turgor and cell function for a longer time under drought.

*ZmDREB2.7*, are candidates for drought stress tolerance in maize [28]. The *bZIP* TFs have also been reported to enhance plant tolerance to stress and hormone signal transduction, e.g., *OsbZIP23* in rice [29] and *ZmbZIP72* in maize [30]. Within the *NAC* family, *RD26* (*responsive to dehydration 26*) was the first *NAC* gene identified as a regulator in mediating crosstalk between abscisic acid and jasmonic acid (JA) signaling during drought stress responses in *Arabidopsis* [31]. Overexpression of other *NAC* genes, including *ANAC019*, *ANAC055* and *ANAC072,* has been shown to confer drought tolerance in transgenic *Arabidopsis* [32]. Similarly, overexpres‐ sion of *SNAC1*, *OsNAC10* and *OsNAC5* driven by a root-specific promoter *RCc3* confers increased drought resistance under field conditions [33, 34]. The nuclear factor Y (*NF-Y*) TFs are emerging as important regulators of drought-stress response, particularly with respect to ABA biosynthesis. For instance, ectopic expression of *Amaranthus hypochondriacus NF-YC* gene (*AhNF-YC*) in *Arabidopsis* and overexpression of Bermuda grass *Cdt-NF-YC1* in rice has shown that these genes confer drought tolerance [35, 36]. *Cdt-NF-YC1* induces expression of both ABA-responsive genes (e.g., *OsRAB16A*, *OsLEA3*, *OsP5CS1* and *OsLIP9*) and signaling genes (e.g., *OsABI2* and *OsNCED3*), as well as, ABA independent genes (e.g., *OsDREB1A*, *Os‐ DREB2B* and *OsDREB1B*). In fact there is an increasing evidence that some NAC genes, e.g., *SNAC3*, contribute to drought resistance and osmotic adjustment independent of ABA [37]. *SNAC3* interacts with *phosphoglycerate mutase*, *cytochrome P450 72A1*, *PP2C*, WD domaincontaining protein and *oxidoreductase* to modulate ROS in rice. These findings suggest a complex regulatory mechanisns of drought response and tolerance in plants, involving both

(JA) other under [33, factor drought is an ,

Recent work on inhibitors of phosphoinositide-dependent phospholipases C (*PI-PLCs*) in *Arabidopsis* has also provided considerable insight into the drought-stress-related lipid signaling by identifying links of phosphoinositides to the *DREB2* pathway [38]. Moreover, overexpression of phosphatidylinositol synthase gene *(ZmPIS)* in tobacco plants changed membrane lipids' composition and improved drought stress tolerance [39]. The best charac‐ terized lipid derivative, so far, is inositol 1,4,5-trisphosphate (IP3). IP3 levels have been shown to increase in response to exogenous ABA in *Vicia faba* guard cell protoplasts and in *Arabidop‐ sis* seedlings, for review see [40]. IP3 acts as a second messenger involved in releasing Ca2+ from internal stores such as vacuoles. This pathway has been reported to induce osmotic-stressresponsive genes, as well as ABA stress-responsive genes [40]. Another lipid derivative, phospholipase D (PLD), has been reported by the same authors to be functionally associated with ABA; and the application of phosphatidic acid (PA), a PLD derivative, has been shown to mimic the effect of ABA in inducing stomatal closure [41]. This could probably suggest that lipid signaling is linked to ABA in drought stress response, and it is worthwhile to study how the different lipid derivatives enter in action, either simultaneously or timely synchronized

*SNAC3* response involving derivative, 1,4,5-trisphosphate

Downstream of the TFs are numerous responsive genes that function either in a constitutive manner (i.e., also expressed under well-watered conditions) or a drought-responsive manner (i.e., expressed only under pronounced water shortage). Amongst them, genes encoding for receptor-like kinases (RLKs) with Ser/Thr kinase domain could play an important role in optimizing plant responses to drought stress [18]. Other genes that have been shown to be up-

ABA and other signaling pathways.

with ABA.

172 Plant Genomics

**Figure 3.** Physiological, biochemical, and molecular basis of drought stress tolerance in plants. Both major and minor changes that occur downstream of the transcriptional regulatory network are shown, although some of them, e.g. pro‐ line, glycine betaine and other amino acids, were previously shown not to be important in plant resistance to drought stress.

Water-channel proteins, e.g. aquaporins (*AQPs*), and sugar transporters are believed to facilitate the adjustment of osmotic pressure under stress by transporting water and sugars to the cytosol [42]. More recently, *AQPs* encoding genes (e.g., *MaPIP1;1*) were shown to be strongly induced in banana plants exposed to drought [43]. The same authors indicate that overexpression of *MaPIP1;1* in *Arabidopsis* exhibited better growth, reduced water loss and higher survival rates. Li et al. [44] also showed that *AQPs* were elevated under drought stress in Tibetan *Sophora moorcroftiana,* which is consistent with the previous reports [45]. However, the same authors indicate conflicting functions of plasma membrane intrinsic proteins (*PIP*s). For instance, overexpression of *GoPIP1,* cloned from *Galega orientalis*, showed increased sensitivity to drought in transgenic *Arabidopsis* plants. This indicates that AQPs are able to facilitate both tolerance and sensitivity, which warrants further research to delineate *AQP*s that are potentially helpful in improving drought tolerance in plants.

Studies have also shown that the *K <sup>+</sup> uptake transporter 6* (*KUP6*) subfamily of transporters act as key factors in osmotic adjustment by balancing potassium homeostasis in cell growth and drought stress responses [46]. *KUP6* is apparently under the control of abscisic acid and interacts with ABA-activated *SnRK2*-type protein kinase, *SnRK2E*, resulting in phosphoryla‐ tion of the *KUP6* C-terminal domain. This indicates that *KUP6* is a downstream target for *SnRK2E* in the control of water stress responses. However, other interacting proteins, and probably hormones, e.g. auxins, could regulate the activity of *KUP6* in the maintenance of water status during drought stress. Indeed, it was reported previously that a variant of *KUP6, KUP4*/*TRH1,* facilitates root-specific auxin distribution [47]. This was substantiated by the findings that triple mutants of the *KUP* genes (i.e., *kup2 kup6 kup8*and*kup6 kup8 gork*) showed enhanced cell expansion and auxin responses in lateral root formation [54]. Moreover, auxinresponsive TFs, *LBD18* and *LBD29,* were highly expressed in the triple mutants in the presence of IAA, indicating that auxin could be modulating K+ and proton fluxes during drought stress.

The biosynthesis of osmoprotectants such as amino acid, amines and carbohydrates is another indispensable strategy for plant resistance to drought stress. The most common osmoprotec‐ tants are proline (Pro), γ-aminobutyric acid (GABA), glycine betaine (GB), fructans, starch, mono- and disaccharides, trehalose (Tre) and raffinose family oligosaccharides (RFO). The biosynthesis and transport of trehalose and raffinose is particularly relevant in drought stress response. More recently, genes encoding for trehalose and raffinose biosynthesis were significantly upregulated in the roots and leaves of *Jatropha curcas* under drought [48], suggesting that these compounds may have major impacts on osmotic adjustment and ROS scavenging during drought stress. The same authors indicated that dozens of genes in‐ volved in wax biosynthesis, including *KCS* and *WSD*, and their regulators (e.g., *MYB96, CER*) were upregulated more than four-fold in leaves under drought conditions. Overexpression of genes encoding for *MYB96, CER KCS* and *WSD* could probably strengthen the hydropho‐ bic barrier that prevents non-stomatal water loss and increase plant tolerance to drought.

Genes encoding for proteins involved in cellular structure stabilization have also been reported to be induced in plant tolerance to drought. For instance, dehydrins (DHNs) function to protect cells from damage caused by drought stress-induced dehydration [49]. Proteins related to lignin biosynthesis, such as caffeoyl-CoA 3-O-methyl-transferases and class III plant peroxi‐ dases, were also found to be induced by drought in wild watermelon [50] and in maize roots [51]. In winter triticale, water-deficit-induced leaf rolling was correlated with a higher level of cell wall-bound phenolics in the leaves [52]. These adaptive mechanism could probably limit water loss by restricting the leaf transpiration surface. In addition, carbon/nitrogen-metabo‐ lism-related proteins have been reported to be more abundant in roots of soybean [53], wild watermelon [50] and rapeseed [54] after drought treatment, suggesting an increased energy demand as well as enhanced cellular activities in the root tissues during drought stress. The same authors reported a relative increase in the root growth rate and abundance of rootgrowth-related small G-protein family members such as *Ran GTPases*, which suggests in‐ creased membrane trafficking activity in an effort by the plant roots to absorb water from deep soil layers.

Taken together, the vast amount of data from 'omic' tools provide a basis for identification of more functional genes, which could contribute directly to cellular drought stress tolerance. In addition, understanding expression networks of genes encoding for the aforementioned proteins, especially genes involved in cellular structure stabilization, molecular chaperones, enzymes for detoxification of reactive oxygen species, and those for the biosynthesis of sugars, wax and dehydrins, which are important as protectants [55], may allow for the realization of significant genetic gains in breeding for plant tolerance to drought. Further genomic scale investigations will enable understanding of transcriptional regulators behind co-expressed genes and their association with particular genomic regions (QTLs). Although QTL identifi‐ cation for tracing drought tolerance remains a challenge due to the large number of genes influencing drought tolerance traits, continued investigation into the basis of tolerance in crops like *Jatropha curcas* will probably provide a clearer understanding of drought tolerance. Besides this, the mechanism by which drought tolerance associated protein networks effectively protect PSII and granal stability, as well as maintain photosynthetic competence will need further elucidation.

#### **3. Advances in plant tolerance to heat stress**

Studies have also shown that the *K <sup>+</sup> uptake transporter 6* (*KUP6*) subfamily of transporters act as key factors in osmotic adjustment by balancing potassium homeostasis in cell growth and drought stress responses [46]. *KUP6* is apparently under the control of abscisic acid and interacts with ABA-activated *SnRK2*-type protein kinase, *SnRK2E*, resulting in phosphoryla‐ tion of the *KUP6* C-terminal domain. This indicates that *KUP6* is a downstream target for *SnRK2E* in the control of water stress responses. However, other interacting proteins, and probably hormones, e.g. auxins, could regulate the activity of *KUP6* in the maintenance of water status during drought stress. Indeed, it was reported previously that a variant of *KUP6, KUP4*/*TRH1,* facilitates root-specific auxin distribution [47]. This was substantiated by the findings that triple mutants of the *KUP* genes (i.e., *kup2 kup6 kup8*and*kup6 kup8 gork*) showed enhanced cell expansion and auxin responses in lateral root formation [54]. Moreover, auxinresponsive TFs, *LBD18* and *LBD29,* were highly expressed in the triple mutants in the presence of IAA, indicating that auxin could be modulating K+ and proton fluxes during drought stress.

The biosynthesis of osmoprotectants such as amino acid, amines and carbohydrates is another indispensable strategy for plant resistance to drought stress. The most common osmoprotec‐ tants are proline (Pro), γ-aminobutyric acid (GABA), glycine betaine (GB), fructans, starch, mono- and disaccharides, trehalose (Tre) and raffinose family oligosaccharides (RFO). The biosynthesis and transport of trehalose and raffinose is particularly relevant in drought stress response. More recently, genes encoding for trehalose and raffinose biosynthesis were significantly upregulated in the roots and leaves of *Jatropha curcas* under drought [48], suggesting that these compounds may have major impacts on osmotic adjustment and ROS scavenging during drought stress. The same authors indicated that dozens of genes in‐ volved in wax biosynthesis, including *KCS* and *WSD*, and their regulators (e.g., *MYB96, CER*) were upregulated more than four-fold in leaves under drought conditions. Overexpression of genes encoding for *MYB96, CER KCS* and *WSD* could probably strengthen the hydropho‐ bic barrier that prevents non-stomatal water loss and increase plant tolerance to drought.

Genes encoding for proteins involved in cellular structure stabilization have also been reported to be induced in plant tolerance to drought. For instance, dehydrins (DHNs) function to protect cells from damage caused by drought stress-induced dehydration [49]. Proteins related to lignin biosynthesis, such as caffeoyl-CoA 3-O-methyl-transferases and class III plant peroxi‐ dases, were also found to be induced by drought in wild watermelon [50] and in maize roots [51]. In winter triticale, water-deficit-induced leaf rolling was correlated with a higher level of cell wall-bound phenolics in the leaves [52]. These adaptive mechanism could probably limit water loss by restricting the leaf transpiration surface. In addition, carbon/nitrogen-metabo‐ lism-related proteins have been reported to be more abundant in roots of soybean [53], wild watermelon [50] and rapeseed [54] after drought treatment, suggesting an increased energy demand as well as enhanced cellular activities in the root tissues during drought stress. The same authors reported a relative increase in the root growth rate and abundance of rootgrowth-related small G-protein family members such as *Ran GTPases*, which suggests in‐ creased membrane trafficking activity in an effort by the plant roots to absorb water from deep

soil layers.

174 Plant Genomics

Temperatures above the normal optimum cause heat stress (HS) at different levels in all living organisms. Heat stress disturbs cellular homeostasis, and causes denaturation and dysfunction in many proteins, leading to severe retardation in growth, development and even death. In plants, the major sites of heat stress injury are the oxygen-evolving complex (OEC) along with associated biochemical reactions in photosystem II (PSII). Ultimately, efficiency of electron transport is reduced or altered affecting electron flow from OEC towards the acceptor side of PSII. These alterations affect the generation of ATP and the regeneration of Rubisco for carbon fixation [56]. Starch synthesis is also negatively affected by heat stress because of the reduced activity of enzymes such as invertase, sucrose phosphate synthase and ADP glucose pyro‐ phosphorylase. Usually, ROS induction and accumulation in the chloroplasts precedes these changes. Accumulated ROS can severely damage DNA and cause autocatalytic peroxidation of membrane lipids and pigments, altering membrane functions and cell semi-permeability. Physiological changes associated with biochemical damage may include a decrease in chlorophyll a:b ratio, inhibitions of stomatal conductance and net photosynthesis, and low plant water potential. These changes ultimately reduce the partitioning of photosynthates, which morphologically manifest as retarded growth, reduced economic yield and harvest index. Scorching and sunburns of leaves and twigs, branches and stems, leaf senescence and abscission, and fruit discoloration and damage are other morphological damages associated with heat stress [57].

Perception of heat stress by plants usually triggers sensors at the plasma membrane and causes a transient opening of Ca2+ channels, possibly via modulation of membrane fluidity (Figure 4) [58]. Upon entry of Ca2+, putatively through channels possessing cytosolic C-terminus with a calmodulin-binding domain, multiple kinases are activated.

**Figure 4.** Hypothetical model for high-temperature signal sensing and induction of molecular pathways leading to plant defence response. Prolonged high-temperature stress causes membrane depolarization leading to Ca2+ influx or directly activates apoplastic enzymes including GLPs. Increased levels of cytosolic calcium activate the ROS-producing enzyme, RBOHD, which catalyses ROS production. Effect of temperature on R genes through an unknown pathway is likely to further enhance ROS production. ROS/ Ca2+ signaling causes activation of plasma membrane ATPase, which extrude H+ . Alternatively, heat-stress-induced protein damage and protease activity decreases cytosolic pH. Low cyto‐ solic pH and H2O2 accumulation reduces CO2 assimilation, thereby increasing endogenous carbohydrate metabolism. Cytosolic acidification and ATPase activity may also increase accumulation of expansins and methylesterases that eventually affect the cell wall integrity. Activating plasma membrane ATPase is probably reverse phosphorylated by FKBP65 leading to H+ extrusion and K+ intrusion. A part from its targeted role in the nucleus, FKBP65 could be target‐ ed to the chloroplast through the tat pathway to activate photosystem II 10 kDa polypeptides or for directing chaper‐ one functions. Activated HSPs probably cause chromatin remodelling and histone displacement. In addition to activating PM ion channels, heat-induced changes in membrane fluidity triggers lipid signaling. Plants deploy phos‐ pholipids, including phospholipase D (PLD), PIPK (phosphatidylinositol 4,5-bisphosphate kinase), phosphatidic acid (PA), PIP2 (phosphatidylinositol phosphate kinase) and IP3 (D-myo-inositol-1,4,5-trisphosphate) to specific intracellu‐ lar locations. The accumulation of lipid signaling molecules also triggers Ca2+ influx, which initiates downstream sig‐ naling, including activation of CDPKs, hormonal changes, transcription factor activation and secondary metabolism. Question marks indicate the unknown players.

The *MPK6* activity has been particularly shown to increase under heat stress. *MPK6* activates a vacuolar processing enzyme (*VPE*), which has been suggested to play a role in HS-induced programmed cell death [59]. Transcriptional regulators, such as *HSFs*, *WRKY*, *Zat* and *MBF1c*, a transcriptional regulator of *DREB* genes [60], are activated to regulate expression of HSPs and other heat stress response genes.

Heat-induced accumulation of Ca2+ in the cytoplasm also activates the ROS-producing enzymes *RBOHD* and *NADPH oxidase*, by direct interaction or through activation of calciumdependent protein kinases (*CDPK*) that phosphorylate *RBOHD* [61]. When activated, *RBOHD* catalyzes the production of ROS, causing membrane depolarization and/or initiation of ROS/ redox signaling network, which interacts with the above-mentioned *MBF1c*, *HSFs*, *MAPKs* and *SnRK*s to trigger downstream signaling networks [61].

Calcium/calmodulin-binding protein kinases (*CBK*), which also regulate the expression of *HSPs*, are activated via *CaM3*. A well-known example is the activation of *CBK3,* which enhances thermotolerance in *A. thaliana* seedlings by phosphorylating *HsfA1a* and a *CaM* protein phosphatase (*PP7*) [62]. *PP7* interacts with both *AtCaM3* and *AtHsfA1a*. *AtCaM3* increases thermotolerance by activating *WRKY39* and *HSFs,* indicating that *CBK3* plays a key role in heat stress signaling. The TF *Zat* is necessary for the activation of *WRKYs* and ascorbate peroxidase [63]. *MBF1c* modulates the induction of SA and trehalose, which are regulators of plant stress response [64]. SA has been shown to alleviate heat stress by increasing proline production and restricting the formation of ethylene in heat-stressed plants [65].

Another HS-response-associated signaling pathway was shown in the *Hsp90–ROF1* interaction in the cytoplasm and their subsequent translocation to the nucleus. The *Hsp90–ROF1* complex localizes in the nucleus only in the presence of *HsfA2* [66]. The interaction of these three proteins modulates *HSP* gene expression under HS. Although, *ROF1* has been reported to induce expression of small *HSPs*, which increases plant survival rate under HS, to date the upstream signal that regulates the subcellular localization of *Hsp90–ROF1* remains elusive. Interestingly, just like *MBF1c, ROF1* is involved in calcium-dependent phosphorylation of *HSFs*, which suggests that Ca2+-dependent activation of *RBOHD* or *CDPK*s could be the upstream signal for *ROF1*.

**Figure 4.** Hypothetical model for high-temperature signal sensing and induction of molecular pathways leading to plant defence response. Prolonged high-temperature stress causes membrane depolarization leading to Ca2+ influx or directly activates apoplastic enzymes including GLPs. Increased levels of cytosolic calcium activate the ROS-producing enzyme, RBOHD, which catalyses ROS production. Effect of temperature on R genes through an unknown pathway is likely to further enhance ROS production. ROS/ Ca2+ signaling causes activation of plasma membrane ATPase, which

solic pH and H2O2 accumulation reduces CO2 assimilation, thereby increasing endogenous carbohydrate metabolism. Cytosolic acidification and ATPase activity may also increase accumulation of expansins and methylesterases that eventually affect the cell wall integrity. Activating plasma membrane ATPase is probably reverse phosphorylated by FKBP65 leading to H+ extrusion and K+ intrusion. A part from its targeted role in the nucleus, FKBP65 could be target‐ ed to the chloroplast through the tat pathway to activate photosystem II 10 kDa polypeptides or for directing chaper‐ one functions. Activated HSPs probably cause chromatin remodelling and histone displacement. In addition to activating PM ion channels, heat-induced changes in membrane fluidity triggers lipid signaling. Plants deploy phos‐ pholipids, including phospholipase D (PLD), PIPK (phosphatidylinositol 4,5-bisphosphate kinase), phosphatidic acid (PA), PIP2 (phosphatidylinositol phosphate kinase) and IP3 (D-myo-inositol-1,4,5-trisphosphate) to specific intracellu‐ lar locations. The accumulation of lipid signaling molecules also triggers Ca2+ influx, which initiates downstream sig‐ naling, including activation of CDPKs, hormonal changes, transcription factor activation and secondary metabolism.

The *MPK6* activity has been particularly shown to increase under heat stress. *MPK6* activates a vacuolar processing enzyme (*VPE*), which has been suggested to play a role in HS-induced programmed cell death [59]. Transcriptional regulators, such as *HSFs*, *WRKY*, *Zat* and *MBF1c*, a transcriptional regulator of *DREB* genes [60], are activated to regulate expression of

Heat-induced accumulation of Ca2+ in the cytoplasm also activates the ROS-producing enzymes *RBOHD* and *NADPH oxidase*, by direct interaction or through activation of calciumdependent protein kinases (*CDPK*) that phosphorylate *RBOHD* [61]. When activated, *RBOHD*

. Alternatively, heat-stress-induced protein damage and protease activity decreases cytosolic pH. Low cyto‐

extrude H+

176 Plant Genomics

Question marks indicate the unknown players.

HSPs and other heat stress response genes.

Heat stress also triggers lipid signaling. Activation of *phospholipase D* (*PLD*) and a *phosphati‐ dylinositol 4, 5-bisphosphate kinase* (*PIPK*) increases the accumulation of phosphatidic acid (*PA*), phosphatidylinositol phosphate kinase and D-myo-inositol-1,4,5-trisphosphate (*IP3*); and an active cycling of a G protein appears necessary in this process. The accumulation of lipid signaling molecules could in turn cause the opening of channels and the triggering of Ca2+ influx [67].

Downstream effects of heat stress signals have been reported to activate a signaling pathway called unfolded protein response (UPR) in the endoplasmic reticulum, which requires specific calcium signals from the plasma membrane [58]. Within the endoplasmic reticulum, the activity of UPRs involves two signaling pathways: one involving proteolytic processing of membrane-associated *bZIP* TFs and the other involving RNA splicing factor, inositol requiring enzyme-1 (*IRE1*) and its mRNA target [68]. *IRE1* is a dual functional enzyme possessing both serine/threonine protein kinase and endoribonuclease activity. In *Arabidopsis*, heat signals activate *IRE1* to splice *bZIP60* mRNA in the cytosol, causing a frameshift, which triggers the synthesis of a tissue factor without a transmembrane domain, but having a nuclear targeting signal [69]. The *bZIP60* (*bZIP60*(s)) spliced forms activate UPR target genes in the nucleus. A cytosolic form of UPR, which is triggered by the presence of unfolded proteins in the cytosol, was also previously reported [70]. Together, these UPRs are associated with the heat shock promoter elements and the involvement of specific *HSFs*, notably *HSFA2*, regulated by alternative splicing and non-sense-mediated decay. Under severe HS (42–45ºC), a novel posttranscriptional regulatory mechanism governing *HSFA2* expression has also been shown to occur. Moreover, a new splice variant of *HSFA2-III* is reported to be generated through the use of acryptic 5′ splice site in the intron. *HSFA2-III* can be translated into the small *HSFA2* (*S-HsfA2*), which binds to the TATA box proximal clusters of HS elements (*HSE*) in the *HSFA2* promoter to activate its own gene expression, thus constituting a positive auto-regulatory loop [71]. Although the TFs interacting with *S-HsfA2* are yet to be validated, this finding suggests that severe HS may alter the splicing pattern of *Hsf* genes, generating isoforms that may autoactivate self-expression and consequently rapidly induce the expression of HSPs required for enhanced response to HS.

Apart from *HSFs*, overexpression of *DPB3-1,* which regulates expression of *DREB2A* and *DREB2B*, increases thermotolerance [72]. Other studies have also shown the role of *bZIP28* [73] and *WRKY* proteins in plants thermotolerance [74, 75]. Furthermore, the basic helix-loop-helix (*bHLH*) TF, *phytochrome interacting factor 4* (*PIF4*), was reported to control acclimation to changes in ambient temperature by regulating important hormonal and developmental pathways modulating the acclimation mechanisms [76]. *PIF4* alleles control floral timing by modulating *FLOWERING LOCUS T (FT). PIF4* also controls early inflorescence internode elongation and high-temperature-induced hypocotyl elongation by modulating levels of free indole-3-acetic acid (*IAA*) through the triggering of *YUC8 (YUCCA8)* or *TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS* (*TAA1*) gene expression [57, 77]. Thus, *PIF4* is a potential regulator of plant responses to high temperature. However, its physical interaction with *cryptochrome 1* (*CRY1*) on nuclear DNA suggests that these two proteins co-regulate temperature responses in plants. Another regulator, *E3 ubiquitin ligase CONSTITUTIVE PHOTOMORPHOGENIC1* (*COP1),* was shown to be essential for plant responses to HS [77]. However, it is not known whether *COP1* signaling is independent of *PIF4*. Orthologs of *PIF4* have been identified in several crop species. Thus, if the interaction with other associated proteins is resolved, *PIF4* has a potential promise to improve plant tolerance to HS in several crops through genetic engineering.

Other components of heat sensing that could be linked to these signaling pathways include the transcriptional modulator, the *nuclear actin-related protein 6* (*ARP6*), which is part of the Snf-2-related CREB-binding activator protein (*SRCAP*) encoding a subunit of the *SWR1* chromatin remodelling complex is necessary for inserting the alternative histone, *H2A.Z*, into nucleosomes, while replacing the core histone H2A [78]. Heat stress induces a decrease in *H2A.Z* occupancy in nucleosomes located at the transcription start site of heat response genes, a process that probably allows nucleosome opening and enhanced transcription of these genes.

Plant adaptation to thermotolerance also involves the activity of superoxide reductase (*SOR*), *S*-nitrosoglutathione reductase (*GSNOR*) and rubisco activase (*RCA*). The functions of these proteins are reasonably well described in a review by [67]. Other commonly reported antioxidant enzymes produced by plants under HS include superoxide dismutase (*SOD*), catalase (*CAT*), guaiacol peroxidase (*GPX*), ascorbate peroxidase (*APX*), dehydroascorbate reductase (*DHAR*), glutathione reductase (*GR*), glutathione S-transferase (*GST*) and non-enzymatic antioxidants such as flavanoids, anthocyanin, carotenoids and ascorbic acid (*AA*) [60]. The accumulation of other osmolytes such as glycine betaine and trehalose is another well-known adaptive mechanism in plants against HS. Generally, most of these compounds are involved in ROS removal (anti-oxidants), osmotic adjustment, saturation of membrane-associated lipids, protection of photosynthetic reactions, production of polyamines and protein biosyn‐ thesis [94], which enable plants to exhibit basal or acquired thermotolerance. Proline and glycine betaine application considerably reduce the H2O2 production, improve the accumula‐ tion of soluble sugars and protect the developing tissues from HS [79]. Tocopherol is another important lipid-soluble redox buffer and an important scavenger of singlet oxygen species and other ROS. Moreover α-tocopherol has the highest anti-oxidant activity of all the tocopherol types reported in plants [80].

A number of studies have demonstrated the presence of QTLs associated with most HS-related traits and promise to the use of molecular markers in breeding for heat stress tolerance. More than 50 QTLs have been identified in various crops so far, including maize, wheat, rice, cowpea, lettuce, *Medicago truncatula* and *Brassica napus*. Recent studies in transcriptomics [81, 82], proteomics [83, 84], metabolomics [85, 86] and microRNAs [87] have also provided additional information on the mechanisms controlling plant responses to HS. Understanding the relationship between these mechanisms and the genomic regions mapped and delineated as QTLs would validate the genes controlling plant responses to HS, and subsequently improve genetic gains in plant improvement programmes. Besides, the possibility of developing transgenic plants with enhanced tolerance to HS would also gain significance. This approach has already been demonstrated in cotton [88], *Arabidopsis* [89], tobacco [90] and rice [91], but needs further validation, especially in economically important crops where it has not been applied before. Taken together, heat stress responses discussed here demonstrate that heat stress is a quantitative trait, which requires a combination of several disciplines to improve plant tolerance.

#### **4. Advances in plant tolerance to cold stress**

occur. Moreover, a new splice variant of *HSFA2-III* is reported to be generated through the use of acryptic 5′ splice site in the intron. *HSFA2-III* can be translated into the small *HSFA2* (*S-HsfA2*), which binds to the TATA box proximal clusters of HS elements (*HSE*) in the *HSFA2* promoter to activate its own gene expression, thus constituting a positive auto-regulatory loop [71]. Although the TFs interacting with *S-HsfA2* are yet to be validated, this finding suggests that severe HS may alter the splicing pattern of *Hsf* genes, generating isoforms that may autoactivate self-expression and consequently rapidly induce the expression of HSPs required for

Apart from *HSFs*, overexpression of *DPB3-1,* which regulates expression of *DREB2A* and *DREB2B*, increases thermotolerance [72]. Other studies have also shown the role of *bZIP28* [73] and *WRKY* proteins in plants thermotolerance [74, 75]. Furthermore, the basic helix-loop-helix (*bHLH*) TF, *phytochrome interacting factor 4* (*PIF4*), was reported to control acclimation to changes in ambient temperature by regulating important hormonal and developmental pathways modulating the acclimation mechanisms [76]. *PIF4* alleles control floral timing by modulating *FLOWERING LOCUS T (FT). PIF4* also controls early inflorescence internode elongation and high-temperature-induced hypocotyl elongation by modulating levels of free indole-3-acetic acid (*IAA*) through the triggering of *YUC8 (YUCCA8)* or *TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS* (*TAA1*) gene expression [57, 77]. Thus, *PIF4* is a potential regulator of plant responses to high temperature. However, its physical interaction with *cryptochrome 1* (*CRY1*) on nuclear DNA suggests that these two proteins co-regulate temperature responses in plants. Another regulator, *E3 ubiquitin ligase CONSTITUTIVE PHOTOMORPHOGENIC1* (*COP1),* was shown to be essential for plant responses to HS [77]. However, it is not known whether *COP1* signaling is independent of *PIF4*. Orthologs of *PIF4* have been identified in several crop species. Thus, if the interaction with other associated proteins is resolved, *PIF4* has a potential promise to improve plant tolerance to HS in several

Other components of heat sensing that could be linked to these signaling pathways include the transcriptional modulator, the *nuclear actin-related protein 6* (*ARP6*), which is part of the Snf-2-related CREB-binding activator protein (*SRCAP*) encoding a subunit of the *SWR1* chromatin remodelling complex is necessary for inserting the alternative histone, *H2A.Z*, into nucleosomes, while replacing the core histone H2A [78]. Heat stress induces a decrease in *H2A.Z* occupancy in nucleosomes located at the transcription start site of heat response genes, a process that probably allows nucleosome opening and enhanced transcription of these genes.

HS the

Plant adaptation to thermotolerance also involves the activity of superoxide reductase (*SOR*), *S*-nitrosoglutathione reductase (*GSNOR*) and rubisco activase (*RCA*). The functions of these proteins are reasonably well described in a review by [67]. Other commonly reported antioxidant enzymes produced by plants under HS include superoxide dismutase (*SOD*), catalase (*CAT*), guaiacol peroxidase (*GPX*), ascorbate peroxidase (*APX*), dehydroascorbate reductase (*DHAR*), glutathione reductase (*GR*), glutathione S-transferase (*GST*) and non-enzymatic antioxidants such as flavanoids, anthocyanin, carotenoids and ascorbic acid (*AA*) [60]. The accumulation of other osmolytes such as glycine betaine and trehalose is another well-known adaptive mechanism in plants against HS. Generally, most of these compounds are involved

*SRCAP*) include

enhanced response to HS.

178 Plant Genomics

crops through genetic engineering.

Cold stress occurs at temperatures less than 20ºC and varies with the degree of temperature duration and plant type. Chilling (<20ºC) or freezing (<0ºC) temperatures can trigger the formation of ice in plant tissues, which causes cellular dehydration [92]. Ultimately, cold stress reduces plasma membrane (PM) integrity, causing leakage of intracellular solutes. Cold stress severely affects plant growth and survival, and leads to substantial crop losses in temperate climatic regions and hilly areas of the tropics and subtropics [93]. In rice, for instance, losses due to cold stress can range from 0.5 to 2.5 t/ha and grain yields can drop by up to 26%, especially when low temperatures occur during the reproductive stage [94].

To cope with this adverse condition, plants adapt several strategies such as producing more energy by activation of primary metabolisms, raising the level of anti-oxidants and chaperones, and maintaining osmotic balance by altering cell membrane structure [95]. These mechanisms of plant response to cold stress are closely similar to that of heat stress. However, the difference lies in the fact that membrane rigidification occurs in cold stress as opposed to heat stress. Thus, membrane rigidification is the upstream trigger for the induction cytosolic Ca2+ signatures leading to a transient increase in cytosolic Ca2+levels [96]. It is assumed that dimethyl sulfoxide (DMSO) mediates the perception of membrane rigidification by mechanosensitive Ca2+channels [97]. Other upstream factors such as changes in the metabolic reactions and metabolite concentrations, protein and nucleic acid conformation could contribute to enhance perception of cold stress. These factors as well, either directly or indirectly, induce an increase in cytosolic Ca2+, which is a well-known upstream second messenger, regulating cold regulated (*COR*) gene expression.

Cold-stress-induced cytosolic Ca2+ signals can be decoded by different pathways. More recently, Ca2+ signal was reported to be transduced directly into the nucleus. The concentration of nuclear Ca2+ is monitored by a chimera protein formed by the fusion of aequorin to nucle‐ aoplasmin, which is also transiently increased after cold shock [95]. Aequorin possesses several EF-hand-type binding sites for Ca2+ ions. The binding of Ca2+ to these sites causes a conforma‐ tional change in aequorin which enables the monitoring of Ca2+ concentration. It has been reported that nuclear Ca2+ concentration peaks at about 5–10s later than the cytosolic Ca2+ [95]. The same authors have reported that nuclear Ca2+ signal may be initiated from the nuclear envelope and is assumed to be propagated by cytosolic Ca2+ transients in plants.

In the cytoplasm, a range of Ca2+ sensors have been reported, including calmodulin (*CaM*), CaM-like (*CMLs*), Ca2+-dependent protein kinases (*CDPKs*), Ca2+-and Ca2+/CaM-dependent protein kinase (*CCaMK*), CaM-binding transcription activator (*CAMTA*), calcineurin B-like proteins (*CBLs*) and *CBL*-interacting protein kinases (*CIPKs*) [98]. Some of the sensors work as negative regulators of cold tolerance in plants, e.g., calmodulin3, a SOS3-like or a CBL calciumbinding protein and a protein phosphatase 2C (*AtPP2CA*). The positive regulators, e.g., CDPKs and probably some *CBLs*, relay the Ca2+ signal by interacting with and regulating the family of *CIPKs*. For instance, *CBL1* has been shown to regulate cold response by interacting with *CIPK7* [99], whereas *CAMTA3* has been identified as a positive regulator of *CBF2/DREB1C* through binding to a regulatory element (*CG-1*, *vCGCGb*) in its promoter [100]. Although *CBF2/ DREB1C* was previously reported to negatively regulate *CBF1/DREB1B* and *CBF3/DREB1A*, its expression appears to be necessary for integrating cold-inducible calcium signaling with gene expression, but under transient and tight control to avoid repression of freezing tolerance. Both *CBF1*/*DREB1B* and *CBF3*/*DREB1A* are required for constitutive expression of coldinducible genes in *Arabidopsis,* and play an important role in cold acclimation (see discussion below).

Ca2+ influx into the cytoplasm also apparently activates phospholipase C (PLC) and D (PLD), which are precursors for IP3 and PA, respectively. IP3 activates IP3-gated Ca2+ channels that can amplify Ca2+ signatures in the cytoplasm, leading to higher induction of *COR* genes and CBFs, for review see [101].

There are some reports that the chloroplast may also play a role in sensing low temperature [98]. Cold stress is considered to cause excess photosystem II (PSII) excitation pressure, as a result of the imbalance between the capacity for harvesting light energy and the capacity to consume this energy on metabolic activity in the leaves, which probably leads to ROS gener‐ ation. The damaging effect of ROS on the photosynthetic apparatus presumably leads to photoinhibition, which occurs even under relatively low irradiance [102] and is apparently a mechanism of cold acclimation or freezing tolerance. ROS also acts as the second messenger and may reprogramme transcriptome changes through induction of Ca2+ signatures and activation of MAPKs and redox-responsive TFs. The MAPK cascades in *Arabidopsis* , including AtMEKK1/ANP1 (MAPKKK)–AtMKK2 (MAPKK)–AtMPK4/6 (MAPK), positively regulate cold acclimation in plants [103].

sulfoxide (DMSO) mediates the perception of membrane rigidification by mechanosensitive Ca2+channels [97]. Other upstream factors such as changes in the metabolic reactions and metabolite concentrations, protein and nucleic acid conformation could contribute to enhance perception of cold stress. These factors as well, either directly or indirectly, induce an increase in cytosolic Ca2+, which is a well-known upstream second messenger, regulating cold regulated

Cold-stress-induced cytosolic Ca2+ signals can be decoded by different pathways. More recently, Ca2+ signal was reported to be transduced directly into the nucleus. The concentration of nuclear Ca2+ is monitored by a chimera protein formed by the fusion of aequorin to nucle‐ aoplasmin, which is also transiently increased after cold shock [95]. Aequorin possesses several EF-hand-type binding sites for Ca2+ ions. The binding of Ca2+ to these sites causes a conforma‐ tional change in aequorin which enables the monitoring of Ca2+ concentration. It has been reported that nuclear Ca2+ concentration peaks at about 5–10s later than the cytosolic Ca2+ [95]. The same authors have reported that nuclear Ca2+ signal may be initiated from the nuclear

In the cytoplasm, a range of Ca2+ sensors have been reported, including calmodulin (*CaM*), CaM-like (*CMLs*), Ca2+-dependent protein kinases (*CDPKs*), Ca2+-and Ca2+/CaM-dependent protein kinase (*CCaMK*), CaM-binding transcription activator (*CAMTA*), calcineurin B-like proteins (*CBLs*) and *CBL*-interacting protein kinases (*CIPKs*) [98]. Some of the sensors work as negative regulators of cold tolerance in plants, e.g., calmodulin3, a SOS3-like or a CBL calciumbinding protein and a protein phosphatase 2C (*AtPP2CA*). The positive regulators, e.g., CDPKs and probably some *CBLs*, relay the Ca2+ signal by interacting with and regulating the family of *CIPKs*. For instance, *CBL1* has been shown to regulate cold response by interacting with *CIPK7* [99], whereas *CAMTA3* has been identified as a positive regulator of *CBF2/DREB1C* through binding to a regulatory element (*CG-1*, *vCGCGb*) in its promoter [100]. Although *CBF2/ DREB1C* was previously reported to negatively regulate *CBF1/DREB1B* and *CBF3/DREB1A*, its expression appears to be necessary for integrating cold-inducible calcium signaling with gene expression, but under transient and tight control to avoid repression of freezing tolerance. Both *CBF1*/*DREB1B* and *CBF3*/*DREB1A* are required for constitutive expression of coldinducible genes in *Arabidopsis,* and play an important role in cold acclimation (see discussion

Ca2+ influx into the cytoplasm also apparently activates phospholipase C (PLC) and D (PLD), which are precursors for IP3 and PA, respectively. IP3 activates IP3-gated Ca2+ channels that can amplify Ca2+ signatures in the cytoplasm, leading to higher induction of *COR* genes and CBFs,

There are some reports that the chloroplast may also play a role in sensing low temperature [98]. Cold stress is considered to cause excess photosystem II (PSII) excitation pressure, as a result of the imbalance between the capacity for harvesting light energy and the capacity to consume this energy on metabolic activity in the leaves, which probably leads to ROS gener‐ ation. The damaging effect of ROS on the photosynthetic apparatus presumably leads to photoinhibition, which occurs even under relatively low irradiance [102] and is apparently a mechanism of cold acclimation or freezing tolerance. ROS also acts as the second messenger

envelope and is assumed to be propagated by cytosolic Ca2+ transients in plants.

(*COR*) gene expression.

180 Plant Genomics

below).

for review see [101].

The downstream signals that promote the production of *COR* proteins and cold response to metabolites are reasonably discussed in references [95, 104]. Specific examples include the upregulation of the TFs, *CBF/DREB1s* (CRT (C-repeat)/DRE binding proteins) [103], which initiate the transcription process. The *CBF/DREB1* (mainly *CBF3/DREB1A*) pathway is controlled by a myelocytomatosis oncogene (*MYC*)-type TF, inducer of CBF expression1 (*ICE1*), which binds to the *MYC* recognition cis-elements (*CANNTG*) in the promoter of *CBF3*/ *DREB1A,* and induces the expression of *CBF3*/*DREB1A* and its regulons during cold acclima‐ tion [105]. The function of *ICE1* in cold response is conserved; and overexpression of *Arabi‐ dopsis ICE1* improves chilling tolerance and enhances the accumulation of soluble sugars and proline concentration in cucumber [106]. In rice, *OsICE1* and *OsICE2* are induced by cold stress and sequentially upregulate *OsDREB1B*, rice heat shock factor A3 (*OsHsfA3*) and rice trehalose 6-phosphate phosphatase (*OsTPP1*). The *CBF*/*DREB1s* can bind to *CRT/DRE* cis-elements, A/ GCCGAC, in the promoter of *COR* genes to regulate expression of *COR* genes [107]. Moreover, *CBF/DREB1* genes are organized in tandem (*CBF1/DREB1B-CBF3/DREB1A-CBF2/DREB1C*) on *Arabidopsis* chromosome IV and have been reported to be induced at the same time, suggesting that combining these TFs in one genotype could probably improve cold tolerance. However, the inconsistent target specificity amongst the three *CBF* factors in *CBF/DREB1*-overexpressing transgenic plants reveals variability in their roles [108]. Indeed, *CBF2/DREB1C* has been shown to be a negative regulator of both *CBF1/DREB1B* and *CBF3/DREB1A* [109], while *CBF1/ DREB1B* and *CBF3/DREB1A* act as positive regulators of cold acclimation by activating the same subset of *CBF/DREB1*-target genes [110]. *CBF1/DREB1B* and *CBF3/DREB1A* are therefore concertedly required to induce the whole *CBF*/*DREB1*-regulon to complete the development of cold acclimation, while the expression of *CBF2/DREB1C* is tightly controlled to avoid its negative modulation of *CBF1/DREB1B* and *CBF3/DREB1A*. The exact mechanism by which this happens is unknown.

Downstream of these TFs are *COR* genes, which are mainly linked to the onset of tolerance mechanisms and ultimately lead to acclimation. Genes encoding for annexin; hyper-sensitiveinduced response (HIR) protein families (e.g., prohibitins and stomatins); dehydrins (e.g., 25 kDa dehydrin-like protein, *ERD14*, and *cold acclimation-specific protein 15* (*CAS15*)); antioxidants (e.g., superoxide dismutase, catalase and ascorbate peroxidase); *HSPs* (e.g., *HSP70* family being the most abundant); defence-related proteins such as protein disulfide isomerase; disease resistance response proteins, peptidylprolyl isomerase *Cyp2* and cysteine proteinase; amino acids, polyamines and polyols; and cellulose synthesis, such as UDP-glucose pyro‐ phosphorylase, are commonly reported in expression studies [111]. Several metabolismassociated proteins, including carbohydrate metabolism enzymes, such as phosphogluconate dehydrogenase, NADP-specific isocitrate dehydrogenase, fructokinase, cytoplasmic malate dehydrogenase, pyruvate orthophosphate dikinase precursors (PPDK), aconitate hydratase, glycine dehydrogenase and enolase, have also been reported to be activated during cold stress [112]. Thus, several genes and the corresponding proteins are associated with the regulation of the metabolic pathways operating under cold stress.

However, identification of functional polymorphism in these genes remains a daunting task. A similar challenge is observed in the QTLs identified, so far, in various crops, including maize, barley, rice, wheat, sorghum and many other economically important crops. Identification of effective cold sensors also remains elusive, as multiple primary sensors are thought to be involved in sensing low temperatures. Thus, a comprehensive understanding of the defence mechanism from sensors, cold signaling, to the defence response will require further research on both upstream and downstream regulations of *ICE1*-*CBF*/*DREB1*-dependent pathway, as well as proteins that may be functioning independent of this pathway.

#### **5. Advances in plant tolerance to salinity**

Salinity is increasingly becoming a major threat to crop production, particularly due to inappropriate irrigation regimes and increasing use of brackish water for irrigation. As much as 6% of the total world land is subjected to salinity [113], and more than 20% of irrigated land is affected by salinity [114]. Moreover, major reductions in cultivated land area, crop produc‐ tivity and quality that have been reported in the recent past are due to salt-induced stress [115]. Climate-change-associated rise in sea levels and coastal floods are expected to further con‐ tribute to this phenomenon in the future.

Salt stress in plants occurs when electrical conductivity of saturated soil paste extract (ECe) reaches 4.0 deci-Siemens per meter (dS/m; approximately 40 mM NaCl). The minimum level may, however, vary from crop to crop. For instance, the salinity threshold for rice is 3.0 dS/m [163]. Beyond this threshold, a yield reduction of 12% per dS/m has been reported to occur. When plants gradually accumulate salts, osmotic stress, nutrient imbalance and oxidative stress occur [116]. These salt effects disrupt intracellular ion homeostasis, membrane function and metabolic activity [117]. As secondary effects, salt-induced osmotic stress decreases root epidermal cell division and elongation rates, reducing primary root growth, eventually resulting in inhibition of growth and reduction of crop yields [118].

Alkalinity stress is a heightened version of salinity stress which has been reported to be much harsher than equimolar salinity, especially at neutral pH [119]. Although it is fairly understood that alkalinity causes osmotic challenge and ionic stress, and precipitates nutrients such as metallic micronutrients and phosphates, and disrupts the integrity of root cellular structure, the molecular signals and adaptive mechanisms are not well understood. Because many saline soils are also alkaline due to the presence of sodium (Na) carbonates, in this section we will exclusively focus on salinity, which is wide spread, and has been extensively researched and discussed in several studies.

To cope with saline soils, plants deploy a range of mechanisms that range from exclusion of Na+ from the cells to tolerance within the cells. When plants are subjected to salinity, a series of responses ranging from genetic molecular expression through biochemical metabolism to physiological processes occur (Figure 5).

[112]. Thus, several genes and the corresponding proteins are associated with the regulation

However, identification of functional polymorphism in these genes remains a daunting task. A similar challenge is observed in the QTLs identified, so far, in various crops, including maize, barley, rice, wheat, sorghum and many other economically important crops. Identification of effective cold sensors also remains elusive, as multiple primary sensors are thought to be involved in sensing low temperatures. Thus, a comprehensive understanding of the defence mechanism from sensors, cold signaling, to the defence response will require further research on both upstream and downstream regulations of *ICE1*-*CBF*/*DREB1*-dependent pathway, as

Salinity is increasingly becoming a major threat to crop production, particularly due to inappropriate irrigation regimes and increasing use of brackish water for irrigation. As much as 6% of the total world land is subjected to salinity [113], and more than 20% of irrigated land is affected by salinity [114]. Moreover, major reductions in cultivated land area, crop produc‐ tivity and quality that have been reported in the recent past are due to salt-induced stress [115]. Climate-change-associated rise in sea levels and coastal floods are expected to further con‐

Salt stress in plants occurs when electrical conductivity of saturated soil paste extract (ECe) reaches 4.0 deci-Siemens per meter (dS/m; approximately 40 mM NaCl). The minimum level may, however, vary from crop to crop. For instance, the salinity threshold for rice is 3.0 dS/m [163]. Beyond this threshold, a yield reduction of 12% per dS/m has been reported to occur. When plants gradually accumulate salts, osmotic stress, nutrient imbalance and oxidative stress occur [116]. These salt effects disrupt intracellular ion homeostasis, membrane function and metabolic activity [117]. As secondary effects, salt-induced osmotic stress decreases root epidermal cell division and elongation rates, reducing primary root growth, eventually

Alkalinity stress is a heightened version of salinity stress which has been reported to be much harsher than equimolar salinity, especially at neutral pH [119]. Although it is fairly understood that alkalinity causes osmotic challenge and ionic stress, and precipitates nutrients such as metallic micronutrients and phosphates, and disrupts the integrity of root cellular structure, the molecular signals and adaptive mechanisms are not well understood. Because many saline soils are also alkaline due to the presence of sodium (Na) carbonates, in this section we will exclusively focus on salinity, which is wide spread, and has been extensively researched and

To cope with saline soils, plants deploy a range of mechanisms that range from exclusion of Na+ from the cells to tolerance within the cells. When plants are subjected to salinity, a series of responses ranging from genetic molecular expression through biochemical metabolism to

of the metabolic pathways operating under cold stress.

182 Plant Genomics

**5. Advances in plant tolerance to salinity**

tribute to this phenomenon in the future.

discussed in several studies.

physiological processes occur (Figure 5).

well as proteins that may be functioning independent of this pathway.

resulting in inhibition of growth and reduction of crop yields [118].

**Figure 5.** Adaptive mechanisms of salt tolerance. Cellular functions that would apply to all cells within the plant are the first adaptation mechanisms, followed by the functions of specific tissues or organs. Most of these functions are explained in the text (modified from [140].

Amongst the receptor proteins identified as the first detectors of salt stress are G-proteincoupled receptors, ion channel, receptor-like kinase or histidine kinase. These receptors transduce signals that generate secondary signals such as Ca2+, inositol phosphates, ROS, nitric oxide (NO) and ABA. The signaling pathway associated with increased concentration of cytosolic Ca2+ is the most reported.

Cytosolic Ca2+ activates calcium-dependent protein kinases (*CDPKs*), calcineurin B-like proteins (*CBLs*) and CBL-interacting protein kinases (*CIPKs*) to transduce signals to down‐ stream protein activity and gene transcription [120]. Transcription factors such as calmodulinbinding transcription activators (*CAMTAs*), GT element-binding-like proteins (*GTLs*) and MYBs have been reported to be activated by Ca2+/calmodulin directly [121–123]. Other commonly expressed TFs in response to salt stress include the basic leucine zipper (*bZIP*), e.g., *OsbZIP71* in rice [124], *WRKY* [125], *APETALA2/ETHYLENE RESPONSE FACTOR* (*AP2/ERF*) [126], *MYB* [127], basic helix–loop–helix [128] and *NAC* [42] families. These TFs regulate the expression of genes related to water potential decrease, which results from osmotic stress caused by salinity.

Downstream of these TFs, there are several genes associated with salinity tolerance. The most reported are genes encoding for salt exclusion proteins, e.g., *SOS1*, cation:proton **antiporter family**1 of Na+ /H+ anti-porters, salt compartmentalization genes, e.g., *vacuolar H* <sup>+</sup> *-pyrophos‐ phatase* [129], and osmotic adjustment, e.g., *pyrroline-5-carboxylate synthetase* [130].

The salt overly sensitive (*SOS*) Ca2+ sensor regulatory mechanism is believed to be conserved in higher plants including monocots and dicots [131]. *SOS* consists of three functionally interlinked proteins, *SOS3*/*SCaBP8–SOS2–SOS1*. *SOS3* mainly functions in the roots, while *CBL10*/*SCaBP8*, an alternative regulator of *SOS2* that has been described as *SOS3*-like, primarily functions in the shoots. At high Na+ concentrations, increased influx of Ca2+ is perceived by *SOS3* that encodes a myristoylated EF hand (a domain of five serially repeated helix–loop–helix calcium-binding motifs). Upon Ca2+ binding, a conformational change occurs and *SOS3* activates the downstream serine/threonine protein kinase, *SOS2*, and recruits it to the plasma membrane. Subsequently, the *SOS3–SOS2* complex stimulates the plasma mem‐ brane-localized Na+ /H+ anti-porter (*SOS1*), leading to the extrusion of the excess Na+ out of the cells [132]. Different from *SOS3, SOS3*-like proteins (*CBL10*/*SCaBP8*) are phosphorylated by their interacting protein kinases apparently regulating *CBL*/*SCaBP*–*CIPK*/*PKS* modules [133].

Besides extruding Na+ , the adaptive *SOS* module also links cytosolic Na+ with Ca2+ binding proteins. The PM-localized *NHX7/SOS1* and the intracellular localized cation:proton **antiport‐ er family**1 (*CPA1*) of Na+ /H+ anti-porters (*NHX1-NHX4*; tonoplast-localized) are a ubiquitous family of transporters that mediate the exchange of K+ or Na+ for H+ while regulating cytoplas‐ mic salt overloads [134].In the cytosol, increased influx of Ca2+ associated with excess Na+ levels is perceived by Ca2+-binding calmodulins/calmodulin-like proteins, which interact with *NHX1* transporters to sequester excess Na+ in the vacuole. In *Arabidopsis*, a calmodulin-like protein, *AtCaM15,* regulates the tonoplast localized *AtNHX1* [135]. The interaction of *AtCaM15* with *AtNHX1* occurs in the vacuolar lumen and is dependent on Ca2+ and pH. The C-terminus of *AtNHX1* has been shown to localize in the cytosol, which might suggest that this strategic placementis targetedforphosphorylationbyproteinkinases orfor sensing changes in cytosolic pH. However, the protein kinase targeting *AtNHX1* is unknown, and further studies on the interaction of this transporter with other proteins, especially protein kinases, will be necessary.

Interestingly, at moderate salt levels, the role of these transporters is less clear. Indeed, the *nhx1/nhx2* **double mutants** are not sensitive to moderate external Na+ concentrations, yet they are sensitive to moderate external K+ concentrations, for review see [134]. Conversely, the trans-Golgi network-localized *NHX* double knockouts, *nhx5/nhx6*, highly respond to moderate salinity and interfere with vesicle trafficking to the vacuole. This suggests that the endosomal *NHXs* are more sensitive to Na+ accumulation than vacuolar *NHXs*. This difference has implications on Na+ tolerance in plants. Recently, another *CPA* family member, a cation/H+ exchanger (*CHX*), *GmSALT3*, was shown to improve shoot Na+ exclusion and salt tolerance in soybean [136]. Fluorescent protein fusions suggested that *GmSALT3* and other *CHX* proteins are localized to the endoplasmic reticulum, further indicating that endosomal *NHXs* could be more reliable in sensing abnormal Na+ levels in the cell and has a positive implication on salt tolerance in plants.

Other genes encoding for *Mannose-1-phosphate guanyl transferase* **(***OsMPG1***)** and **the rice** homologue of Shaker family K+ channel *KAT1* (*OsKAT1*) have also been reported to confer salinity tolerance [137, 138]. *OsMPG1* is an important enzyme for the biosynthesis of ascorbic acid in plants, whereas *OsKAT1* reduces the cellular Na+ to K+ ratio by increasing the cellular K+ content. Another rice potassium transporter (*OsHAK5*) was shown to accumulate more K+ and less Na+ when constitutively expressed in *Nicotiana tabacum* cv. Bright Yellow 2 under salinity stress [198]. Several other genes were recently identified by Chen et al. [139] while studying the halophyte seashore Paspalum (*Paspalum vaginatum*).

The salt overly sensitive (*SOS*) Ca2+ sensor regulatory mechanism is believed to be conserved in higher plants including monocots and dicots [131]. *SOS* consists of three functionally interlinked proteins, *SOS3*/*SCaBP8–SOS2–SOS1*. *SOS3* mainly functions in the roots, while *CBL10*/*SCaBP8*, an alternative regulator of *SOS2* that has been described as *SOS3*-like,

perceived by *SOS3* that encodes a myristoylated EF hand (a domain of five serially repeated helix–loop–helix calcium-binding motifs). Upon Ca2+ binding, a conformational change occurs and *SOS3* activates the downstream serine/threonine protein kinase, *SOS2*, and recruits it to the plasma membrane. Subsequently, the *SOS3–SOS2* complex stimulates the plasma mem‐

cells [132]. Different from *SOS3, SOS3*-like proteins (*CBL10*/*SCaBP8*) are phosphorylated by their interacting protein kinases apparently regulating *CBL*/*SCaBP*–*CIPK*/*PKS* modules [133].

proteins. The PM-localized *NHX7/SOS1* and the intracellular localized cation:proton **antiport‐**

mic salt overloads [134].In the cytosol, increased influx of Ca2+ associated with excess Na+ levels is perceived by Ca2+-binding calmodulins/calmodulin-like proteins, which interact with *NHX1*

*AtCaM15,* regulates the tonoplast localized *AtNHX1* [135]. The interaction of *AtCaM15* with *AtNHX1* occurs in the vacuolar lumen and is dependent on Ca2+ and pH. The C-terminus of *AtNHX1* has been shown to localize in the cytosol, which might suggest that this strategic placementis targetedforphosphorylationbyproteinkinases orfor sensing changes in cytosolic pH. However, the protein kinase targeting *AtNHX1* is unknown, and further studies on the interaction of this transporter with other proteins, especially protein kinases, will be necessary.

Interestingly, at moderate salt levels, the role of these transporters is less clear. Indeed, the *nhx1/nhx2* **double mutants** are not sensitive to moderate external Na+ concentrations, yet they

Golgi network-localized *NHX* double knockouts, *nhx5/nhx6*, highly respond to moderate salinity and interfere with vesicle trafficking to the vacuole. This suggests that the endosomal

exchanger (*CHX*), *GmSALT3*, was shown to improve shoot Na+ exclusion and salt tolerance in soybean [136]. Fluorescent protein fusions suggested that *GmSALT3* and other *CHX* proteins are localized to the endoplasmic reticulum, further indicating that endosomal *NHXs* could be

Other genes encoding for *Mannose-1-phosphate guanyl transferase* **(***OsMPG1***)** and **the rice** homologue of Shaker family K+ channel *KAT1* (*OsKAT1*) have also been reported to confer salinity tolerance [137, 138]. *OsMPG1* is an important enzyme for the biosynthesis of ascorbic

content. Another rice potassium transporter (*OsHAK5*) was shown to accumulate more K+

, the adaptive *SOS* module also links cytosolic Na+

anti-porter (*SOS1*), leading to the extrusion of the excess Na+ out of the

anti-porters (*NHX1-NHX4*; tonoplast-localized) are a ubiquitous

for H+

in the vacuole. In *Arabidopsis*, a calmodulin-like protein,

concentrations, for review see [134]. Conversely, the trans-

accumulation than vacuolar *NHXs*. This difference has

levels in the cell and has a positive implication on salt

ratio by increasing the cellular

tolerance in plants. Recently, another *CPA* family member, a cation/H+

to K+

or Na+

concentrations, increased influx of Ca2+ is

with Ca2+ binding

while regulating cytoplas‐

primarily functions in the shoots. At high Na+

/H+

/H+

family of transporters that mediate the exchange of K+

brane-localized Na+

184 Plant Genomics

Besides extruding Na+

**er family**1 (*CPA1*) of Na+

transporters to sequester excess Na+

are sensitive to moderate external K+

*NHXs* are more sensitive to Na+

more reliable in sensing abnormal Na+

acid in plants, whereas *OsKAT1* reduces the cellular Na+

implications on Na+

tolerance in plants.

K+

Another process, downstream of transcriptional regulatory networks, involves accumulation of sufficient solutes (e.g., proline and glycine betaine) to balance extra osmotic pressure in the soil solution to maintain turgor [140]. Moreover, plants can also accumulate sufficient Na+ and Cl<sup>−</sup> to balance those in the soil solution, but this is tightly controlled through strict ionic regulation in various cell compartments ('tissue tolerance'). These tolerance strategies are achieved through a series of ion transporters and their localization in key cell types. Na+ /H+ anti-porter proteins are the key regulators of these tolerance strategies. Examples include *TaHKT1;5-D* protein, which maintains high cytosolic K+ /Na+ ratios in bread wheat shoots by restricting Na+ loads in the root xylem before entering the shoot [141]. Recently, the introgres‐ sion of the *Triticum monococcum HKT1;5-A* into durum wheat improved shoot Na+ exclusion and improved grain yield in the field by 25% [142], indicating the significance and functional stability of these transporters even in interspecific hybrids. Additionally, Eswaran et al. [143] used the yeast Full-length cDNA Over-eXpressor (*FOX*) gene hunting to identify several saltresponsive genes in *Jatropha curcas*. The late embryogenesis-abundant protein **(***LEA-5***),** aquaporins and a cytosolic ascorbate peroxidase-1 (*Apx1*) were amongst the identified genes involved in salinity tolerance. *LEA5* are group 5 LEA genes that have been shown to play roles in the combining of concentrated ions and dehydration [143]. This group of LEA proteins have attracted fewer investigations and will require further studies at salt stress conditions. Aquaporin proteins are members of a large multigenic family that regulates a large proportion of water transport across membranes. Aquaporins are rapidly influenced both transcription‐ ally and post-translationally, and enhance salt stress tolerance in plants. For instance, a plasma membrane intrinsic protein (*GmPIP1;6*, which belongs to a subfamily of aquaporin specifically located in the PM) in soybean increases shoot Na+ exclusion and improves the seed yield from a saline field [144]. Orthologous *PIP* proteins are found in *Arabidopsis* , tobacco, barley, rice and wheat. For instance, *GmPIP1;6* is the ortholog of *AtPIP1;2, NtAQP1, HvPIP1;6/1;1* and *TaAQP8.* Overexpression of *NtAQP1* in tobacco increases photosynthetic rate, water use efficiency and yield under salt stress [145]. Overexpression of *TaAQP8, TaNIP* and *TaAQP7* genes in Arabidopsis or tobacco also increases salt tolerance of transgenic plants [146–148]. Root stellar cells also confer control over shoot Cl<sup>−</sup> accumulation [149]. The expression of *GmPIP1;6* in roots was recently shown to be correlated with rapid and longer term changes in root hydraulic conductance (*L* o) in response to shoot treatments and appeared to be more concentrated in stellar tissue [150]. These results indicated that *GmPIP1;6* could be the protein responsible for the control of root water transport, particularly in response to shoot signals. More recently, overexpression of *GmPIP1;6* was shown to significantly increase salt tolerance of soybean by improving root *L* o and Na+ exclusion, which provided additional evidence that *GmPIP1;6*'s activity is in the stellar tissue. However, as there is no conclusive interactive or independent role of *AQPs* in salt tolerance, *AQPs* could instead be playing an indirect role through their impact on osmotically driven water and solute flow in roots and leaves. Further research will probably provide clear insight as to whether *GmPIP1;6* is responsible for salt regulation in the stellar cells, and whether there are other co-factors involved.

Wheat tonoplast intrinsic protein (*TIP2; 2*) is also reported to enhance salt tolerance [151]. However, the functional role of this protein is regulated by methylation following salt treatment as is *HKT1* in *Arabidopsis* [152]. This suggests that aquaporin methylation could also play a role in regulating salt tolerance in plants and is worth further exploration.

Accumulation of ROS scavenging enzymes has also been reported to lower cellular damage, maintain photosynthetic energy capture, and improve shoot and root growth under saline conditions. For instance, salt-stress-induced accumulation of SOD has been reported to play a protective role in *Canola*, *S. europaea*, *S. chilense* and *K. candel*[153–155]. Furthermore, expression levels of anti-oxidant enzymes *APX* (e.g.,*Apx1***)** *, Trx, Prx, GPX* and *GST* were observed to be enhanced in *Tangut nitraria* [156] under salinity conditions. Moreover, the same authors have reported that a photosynthetic enzyme, Ferredoxin—NADP (+) reductase (*FNR*), activity also increased in *T. nitraria*. Pea plants grown under saline stress also showed an enhancement of both APX activity and S-nitrosylated APX, which suggests that APX plays a significant role in plant tolerance to salt stress. However, apart from ascorbic acid biosynthesis, which has been shown to be modulated by *OsMPG1,* the molecular regulation of most anti-oxidants in response to salinity remains to be explored.

The recent discovery that salt-tolerant plant growth promoting rhizobacteria (PGPR) popula‐ tions reduce Na+ concentration in the plant shoots [157] provides further insights into plant tolerance to saline conditions. The PGPRs increase the expression of stress-responsive TFs, induce greater proline synthesis, enhance ROS scavenging and improve plant biomass under salinity stress. Therefore, treatment with rhizospheric organisms, and understanding the mechanisms associated with these PGPRs leading to salt tolerance, is an attractive option to improve crop yields under saline conditions.

Fundamental insights into genetic control of salt tolerance mechanisms have also led to identification of more than 100 QTLs in various crops including *Arabidopsis* , barley, rice and wheat, amongst others. The earlier mentioned **salt overly sensitive** (*SOS*) pathway genes and *AtCIPK16* are amongst the salt tolerance factors spanning several QTLs identified [158]. *CIPK16* is an SNF1-related kinase/CBL-interacting protein kinase, underlying a quantitative trait locus for Na+ exclusion in the *Arabidopsis* Bay-0×Shahadara mapping population. *CIPK16* was also recently shown to be expressed in barley and improves Na+ exclusion and biomass in a saline field.

Taken together, several genes and proteins have been shown to enhance salt tolerance in plants. However, the limited number of genes with functional polymorphism for salt tolerance makes it difficult to employ marker-assisted breeding for salt tolerance traits. In addition, the complex molecular mechanisms underlying the difference between seedling and reproductive stage salt tolerance in plants, e.g. rice [159], suggest the need for further research. The importance of the apoplastic bypass flow in delivering Na+ to the xylem, thus reducing leaf Na+ concen‐ tration and improving tolerance as suggested by [160], is also worth exploring further. Moreover, more insights into the molecular regulation of salt response will provide avenues for combining tolerance mechanisms to develop varieties that are widely adapted to salt stress.

#### **6. Advances in plant tolerance to submergence/flooding**

Wheat tonoplast intrinsic protein (*TIP2; 2*) is also reported to enhance salt tolerance [151]. However, the functional role of this protein is regulated by methylation following salt treatment as is *HKT1* in *Arabidopsis* [152]. This suggests that aquaporin methylation could also

Accumulation of ROS scavenging enzymes has also been reported to lower cellular damage, maintain photosynthetic energy capture, and improve shoot and root growth under saline conditions. For instance, salt-stress-induced accumulation of SOD has been reported to play a protective role in *Canola*, *S. europaea*, *S. chilense* and *K. candel*[153–155]. Furthermore, expression levels of anti-oxidant enzymes *APX* (e.g.,*Apx1***)** *, Trx, Prx, GPX* and *GST* were observed to be enhanced in *Tangut nitraria* [156] under salinity conditions. Moreover, the same authors have reported that a photosynthetic enzyme, Ferredoxin—NADP (+) reductase (*FNR*), activity also increased in *T. nitraria*. Pea plants grown under saline stress also showed an enhancement of both APX activity and S-nitrosylated APX, which suggests that APX plays a significant role in plant tolerance to salt stress. However, apart from ascorbic acid biosynthesis, which has been shown to be modulated by *OsMPG1,* the molecular regulation of most anti-oxidants in

The recent discovery that salt-tolerant plant growth promoting rhizobacteria (PGPR) popula‐

tolerance to saline conditions. The PGPRs increase the expression of stress-responsive TFs, induce greater proline synthesis, enhance ROS scavenging and improve plant biomass under salinity stress. Therefore, treatment with rhizospheric organisms, and understanding the mechanisms associated with these PGPRs leading to salt tolerance, is an attractive option to

Fundamental insights into genetic control of salt tolerance mechanisms have also led to identification of more than 100 QTLs in various crops including *Arabidopsis* , barley, rice and wheat, amongst others. The earlier mentioned **salt overly sensitive** (*SOS*) pathway genes and *AtCIPK16* are amongst the salt tolerance factors spanning several QTLs identified [158]. *CIPK16* is an SNF1-related kinase/CBL-interacting protein kinase, underlying a quantitative trait locus

recently shown to be expressed in barley and improves Na+ exclusion and biomass in a saline

Taken together, several genes and proteins have been shown to enhance salt tolerance in plants. However, the limited number of genes with functional polymorphism for salt tolerance makes it difficult to employ marker-assisted breeding for salt tolerance traits. In addition, the complex molecular mechanisms underlying the difference between seedling and reproductive stage salt tolerance in plants, e.g. rice [159], suggest the need for further research. The importance

tration and improving tolerance as suggested by [160], is also worth exploring further. Moreover, more insights into the molecular regulation of salt response will provide avenues for combining tolerance mechanisms to develop varieties that are widely adapted to salt stress.

exclusion in the *Arabidopsis* Bay-0×Shahadara mapping population. *CIPK16* was also

to the xylem, thus reducing leaf Na+ concen‐

concentration in the plant shoots [157] provides further insights into plant

play a role in regulating salt tolerance in plants and is worth further exploration.

response to salinity remains to be explored.

improve crop yields under saline conditions.

of the apoplastic bypass flow in delivering Na+

tions reduce Na+

186 Plant Genomics

for Na+

field.

Over the past 25 years, yield losses caused by flooding have been increasing in various parts of the world, including the United States, China, Europe, Pakistan and Australia [161, 162]. Flooding is expected to increase as a result of erratic weather patterns, including frequent and lengthy storms associated with climate change, and could severely affect food production if mitigation measures are not sought.

Generally, submergence/flooding stress results from reduced oxygen levels in the plant root zone due to the low diffusion rate of oxygen in water. Submergence inhibits electron flows that underpin photosynthesis and aerobic respiration from the air causing energy shortfalls that can prove injurious to the plant [162]. Flooding also leads to accumulation of gases such as ethylene and carbondioxide by preventing their diffusive escape and oxidative breakdown [163]. A high concentration of ethylene limits root extension, while carbon dioxide can severely damage plant roots. Trapped carbondioxide may also form bicarbonate ions that can accen‐ tuate the effect of high lime content, leading to iron unavailability and chlorosis. The hypoxic environment also leads to restricted production of ATP, forcing cells to rely on glycolysis and fermentation to generate ATP and regenerate NAD+ to cope with the energy crisis [164]. Moreover, survival through prolonged inundation hypoxia involves the use of inorganic pyrophosphate (PPi) as an alternative energy source and induction of enzymes that reduce reactive oxygen species (ROS) or cytoplasmic acidosis, which are equally energy consuming processes. Because translation is a tremendously energy-intensive process, protein synthesis is affected in such oxygen-deprived conditions. Subsequently, essential metabolic processes slow down affecting the overall growth of the plant. In rice, soybean and wheat, various deleterious effects have been observed, such as suppression or reduction of hypocotyl and root elongation, and suppression of lateral root development [162, 164, 165].

Plant tolerance to submergence/flooding is generally a metabolic adaptation in response to anaerobiosis that enables cells to maintain their integrity so that the plant survives hypoxia without major damages. Several defence-related changes occur in submergence tolerant plants, including anatomical (e.g. formation of higher aerenchyma tissue in the nodal region in rice), physiological (more shoot elongation) and biochemical (inhibition of chlorophyll degradation, less utilization of storage carbohydrates and increased activity of anti-oxidative enzymes). At the molecular level, plants need to adapt these several changes in their gene expression profiles as well as cellular protein profiles. We will focus more on molecular adaptation, with a preference for adaptive QTLs, genes and proteins of significance to crop tolerance to flooding.

One of the early responses to submergence involves the differential regulation of a suite of TFs belonging to the ethylene response factor (*ERFs*) gene family. In rice, a major QTL locus belonging to ERF family, which is responsible for submergence tolerance, was mapped to chromosome 9, designated as Submergence1 (*Sub1*) [166]. This QTL was reported to account for about 70% of the phenotypic variation under submergence [167]. One of the genes adhered to *Sub1* locus is *Sub1A*, which limits shoot elongation during submergence by repressing gibberellic acid (GA) levels and modulating GA signaling. In the process, the consumption of energy reserves is reduced, and upon de-submergence, genotypes with *SUB1A* are able to resume development when flood water subsides.

Two *ERFs*, *SNORKEL1* (*SK1*) and *SNORKEL2* (*SK2*) from Thai deep water accession C9285, also confer submergence adaptation in deep water rice by inducing rapid internode elongation [168]. SKs have also been found in the genomes of accessions of wild *O. rufipogon* from Asia and *O. glumaepatula* from South America but missing in most cultivated rice varieties, which suggests that an ancient genomic region of *Oryza* was lost during the establishment of rice grown in shallow paddies, but was safeguarded in deep water ecosystems. More recently, two QTLs on chromosome 3 and 12, including *O. sativa*-*GROWTH-REGULATING FACTOR7* (*OsGRF7*), were reported to be involved in GA-dependent stem elongation and meristem maintenance in deep water rice [169]. *OsGRF7* on chromosome 12 could probably be a regulator of GA responsiveness for internode elongation, whereas a QTL on chromosome 3 and other QTLs may regulate the *DELLA* function or act downstream of GA signaling. The *DELLA* proteins are the key regulators of GA signaling and suppress plant growth in the absence of GA.

In maize, a major QTL, *Subtol6*, was also recently shown to be associated with submergence tolerance [170]. Based on the expression differences between the parent inbreds, *subtol6* is associated with *HEMOGLOBIN2* (*HB2*), a gene which was previously reported to be associated with plant survival in low oxygen or low ATP conditions [171]. The same authors indicate that haemoglobin proteins in maize repress ROS levels and maintain the energy status of maize cells during hypoxia. Other notable candidate genes, including genes related to *ABA-INSEN‐ SITIVE3* (*ABI3*)/*VIVIPAROUS1* (*RAV1*), genes related to accumulation and metabolism of carbohydrates, e.g., alpha subunit of *PYROPHOSPHATE-DEPENDENT FRUCTOSE-6- PHOSPHATE 1-PHOSPHOTRANSFERASE* (*PFP*) and *ALCOHOL DEHYDROGENASE1* (*ADH1*), have been reported to be highly upregulated in response to submergence [170].

In association with these tolerance genes, a number of other QTLs have also been identified in various crops, including barley, wheat, *Brassica napus*, maize and *Lolium perenne*, amongst others.

In addition to these QTLs studies, several proteins have been reported to enhance submergence tolerance in plants. Enzymes involved in primary metabolism are differentially regulated in response to flooding. For instance, UDP-glucose dehydrogenase, UDP-glucose pyrophos‐ phorylase, β-glucosidase G4 and rhamnose synthase, aspartate aminotransferase and lipoxy‐ genase have been reported as early flood-responsive proteins in rice and soybeans [164, 172]. The same authors indicate that phenlypropanoid pathway and cell wall synthesis enzymes decrease in abundance during flooding, which could be an energy-conserving adaptive strategy towards enhanced flooding tolerance.

Together these findings suggest that during flooding several processes are inhibited to reduce energy consumption. It is crucial for the plant to preserve some carbohydrates for release of energy to support further growth when the water level recedes. The regulatory genes in this category may also serve some ABA-mediated water stress recovery and inhibition of GAinduced internodal elongation as quiescence strategies adopted by plants [173]. On the other

hand, avoidance mechanisms employed under deep water conditions involve rapid internode elongation. In *R. palustris*, there are populations that show either the quiescence response or the avoidance response to submergence. This divergence shows that quiescence and avoidance are two strategies that can be employed by plants depending on the duration of flooding. Quiescence can be the optimal strategy for short-duration 'flash' floods, whereas avoidance via growth could be more reliable in prolonged deep flooding. Notwithstanding the abovementioned tolerance genes and proteins, a deeper insight into the molecular regulation of quiescence and avoidance, and the associated regulatory networks, is still needed to provide sustainable avenues for improving plants specific to either flooding condition or able to grow in both.

#### **7. Advances in plant tolerance to nutrient imbalances**

#### **7.1. Tolerance to nutrient deficiency**

energy reserves is reduced, and upon de-submergence, genotypes with *SUB1A* are able to

Two *ERFs*, *SNORKEL1* (*SK1*) and *SNORKEL2* (*SK2*) from Thai deep water accession C9285, also confer submergence adaptation in deep water rice by inducing rapid internode elongation [168]. SKs have also been found in the genomes of accessions of wild *O. rufipogon* from Asia and *O. glumaepatula* from South America but missing in most cultivated rice varieties, which suggests that an ancient genomic region of *Oryza* was lost during the establishment of rice grown in shallow paddies, but was safeguarded in deep water ecosystems. More recently, two QTLs on chromosome 3 and 12, including *O. sativa*-*GROWTH-REGULATING FACTOR7* (*OsGRF7*), were reported to be involved in GA-dependent stem elongation and meristem maintenance in deep water rice [169]. *OsGRF7* on chromosome 12 could probably be a regulator of GA responsiveness for internode elongation, whereas a QTL on chromosome 3 and other QTLs may regulate the *DELLA* function or act downstream of GA signaling. The *DELLA* proteins are the key regulators of GA signaling and suppress plant growth in the absence of

In maize, a major QTL, *Subtol6*, was also recently shown to be associated with submergence tolerance [170]. Based on the expression differences between the parent inbreds, *subtol6* is associated with *HEMOGLOBIN2* (*HB2*), a gene which was previously reported to be associated with plant survival in low oxygen or low ATP conditions [171]. The same authors indicate that haemoglobin proteins in maize repress ROS levels and maintain the energy status of maize cells during hypoxia. Other notable candidate genes, including genes related to *ABA-INSEN‐ SITIVE3* (*ABI3*)/*VIVIPAROUS1* (*RAV1*), genes related to accumulation and metabolism of carbohydrates, e.g., alpha subunit of *PYROPHOSPHATE-DEPENDENT FRUCTOSE-6- PHOSPHATE 1-PHOSPHOTRANSFERASE* (*PFP*) and *ALCOHOL DEHYDROGENASE1* (*ADH1*), have been reported to be highly upregulated in response to submergence [170].

In association with these tolerance genes, a number of other QTLs have also been identified in various crops, including barley, wheat, *Brassica napus*, maize and *Lolium perenne*, amongst

In addition to these QTLs studies, several proteins have been reported to enhance submergence tolerance in plants. Enzymes involved in primary metabolism are differentially regulated in response to flooding. For instance, UDP-glucose dehydrogenase, UDP-glucose pyrophos‐ phorylase, β-glucosidase G4 and rhamnose synthase, aspartate aminotransferase and lipoxy‐ genase have been reported as early flood-responsive proteins in rice and soybeans [164, 172]. The same authors indicate that phenlypropanoid pathway and cell wall synthesis enzymes decrease in abundance during flooding, which could be an energy-conserving adaptive

Together these findings suggest that during flooding several processes are inhibited to reduce energy consumption. It is crucial for the plant to preserve some carbohydrates for release of energy to support further growth when the water level recedes. The regulatory genes in this category may also serve some ABA-mediated water stress recovery and inhibition of GAinduced internodal elongation as quiescence strategies adopted by plants [173]. On the other

resume development when flood water subsides.

strategy towards enhanced flooding tolerance.

GA.

188 Plant Genomics

others.

A total of 21 mineral nutrients are essential for crop growth and development. Most nutrients in the soil are primarily generated from the weathering of the parent material in the Earth's crust. Moreover, nutrient levels can vary widely across locations because of initial influence of the composition of the parent material. In most cases, inadequate replenishment from the parent material and from the adsorbed and complexed fractions causes nutrient deficiencies in the soil. In addition, natural factors, including acidity, alkalinity and human activities such as inadequate fertilization also cause nutrient deficiencies. In countries such as India and China, mineral deficiencies have significantly stagnated or limited crop yields. More than 30% of agricultural soils are boron deficient, not only in China and India, but in the whole world. Moreover, zinc deficiency is even more widespread, affecting approximately 50% of the soils. Significant zinc deficiencies occur in sub-Saharan Africa, Turkey, Iran and Pakistan [174].

Several studies have been conducted on understanding plant nutrition; the most noteworthy being the work of the German scientist Justus von Liebig, who stipulated that plant growth is controlled not only by the total resources (nutrients) available, but also by the scarcest resource (the limiting factor). This submission has stimulated a series of studies on nutrient manage‐ ment, including plant breeding for tolerance to nutrient deficiencies. Tolerance to nutrient deficiency is associated with the genotype's nutrient use efficiency. Genotypic variation in nutrient use efficiency is closely related to root nutrient acquisition capacity and utilization. In this section, we will focus on nitrogen and phosphorus, the two most limiting nutrients that are essential for several biological processes in plants.

#### *7.1.1. Plant tolerance to nitrogen deficiency*

Nitrogen is the most limiting nutrient to plant growth in most ecosystems despite its abun‐ dance in the atmosphere. This problem occurs because most plants can only take up nitrogen in two solid forms: ammonium ion (NH4 + ) and nitrate ion (NO3 − ). Ammonium is used less by plants because it is extremely toxic if taken up in large concentrations, so inorganic nitrate is the most usable form obtained by plants from the soil solution. Nitrogen-deficiency effect on crop yields depends on the growth stage at which it occurs, as well as on its duration and extent [175]. However, reduced radiation interception, low radiation use efficiency, poor dry matter partitioning to reproductive organs, reduced leaf area index and decreased protein content of the plant and seed are the common effects of nitrogen deficiency.

Plants react in many different ways to changes in N provision; and physiological and molecular components governing N uptake, assimilation and remobilization during the plant life cycle have been studied extensively in the past decades, for review see [176, 177]. Three types of responses have been recently unraveled: (i) regulation of root N uptake systems, (ii) plasticity of root system architecture and (iii) fast modulation of shoot growth [178]. The first two responses generally improve efficiency of root N uptake under deficient conditions. The upregulation of specific high-affinity membrane transporters and enhanced foraging by the root system are implicated in these responses. When soil conditions for N uptake are seemingly unfavourable, e.g. limited water availability, plants will quickly slow down the overall N demand, as a nutrient conserving adaptive strategy, to prevent N starvation until conditions for N uptake become favourable.

In various plant species, nitrate transporters play a dominant role in N uptake. In *Arabidopsis*, three major families of nitrate transporters have been identified: Chlorate resistant 1 (*CHL1*/ *NRT1*), *NRT2* and chloride channel (*CLC*) [177]. *NRT2* belongs to the high-affinity nitrate transporter group while most of the *NRT1* family members belong to low-affinity nitrate transporters. The only exception, so far, in the latter group is *NRT1.1* that is a dual affinity nitrate transporter. Thus, the high-affinity transporters that have been identified and primarily associated with nitrate uptake from the external environment include *NRT1.2*, *NRT2.1*, *NRT2.2* and the dual affinity transporter, *NRT1.1*.

*NRT1.1* is functionally regulated by phosphorylation of a threonine residue, *Thr101*, which facilitates the switching of its activity from a low- to a high-affinity state. *AtNRT1.1*, which is also induced by auxin and is itself an auxin influx facilitator, is a dimer in the asymmet‐ ric unit cell despite being monomeric in solution. At low nitrate levels, *AtNRT1.1* is phos‐ phorylated at the dimer interface, dissociates the *NRT1.1* dimer, changes into a highaffinity transporter and represses lateral root (LR) development by promoting basipetal auxin transport out of LR primordia (LRP) [179]. At high nitrate levels, *NRT1 1* is dephosphorylat‐ ed, adopts a dimeric structure and adapts a low-affinity transporter configuration. In this state, trafficking of auxin out of the LR is blocked, and auxin accumulates in the LR initials promoting LR development. *NRT1.1* is also shown to act upstream of the *MADS box ARABIDOPSIS NITRATE REGULATED1* (*ANR1*) when modulating LR growth [179]. *ANR1* mediates localized N response and modulates the proliferation of LRs in N-dense patches. Moreover, *NRT1.1* has been shown to regulate genes encoding for other nitrate transport‐ ers, including *NRT2.1* and *NRT3.1* [180]. However, *NRT1.1* and *NRT2.1* are localized in different cell layers in the roots, and their adaptive/complementary strategy in nitrate uptake is not well elucidated. The *NRT1.1*-auxin modulation and nitrate signaling has also been a topic of interest and requires elucidation [181].

Amongst the *CLC* family members, *CLCa* and *CLCb* function as proton-nitrate exchanges, and have high selectivity for nitrates over chlorides [182]. Both transporters are known to mediate

nitrate accumulation in the plant vacuoles. Besides the above-mentioned transporters, the acquisition of nitrate is also regulated by slow anion channel (*SLAC1*) and *SLAC1* homo‐ logue (*SLAH*) and nitrate excretion transporter (*NAXT-1)*. Five *SLAC* genes were previous‐ ly reported in *Arabidopsis* . Amongst these genes, *SLAC1* and *SLAH3* show nitrate transport activity, but their channel activity is co-regulated by kinases (e.g., *CPK21*) [183]. An efflux component operated by *NAXT-1*, associated with the nitrate transporter 1/peptide transport‐ er (*NRT1*/*PTR*) family of proteins, mediates nitrate efflux under acid load in the cytosol [184]. Similarly, *NRT1.5*, which loads nitrates into the xylem for root-to-shoot translocation, also mediates nitrate efflux. However, the proton-coupling mechanism of *NAXT1* remains to be elucidated. Two other transporters, *NRT1.8* and *NRT1.9*, have been reported to regulate rootto-shoot nitrate translocation [185, 186]. Both transporters are apparently negative regula‐ tors of root-to-shoot nitrate transport. The subsequent nitrate allocation into the vegetative tissues, reproductive tissues and osmotic regulation of guard cells is reasonably described elsewhere [187].

crop yields depends on the growth stage at which it occurs, as well as on its duration and extent [175]. However, reduced radiation interception, low radiation use efficiency, poor dry matter partitioning to reproductive organs, reduced leaf area index and decreased protein content of

Plants react in many different ways to changes in N provision; and physiological and molecular components governing N uptake, assimilation and remobilization during the plant life cycle have been studied extensively in the past decades, for review see [176, 177]. Three types of responses have been recently unraveled: (i) regulation of root N uptake systems, (ii) plasticity of root system architecture and (iii) fast modulation of shoot growth [178]. The first two responses generally improve efficiency of root N uptake under deficient conditions. The upregulation of specific high-affinity membrane transporters and enhanced foraging by the root system are implicated in these responses. When soil conditions for N uptake are seemingly unfavourable, e.g. limited water availability, plants will quickly slow down the overall N demand, as a nutrient conserving adaptive strategy, to prevent N starvation until conditions

In various plant species, nitrate transporters play a dominant role in N uptake. In *Arabidopsis*, three major families of nitrate transporters have been identified: Chlorate resistant 1 (*CHL1*/ *NRT1*), *NRT2* and chloride channel (*CLC*) [177]. *NRT2* belongs to the high-affinity nitrate transporter group while most of the *NRT1* family members belong to low-affinity nitrate transporters. The only exception, so far, in the latter group is *NRT1.1* that is a dual affinity nitrate transporter. Thus, the high-affinity transporters that have been identified and primarily associated with nitrate uptake from the external environment include *NRT1.2*, *NRT2.1*, *NRT2.2*

*NRT1.1* is functionally regulated by phosphorylation of a threonine residue, *Thr101*, which facilitates the switching of its activity from a low- to a high-affinity state. *AtNRT1.1*, which is also induced by auxin and is itself an auxin influx facilitator, is a dimer in the asymmet‐ ric unit cell despite being monomeric in solution. At low nitrate levels, *AtNRT1.1* is phos‐ phorylated at the dimer interface, dissociates the *NRT1.1* dimer, changes into a highaffinity transporter and represses lateral root (LR) development by promoting basipetal auxin transport out of LR primordia (LRP) [179]. At high nitrate levels, *NRT1 1* is dephosphorylat‐ ed, adopts a dimeric structure and adapts a low-affinity transporter configuration. In this state, trafficking of auxin out of the LR is blocked, and auxin accumulates in the LR initials promoting LR development. *NRT1.1* is also shown to act upstream of the *MADS box ARABIDOPSIS NITRATE REGULATED1* (*ANR1*) when modulating LR growth [179]. *ANR1* mediates localized N response and modulates the proliferation of LRs in N-dense patches. Moreover, *NRT1.1* has been shown to regulate genes encoding for other nitrate transport‐ ers, including *NRT2.1* and *NRT3.1* [180]. However, *NRT1.1* and *NRT2.1* are localized in different cell layers in the roots, and their adaptive/complementary strategy in nitrate uptake is not well elucidated. The *NRT1.1*-auxin modulation and nitrate signaling has also been a

Amongst the *CLC* family members, *CLCa* and *CLCb* function as proton-nitrate exchanges, and have high selectivity for nitrates over chlorides [182]. Both transporters are known to mediate

the plant and seed are the common effects of nitrogen deficiency.

for N uptake become favourable.

190 Plant Genomics

and the dual affinity transporter, *NRT1.1*.

topic of interest and requires elucidation [181].

Further studies on signaling, transcriptional and post-translational regulation have revealed evidence that a CBL-interacting protein kinase, *CIPK8*, regulates the activity of nitrate transporters and the expression of nitrate assimilation genes [188]. Like *CIPK8*, *CIPK23* is also suggested to be activated by a CBL protein, *CBL9*, but the exact mechanism is elusive. *CIPK23* directly interacts with *NRT1.1* in the plasma membrane and phosphorylates *NRT1.1* at *Thr101* to adopt a monomeric structure when the nitrate concentration is low. This process helps plants to adapt to low nitrogen levels.

Several TFs have been implicated in regulating *NRT1.1* activity*.* For instance, the activity of two *bZIP* TFs in *Arabidopsis*, *ELONGATED HYPOCOTYL5* (*HY5*) and *HY5-HOMOLOG* (*HYH*), was suggested to positively modulate *NITRATE REDUCTASE2* (*NIA2*) and negatively modulate *NRT1.1* [189]. The *NODULE INCEPTION* (*NIN*)-like TFs have also been shown to play a central role in the regulation of nitrate-inducible genes [190]. Nitrate signaling activates *NIN*-like transcription factors through their N-terminal regions. The activated factors promote the expression of nitrogen assimilation-related genes and genes encoding regulatory proteins. *NLP7* is the most reported in this family of TFs. *NLP7* is strongly induced in vascular tissues and root hairs, and is required for the induction of several nitrate uptake and assimilatory genes. Thus, *NLP7* is is probably a key regulator of nitrogen utilization mechanisms. More recently, the presence of nitrate in the external solution induced the expression of *NRT* accessory proteins (*NAR*), nitrate reductase, nitrite reductase and genes involved in the GS-GOGAT cycle, in *Arabidopsis*, as well as in maize and other plants [191]. These proteins likely play a role in nitrate sensing.

Strigolactones (SLs), a new class of plant hormones and rhizosphere signaling molecules, also appear to be upregulated in plants under low N conditions [192]; however, the impact of SL levels on root growth is yet to be determined. Changes in root system architecture (RSA) may also be induced depending on the prevailing available organic form of nitrogen, for review see [118]. The most commonly reported organic forms are l-glutamate or carnitine. In *Arabidopsis* seedlings, l-glutamate inhibits cell division in the root apical meristem (PRM) of the primary root (PR) tip and promotes LR formation and outgrowth. However, several *Arabidopsis* auxin-signaling mutants display different levels of sensitivity to l-glutamate, suggesting that l-glutamate is rather a signaling molecule as opposed to a nitrogen source [193]. In addition, the rice glutamate receptor mutants display a host of RSA changes, including short PR and LR, reduced cell division and the cell death of root apical meristem [194], further suggesting that l-glutamate is a signaling molecule. l-Glutamate could be a major anchor in the signaling process leading to nitrate uptake and assimilation. This is supported by previous studies that have shown that glutamine synthetase (*GS1*) from alfalfa causes an increase in photosynthesis and growth under low N fertilization regime [195]. Glutamine synthetase also mediates ammonium assimilation into glutamine. Ammonium form of nitrogen is rapidly assimilated into organic nitrogen forms to avoid tissue toxicity, for review see [196]. Several other reviews have documented the genes and proteins regulating nitrogen use efficiency (NUE) in plants. The reader is referred to excellent reviews by [177, 196]. In addition, more than 50 QTLs for nitrogen use efficiency have been reported in plants, though few of them have been validated. Amongst the identified QTLs are nitrogen deficiency response QTLs in rice, nitrogen supply responses and yield in wheat and nitrogen use efficiency in barley.

Collectively, nitrogen use efficiency in plants is controlled by a complex array of physiological, developmental and environmental interactions that are specific to the genotype of a given species. Notwithstanding the aforementioned N uptake and utilization genes and QTLs, an extensive molecular survey of a wide range of genotypes covering the genetic diversity of a crop could provide further evidence on the genetic control of these trait. This can be achieved using the various available 'omics' techniques, combined with agronomic and physiological approaches in order to identify more elements controlling NUE in plants, both universal and specific, for use in crop improvement.

#### *7.1.2. Plant tolerance to phosphorus deficiency*

Phosphorus (P) is the second most limiting mineral nutrient in almost all soils, and >30% of the world's arable land has low P [197]. Phosphorus availability is particularly limiting on highly weathered acid soils of the tropics and subtropics due to its fixation by Al and Fe oxides on the surface of clay minerals. Plants take up phosphorus as phosphate (Pi), either directly by the root system or transferred through the fungal symbiont in arbuscular mycorrhizae host plants. Plants have elaborate sensing and signaling mechanisms in response to Pi deficiency, and both local and systemic signaling in response to Pi deficiency have been reported [197]. Key responses in the plant include changes in the root system architecture (RSA), a reduction in photosynthetic rate; increased activity of high-affinity Pi transporter activities; secretion of APases, ribonucleases and organic acids; membrane phospholipid replacement with glycoli‐ pids and sulfolipids; and increased availability of anthocyanin and starch [198]. Putative signaling molecules in response to Pi deficiency include sugars, hormones and microRNAs.

Under limiting Pi conditions, plants can monitor Pi deficiency both locally and systemically, and root foraging strategy to explore top soil layers for Pi is employed. The Pi foraging strategy is accomplished through one of the several different RSA and physiological changes [118]. The local external Pi rather than the systemic Pi status of the whole plant regulates the remodelling of RSA [199]. In maize and some species in the *Proteaceae* and *Casuarinaceae* families, the remodelling of RSA involves production of adventitious roots and cluster roots [200, 201], which increases root surface area for Pi absorption. While a plant Pi receptor is yet to be identified, recent reports have suggested that ethylene biosynthesis and signaling are involved in the Pi-deficiency-triggered remodelling of RSA, for review see [118, 195]. The evidence is supported by previous finding that inhibition of ethylene biosynthesis with 2*-aminoethoxyvinyl glycine* (*AVG*) or ethylene perception with Ag+ restricted the low Pi-induced meristem exhaus‐ tion of the primary root [202]. Correspondingly, application of Ag+ was found to reduce the inhibition of primary root growth triggered by Pi deficiency. Moreover, Pi deficiency induced the formation of aerenchyma in adventitious roots, which is similarly induced by ethylene perception.

*Arabidopsis* auxin-signaling mutants display different levels of sensitivity to l-glutamate, suggesting that l-glutamate is rather a signaling molecule as opposed to a nitrogen source [193]. In addition, the rice glutamate receptor mutants display a host of RSA changes, including short PR and LR, reduced cell division and the cell death of root apical meristem [194], further suggesting that l-glutamate is a signaling molecule. l-Glutamate could be a major anchor in the signaling process leading to nitrate uptake and assimilation. This is supported by previous studies that have shown that glutamine synthetase (*GS1*) from alfalfa causes an increase in photosynthesis and growth under low N fertilization regime [195]. Glutamine synthetase also mediates ammonium assimilation into glutamine. Ammonium form of nitrogen is rapidly assimilated into organic nitrogen forms to avoid tissue toxicity, for review see [196]. Several other reviews have documented the genes and proteins regulating nitrogen use efficiency (NUE) in plants. The reader is referred to excellent reviews by [177, 196]. In addition, more than 50 QTLs for nitrogen use efficiency have been reported in plants, though few of them have been validated. Amongst the identified QTLs are nitrogen deficiency response QTLs in rice, nitrogen supply responses and yield in wheat and nitrogen use efficiency in barley.

Collectively, nitrogen use efficiency in plants is controlled by a complex array of physiological, developmental and environmental interactions that are specific to the genotype of a given species. Notwithstanding the aforementioned N uptake and utilization genes and QTLs, an extensive molecular survey of a wide range of genotypes covering the genetic diversity of a crop could provide further evidence on the genetic control of these trait. This can be achieved using the various available 'omics' techniques, combined with agronomic and physiological approaches in order to identify more elements controlling NUE in plants, both universal and

Phosphorus (P) is the second most limiting mineral nutrient in almost all soils, and >30% of the world's arable land has low P [197]. Phosphorus availability is particularly limiting on highly weathered acid soils of the tropics and subtropics due to its fixation by Al and Fe oxides on the surface of clay minerals. Plants take up phosphorus as phosphate (Pi), either directly by the root system or transferred through the fungal symbiont in arbuscular mycorrhizae host plants. Plants have elaborate sensing and signaling mechanisms in response to Pi deficiency, and both local and systemic signaling in response to Pi deficiency have been reported [197]. Key responses in the plant include changes in the root system architecture (RSA), a reduction in photosynthetic rate; increased activity of high-affinity Pi transporter activities; secretion of APases, ribonucleases and organic acids; membrane phospholipid replacement with glycoli‐ pids and sulfolipids; and increased availability of anthocyanin and starch [198]. Putative signaling molecules in response to Pi deficiency include sugars, hormones and microRNAs.

Under limiting Pi conditions, plants can monitor Pi deficiency both locally and systemically, and root foraging strategy to explore top soil layers for Pi is employed. The Pi foraging strategy is accomplished through one of the several different RSA and physiological changes [118]. The local external Pi rather than the systemic Pi status of the whole plant regulates the remodelling of RSA [199]. In maize and some species in the *Proteaceae* and *Casuarinaceae* families, the

soil

specific, for use in crop improvement.

192 Plant Genomics

*7.1.2. Plant tolerance to phosphorus deficiency*

At the transcriptional level, Lei et al. [203], using an *Arabidopsis* transgenic line that carries a *LUC* gene fused to the promoter of the high-affinity Pi transporter, *AtPT2*, showed that the transcription of *AtPT2* is induced by Pi starvation. Using this marker line, the authors identified the *Arabidopsis* mutant *etr1*/*hps2* (*constitutive triple response 1*/*hyper-sensitive to Pi starvation2*), which showed hyper-induction of the *AtPT2::LUC* gene by Pi deficiency. Interestingly, the expression of *AtPT2* was partially blocked in *ethylene insensitive* 2 (*ein2)* mutants*,* but was enhanced in *ethylene over producer1* (*eto1*) mutants*.* A similar expression pattern was observed for several other Pi starvation-induced (*PSI*) genes in the *hps2* (negative regulator of ethylene response) and *ein2* mutants, including high-affinity phosphate transporter, *AtPT1* (*Pht1;1)*; a non-coding transcript, *At4*; an APase, *ACP5*; a ribonuclease, *Rxlink*; and *miR399d* [204]. Enhanced transcription of *PSI* genes was also observed in the mutant *hps3* and *hps4,* which are *ETO1* alleles [205, 206]. *ETO1* protein is a member of the broad complex/tramtrack/bric-a-brac (BTB) protein superfamily that participates in substrate recognition during ubiquitin-mediated protein degradation [204, 207]. *ETO1* directly binds to the C-terminal of *ACS5* and mediates its degradation. When *ETO1* is mutated, it causes an overproduction of ethylene in young seedlings [208]. Application of 25 μM ACC to young *Arabidopsis* seedlings under high Pi conditions barely induces the expression of *AtPT2*. Under Pi deficiency, however, 0.5 μM ACC dramatically increases *AtPT2* expression and induces ectopic root-hair development [203]. Thus, these results provide evidence that ethylene production and signaling is involved in the transcriptional responses of plants to Pi deficiency and primarily integrates with other Pideficiency-induced signaling pathways.

The other signaling component involving increased transcription of purple acid phosphatase 10 (*AtPAP10*) by Pi starvation in the whole seedlings of *hps3* and *hps4* has been reported [205, 206]. *AtPAP10* is a Pi starvation-induced *APase* (enzymes that scavenge Pi from organophos‐ phate compounds) associated with the root surface. Functional analyses of *atpap10* mutants suggest that *AtPAP10* is important for plant tolerance to Pi starvation. However, the tran‐ scription of *AtPAP10* does not significantly increase in *ACC*-treated seedlings or the *constitutive triple response I* (*ctr1*) mutant under Pi deficiency, nor does the accumulation of *AtPAP10* proteins, which could suggest that ethylene has no effect on *AtPAP10* transcription. More recently, Zhang *et al.* [209] have shown that positive regulation of *AtPAP10* depends on sucrose and not ethylene. Moreover, they have also shown that ethylene does not affect *AtPAP10* activity without sucrose, but the opposite is true. This suggests that ethylene could be a local but indirect signal for *AtPAP10* activity. However, as discussed before, ethylene could be regulating other components of Pi starvation response at the transcriptional level. Song and Liu [204] have demonstrated that accumulation of anthocyanin is lower in *hps2*, *hps3* and *hps4* mutants under low Pi but increases in Pi-starved *ein2* mutants. As mentioned before, accu‐ mulation of anthocyanins is an indicator of Pi-deficiency response in plants, thus ethylene could be a negative regulator of Pi-deficiency-induced anthocyanin accumulation probably through the regulation of genes involved in anthocyanin synthesis. Thus, ethylene likely participates at both the transcriptional and post-transcriptional levels, and this has implica‐ tions on Pi starvation response in plants.

The systemic response to P starvation is also carried out through a complex signaling network that involves other plant hormones [210, 211], sugars [212] and nitric oxide [213], collectively resulting in the alteration of carbohydrate distribution between roots and shoots. Amongst the plant hormones, other than ethylene, auxin likely plays a role in response to Pi starvation. However, ethylene likely exerts its influence through regulating auxin activity, as it has been associated with RSA remodelling [198]. Indeed, ethylene has been reported to interact with auxin and sugars, and changes in auxin transport and localization appear to be at least partially responsible for Pi stress-induced LR development [214]. Decreased sensitivity to CK and GA also appears to be at least partially responsible for Pi-stress-induced LR development [215]. Under low Pi, GA has been shown to repress Pi-induced root architecture changes [216]. Moreover, Pi-deficient plants were shown to accumulate *DELLA* proteins, the negative regulators of GA-induced root growth, which are modulated by auxin.

As discussed before, amongst sugars, sucrose is key to Pi-deficiency response and appears to regulate ethylene activity. Amongst the TFs, phosphate starvation response proteins (e.g., *OsPHR1*, *OsPHR2*, *PvPHR1*, *ZmPHR1* and *TaPHR1*), which bind the promoter sequences of low Pi-induced genes, and their regulator *SMALL UBIQUITIN-LIKE MODIFIER1* [*AtSIZ1*; 217], a small ubiquitin-modified E3 ligase, and the downstream *PHOSPHATE2* (*PHO2*), an E2 conjugase, are involved in Pi-deficiency-related transcriptional changes. Other TFs, including the *bHLH*, *PTF1* (e.g., *OsPTF1* and *ZmPTF1*) and *MYB2P-1* (e.g., *OsMYB2P1*), *MYB62*, *WRKY* (e.g., *WRKY75*, *WRKY6*), *bHLH32* and *ZAT6* are also involved in the signaling network to regulate plant adaptation to P stress, for review see [218].

Based on genetic analysis, two proteins, the P5 type ATPase encoded by *PHOSPHATE DEFICIENCY RESPONSE2* (*PDR2*), and multicopper oxidase *LOW PHOSPHATE ROOT1* (*LPR1*), were also previously shown to modulate Pi signaling in an endoplasmic-reticulumlocalized pathway [219]. *PDR2* is required for maintaining the levels of the root patterning gene, *SCARECROW* (*SCR*), and *SHORT-ROOT* protein (*SHR*) trafficking from stele into endodermis. *PDR2* was proposed to act upstream of *LPR1*/*LPR2* to adjust meristem activity. A recent study has shown that *LPR1* is a ferroxidase [220]. Mutation of *LPR1* reduces Fe3+ levels in the meristemic tissues of Pi-deficient plants. In contrast, increased levels of Fe3+ have been reported in *pdr2* mutants leading to high production levels of reactive oxygen species (ROS). ROS signaling increases deposition of callose, which has been suggested to impair the trafficking of *SHR*, thus restricting root tip growth. Thus, PDR2 appears to modulate Pideficiency response by limiting Fe3+ accumulation in root tips.

More recently, molecular mechanisms defining the phosphate signaling pathway showed that *phosphate uptake 1* (*Pup1*)-specific protein kinase gene, named *phosphorus-starvation tolerance 1* (*PSTOL1*), was confirmed to be involved in regulating root growth and architecture during early stages of rice growth [221]. Allele-specific markers for this gene have been reported recently [222]. Interestingly, *OsPSTOL1* is located within the Kasalath-specific INDEL region and is absent from the rice variety Nipponbare reference genome. Thus, the configuration of the functional mechanism of *PSTOL1* is still elusive. We speculate that *PSTOL1* could be a local sensor of Pi starvation which transduces signals for sucrose or ethylene biosynthesis or both. The interplay of sucrose accumulation and ethylene biosynthesis is apparently the hallmark of Pi starvation response in plants.

but indirect signal for *AtPAP10* activity. However, as discussed before, ethylene could be regulating other components of Pi starvation response at the transcriptional level. Song and Liu [204] have demonstrated that accumulation of anthocyanin is lower in *hps2*, *hps3* and *hps4* mutants under low Pi but increases in Pi-starved *ein2* mutants. As mentioned before, accu‐ mulation of anthocyanins is an indicator of Pi-deficiency response in plants, thus ethylene could be a negative regulator of Pi-deficiency-induced anthocyanin accumulation probably through the regulation of genes involved in anthocyanin synthesis. Thus, ethylene likely participates at both the transcriptional and post-transcriptional levels, and this has implica‐

The systemic response to P starvation is also carried out through a complex signaling network that involves other plant hormones [210, 211], sugars [212] and nitric oxide [213], collectively resulting in the alteration of carbohydrate distribution between roots and shoots. Amongst the plant hormones, other than ethylene, auxin likely plays a role in response to Pi starvation. However, ethylene likely exerts its influence through regulating auxin activity, as it has been associated with RSA remodelling [198]. Indeed, ethylene has been reported to interact with auxin and sugars, and changes in auxin transport and localization appear to be at least partially responsible for Pi stress-induced LR development [214]. Decreased sensitivity to CK and GA also appears to be at least partially responsible for Pi-stress-induced LR development [215]. Under low Pi, GA has been shown to repress Pi-induced root architecture changes [216]. Moreover, Pi-deficient plants were shown to accumulate *DELLA* proteins, the negative

As discussed before, amongst sugars, sucrose is key to Pi-deficiency response and appears to regulate ethylene activity. Amongst the TFs, phosphate starvation response proteins (e.g., *OsPHR1*, *OsPHR2*, *PvPHR1*, *ZmPHR1* and *TaPHR1*), which bind the promoter sequences of low Pi-induced genes, and their regulator *SMALL UBIQUITIN-LIKE MODIFIER1* [*AtSIZ1*; 217], a small ubiquitin-modified E3 ligase, and the downstream *PHOSPHATE2* (*PHO2*), an E2 conjugase, are involved in Pi-deficiency-related transcriptional changes. Other TFs, including the *bHLH*, *PTF1* (e.g., *OsPTF1* and *ZmPTF1*) and *MYB2P-1* (e.g., *OsMYB2P1*), *MYB62*, *WRKY* (e.g., *WRKY75*, *WRKY6*), *bHLH32* and *ZAT6* are also involved in the signaling network to

Based on genetic analysis, two proteins, the P5 type ATPase encoded by *PHOSPHATE DEFICIENCY RESPONSE2* (*PDR2*), and multicopper oxidase *LOW PHOSPHATE ROOT1* (*LPR1*), were also previously shown to modulate Pi signaling in an endoplasmic-reticulumlocalized pathway [219]. *PDR2* is required for maintaining the levels of the root patterning gene, *SCARECROW* (*SCR*), and *SHORT-ROOT* protein (*SHR*) trafficking from stele into endodermis. *PDR2* was proposed to act upstream of *LPR1*/*LPR2* to adjust meristem activity. A recent study has shown that *LPR1* is a ferroxidase [220]. Mutation of *LPR1* reduces Fe3+ levels in the meristemic tissues of Pi-deficient plants. In contrast, increased levels of Fe3+ have been reported in *pdr2* mutants leading to high production levels of reactive oxygen species (ROS). ROS signaling increases deposition of callose, which has been suggested to impair the trafficking of *SHR*, thus restricting root tip growth. Thus, PDR2 appears to modulate Pi-

regulators of GA-induced root growth, which are modulated by auxin.

regulate plant adaptation to P stress, for review see [218].

deficiency response by limiting Fe3+ accumulation in root tips.

tions on Pi starvation response in plants.

194 Plant Genomics

The post-transcriptional regulation as well as long-distance signaling is carried out by microRNAs. As mentioned before, *miR399*, which is regulated by *PHR1*, a conserved *MYB* TF, maintains P homeostasis by regulating P transporter *PHO2* [223]. In tomato, overexpression of *Arabidopsis miR399* increases both the Pi accumulation and secretion of acid phosphatase and protons in the roots [223]. Thus, *miR399* is important for Pi acquisition, and could be acting downstream of sucrose and probably ethylene. Overexpression of *miR399* in *Arabidopsis* also increases P uptake and allocation to the shoot. Moreover, P remobilization from older leaves to young leaves is defective in *Arabidopsis miR399* transgenic lines [224]. This suggests that *miR399* is important for allocation and remobilization of P. The targets of *miR399* include a ubiquitin-conjugating E2 enzyme (*UBC24*) encoded by *PHO2*, which is upregulated under Psufficient conditions and downregulated in P-starved plant roots. Homologues of *PHO2/ UBC24* have a conserved structure in many species, and their 5′ UTR regions possess multiple *miR399*-complementary sequences. Thus, the regulatory mechanism of *miR399-PHO2* complex is evolutionarily conserved in angiosperms, making it a potential target for improving P nutrition efficiency in plants.

Strigolactones (SL) have also been shown to be induced by low Pi in many species, including tomato, *Arabidopsis*, pea and rice [225–229]. Strigolactones are terpenoid lactones that function as either endogenous hormones that control plant development or as components of root exudates that promote symbiotic interactions between plants and soil microbes. The produc‐ tion and exudation of SLs may depend on whether the plant is arbuscular mycorrhizal fungi (AMF)-compatible host or an arbuscular mycorrhizal symbiosis (AMS) for Pi and N uptake. A well-known synthetic SL, *GR24*, apparently increases LR formation under low Pi or decreases LR formation under sufficient Pi. In addition, SL biosynthesis (*more axillary growth; max4-1*) and signaling (*max2-1*) mutants have reduced number of root hairs under low Pi condition at the early stages of seedling development. This suggests that SLs mediate plant responses to low Pi; however, the mechanism by which SL exudation affects root growth is not fully understood.

In conclusion, although the molecular components of P stress signaling in plants have been fairly documented, the overall pathway is still less understood and requires further investi‐ gation. Nonetheless, the recent developments in whole genome sequencing technologies provide hope for more studies on plants with better P acquisition and utilization. Successes in QTL analysis have also set a stage for subsequent studies. Besides the success story of *PSTOL1* in rice*,* QTL analysis in common bean has shown the importance of basal roots and adventi‐ tious roots for P acquisition [230–232]. Another study by Yan et al. [233] identified a large number of QTLs for Hþ exudation, root-hair density and length, associated with P efficiency. Additionally, QTLs for root traits related to P efficiency have also been identified in soybean [234, 235]. Moreover, QTLs controlling P deficiency tolerance were mapped by Zhang et al. [344] using 152 RILs derived from a cross between P-stress-tolerant and P-stress-sensitive parents. Thus, future studies will build on these present discoveries to facilitate genetic improvement for Pi-deficiency tolerance.

#### **7.2. Advances in plant tolerance to nutrient toxicities**

Metal toxicity is an important factor limiting the growth of plants in many environments. Some metals, such as copper and zinc, are micronutrients at low concentrations and become toxic at higher levels, whereas others (e.g., aluminium, iron, cadmium, chromium and lead) are well known for their toxicity [236]. These elements can be highly phytotoxic and seriously impair plant root growth. However, some crops are able to tolerate toxic environments, without significant display of toxicity symptoms. Three main strategies are employed by such plants to manage toxic soil compounds: (1) Producing root exudates that bind and neutralize the toxin in the rhizosphere, (2) actively transport the compound into the root, but neutralizing and sequestering it in vacuoles for safe accumulation or eliminating it through exudation and (3) excluding the toxic elements by preventing entry into the plant tissues. For the purpose of this chapter, we will focus on aluminium and iron toxicities as these elements have been frequently reported as major constraints in the production of economically important crops.

#### *7.2.1. Plant tolerance to aluminium toxicity*

Aluminium (Al) is a light metal that makes up 7% of the Earth's crust and is the third most abundant element after oxygen and silicon. Aluminium toxicity is one of the major constraints to crop productivity worldwide, especially in the acid soils of the tropics and subtropics that comprise almost 50% of all non-irrigated arable land in those regions [118, 237]. The soil pH has a crucial role for Al toxicity to occur, by affecting both solubility and the ability of plant roots to absorb Al. Al solubilizes into its toxic form (Al3+) when the soil pH drops to 5.5 or less, and is most severe in solutions of low ionic strength and low cation concentrations. Al3+ is taken up by plants through diffusion [238], and toxic concentrations of >12 μM are detrimental to root growth. Possible exceptions of Al(OH)3 4− toxicity at higher pH values have also been reported [239].

The initial effects of Al3+ toxicity on the roots include rapid inhibition of cell division and a reduction in root apical cell expansion and elongation. Consequently, plants develop stubby and brittle roots with swollen malformed root tips. Moreover, lateral root initiation and outgrowth are also inhibited. Root-hair malformation is often reported, and nutrient (mainly P, K, Ca and Mg) and water uptake capacity is impaired [238]. Plant responses in the shoots include reduced stomatal opening, chlorosis, foliar necrosis and reduced photosynthetic activity.

Plant tolerance to aluminium toxicity occurs through (1) external avoidance, which involves root secretion of organic acids to chelate Al3+ in the rhizosphere, limiting its diffusion into the roots [240], and (2) true or internal tolerance, which involves regulation of Al3+ uptake, and organic acid chelation and sequestration of aluminium bound substrates [241]. In rice, the latter is the main tolerance mechanism, and is apparently associated with the differential expression and transport properties of membrane transporters, e.g., *NRAMP Al 3+ transporter 1* (*NRAT1*) [242]. Most other plant species also vary significantly in these mechanisms; however, there are some tolerance mechanisms that are largely shared. Cereal crops, such as wheat, barley, sorghum (*Sorghumbicolor* L.) and oat were reported to have simple genetic mechanisms of Al tolerance, whereas rice and maize (*Zea mays* L.) have over time developed complicated inheritance controlled by numerous genes/loci involved [118, 243].

in rice*,* QTL analysis in common bean has shown the importance of basal roots and adventi‐ tious roots for P acquisition [230–232]. Another study by Yan et al. [233] identified a large number of QTLs for Hþ exudation, root-hair density and length, associated with P efficiency. Additionally, QTLs for root traits related to P efficiency have also been identified in soybean [234, 235]. Moreover, QTLs controlling P deficiency tolerance were mapped by Zhang et al. [344] using 152 RILs derived from a cross between P-stress-tolerant and P-stress-sensitive parents. Thus, future studies will build on these present discoveries to facilitate genetic

Metal toxicity is an important factor limiting the growth of plants in many environments. Some metals, such as copper and zinc, are micronutrients at low concentrations and become toxic at higher levels, whereas others (e.g., aluminium, iron, cadmium, chromium and lead) are well known for their toxicity [236]. These elements can be highly phytotoxic and seriously impair plant root growth. However, some crops are able to tolerate toxic environments, without significant display of toxicity symptoms. Three main strategies are employed by such plants to manage toxic soil compounds: (1) Producing root exudates that bind and neutralize the toxin in the rhizosphere, (2) actively transport the compound into the root, but neutralizing and sequestering it in vacuoles for safe accumulation or eliminating it through exudation and (3) excluding the toxic elements by preventing entry into the plant tissues. For the purpose of this chapter, we will focus on aluminium and iron toxicities as these elements have been frequently

reported as major constraints in the production of economically important crops.

Aluminium (Al) is a light metal that makes up 7% of the Earth's crust and is the third most abundant element after oxygen and silicon. Aluminium toxicity is one of the major constraints to crop productivity worldwide, especially in the acid soils of the tropics and subtropics that comprise almost 50% of all non-irrigated arable land in those regions [118, 237]. The soil pH has a crucial role for Al toxicity to occur, by affecting both solubility and the ability of plant roots to absorb Al. Al solubilizes into its toxic form (Al3+) when the soil pH drops to 5.5 or less, and is most severe in solutions of low ionic strength and low cation concentrations. Al3+ is taken up by plants through diffusion [238], and toxic concentrations of >12 μM are detrimental to root growth. Possible exceptions of Al(OH)3 4− toxicity at higher pH values have also been

The initial effects of Al3+ toxicity on the roots include rapid inhibition of cell division and a reduction in root apical cell expansion and elongation. Consequently, plants develop stubby and brittle roots with swollen malformed root tips. Moreover, lateral root initiation and outgrowth are also inhibited. Root-hair malformation is often reported, and nutrient (mainly P, K, Ca and Mg) and water uptake capacity is impaired [238]. Plant responses in the shoots include reduced stomatal opening, chlorosis, foliar necrosis and reduced photosynthetic

improvement for Pi-deficiency tolerance.

196 Plant Genomics

*7.2.1. Plant tolerance to aluminium toxicity*

reported [239].

activity.

**7.2. Advances in plant tolerance to nutrient toxicities**

Genetic control of organic acid exudation either rests on the Multidrug and Toxin Efflux (MATE) family encoding a citrate transporter or on the membrane localized Al3+-activated malate transporters (*ALMT*). Several transporters in these families, including *HvAACT1* in barley [244], *TaALMT1* and *TaMATE1* in wheat [245] and *ZmMATE1* and *ZmMATE2* in maize [246] are responsible for organic acid exudation and Al tolerance. Specific markers for *HvAACT1* and the MATE gene, *HvMATE-21*, have been developed and can be used to differentiate tolerant and sensitive barley cultivars. Differences amongst these transporters however exist. For instance, *TaALMT1* encodes a malate transporter on chromosome 4D and is constitutively expressed on root apices, whereas *TaMATE1* reportedly responds to Al stress based on citrate efflux. ZmMATE1 and *ZmMATE2* co-segregate with two major Al-tolerance QTLs [247]. *ZmMATE1* was shown to be induced by Al and enhances Al tolerance, whereas *ZmMATE2* did not respond to Al [246], suggesting variability in their roles. In sorghum, Al tolerance is controlled by *SbMATE*, encoded by a major Al-tolerant locus AltSB on chromosome 3 [248]. In *Arabidopsis* , two genes were reportedly responsible for Al tolerance: *AtALMT1* that also encodes a malate transporter responsible for malate efflux on chromosome 1 [249] and *AtMATE* that encodes an Al-activated citrate transporter [389]. These two genes function independently, but both are regulated by the C2H2-type zinc finger transcription factor *STOP1* [250], which is also reportedly induced by with low pH tolerance [366]. In rye, *ScALMT1*, which is mainly expressed in the root apex and upregulated by Al, co-segregates with the *Alt4* locus on chromosome 7RS [367]. Another candidate gene *ScAACT1* on chromosome 7RS was mapped to 25 cM from *ScALMT1* [251].

At the transcriptome level, two genes, *SENSITIVE TO ALUMINUM RHIZOTOXICITY1* and *2* (*STAR1* and *2*), which encode the nuclear binding domain and the transmembrane domain, respectively, of an ABC transporter, with specificity for uridine diphosphate (UDP) glucose, are upregulated following root exposure to Al3+ [252]. Both *STAR* genes were previously reported to be upregulated by the constitutively expressed rice root *ALUMINUM RESISTANT TRANSCRIPTION FACTOR1* (*ART1*), which also upregulates several other genes implicated in different aluminium tolerance mechanisms [253]. More recently, *ASR5* was reported to act as a key TF that is essential for Al-responsive *STAR1* and other Al response genes [254]. Rice homologues, which encode α-expansin (e.g., *EXPA10*), belong to this family of TFs, and have been implicated in the regulation of root elongation and cell wall elasticity. The members of *EXPA10* decrease cell wall extension potential when exposed to Al3+ [255] and are downregu‐ lated during Al3+ stress. The functions of *STAR1*, *STAR2*/*ALS3* and *ALS1* in Al tolerance are fairly conserved and ubiquitous in monocot and dicot species. However, these genes are differentially expressed between species. For instance, the expression and induction levels of these genes in response to Al3+ stress are higher in the Al-tolerant species of rice than in the Al-sensitive species of *Arabidopsis* , suggesting that Al-tolerant species may require increased expression of these conserved Al-tolerance genes to overcome Al3+ stress [256]. The same authors show that Tartary buckwheat shows high expression of the Al-tolerance gene homo‐ logues under Al3+ stress. Al-tolerance in buckwheat is evolutionarily closer to *Arabidopsis* than rice, suggesting that buckwheat could have rapidly evolved higher expression of Al-tolerance genes to detoxify Al3+ than *Arabidopsis* . In addition, the gene duplication of *ART1/STOP1*, *STAR1* and *ALS1* has been suggested to play a significant role in Al tolerance. This is consistent with the previous findings that duplication of key genes responsible for metal translocation and detoxification in *Arabidopsis halleri* facilitates hyper-accumulation of zinc/cadmium [257]. However, further functional analysis by creating knockdown or knockout mutants will be necessary to provide additional insights into the role of each homologous gene in Al detoxi‐ fication and accumulation in buckwheat.

An *Arabidopsis* cell-wall-associated putative endochitinase, CHITINASE A (*AtCHIA*), likely involved in modulating cell wall extension by regulating chitin levels, has also been suggested to play a role in Al tolerance [258]. Another signal of Al3+-induced cellular response is the induction of *1,3-β-d-glucan synthase*, which leads to the accumulation of callose in root apices, especially in endodermal and cortical cell walls [259, 260]. This callose deposition is suggested to be an inhibitory process that may block symplastic and apoplastic flows. Whether callose deposition represents Al3+-induced injury or a defence response to block further Al3+ binding and movement remains to be confirmed.

In *Arabidopsis*, the ethylene receptor gene *ETHYLENE RECEPTOR1* (*ETR1*) and the ethylene signal transducer *ETHYLENE INSENSITIVE2* (*EIN2*) were found to be important for Al3+ induced inhibition of root elongation [261]. These genes apparently regulate Al3+-induced upregulation of the *Arabidopsis* ethylene synthesis genes *1-AMINOCYCLOPROPANE-1- CARBOXYLIC ACID SYNTHASE2*, *6*, and *8* and *1-AMINOCYCLOPROPANE-1-CARBOXYLIC ACID OXIDASE1* and *2*. Moreover, ET was recently shown to negatively regulate aluminiuminduced malate efflux from wheat roots and tobacco cells transformed with *TaALMT1* [262], which suggests that ethylene could be a negative regulator of root secretion of organic acids. The upregulation of auxin transporters *PIN FORMED2* (*PIN2)* and auxin influx carrier *AUXIN RESISTANT1* (*AUX1)*, which regulate auxin distribution, is associated with the regulation of root elongation in *Arabidopsis* plants [263]. *AUX1* and *PIN2* are apparently disrupted by ethylene signal that alters auxin distribution and transport in the roots. He et al. [264] suggests that auxin could be involved in aluminium-induced efflux of malic acid acting on anion channels. Thus, auxin/IAA transport could be a target for Al3+ toxicity tolerance if the modu‐ lation by ET is attenuated. However, considering several phytohormonal changes that occur during Al stress, molecular mechanisms associated with their interplay will require further elucidation. Recent evidence that microRNAs are involved in Al stress tolerance [265] also provides new insights into understanding the mechanism of Al3+ tolerance in plants.

Overall, we expect that major advances in understanding physiological and molecular basis for Al tolerance will happen in the near future, considering that the pace at which new genes are being discovered has improved with new sequencing technologies. The future challenge for studying Al tolerance is the identification of new tolerance mechanisms. The discovery of the key molecular regulators, e.g., *ASR5*, which was recently shown to mediate Al-responsive gene expression to provide Al tolerance in rice, is an indication that several other mechanism of Al tolerance exist in plants. The blocking of Al3+ cell wall binding sites in rice may be one of the major mechanisms of aluminium tolerance that will need further investigation. Studies on barley, wheat and maize have shown variation in gene expression associated with variation in gene sequence, which would require further investigation to understand the regulatory networks affected by this sequence polymorphisms.

#### *7.2.2. Advances in plant tolerance to iron toxicity*

*EXPA10* decrease cell wall extension potential when exposed to Al3+ [255] and are downregu‐ lated during Al3+ stress. The functions of *STAR1*, *STAR2*/*ALS3* and *ALS1* in Al tolerance are fairly conserved and ubiquitous in monocot and dicot species. However, these genes are differentially expressed between species. For instance, the expression and induction levels of these genes in response to Al3+ stress are higher in the Al-tolerant species of rice than in the Al-sensitive species of *Arabidopsis* , suggesting that Al-tolerant species may require increased expression of these conserved Al-tolerance genes to overcome Al3+ stress [256]. The same authors show that Tartary buckwheat shows high expression of the Al-tolerance gene homo‐ logues under Al3+ stress. Al-tolerance in buckwheat is evolutionarily closer to *Arabidopsis* than rice, suggesting that buckwheat could have rapidly evolved higher expression of Al-tolerance genes to detoxify Al3+ than *Arabidopsis* . In addition, the gene duplication of *ART1/STOP1*, *STAR1* and *ALS1* has been suggested to play a significant role in Al tolerance. This is consistent with the previous findings that duplication of key genes responsible for metal translocation and detoxification in *Arabidopsis halleri* facilitates hyper-accumulation of zinc/cadmium [257]. However, further functional analysis by creating knockdown or knockout mutants will be necessary to provide additional insights into the role of each homologous gene in Al detoxi‐

An *Arabidopsis* cell-wall-associated putative endochitinase, CHITINASE A (*AtCHIA*), likely involved in modulating cell wall extension by regulating chitin levels, has also been suggested to play a role in Al tolerance [258]. Another signal of Al3+-induced cellular response is the induction of *1,3-β-d-glucan synthase*, which leads to the accumulation of callose in root apices, especially in endodermal and cortical cell walls [259, 260]. This callose deposition is suggested to be an inhibitory process that may block symplastic and apoplastic flows. Whether callose deposition represents Al3+-induced injury or a defence response to block further Al3+ binding

In *Arabidopsis*, the ethylene receptor gene *ETHYLENE RECEPTOR1* (*ETR1*) and the ethylene signal transducer *ETHYLENE INSENSITIVE2* (*EIN2*) were found to be important for Al3+ induced inhibition of root elongation [261]. These genes apparently regulate Al3+-induced upregulation of the *Arabidopsis* ethylene synthesis genes *1-AMINOCYCLOPROPANE-1- CARBOXYLIC ACID SYNTHASE2*, *6*, and *8* and *1-AMINOCYCLOPROPANE-1-CARBOXYLIC ACID OXIDASE1* and *2*. Moreover, ET was recently shown to negatively regulate aluminiuminduced malate efflux from wheat roots and tobacco cells transformed with *TaALMT1* [262], which suggests that ethylene could be a negative regulator of root secretion of organic acids. The upregulation of auxin transporters *PIN FORMED2* (*PIN2)* and auxin influx carrier *AUXIN RESISTANT1* (*AUX1)*, which regulate auxin distribution, is associated with the regulation of root elongation in *Arabidopsis* plants [263]. *AUX1* and *PIN2* are apparently disrupted by ethylene signal that alters auxin distribution and transport in the roots. He et al. [264] suggests that auxin could be involved in aluminium-induced efflux of malic acid acting on anion channels. Thus, auxin/IAA transport could be a target for Al3+ toxicity tolerance if the modu‐ lation by ET is attenuated. However, considering several phytohormonal changes that occur during Al stress, molecular mechanisms associated with their interplay will require further

fication and accumulation in buckwheat.

198 Plant Genomics

and movement remains to be confirmed.

The problem of iron toxicity occurs in most wetland rice growing areas of the world, primarily in flooded acidic soils, inland and coastal swamps. Some of the irrigated lands in South and Southeast Asia, Africa and South America are affected [266]. In India alone, about 11.7 million hectares of land are affected by iron toxicity. In Burkina Faso, 300 ha of ferrous iron intoxicated soils were abandoned in the Valley du Kou in 1986, most of which remained uncultivated to date [267]. Iron toxicity is also becoming a major rice yield limiting factor in East Africa, including lowland rice cultivation areas of Uganda [268]. Yield losses in the range of 10% to 100% have been reported [266]. Moreover, toxicity at seedling and early vegetative stages can strongly affect plant growth and hinder development, and can result in complete crop failure.

Three major adaptation mechanisms are generally reported for Fe-toxicity tolerance. The details by which rice plants execute these processes and their molecular components are not yet fully understood, but there are some clues from various studies on rice and other plant species. For instance, plant tolerance by root oxidizing power is mediated by diffusion of molecular oxygen from the shoots to the roots through aerenchyma tissue and its subsequent release in the rhizosphere. Oxidation of Fe2+ in the rhizosphere results in the precipitation of insoluble iron oxides at the root surface, forming iron plaques. These iron plaques not only reduce Fe2+ concentration in the soil solution, but also form a physical barrier against further influx of Fe2+ into the roots.

Plant tolerance by retention of iron in the root or shoot involves compartmentalization. Nicotianamine (NA), Fe-NA complex transporters, *VIT* proteins, *FPN2*-like proteins, *MIT-* and *PIC1*-like proteins, organic acids, ferritins, Fe-sulphur and other heme proteins that can sequester Fe are all potential candidates for plant tolerance to excess iron through regulated storage and compartmentalization (Figure 6).

In *Arabidopsis* , apoplasmic Fe is mostly found within the stele [269], suggesting that compart‐ mentalization within the stele could restrict excess Fe from reaching the shoot during trans‐ portation towards the aerial parts. Fe2+ decreases could also occur in association with an

**Figure 6.** Iron transport in rice. Fe is taken up into the symplast by transporters in the epidermis (OsIRT1, OsNRAMP, OsZIPL1 and OsYSLs). Proteins encoded by bHLH, IRUNLP1 and IRT2 likely regulate the activities of the above trans‐ porters. Radial oxygen loss into the rhizosphere through aerenchyma cells detoxifies part of the excess iron forming insoluble Fe3+ at the root surfaces, a process referred to as exclusion. Excess Fe2+ travels through the symplastic space to the vasculature, bypassing the waxy Casparian strip on the endodermis. Prior to reaching the xylem, excess iron is re‐ tained in the root cell vacuoles, mitochondria and probably detoxified by organic acids within the root cells. Transport into the xylem is mediated by putative chelate effluxers: FRDL1, OsYSLs, TOM1, OsIRT1, PEZ1 and FPN1. In the xy‐ lem, iron is carried to the shoot through the transpiration stream either in the form of Fe3+ or in both Fe3+ and Fe2+ forms, and unloaded into the shoot, most likely by YSLs, FRO1 and OsIRT1 proteins. Within the phloem, the rate at which NA, DMA and ITP are synthesized, the kinetic stability of the complexes formed and the oxido-reduction sys‐ tem likely determines the iron speciation. Enzymes involved in NA, DMA and ITP synthesis, including OsIRO2, Os‐ NAS1, NAAT1 and DMAS1, likely play a significant role in determining iron loading into the phloem. Genes encoding for putative iron effluxers from the phloem to storage organs (VIT, OsNRAMP, HMA3, MTP1, ENA, MIT1, ATM1) are co-regulated with IREG2/FPN2 and YSLs to limit potentially toxic iron in the cytosol, by compartmentalizing in the vacuoles, mitochondria, chloroplast and other non-characterized intracellular vesicles. In the chloroplasts, Fe excess probably promotes NO production. NO is probably involved in activation of the transcription factor (TF) cascades re‐ sponsible for the regulation of Fe uptake, homeostasis and for the tuning of cellular metabolism, including increased synthesis of ferritins and betalains in chloroplasts and frataxins in the mitochondria. Because NO also triggers the syn‐ thesis of ROS, heme biosynthesis likely occurs to compartmentalize excess iron and to limit NO production. Alongside heme biosynthesis, the potent antioxidant system involving SOD and APX probably scavenge and detoxify the excess ROS. Also presented are targets of iron utilization, which could reduce iron overload. This includes synthesis of ferro‐ chelatase (FC) for heme biosynthesis, mitochondrial iron-sulphur cluster (ISC) and plastid-localized sulphur utilization factors (SUF).

alkalization of apoplastic pH, which reduces Fe2+ mobility and chemical stability [269]. Alkalization has been reported to be modulated by ethylene [270], suggesting additional role of ethylene in regulating Fe2+ besides its role in aerenchyma formation. Tissue tolerance of Fe toxicity is mediated by detoxification of free radicals. In rice, expression of several genes involved in oxidative stress control, including peroxidases, glutathione transferase (GST) and cytochromes, was upregulated in roots and shoots in response to excess Fe [271]. Similar trends were observed at the protein and enzymatic activity levels of the same genes. Excess iron was reported to induce the activity of superoxide dismutase (SOD) and ascorbate peroxidase (APX) in the leaf sheath and laminae, respectively, in a tolerant variety from *Oryza glaberrima* [272]. The activity of glutathione reductase and peroxidase (POD) was also reported to increase in rice leaf segments exposed to excess iron [273]. Fang et al. [274] also showed that lipid peroxidation resulting from Fe toxicity was inhibited by free radical scavengers such as mannitol and GSH. Moreover, the differential expression of anti-oxidant enzyme activities (SOD, APX, CAT, GR and DHR) was observed between rice varieties contrasting in tolerance of Fe toxicity [275].

Several genetic studies also reflect that iron toxicity tolerance is a complex quantitative trait controlled by a large number of rather small effect quantitative trait loci (QTLs), indicating the involvement of multiple tolerance mechanisms. For instance, Wu et al. [276] identified QTLs for leaf bronzing and shoot dry weight on chromosome 1 and 8, explaining 10–32% of the phenotypic variation. Interestingly, QTLs associated with enzymatic activity of anti-oxidants in rice leaves were detected in the same region [277]. Similarly, Fukuda et al. [278] detected a region on chromosome 3 responsible for high shoot iron content in a susceptible variety, which co-localize with the QTL previously identified by Shimizu et al. [279] for the same trait. Colocalization of most of these QTLs was captured in an integrative genetic map reflecting mapping studies from different conditions of Fe toxicity [277], which substantiates on recurrent chromosomal regions identified in several QTL studies.

A major limitation of iron toxicity tolerance studies, however, is that most of the QTLs associated with iron toxicity tolerance have not been furthered to cloning of tolerance genes. It is thus critical to devote some effort to fine-map the few, but consistent QTLs mentioned herein in order to increase precision and accelerate candidate gene identification. Subsequent‐ ly, functional validation of several genes identified in microarray studies will need to be explored. Exploring allelic variation of these genes in contrasting genotypes and evaluating the promising alleles in well designed and efficient phenotyping experiments would provide a basis for their use in marker-assisted breeding (MAB) for Fe-toxicity tolerance.

#### **8. Conclusions and perspectives**

alkalization of apoplastic pH, which reduces Fe2+ mobility and chemical stability [269]. Alkalization has been reported to be modulated by ethylene [270], suggesting additional role

factors (SUF).

200 Plant Genomics

**Figure 6.** Iron transport in rice. Fe is taken up into the symplast by transporters in the epidermis (OsIRT1, OsNRAMP, OsZIPL1 and OsYSLs). Proteins encoded by bHLH, IRUNLP1 and IRT2 likely regulate the activities of the above trans‐ porters. Radial oxygen loss into the rhizosphere through aerenchyma cells detoxifies part of the excess iron forming insoluble Fe3+ at the root surfaces, a process referred to as exclusion. Excess Fe2+ travels through the symplastic space to the vasculature, bypassing the waxy Casparian strip on the endodermis. Prior to reaching the xylem, excess iron is re‐ tained in the root cell vacuoles, mitochondria and probably detoxified by organic acids within the root cells. Transport into the xylem is mediated by putative chelate effluxers: FRDL1, OsYSLs, TOM1, OsIRT1, PEZ1 and FPN1. In the xy‐ lem, iron is carried to the shoot through the transpiration stream either in the form of Fe3+ or in both Fe3+ and Fe2+ forms, and unloaded into the shoot, most likely by YSLs, FRO1 and OsIRT1 proteins. Within the phloem, the rate at which NA, DMA and ITP are synthesized, the kinetic stability of the complexes formed and the oxido-reduction sys‐ tem likely determines the iron speciation. Enzymes involved in NA, DMA and ITP synthesis, including OsIRO2, Os‐ NAS1, NAAT1 and DMAS1, likely play a significant role in determining iron loading into the phloem. Genes encoding for putative iron effluxers from the phloem to storage organs (VIT, OsNRAMP, HMA3, MTP1, ENA, MIT1, ATM1) are co-regulated with IREG2/FPN2 and YSLs to limit potentially toxic iron in the cytosol, by compartmentalizing in the vacuoles, mitochondria, chloroplast and other non-characterized intracellular vesicles. In the chloroplasts, Fe excess probably promotes NO production. NO is probably involved in activation of the transcription factor (TF) cascades re‐ sponsible for the regulation of Fe uptake, homeostasis and for the tuning of cellular metabolism, including increased synthesis of ferritins and betalains in chloroplasts and frataxins in the mitochondria. Because NO also triggers the syn‐ thesis of ROS, heme biosynthesis likely occurs to compartmentalize excess iron and to limit NO production. Alongside heme biosynthesis, the potent antioxidant system involving SOD and APX probably scavenge and detoxify the excess ROS. Also presented are targets of iron utilization, which could reduce iron overload. This includes synthesis of ferro‐ chelatase (FC) for heme biosynthesis, mitochondrial iron-sulphur cluster (ISC) and plastid-localized sulphur utilization

In this chapter, we have attempted to present the recent advances in crop tolerance to abiotic stresses. Various strategies used by plants to counteract stress, and some success in identifying genomic regions associated with plant tolerance is presented. Interestingly, plants have evolved common regulatory networks in response to abiotic stresses. For instance, drought, salt and cold stress induce calcium influx to activate the downstream second messengers to yield different or similar responses. Calcium influx channels at the membrane (e.g., the recently reported *hyper-osmolality induced [Ca 2+ ] increases 1* (*OSCA1*) from *Arabidopsis thaliana* that is gated by hyper-osmotic stress [280]) act in concert with the membrane-located NADPHoxidase Respiratory burst oxidase Homolog (RboH), generating apoplastic ROS. Intracellular transduction is conveyed by calcium-binding proteins (e.g., CBLs/CIPKs, CDPKs and calci‐ neurins), a MAP-Kinase cascade and phytohormones (e.g., ABA, ET, JA and SA), which apparently act as integrators of early signals. Depending on the relative temporal patterns of these upstream signals, the activity of TFs and their interacting proteins will decipher specific combinations of genes required to be expressed to boost enzymatic or protein reaction levels necessary to counter the stress perceived. These proteins largely contribute to adaptive response in most plants, e.g., production of compatible osmolytes that helps to reinstall turgidity during drought and synthesis of LEA proteins that prevent protein precipitation. Other examples include chelation/sequestering of ions into cellular compartments in response to toxic elements, induction of anti-oxidative enzymes, induction of molecular chaperones and adaptive regulation of plant hormones. These adaptive strategies and the molecular compo‐ nents involved provide potential molecular genetic targets for enhancing abiotic resistance in crops.

However, many challenges still lie ahead. For example, the regulation of signaling cascades, especially how plants can discriminate the signaling components, and even their specific combinations, to activate specific downstream biological processes for a given stress. A frequent manifestation has been the case of ethylene controversial role in abiotic stress response. Whether the negative regulations associated with ethylene represent a plant strategic mechanism to prime the subsequent useful reaction remains to be confirmed. Also, temporal and specific differences in activation of upstream signaling components will need to be explored to help in identifying molecular components essentially required to counter a given stress. Moreover, the specific downstream components for which much of the studies have been conducted, e.g. transcription factors, transmembrane proteins, transporters, enzymes for osmolyte biosynthesis, hormonal regulators, ROS scavengers and other traits that have been shown to play major roles in plant response to stress, will need classification according to their aptitude and functional significance in response to a given abiotic stress. Morpho-physiolog‐ ical traits associated with stress tolerance would also substantially reinforce the successes in molecular biology if addressed to a greater extent. The use of models for predicting gene effects, particularly when combining multiple traits, will also find greater application in dissecting G × E interactions and will help breeders to improve target varieties. Thus, there is need to integrate molecular tools with precise high-throughput phenotyping and biochemical analysis to confirm the consistency of various molecular findings, and to realize the full benefits of molecular biology in selecting genotypes that are stably tolerant under a given stress, considering the interaction with various environments. Here, we emphasize stresses that have been commonly reported in literature, which would provide a basis for understanding other minor stresses. We also refer to the chapter on biotic stresses and the numerous interactions in signaling pathways and expressions of resistance and tolerance on molecular level towards abiotic and biotic stress in plants. Additional background information can also be found in excellent reviews and references therein.

#### **Acknowledgements**

reported *hyper-osmolality induced [Ca 2+ ] increases 1* (*OSCA1*) from *Arabidopsis thaliana* that is gated by hyper-osmotic stress [280]) act in concert with the membrane-located NADPHoxidase Respiratory burst oxidase Homolog (RboH), generating apoplastic ROS. Intracellular transduction is conveyed by calcium-binding proteins (e.g., CBLs/CIPKs, CDPKs and calci‐ neurins), a MAP-Kinase cascade and phytohormones (e.g., ABA, ET, JA and SA), which apparently act as integrators of early signals. Depending on the relative temporal patterns of these upstream signals, the activity of TFs and their interacting proteins will decipher specific combinations of genes required to be expressed to boost enzymatic or protein reaction levels necessary to counter the stress perceived. These proteins largely contribute to adaptive response in most plants, e.g., production of compatible osmolytes that helps to reinstall turgidity during drought and synthesis of LEA proteins that prevent protein precipitation. Other examples include chelation/sequestering of ions into cellular compartments in response to toxic elements, induction of anti-oxidative enzymes, induction of molecular chaperones and adaptive regulation of plant hormones. These adaptive strategies and the molecular compo‐ nents involved provide potential molecular genetic targets for enhancing abiotic resistance in

However, many challenges still lie ahead. For example, the regulation of signaling cascades, especially how plants can discriminate the signaling components, and even their specific combinations, to activate specific downstream biological processes for a given stress. A frequent manifestation has been the case of ethylene controversial role in abiotic stress response. Whether the negative regulations associated with ethylene represent a plant strategic mechanism to prime the subsequent useful reaction remains to be confirmed. Also, temporal and specific differences in activation of upstream signaling components will need to be explored to help in identifying molecular components essentially required to counter a given stress. Moreover, the specific downstream components for which much of the studies have been conducted, e.g. transcription factors, transmembrane proteins, transporters, enzymes for osmolyte biosynthesis, hormonal regulators, ROS scavengers and other traits that have been shown to play major roles in plant response to stress, will need classification according to their aptitude and functional significance in response to a given abiotic stress. Morpho-physiolog‐ ical traits associated with stress tolerance would also substantially reinforce the successes in molecular biology if addressed to a greater extent. The use of models for predicting gene effects, particularly when combining multiple traits, will also find greater application in dissecting G × E interactions and will help breeders to improve target varieties. Thus, there is need to integrate molecular tools with precise high-throughput phenotyping and biochemical analysis to confirm the consistency of various molecular findings, and to realize the full benefits of molecular biology in selecting genotypes that are stably tolerant under a given stress, considering the interaction with various environments. Here, we emphasize stresses that have been commonly reported in literature, which would provide a basis for understanding other minor stresses. We also refer to the chapter on biotic stresses and the numerous interactions in signaling pathways and expressions of resistance and tolerance on molecular level towards abiotic and biotic stress in plants. Additional background information can also be found in

crops.

202 Plant Genomics

excellent reviews and references therein.

This publication was supported by Erfurt University of Applied Sciences.

#### **Author details**

Geoffrey Onaga1 and Kerstin Wydra2\*

\*Address all correspondence to: kerstin.wydra@fh-erfurt.de

1 National Crops Resources Research Institute, Kampala, Uganda

2 Erfurt University of Applied Sciences, Faculty of Landscape Architecture, Horticulture and Forestry, Erfurt, Germany

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**Chapter 10**

**Advances in Plant Tolerance to Biotic Stresses**

Plants being sessile in nature encounter numerous biotic agents, including bacteria, fun‐ gi, viruses, insects, nematodes and protists. A great number of publications indicate that biotic agents significantly reduce crop productivity, although there are some biotic agents that symbiotically or synergistically co-exist with plants. Nonetheless, scientists have made significant advances in understanding the plant defence mechanisms ex‐ pressed against biotic stresses. These mechanisms range from anatomy, physiology, bio‐ chemistry, genetics, development and evolution to their associated molecular dynamics. Using model plants, e.g., Arabidopsis and rice, efforts to understand these mechanisms have led to the identification of representative candidate genes, quantitative trait loci (QTLs), proteins and metabolites associated with plant defences against biotic stresses. However, there are drawbacks and insufficiencies in precisely deciphering and deploy‐ ing these mechanisms, including only modest adaptability of some identified genes or QTLs to changing stress factors. Thus, more systematic efforts are needed to explore and expand the development of biotic stress resistant germplasm. In this chapter, we provid‐ ed a comprehensive overview and discussed plant defence mechanisms involving mo‐ lecular and cellular adaptation to biotic stresses. The latest achievements and perspective on plant molecular responses to biotic stresses, including gene expression, and targeted functional analyses of the genes expressed against biotic stresses have been

**Keywords:** Biotic stress, climate change, innate immunity, phytohormones

Biotic stresses are the damage to plants caused by other living organisms such as bacteria, fungi, nematodes, protists, insects, viruses and viroids. Numerous biotic stresses are of historical significance, for instance, the potato blight in Ireland, coffee rust in Brazil, maize leaf blight caused by *Cochliobolus heterostrophus* in the United States and the great Bengal famine

and reproduction in any medium, provided the original work is properly cited.

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

Geoffrey Onaga and Kerstin Wydra

http://dx.doi.org/10.5772/64351

presented and discussed.

**1. Introduction**

**Abstract**

Additional information is available at the end of the chapter


## **Advances in Plant Tolerance to Biotic Stresses**

#### Geoffrey Onaga and Kerstin Wydra

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64351

#### **Abstract**

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[280] Fukuda A, Shiratsuchi H, Fukushima A, Yamaguchi H, Mochida H, Terao T, Ogi‐ wara H. Detection of chromosomal regions affecting iron concentration in rice shoots subjected to excess ferrous iron using chromosomal segment substitution lines be‐ tween Japonica and Indica. Plant Production Science. 2012;15:183–191. DOI: 10.1626/

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rice leaves. Plant and Soil. 1996;180:159–163. DOI: 10.1007/BF00015422

2001;35(1):75–80. DOI: 10.1023/A:1013879019368

2014;26:135–146. DOI: 10.1007/s40626-014-0013-3

s12284-014-0008-3

228 Plant Genomics

s10681-014-1255-5

10.1080/15228860903064989

514(7522):367-371. DOI: 10.1038/nature13593

pps.15.183

Plants being sessile in nature encounter numerous biotic agents, including bacteria, fun‐ gi, viruses, insects, nematodes and protists. A great number of publications indicate that biotic agents significantly reduce crop productivity, although there are some biotic agents that symbiotically or synergistically co-exist with plants. Nonetheless, scientists have made significant advances in understanding the plant defence mechanisms ex‐ pressed against biotic stresses. These mechanisms range from anatomy, physiology, bio‐ chemistry, genetics, development and evolution to their associated molecular dynamics. Using model plants, e.g., Arabidopsis and rice, efforts to understand these mechanisms have led to the identification of representative candidate genes, quantitative trait loci (QTLs), proteins and metabolites associated with plant defences against biotic stresses. However, there are drawbacks and insufficiencies in precisely deciphering and deploy‐ ing these mechanisms, including only modest adaptability of some identified genes or QTLs to changing stress factors. Thus, more systematic efforts are needed to explore and expand the development of biotic stress resistant germplasm. In this chapter, we provid‐ ed a comprehensive overview and discussed plant defence mechanisms involving mo‐ lecular and cellular adaptation to biotic stresses. The latest achievements and perspective on plant molecular responses to biotic stresses, including gene expression, and targeted functional analyses of the genes expressed against biotic stresses have been presented and discussed.

**Keywords:** Biotic stress, climate change, innate immunity, phytohormones

#### **1. Introduction**

Biotic stresses are the damage to plants caused by other living organisms such as bacteria, fungi, nematodes, protists, insects, viruses and viroids. Numerous biotic stresses are of historical significance, for instance, the potato blight in Ireland, coffee rust in Brazil, maize leaf blight caused by *Cochliobolus heterostrophus* in the United States and the great Bengal famine

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

in 1943 [1]. These are some of the major events that devastated food production and led to millions of human deaths and migration to other countries in the past. Presently, the occur‐ rence of new pathogen races and insect biotypes poses further threat to crop production [2]. Pathogens account for about 15% losses in global food production, and are a major challenge in breeding resistant crops. Considering that genetic polymorphism is present in phytopatho‐ genic agents and insect populations, changes in the climatic factors are considered to further influence/modify this polymorphism, causing evolution of aggressive strains or biotypes [3] that will alter the outcome of host-pathogen interaction. Thus, disease or insect pest outbreaks are expected to continue to cause food production losses or even worsen by expanding to the areas they were not prevalent before [4]. This has important implications for the management options available. Using a combination of options provides certainly more reliability. How‐ ever, in areas where resources are limiting, e.g., the smallholder farming systems in rural Africa and South East Asia, plant breeders are compelled to make the best use of the diverse disease and pest resistance alleles existing in cultivated crop gene pools and their wild relatives. Thus, exploring the mechanisms of resistance regulated by these resistance alleles is required to enable their exploitation for improving the cultivated elite germplasm that support most of the rural poor livelihoods.

but also systemically in uninfected tissues and/or plants. SAR provides long-term defense against a broad-spectrum of pathogens and insects. Another form of induced resistance, which, in many aspects, is similar to SAR, is induced systemic resistance (ISR). ISR is potentiated by plant growth promoting rhizobacteria (PGPR), many of them belonging to *Pseudomonas* species. Obviously, the sessile nature of plants requires an efficient signalling system capable of detecting, transporting and interpreting signals produced at the plant-pathogen interface, and SAR and ISR provide a practical means to confer a fitness advantage to plants in conditions of high disease pressure, since plants are primed to more quickly and effectively activate their defences ahead of pathogen/ insect attack. Plants also defend themselves through RNA interference to target and inactivate invading nucleic acids from viruses, and more recently

Advances in Plant Tolerance to Biotic Stresses

http://dx.doi.org/10.5772/64351

231

These are the aspects that this chapter has addressed to provide background information for a more detailed discussion of the diverse aspects of plant defence patterns, including qualita‐ tive and quantitative mechanisms and their associated molecular patterns. Although patho‐ genic mechanisms would be interesting to the reader, this chapter does not delve extensively into this aspect, except to mention it as a consideration in emphasizing certain aspects of plant resistance. For additional background, the reader is referred to excellent reviews and the

Plants respond to various pathogens through an intricate and dynamic defence system. The mechanism of defence has been classified as innate and systemic plant response. The overview of plant defence response is represented in Figure 1. An innate defence is exhibited by the plant in two ways, viz., specific (cultivar/pathogen race specific) and non-specific (non-host or general resistance) [8]. The molecular basis of non-host resistance is not well studied, but presumably relies on both constitutive barriers and inducible responses that involve a large array of proteins and other organic molecules produced prior to infection or during pathogen attack [9, 10]. Constitutive defences include morphological and structural barriers (cell walls, epidermis layer, trichomes, thorns, etc.), chemical compounds (metabolites, phenolics, nitrogen compounds, saponins, terpenoids, steroids and glucosinolates), and proteins and enzymes [11, 12, 199]. These compounds confer tolerance or resistance to biotic stresses by not only protecting the plant from invasion, but also giving the plant strength and rigidity. The inducible defences, e.g., the production of toxic chemicals, pathogen-degrading enzymes e.g., chitinases and glucanases, and deliberate cell suicide are conservatively used by plants because of the high energy costs and nutrient requirements associated with their production and maintenance. These compounds may be present in their biologically active forms or stored as inactive precursors that are converted to their active forms by host enzymes in response to pathogen attack or tissue damage. Plant defence strategies involving these compounds can fall in either category, innate or SAR. Although innate immunity is of greater efficiency and is the most common form of plant resistance to microbes, both defence strategies depend on the

references therein that address plant-pathogen interaction.

**2. Plant defence mechanisms in response to pathogens**

fungal pathogens.

Plant mechanisms of resistance to various pathogens and insect pests are known to involve an array of morphological, genetic, biochemical and molecular processes [5]. These mechanisms may be expressed continuously (constitutively) as preformed resistance, or they may be inducible and deployed only after attack. Plant success in deploying these resistance mecha‐ nisms is an evolved ability to persist in unfavourable and variable environments [6]. The recent realization that plant mechanisms of disease/insect resistance or susceptibility are related to mechanistic animal immunity [7] has significantly reshaped our view of plant immunity. The identification of plant pattern recognition receptors (PRRs) that sense pathogens' or insect pests'conserved molecules termed pathogen-associated molecular patterns or herbivoreassociated molecular patterns (PAMPs/MAMPs/HAMPs)—and the subsequent PAMPtriggered immunity (PTI) [8] is a paradigm for plant-pathogen interaction studies.

On the other hand, the ability of pathogens/insect pests to suppress or evade PTI, as a structural and functional basis of pathogen survival and evolutionary dynamics in their feeding mech‐ anisms has revitalized research on the so-called 'gene-for-gene' effector induced resistance in plants. It is now clear that effectors are important determinants of pathogens' ability to evade the plant's arsenal targeted towards PAMPs/HAMPs. Effector induced resistance or vertical resistance, often interchangeably translated in modern terms as effector triggered immunity (ETI), is the most successful means of controlling pathogens able to evade PTI [6]. ETI engages a compensatory mechanism within the defense network to transcriptionally coordinate and boost the defense output against pathogens. ETI mostly relies on the endogenious NB-LRR protein products encoded by the resistance (R)-genes. Although R gene mediated resistance is generally not durable, ETI is now effectively deployed through pyramiding of several resistance (R)-genes in the same cultivar, which increases resistance durability and spectrum.

Another aspect of resistance that has gained significance in plant defence studies is the systemic acquired resistance (SAR), in which defence proteins accumulate not only at the site of infection but also systemically in uninfected tissues and/or plants. SAR provides long-term defense against a broad-spectrum of pathogens and insects. Another form of induced resistance, which, in many aspects, is similar to SAR, is induced systemic resistance (ISR). ISR is potentiated by plant growth promoting rhizobacteria (PGPR), many of them belonging to *Pseudomonas* species. Obviously, the sessile nature of plants requires an efficient signalling system capable of detecting, transporting and interpreting signals produced at the plant-pathogen interface, and SAR and ISR provide a practical means to confer a fitness advantage to plants in conditions of high disease pressure, since plants are primed to more quickly and effectively activate their defences ahead of pathogen/ insect attack. Plants also defend themselves through RNA interference to target and inactivate invading nucleic acids from viruses, and more recently fungal pathogens.

These are the aspects that this chapter has addressed to provide background information for a more detailed discussion of the diverse aspects of plant defence patterns, including qualita‐ tive and quantitative mechanisms and their associated molecular patterns. Although patho‐ genic mechanisms would be interesting to the reader, this chapter does not delve extensively into this aspect, except to mention it as a consideration in emphasizing certain aspects of plant resistance. For additional background, the reader is referred to excellent reviews and the references therein that address plant-pathogen interaction.

#### **2. Plant defence mechanisms in response to pathogens**

in 1943 [1]. These are some of the major events that devastated food production and led to millions of human deaths and migration to other countries in the past. Presently, the occur‐ rence of new pathogen races and insect biotypes poses further threat to crop production [2]. Pathogens account for about 15% losses in global food production, and are a major challenge in breeding resistant crops. Considering that genetic polymorphism is present in phytopatho‐ genic agents and insect populations, changes in the climatic factors are considered to further influence/modify this polymorphism, causing evolution of aggressive strains or biotypes [3] that will alter the outcome of host-pathogen interaction. Thus, disease or insect pest outbreaks are expected to continue to cause food production losses or even worsen by expanding to the areas they were not prevalent before [4]. This has important implications for the management options available. Using a combination of options provides certainly more reliability. How‐ ever, in areas where resources are limiting, e.g., the smallholder farming systems in rural Africa and South East Asia, plant breeders are compelled to make the best use of the diverse disease and pest resistance alleles existing in cultivated crop gene pools and their wild relatives. Thus, exploring the mechanisms of resistance regulated by these resistance alleles is required to enable their exploitation for improving the cultivated elite germplasm that support most of

Plant mechanisms of resistance to various pathogens and insect pests are known to involve an array of morphological, genetic, biochemical and molecular processes [5]. These mechanisms may be expressed continuously (constitutively) as preformed resistance, or they may be inducible and deployed only after attack. Plant success in deploying these resistance mecha‐ nisms is an evolved ability to persist in unfavourable and variable environments [6]. The recent realization that plant mechanisms of disease/insect resistance or susceptibility are related to mechanistic animal immunity [7] has significantly reshaped our view of plant immunity. The identification of plant pattern recognition receptors (PRRs) that sense pathogens' or insect pests'conserved molecules termed pathogen-associated molecular patterns or herbivoreassociated molecular patterns (PAMPs/MAMPs/HAMPs)—and the subsequent PAMP-

triggered immunity (PTI) [8] is a paradigm for plant-pathogen interaction studies.

On the other hand, the ability of pathogens/insect pests to suppress or evade PTI, as a structural and functional basis of pathogen survival and evolutionary dynamics in their feeding mech‐ anisms has revitalized research on the so-called 'gene-for-gene' effector induced resistance in plants. It is now clear that effectors are important determinants of pathogens' ability to evade the plant's arsenal targeted towards PAMPs/HAMPs. Effector induced resistance or vertical resistance, often interchangeably translated in modern terms as effector triggered immunity (ETI), is the most successful means of controlling pathogens able to evade PTI [6]. ETI engages a compensatory mechanism within the defense network to transcriptionally coordinate and boost the defense output against pathogens. ETI mostly relies on the endogenious NB-LRR protein products encoded by the resistance (R)-genes. Although R gene mediated resistance is generally not durable, ETI is now effectively deployed through pyramiding of several resistance (R)-genes in the same cultivar, which increases resistance durability and spectrum.

Another aspect of resistance that has gained significance in plant defence studies is the systemic acquired resistance (SAR), in which defence proteins accumulate not only at the site of infection

the rural poor livelihoods.

230 Plant Genomics

Plants respond to various pathogens through an intricate and dynamic defence system. The mechanism of defence has been classified as innate and systemic plant response. The overview of plant defence response is represented in Figure 1. An innate defence is exhibited by the plant in two ways, viz., specific (cultivar/pathogen race specific) and non-specific (non-host or general resistance) [8]. The molecular basis of non-host resistance is not well studied, but presumably relies on both constitutive barriers and inducible responses that involve a large array of proteins and other organic molecules produced prior to infection or during pathogen attack [9, 10]. Constitutive defences include morphological and structural barriers (cell walls, epidermis layer, trichomes, thorns, etc.), chemical compounds (metabolites, phenolics, nitrogen compounds, saponins, terpenoids, steroids and glucosinolates), and proteins and enzymes [11, 12, 199]. These compounds confer tolerance or resistance to biotic stresses by not only protecting the plant from invasion, but also giving the plant strength and rigidity. The inducible defences, e.g., the production of toxic chemicals, pathogen-degrading enzymes e.g., chitinases and glucanases, and deliberate cell suicide are conservatively used by plants because of the high energy costs and nutrient requirements associated with their production and maintenance. These compounds may be present in their biologically active forms or stored as inactive precursors that are converted to their active forms by host enzymes in response to pathogen attack or tissue damage. Plant defence strategies involving these compounds can fall in either category, innate or SAR. Although innate immunity is of greater efficiency and is the most common form of plant resistance to microbes, both defence strategies depend on the ability of the plant to distinguish between self and non-self molecules. The molecular bases of these defence mechanisms are discussed below.

to a compromised 'self', also called damage-associated molecular patterns (DAMPs) [14, 15]. Both PAMPs and DAMPs are recognized by transmembrane pattern recognition receptors

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A common strategy employed by adapted pathogens is to secrete effector proteins that avoid or regulate PTI recognition. To counter this stealth afforded by the microbial effectors, plants have evolved an intracellular surveillance involving polymorphic NB-LRR protein products encoded by resistance (R) genes, named after their characteristic feature due to the presence of nucleotide binding (NB) and leucine-rich repeat (LRR) domains [9]. This type of plant defence is referred to as ETI and is synonymous to pathogen race/host plant cultivar-specific

Generally, PTI and ETI trigger similar defence responses, but ETI is much faster and quanti‐ tatively stronger [16]. ETI is often associated with a localized cell death termed the hypersen‐ sitive response (HR) that functions to restrict further spread of microbial attack [9, 17]. Hence, the important feature of ETI is the ability to sense microbe-mediated modifications inferred on points of vulnerability in the host, whereas PTI is able to sense infectious-self and non-self. By guarding against weak points or even setting up decoys to confuse invaders, ETI is an efficient defence system for more progressed infections [15, 18], whereas PTI is important for non-host resistance and for basal immunity in susceptible host plant cultivars. In the following section, we will discuss novel insights and overviews on the dynamics of innate immunity in

**3.1. Pathogen- or microbial-associated molecular-pattern (PAMP/MAMP)-triggered**

PTI (formerly called basal or horizontal disease resistance) is the first facet of active plant defence and can be considered as the primary driving force of plant-microbe interactions [19]. As discussed before, PTI involves the recognition of conserved, indispensable microbial elicitors known as PAMPs by PRRs of either the receptor-like kinase (RLK) or receptor-like proteins (RLPs) families, which are membranous bound extracellular receptors. RLPs resemble the extracellular domains of RLKs, but lack the cytosolic signalling domain, whereas RLKs have both extracellular and intracellular kinase domains [6]. Instances of hetero-oligomeric complexes between RLKs and RLPs have been reported to occur, and to complement each other in PAMP detection [8], as will be discussed in the following sections. Examples of RLPs include the S locus glycoprotein (*SLG*), *CLAVATA2* and *Xa21D*. RLKs are numerous, and some examples will also be discussed in the following sections. Despite different configurations, both RLKs and RLPs receptors contribute to blocking infection before the microbe gains a hold

PAMPs occur throughout the pathogen classes, including bacterial flagellin (*flg22*) and EF-Tu (*elf18*), fungal chitin (*CEBiP*) and mannans of yeast, xylanase (*LeEIX1/2*) and Oomycetes' heptaglucan (*HG*) [17, 19–21]. The early responses induced by PAMPs occur within minutes to hours and are varied, ranging from rapid ion fluxes across the plasma membrane, oxidative burst, activation of mitogen-activated protein kinases (MAPKs) and calcium-dependent protein kinases (CDPKs) to local induction of defence -related genes or pathogen cell wall/cell

(PRRs).

plant disease resistance [8].

plant defence.

**immunity (PTI)**

on the plant.

**Figure 1.** Overview of cellular mechanisms of biotic stress response leading to innate immunity and systemic acquired resistance. Plant PRRs or R-genes perceive PAMPS/DAMPs and effectors, respectively. Inside the cell, an overlapping set of downstream immune responses results from the PTI/ETI continuum. This includes the activation of multiple sig‐ naling pathways involving reactive oxygen species (ROS), defense hormones (such as salicylic acid, jasmonic acid and ethylene), mitogen activated protein kinases (MAPK), and transcription factor families, e.g., AP2/ERF, WRKY, MYB, bZIP etc. these signals activate either innate response or acquired immune response or both.

#### **3. Innate immunity**

Innate immunity in plants is divided into microbial-associated molecular-pattern-triggered immunity (MTI; also called PTI) and effector-triggered immunity (ETI). In MTI/PTI, innate immunity is defined by receptors for microbe-associated molecules, conserved mitogenassociated protein kinase signalling cascades and the production of antimicrobial peptides/ compounds [13]. Recognition of microbes is divided into two branches, one involving slowly evolving microbial- or pathogen-associated molecular patterns, such as fungal chitin, xylanase or bacterial flagellin, lipopolysaccharides and peptidoglycans [14], and the other that responds to a compromised 'self', also called damage-associated molecular patterns (DAMPs) [14, 15]. Both PAMPs and DAMPs are recognized by transmembrane pattern recognition receptors (PRRs).

ability of the plant to distinguish between self and non-self molecules. The molecular bases of

**Pathogen**

**Signal transduction (e.g. MAPK cascades (MPK6), EDS1, SGT1, HSPs) (H2O2, SA, JA, ET, NO)** 

**Signals (e.g. endogenous/exogenous elicitors** 

**e.g. Avrs, mechanical stimulation)** 

**Innate resistance Acquired resistance**

Acquired resistance develops against a second infection "Stress memory"

**Signal perception by PAMP receptors e.g. FLS2**

Accumulation of SA; Stimulated antioxidants; Gene silencing; Rhizobacterial induction

Non specific, general

**(HR; ROS; BAX inhibitor-1;**

2. Basal resistance against bacteria **(Flagellin/FLS2 interaction; ROS; Antimicrobial compounds)** 3. Race non-specific mlo resistance and quantitative resistance to fungi

**Antimicrobial compounds; ROS)**  4. Resistance to necrosis-inducing

**(High antioxidant capacity)**

**Figure 1.** Overview of cellular mechanisms of biotic stress response leading to innate immunity and systemic acquired resistance. Plant PRRs or R-genes perceive PAMPS/DAMPs and effectors, respectively. Inside the cell, an overlapping set of downstream immune responses results from the PTI/ETI continuum. This includes the activation of multiple sig‐ naling pathways involving reactive oxygen species (ROS), defense hormones (such as salicylic acid, jasmonic acid and ethylene), mitogen activated protein kinases (MAPK), and transcription factor families, e.g., AP2/ERF, WRKY, MYB,

Innate immunity in plants is divided into microbial-associated molecular-pattern-triggered immunity (MTI; also called PTI) and effector-triggered immunity (ETI). In MTI/PTI, innate immunity is defined by receptors for microbe-associated molecules, conserved mitogenassociated protein kinase signalling cascades and the production of antimicrobial peptides/ compounds [13]. Recognition of microbes is divided into two branches, one involving slowly evolving microbial- or pathogen-associated molecular patterns, such as fungal chitin, xylanase or bacterial flagellin, lipopolysaccharides and peptidoglycans [14], and the other that responds

**(Cell wall thickening;**

resistance

1. Non-host resistance

**PEN genes)**

stresses

bZIP etc. these signals activate either innate response or acquired immune response or both.

these defence mechanisms are discussed below.

Specific resistance (cultivar/ pathogenic race specificity)

symptomless gene-for-gene resist. 2. Rx-resistance against viruses

6. Gene silencing **(Recognition and decomposition of foreign RNAs** 

3. Symptomless reaction to rust pathogens, no visible HR 4. Gene-for-gene resistance **(ROS; Phytoalexins; Phenol oxidation; Stress proteins)** 5. Resistance to pathogen toxins **(Enzymatic detoxification; Lack** 

1. Extreme resistance –

**Signal perception by R genes**

232 Plant Genomics

without HR

**of toxin recept)**

**with ribonucleases)**

**3. Innate immunity**

**Plant defense mechanisms**

A common strategy employed by adapted pathogens is to secrete effector proteins that avoid or regulate PTI recognition. To counter this stealth afforded by the microbial effectors, plants have evolved an intracellular surveillance involving polymorphic NB-LRR protein products encoded by resistance (R) genes, named after their characteristic feature due to the presence of nucleotide binding (NB) and leucine-rich repeat (LRR) domains [9]. This type of plant defence is referred to as ETI and is synonymous to pathogen race/host plant cultivar-specific plant disease resistance [8].

Generally, PTI and ETI trigger similar defence responses, but ETI is much faster and quanti‐ tatively stronger [16]. ETI is often associated with a localized cell death termed the hypersen‐ sitive response (HR) that functions to restrict further spread of microbial attack [9, 17]. Hence, the important feature of ETI is the ability to sense microbe-mediated modifications inferred on points of vulnerability in the host, whereas PTI is able to sense infectious-self and non-self. By guarding against weak points or even setting up decoys to confuse invaders, ETI is an efficient defence system for more progressed infections [15, 18], whereas PTI is important for non-host resistance and for basal immunity in susceptible host plant cultivars. In the following section, we will discuss novel insights and overviews on the dynamics of innate immunity in plant defence.

#### **3.1. Pathogen- or microbial-associated molecular-pattern (PAMP/MAMP)-triggered immunity (PTI)**

PTI (formerly called basal or horizontal disease resistance) is the first facet of active plant defence and can be considered as the primary driving force of plant-microbe interactions [19]. As discussed before, PTI involves the recognition of conserved, indispensable microbial elicitors known as PAMPs by PRRs of either the receptor-like kinase (RLK) or receptor-like proteins (RLPs) families, which are membranous bound extracellular receptors. RLPs resemble the extracellular domains of RLKs, but lack the cytosolic signalling domain, whereas RLKs have both extracellular and intracellular kinase domains [6]. Instances of hetero-oligomeric complexes between RLKs and RLPs have been reported to occur, and to complement each other in PAMP detection [8], as will be discussed in the following sections. Examples of RLPs include the S locus glycoprotein (*SLG*), *CLAVATA2* and *Xa21D*. RLKs are numerous, and some examples will also be discussed in the following sections. Despite different configurations, both RLKs and RLPs receptors contribute to blocking infection before the microbe gains a hold on the plant.

PAMPs occur throughout the pathogen classes, including bacterial flagellin (*flg22*) and EF-Tu (*elf18*), fungal chitin (*CEBiP*) and mannans of yeast, xylanase (*LeEIX1/2*) and Oomycetes' heptaglucan (*HG*) [17, 19–21]. The early responses induced by PAMPs occur within minutes to hours and are varied, ranging from rapid ion fluxes across the plasma membrane, oxidative burst, activation of mitogen-activated protein kinases (MAPKs) and calcium-dependent protein kinases (CDPKs) to local induction of defence -related genes or pathogen cell wall/cell membranes lyasing enzymes/peptides, e.g., chitinases, glucanases and defensins (Figure 1) [22]. Other responses may include production of antimicrobial phytoalexins, plant cell wall modifications, e.g. deposition of papillae, enriched with (1,3)-β-glucan cell wall polymer, callose, lignin biosynthesis, or changes in cell wall proteins and pectic polysaccharide struc‐ tures [14, 22, 89, 90, 200]. When the pathogen gains entry and initiates colonization, a concerted effort of both PTI and ETI may be required to restrict further colonization. In the event that ETI is not active, PTI could probably contribute to effective plant resistance as much as ETI, if the capacity to recognize undetected epitopes could be engineered into plants. Some of the examples of PTI that have been shown to contribute to resistance in plants are discussed in the following section.

for the ROS burst and induction of *MAPK* cascades. These signalling cascades activate transcriptional reprogrammers such as the *WRKY* TFs, which are required for induction of

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Elongation factor Tu (EF-Tu) is the most abundant bacterial protein originally isolated from *Escherichia coli*, and acts as PAMP in *Brassicaceae* family members including *A. thaliana* [33]. The conserved *N*-acetylated epitope *elf18* (first 18 amino acids of the protein) is sufficient to trigger defence responses in plants [33, 34]. The shorter peptide, *elf12* (first 12 N-terminal amino acids), comprising the acetyl group, is inactive as an elicitor but acts as a specific antagonist for EF-Tu–related elicitors. EF-Tu is recognized by the *LRR-RLK EF-TU RECEPTOR* (*EFR*) of the same subfamily (*LRRXII*) as *FLS2* [34]. Interestingly, the ability to perceive *elf18* epitope seems restricted to the plant family *Brassicaceae*. However, heterologous expression of *EFR* in the Solanaceae family, e.g., *N. benthamiana* and *Solanum lycopersicum*, makes them more resistant to a range of phytopathogenic bacteria, suggesting that *EFR* can be as well used to engineer broad-spectrum disease resistance in other families [35]. More recently, *EFa50* central region comprising *Lys176* to *Gly225* was found to be fully active as a PAMP in rice and induced H2O2 generation and callose deposition [36]. Moreover, *AtEFR*-transformed rice plants were shown to be well responsive to the *Xanthomonas oryzae* derived *elf18* peptide by strongly inducing ROS burst and expression of *OsPBZ1* in transgenic cell cultures [37], further sug‐

The mechanism of *EFR* resistance is mediated by heteromeric complex formation. For instance, in rice, the complex formed between *SOMATIC EMBRYOGENESIS RECEPTOR KINASEs* (*OsSERK2;* an ortholog of *BAK1*) and *XA21* binding protein 24 (*XB24*) is the most important component of *XA21*-mediated defence response. Four *SERK* co-receptor-like kinases interact with *EFR* within seconds to minutes of ligand binding [38], and once the ligand is perceived, *EFR* is rapidly phosphorylated, which triggers downstream signal activation, including the activation and release of *BIK1*. *BIK1* plays a central role in conveying signals, as discussed before (see discussion on flagellin-induced resistance). Interaction between *EFR* and *SERK* also triggers the activation and release of other members of the cytoplasmic receptor-like kinase subfamily VII from the complex. Downstream components of these responses include activation of a RING finger ubiquitin ligase (*XB3*), *MAPKs*, the plant-specific ankyrin-repeat

Notwithstanding the *FLS2* and *EFR* PRRs identified so far, relatively fewer PRR genes have been utilized to enhance plant resistance to bacterial pathogens through breeding and transgenic approaches [37], except a few that have been shown to be better adapted to defence signalling. The most famous example is that of *Xa21* gene transferred from *Oryza longistami‐ nata*, which confers high resistance to *X. oryzae* in rice [39]. Heterologous expression of *XA21* in *Citrus sinensis*, *Lycopersicon esculentum* and banana (*Musa* sp.) also conferred moderate resistance to *Xanthomonas axonopodis pv. citri* and resistance to *Ralstonia solanacearum* and *Xanthomonas campestris pv. malvacearum* in experiments under controlled conditions [40–42]. The tomato *RLP Ve1*, which recognizes *Ave1* from *Verticillium dahliae race 1* is another interclass example that confers stable resistance when transferred and expressed in Arabidopsis for use as a model genetic system [43]. Taken together, *XA21* and *Ve1* are an example of

defence genes [201].

*3.1.1.2. Elongation factor (EF-Tu) induced resistance*

gesting that *EFR* confers stable resistance across plant families.

(PANK) containing protein *XB25*, and *WRKY* TFs.

#### *3.1.1. Specific examples of PTI in plants*

#### *3.1.1.1. Flagellin-induced resistance*

Flagellin constitutes the main building block of bacterial flagellum, and is so far the best characterized PAMP in plants. A 22 amino acid (*flg22*) peptide-spanning region in the Nterminal part of flagellin of *Pseudomonas syringae* is sufficient to elicit the whole array of typical immune responses in a broad variety of plants [23]. The PRR responsible for flagellin percep‐ tion in the model plant *Arabidopsis thaliana* is the leucine-rich repeat receptor-like kinase (LRR-RLK) *FLAGELLIN-SENSING 2* (*FLS2*). Functional *FLS2* homologs have been identified in other major groups of higher plants, including tomato, grapevine, *Nicotiana benthamiana* and rice, suggesting that the receptors for the *flg22* epitope of bacterial flagellin are evolutionarily ancient and conserved [14, 24]. Despite evolutionary conservation, *FLS2* proteins from different plant species, such as tomato flagellin receptor (*LeFLS2)*, grapevine *(VvFLS2*) and *A. thaliana* (*AtFLS2*), still exhibit different perception specificities to elicitation determinants of flagellins [24–26]. This suggests that the domains found in *FLS* may have undergone some functional innovations that contribute to different perception specificities. Flagellin also seems to be recognized by other means in certain plant species. For instance, in rice, *flg22* epitope does not allow the activation of PRR, but flagellin induces cell death [26]. Moreover, the glycosylation status of flagellin proteins is emerging as a determinant of recognizing adapted and non-adapted bacteria by *Solanaceae* plants, such as tobacco and tomato [27, 28]. More recently, another flagellin, *flgII-28*, was identified in *Solanaceae* [29], though the corresponding PRR is yet to be identified. Both *flg22* and *flgII-28* are physically linked by a stretch of 33 amino acid residues, suggesting that both molecules are detected by the same receptor, *FLS2* [30].

The signalling events triggered in plant cells following *flg22* detection include rapid binding of *FLS2* to *BAK1* (*BRI1-associated kinase 1*) by reciprocal transphosphorylation of their kinase domains [31]. The plasma membrane localized receptor-like cytoplasmic kinase *BOTRYTIS-INDUCED KINASE 1* (*BIK1*) and related *PBS1-LIKE* (*PBL*) kinases associate with *FLS2/BAK1* [32]. The complex formed triggers multiple rapid phosphorylation events resulting in *BIK1* release. *BIK1* plays a central role in conveying signals from not only *FLS2* but also other PRRs, including *EFR*, *CERK1* and the DAMP receptor, *PEPR1/PEPR2*. The signal transduction downstream of *flg22* perception includes a Ca2+ burst, activation of *CDPKs* and *RbohD* required for the ROS burst and induction of *MAPK* cascades. These signalling cascades activate transcriptional reprogrammers such as the *WRKY* TFs, which are required for induction of defence genes [201].

#### *3.1.1.2. Elongation factor (EF-Tu) induced resistance*

membranes lyasing enzymes/peptides, e.g., chitinases, glucanases and defensins (Figure 1) [22]. Other responses may include production of antimicrobial phytoalexins, plant cell wall modifications, e.g. deposition of papillae, enriched with (1,3)-β-glucan cell wall polymer, callose, lignin biosynthesis, or changes in cell wall proteins and pectic polysaccharide struc‐ tures [14, 22, 89, 90, 200]. When the pathogen gains entry and initiates colonization, a concerted effort of both PTI and ETI may be required to restrict further colonization. In the event that ETI is not active, PTI could probably contribute to effective plant resistance as much as ETI, if the capacity to recognize undetected epitopes could be engineered into plants. Some of the examples of PTI that have been shown to contribute to resistance in plants are discussed in the

Flagellin constitutes the main building block of bacterial flagellum, and is so far the best characterized PAMP in plants. A 22 amino acid (*flg22*) peptide-spanning region in the Nterminal part of flagellin of *Pseudomonas syringae* is sufficient to elicit the whole array of typical immune responses in a broad variety of plants [23]. The PRR responsible for flagellin percep‐ tion in the model plant *Arabidopsis thaliana* is the leucine-rich repeat receptor-like kinase (LRR-RLK) *FLAGELLIN-SENSING 2* (*FLS2*). Functional *FLS2* homologs have been identified in other major groups of higher plants, including tomato, grapevine, *Nicotiana benthamiana* and rice, suggesting that the receptors for the *flg22* epitope of bacterial flagellin are evolutionarily ancient and conserved [14, 24]. Despite evolutionary conservation, *FLS2* proteins from different plant species, such as tomato flagellin receptor (*LeFLS2)*, grapevine *(VvFLS2*) and *A. thaliana* (*AtFLS2*), still exhibit different perception specificities to elicitation determinants of flagellins [24–26]. This suggests that the domains found in *FLS* may have undergone some functional innovations that contribute to different perception specificities. Flagellin also seems to be recognized by other means in certain plant species. For instance, in rice, *flg22* epitope does not allow the activation of PRR, but flagellin induces cell death [26]. Moreover, the glycosylation status of flagellin proteins is emerging as a determinant of recognizing adapted and non-adapted bacteria by *Solanaceae* plants, such as tobacco and tomato [27, 28]. More recently, another flagellin, *flgII-28*, was identified in *Solanaceae* [29], though the corresponding PRR is yet to be identified. Both *flg22* and *flgII-28* are physically linked by a stretch of 33 amino acid residues, suggesting that both molecules are detected by the same receptor, *FLS2* [30].

The signalling events triggered in plant cells following *flg22* detection include rapid binding of *FLS2* to *BAK1* (*BRI1-associated kinase 1*) by reciprocal transphosphorylation of their kinase domains [31]. The plasma membrane localized receptor-like cytoplasmic kinase *BOTRYTIS-INDUCED KINASE 1* (*BIK1*) and related *PBS1-LIKE* (*PBL*) kinases associate with *FLS2/BAK1* [32]. The complex formed triggers multiple rapid phosphorylation events resulting in *BIK1* release. *BIK1* plays a central role in conveying signals from not only *FLS2* but also other PRRs, including *EFR*, *CERK1* and the DAMP receptor, *PEPR1/PEPR2*. The signal transduction downstream of *flg22* perception includes a Ca2+ burst, activation of *CDPKs* and *RbohD* required

following section.

234 Plant Genomics

*3.1.1. Specific examples of PTI in plants*

*3.1.1.1. Flagellin-induced resistance*

Elongation factor Tu (EF-Tu) is the most abundant bacterial protein originally isolated from *Escherichia coli*, and acts as PAMP in *Brassicaceae* family members including *A. thaliana* [33]. The conserved *N*-acetylated epitope *elf18* (first 18 amino acids of the protein) is sufficient to trigger defence responses in plants [33, 34]. The shorter peptide, *elf12* (first 12 N-terminal amino acids), comprising the acetyl group, is inactive as an elicitor but acts as a specific antagonist for EF-Tu–related elicitors. EF-Tu is recognized by the *LRR-RLK EF-TU RECEPTOR* (*EFR*) of the same subfamily (*LRRXII*) as *FLS2* [34]. Interestingly, the ability to perceive *elf18* epitope seems restricted to the plant family *Brassicaceae*. However, heterologous expression of *EFR* in the Solanaceae family, e.g., *N. benthamiana* and *Solanum lycopersicum*, makes them more resistant to a range of phytopathogenic bacteria, suggesting that *EFR* can be as well used to engineer broad-spectrum disease resistance in other families [35]. More recently, *EFa50* central region comprising *Lys176* to *Gly225* was found to be fully active as a PAMP in rice and induced H2O2 generation and callose deposition [36]. Moreover, *AtEFR*-transformed rice plants were shown to be well responsive to the *Xanthomonas oryzae* derived *elf18* peptide by strongly inducing ROS burst and expression of *OsPBZ1* in transgenic cell cultures [37], further sug‐ gesting that *EFR* confers stable resistance across plant families.

The mechanism of *EFR* resistance is mediated by heteromeric complex formation. For instance, in rice, the complex formed between *SOMATIC EMBRYOGENESIS RECEPTOR KINASEs* (*OsSERK2;* an ortholog of *BAK1*) and *XA21* binding protein 24 (*XB24*) is the most important component of *XA21*-mediated defence response. Four *SERK* co-receptor-like kinases interact with *EFR* within seconds to minutes of ligand binding [38], and once the ligand is perceived, *EFR* is rapidly phosphorylated, which triggers downstream signal activation, including the activation and release of *BIK1*. *BIK1* plays a central role in conveying signals, as discussed before (see discussion on flagellin-induced resistance). Interaction between *EFR* and *SERK* also triggers the activation and release of other members of the cytoplasmic receptor-like kinase subfamily VII from the complex. Downstream components of these responses include activation of a RING finger ubiquitin ligase (*XB3*), *MAPKs*, the plant-specific ankyrin-repeat (PANK) containing protein *XB25*, and *WRKY* TFs.

Notwithstanding the *FLS2* and *EFR* PRRs identified so far, relatively fewer PRR genes have been utilized to enhance plant resistance to bacterial pathogens through breeding and transgenic approaches [37], except a few that have been shown to be better adapted to defence signalling. The most famous example is that of *Xa21* gene transferred from *Oryza longistami‐ nata*, which confers high resistance to *X. oryzae* in rice [39]. Heterologous expression of *XA21* in *Citrus sinensis*, *Lycopersicon esculentum* and banana (*Musa* sp.) also conferred moderate resistance to *Xanthomonas axonopodis pv. citri* and resistance to *Ralstonia solanacearum* and *Xanthomonas campestris pv. malvacearum* in experiments under controlled conditions [40–42]. The tomato *RLP Ve1*, which recognizes *Ave1* from *Verticillium dahliae race 1* is another interclass example that confers stable resistance when transferred and expressed in Arabidopsis for use as a model genetic system [43]. Taken together, *XA21* and *Ve1* are an example of engineered resistance strategy under controlled conditions, despite their taxonomic restric‐ tions. However, more PRRs recognizing conserved molecular signatures in bacteria will need to be discovered and their complex interaction with the plant's physiology and metabolism and the environment understood, if the ambition of improving crop plants through genetic engineering of broad-spectrum disease resistance by gene transfer is to become more con‐ vincing.

Other PRRs that have been identified in plants in response to fungal PAMPs include the *Brassica napus LepR3/Rlm2,* for blackleg resistance*,* which perceives *AVRLM1* [56]. In *Arabidop‐ sis, Rlm2* interacts with *suppressor of BAK1*-*interacting receptor-like kinase 1* (*AtSOBIR1*), sug‐ gesting that *SOBIR1* is a component of LRR-RLP-mediated resistance against *Leptosphaeria maculans,* which is similar to that formed by rice *OsCERK1 and* Arabidopsis *AtCERK1* [57]. The tomato *Cf* proteins (*Cf2*, *Cf4* and *Cf9*) that recognize the corresponding effector proteins (*Avr2*, *Avr4* and *Avr9*) secreted by *C. fulvum* are other PRR-like receptors that were previously identified. *Cf4* interacts with *BAK1* in a manner similar to the rice ligand binding and associated

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Wheat and Arabidopsis *RLP1.1* and *RLP30* are also involved in antifungal defence, although the corresponding ligands are unknown so far [58]. Several orphan PAMPs with unknown PRRs, from fungi or oomycetes that can trigger immune signalling have also been identified, including fungal ergosterol [59], oomycete arachidonic acid [60], elicitins (*INF1*) [61], the transglutaminase-derived immunogenic epitope *Pep13* [62], cryptogein [63] and cellulosebinding elicitor lectin (*CBEL*) [64]. Thus, further research is required to understand mechanis‐

Taken together, the identification of several potential host plant receptor targets and receptor complexes, and their stability across plant species and in the field will greatly help to improve plant protection. Moreover, identification of several potential microbial molecules that act as PAMPs would increase chances of identifying more potential host plant PRRs for developing

Although viral patterns inducing PTI are well known from animal systems, there is no similar pattern reported for plants [48]. Instead, plant resistance to viruses is mediated by posttranscriptional gene silencing of viral RNA or ETI. Nevertheless, infection by compatible viruses can also induce defence responses similar to PTI. Typical PTI cellular responses in plant-virus interactions include ion fluxes, ROS production, ethylene, salicylic acid (SA), MAPK signalling and callose deposition, for review see [65]. Commonly reported genes associated with PRRs in response to viruses include *PEPs* that encode longer peptides (*ProPEP*) from which small peptides (*PEP*) are derived. In Arabidopsis, *AtPEP* interact with two DAMP PRRs, *PEP*-receptor 1 (*PEPR1*) and *PEPR2* [66], both of which interact with *BAK1* upon recognition of *AtPEP*. Thus, *BAK1* is important for antiviral defence in *Arabidopsis.* Indeed, the *bak1* mutants show enhanced susceptibility to three different RNA viruses (*TMV-U1*, *ORMV* and *TCV*) during compatible interactions [67]. The immune response induced by *PEPR-BAK1* interaction is a classical PTI. Another viral resistance mechanism, which is highly similar to *BAK1* and *BAK1-like Kinase 1* (*BKK1*), is exhibited by the viral nuclear shuttle protein (NSP) interacting kinases (*NIKs*) from leucine-rich repeats containing receptor-like serine/threonine

Recent reviews have also suggested that the ribonuclease III-type DICER-like (DCL) enzymes could be acting as PRRs perceiving viral nucleic acids and triggering immune responses equivalent to the zig-zag model first layer [66]. The virus-derived molecules (e.g., dsRNAs)

receptor *OsSERK/EFR*.

tically how these orphan PAMPs are involved in PTI.

crops with higher resistance or inducible resistance.

*3.1.1.4. Plant perception of virus PAMPs*

kinase (LRR-RKs) subfamily [68].

#### *3.1.1.3. Plant perception of PAMPs from fungi and oomycetes*

Chitin, a homopolymer of β-(1,4)-linked N-acetylglucosamine (GlcNAc) unit, is a major constituent of fungal cell walls and is a classical PAMP [17]. Chitin is an ideal point of attack during plant defence responses since glucosamine polymers are not found in plants. Upon pathogen contact with the host, plant chitinases (hydrolytic enzymes) break down microbial chitin polymers. Interestingly, different plants have evolved mechanisms that employ common factors for chitin perception, and this could be probably the reason for the evolution of pathogen counter measures, e.g., in the biotrophic fungal pathogen *Cladosporium fulvum* [44]. In this context, the reaction of tomato with induction of defense-related, signal transduction and transcription genes to external chitin application supports the role of the described mechanisms [202].

The first chitin-binding PRR was identified in rice as the *lysine motif* (*LysM*)*-RLP*, and was named *chitin*-elicitor *binding* protein (*CEBiP*) [45]. *CEBiP* is a glycoprotein that localizes in the plasma membrane. Upon chitin binding, *CEBiP* homodimerizes and forms a hetero-oligomeric complex with the *Chitin Elicitor Receptor Kinase 1* (*OsCERK1*), the rice ortholog of Arabidopsis *AtCERK1*. The binding thus forms a sandwich-type receptor system for chitin as described in [45, 46]. The mechanism of perception, however, varies between plant species. For example, *AtCERK1* does not seem to employ *CEBiP*-like *LysM-RLPs* to induce typical immune responses such as reactive oxygen species and immune gene expression upon chitin perception [47]. Instead, *AtCERK1* binds directly to octamers of chitin, which in turn induce *AtCERK1* homodimerization and the resultant immune signalling [48]. Arabidopsis *LysM (AtLYM2)*, the closest ortholog of *AtCEBiP*, and the rice *LysM RLPs* (*OsLYP4* and *OsLYP6*) are also able to bind chitin [49]. However, it is not clear whether *AtLYM2/LYK4* also display the putative homodimerization induced by chitin perception. Two other orthologs of *CEBiP*, *AtLYM1* and *AtLYM3*, which specifically bind *PGN,* but not chitin, interact with *AtCERK1*. This indicates that *AtCERK1* is a multifaceted *RLK* that also forms hetero-oligomeric complexes with ligandbinding *RLPs*, probably across different plant families.

Fungal xylanases also function as fungal PAMPs by eliciting defence responses and promoting necrosis [50, 51]. In tomato, ethylene-inducing xylanases (*EIXs*) produced by *Trichoderma* species are perceived by two specific LRR-RLPs receptors, *LeEix1* and *LeEix2* [52]. Both receptors bind *Eixs*, but o*LeEix2* is the primary mediator of defence responses. *LeEix1* hetero‐ dimerizes with *LeEix2* upon application of the *Eixs* and attenuates *Eix*-induced internalization and the subsequent signalling of the *LeEix2* receptor [53]. Microbial xyloglucan-specific endoglucanases (XEGs) have also been reported to induce plant defences. Fungal XEGs are inhibited by xyloglucan endoglucanase inhibiting proteins (*XEGIPs*), which so far have been characterized in tomato, carrot and tobacco [54, 55].

Other PRRs that have been identified in plants in response to fungal PAMPs include the *Brassica napus LepR3/Rlm2,* for blackleg resistance*,* which perceives *AVRLM1* [56]. In *Arabidop‐ sis, Rlm2* interacts with *suppressor of BAK1*-*interacting receptor-like kinase 1* (*AtSOBIR1*), sug‐ gesting that *SOBIR1* is a component of LRR-RLP-mediated resistance against *Leptosphaeria maculans,* which is similar to that formed by rice *OsCERK1 and* Arabidopsis *AtCERK1* [57]. The tomato *Cf* proteins (*Cf2*, *Cf4* and *Cf9*) that recognize the corresponding effector proteins (*Avr2*, *Avr4* and *Avr9*) secreted by *C. fulvum* are other PRR-like receptors that were previously identified. *Cf4* interacts with *BAK1* in a manner similar to the rice ligand binding and associated receptor *OsSERK/EFR*.

Wheat and Arabidopsis *RLP1.1* and *RLP30* are also involved in antifungal defence, although the corresponding ligands are unknown so far [58]. Several orphan PAMPs with unknown PRRs, from fungi or oomycetes that can trigger immune signalling have also been identified, including fungal ergosterol [59], oomycete arachidonic acid [60], elicitins (*INF1*) [61], the transglutaminase-derived immunogenic epitope *Pep13* [62], cryptogein [63] and cellulosebinding elicitor lectin (*CBEL*) [64]. Thus, further research is required to understand mechanis‐ tically how these orphan PAMPs are involved in PTI.

Taken together, the identification of several potential host plant receptor targets and receptor complexes, and their stability across plant species and in the field will greatly help to improve plant protection. Moreover, identification of several potential microbial molecules that act as PAMPs would increase chances of identifying more potential host plant PRRs for developing crops with higher resistance or inducible resistance.

#### *3.1.1.4. Plant perception of virus PAMPs*

engineered resistance strategy under controlled conditions, despite their taxonomic restric‐ tions. However, more PRRs recognizing conserved molecular signatures in bacteria will need to be discovered and their complex interaction with the plant's physiology and metabolism and the environment understood, if the ambition of improving crop plants through genetic engineering of broad-spectrum disease resistance by gene transfer is to become more con‐

Chitin, a homopolymer of β-(1,4)-linked N-acetylglucosamine (GlcNAc) unit, is a major constituent of fungal cell walls and is a classical PAMP [17]. Chitin is an ideal point of attack during plant defence responses since glucosamine polymers are not found in plants. Upon pathogen contact with the host, plant chitinases (hydrolytic enzymes) break down microbial chitin polymers. Interestingly, different plants have evolved mechanisms that employ common factors for chitin perception, and this could be probably the reason for the evolution of pathogen counter measures, e.g., in the biotrophic fungal pathogen *Cladosporium fulvum* [44]. In this context, the reaction of tomato with induction of defense-related, signal transduction and transcription genes to external chitin application supports the role of the described

The first chitin-binding PRR was identified in rice as the *lysine motif* (*LysM*)*-RLP*, and was named *chitin*-elicitor *binding* protein (*CEBiP*) [45]. *CEBiP* is a glycoprotein that localizes in the plasma membrane. Upon chitin binding, *CEBiP* homodimerizes and forms a hetero-oligomeric complex with the *Chitin Elicitor Receptor Kinase 1* (*OsCERK1*), the rice ortholog of Arabidopsis *AtCERK1*. The binding thus forms a sandwich-type receptor system for chitin as described in [45, 46]. The mechanism of perception, however, varies between plant species. For example, *AtCERK1* does not seem to employ *CEBiP*-like *LysM-RLPs* to induce typical immune responses such as reactive oxygen species and immune gene expression upon chitin perception [47]. Instead, *AtCERK1* binds directly to octamers of chitin, which in turn induce *AtCERK1* homodimerization and the resultant immune signalling [48]. Arabidopsis *LysM (AtLYM2)*, the closest ortholog of *AtCEBiP*, and the rice *LysM RLPs* (*OsLYP4* and *OsLYP6*) are also able to bind chitin [49]. However, it is not clear whether *AtLYM2/LYK4* also display the putative homodimerization induced by chitin perception. Two other orthologs of *CEBiP*, *AtLYM1* and *AtLYM3*, which specifically bind *PGN,* but not chitin, interact with *AtCERK1*. This indicates that *AtCERK1* is a multifaceted *RLK* that also forms hetero-oligomeric complexes with ligand-

Fungal xylanases also function as fungal PAMPs by eliciting defence responses and promoting necrosis [50, 51]. In tomato, ethylene-inducing xylanases (*EIXs*) produced by *Trichoderma* species are perceived by two specific LRR-RLPs receptors, *LeEix1* and *LeEix2* [52]. Both receptors bind *Eixs*, but o*LeEix2* is the primary mediator of defence responses. *LeEix1* hetero‐ dimerizes with *LeEix2* upon application of the *Eixs* and attenuates *Eix*-induced internalization and the subsequent signalling of the *LeEix2* receptor [53]. Microbial xyloglucan-specific endoglucanases (XEGs) have also been reported to induce plant defences. Fungal XEGs are inhibited by xyloglucan endoglucanase inhibiting proteins (*XEGIPs*), which so far have been

*3.1.1.3. Plant perception of PAMPs from fungi and oomycetes*

binding *RLPs*, probably across different plant families.

characterized in tomato, carrot and tobacco [54, 55].

vincing.

236 Plant Genomics

mechanisms [202].

Although viral patterns inducing PTI are well known from animal systems, there is no similar pattern reported for plants [48]. Instead, plant resistance to viruses is mediated by posttranscriptional gene silencing of viral RNA or ETI. Nevertheless, infection by compatible viruses can also induce defence responses similar to PTI. Typical PTI cellular responses in plant-virus interactions include ion fluxes, ROS production, ethylene, salicylic acid (SA), MAPK signalling and callose deposition, for review see [65]. Commonly reported genes associated with PRRs in response to viruses include *PEPs* that encode longer peptides (*ProPEP*) from which small peptides (*PEP*) are derived. In Arabidopsis, *AtPEP* interact with two DAMP PRRs, *PEP*-receptor 1 (*PEPR1*) and *PEPR2* [66], both of which interact with *BAK1* upon recognition of *AtPEP*. Thus, *BAK1* is important for antiviral defence in *Arabidopsis.* Indeed, the *bak1* mutants show enhanced susceptibility to three different RNA viruses (*TMV-U1*, *ORMV* and *TCV*) during compatible interactions [67]. The immune response induced by *PEPR-BAK1* interaction is a classical PTI. Another viral resistance mechanism, which is highly similar to *BAK1* and *BAK1-like Kinase 1* (*BKK1*), is exhibited by the viral nuclear shuttle protein (NSP) interacting kinases (*NIKs*) from leucine-rich repeats containing receptor-like serine/threonine kinase (LRR-RKs) subfamily [68].

Recent reviews have also suggested that the ribonuclease III-type DICER-like (DCL) enzymes could be acting as PRRs perceiving viral nucleic acids and triggering immune responses equivalent to the zig-zag model first layer [66]. The virus-derived molecules (e.g., dsRNAs) act as PAMPs, which trigger PTI and RNA interference (RNAi). However, PTI is typically a form of innate immunity, whereas RNAi induces a form of adaptive immunity. Thus, it is clear that a lot remains to be discovered to prove that virus-derived molecules trigger PTI.

*3.1.1.6. Infection self-perception DAMPs*

then to act as DAMPs.

protection using induced plant endogenous molecules.

and (2) those with a coiled-coil (CC) domain are called CNLs [92].

**3.2. Effector-triggered immunity (ETI)**

As discussed before, plants can also sense self-molecules called damage-associated molecular patterns that are available for recognition only after cell/tissue damage. The striking similari‐ ties of DAMP perception in animals and plants have been reviewed [83]. A perfect example that was discussed earlier is the *Arabidopsis* plasma membrane LRR receptor kinase (LRR-RK), designated *PEPR1*/*PEPR2*, which perceives *AtPep* peptides derived from propeptide (Pro‐ PEPs) encoded by a seven-member multigenic family (*Pep1-Pep7*). Both *PEPR1* and *PEPR2* were reported to be transcriptionally induced by wounding, treatment with methyl jasmonate, *Pep* peptides and pathogen-associated molecular patterns [64, 84]. Moreover, *AtPep* perception is part of a PTI amplification loop and is important for the induction of systemic immunity [85]. In another example, hydroxyproline-containing glycopeptides (*HypSys*) and rapid alkaliniza‐ tion factor (*RALF*) peptides have been shown to induce an *MAPK* cascade in tomato cells [86]. The precursors of *HypSys* and *RALF* are constitutively present in the plant cell walls [14]. Microbial proteases or intracellular proteases release these peptides upon cell injury, making

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Cell wall components derived from the enzymatic activity of highly specific microbial homogalacturonan (HGA) is another good example of DAMPs [87]. The enhanced production of oligogalacturonic acid (OGA) fragments from plant cell walls potentially acts as DAMP, which are perceived by receptors such as *RLK THESEUS1* (*THE1*), *ER* and *WAK1*. Plants may also rely on the recognition of cell wall degrading enzymes (CWDEs) by LRR-RLPs receptors, e.g., *RBPG1* and *LeEIX1-2* [88]. A decisive role of the composition and structure of plant cell wall polysaccharides, specifically of side chains of pectic polysaccharides, in elicitation of plant defence has also been described in tomato interaction with a bacterial pathogen, *R. solanacea‐ rum* [89, 90, 203]. Thus, studying the expression of endogenous molecules and microbial cell wall degrading enzymes and their inhibitors, e.g., polygalacturonases (PGs) and polygalac‐ turonase-inhibiting proteins (PGIPs) [204] is a valuable approach to understanding the dynamics of plant-pathogen interactions as well as to develop a strategy to improve plant

ETI (formerly called *R*-gene-mediated or vertical resistance) is based on the highly specific, direct or indirect interaction of pathogen effectors and the products of plant *R* genes according to the gene-for-gene theory [14]. As discussed before, R genes encode proteins of the intracel‐ lular nucleotide-binding leucine-rich repeat (NB-LRR) class [10]. The NB-LRR consist of Nterminal effector domain, central NB domain and C-terminal LRR domain, which largely vary in plants [91]. Two major subgroups that have distinct N-terminal domains are generally recognized: (1) one group with a Toll–interleukin 1 receptor (*TIR*) domain are called TNLs,

In Arabidopsis, the CNLs functionally interact with the glycosylphosphatidylinositol (GPI) anchored protein—*NON-RACE SPECIFIC DISEASE RESISTANCE 1* (*NDR1*), a positive regulator of SA accumulation, for signalling [93, 94]. Indeed, an *ndr1* mutation compromises resistance conferred by the CC-NBS-LRR proteins *RPS2*, *RPM1* or *RPS5* to *P. syringae* express‐

#### *3.1.1.5. Plant perception of insect PAMPs*

Molecular recognition via ligand-receptor binding phenomena is increasingly becoming important in insect-plant interactions [69]. As reported earlier, the concept of PAMPS has been expanded to include herbivore-associated molecular patterns or damaged-self compounds produced after insect attack [70]. HAMPs isolated and characterized to date include compo‐ nents found in insect oral secretions (proteins, fatty acid-amino acid conjugates (FACs), sulphur-containing fatty acids, as well as plant-derived molecules generated following insect herbivory, including degradation products of ATP synthase and cell walls [71, 72]. The insect oral secretion molecules are released by chewing insects and have been reported to induce ion imbalances, variations in membrane potential, changes in Ca2+ fluxes and the generation of reactive oxygen species (ROS), which stimulate downstream signalling events in plants [73]. Ca2+ influx is obviously preceded by the opening of calcium channels, and it is likely that these channels are associated with plant receptors tuned to insect elicitors. Recently, a mechanism similar to PTI was reported in Arabidopsis in which LRR-RK *BAK1* was shown to contribute to innate immunity against aphids [69]. Moreover, application of synthetic FACs on wounded *N. attenuate* leaves strongly induced *MAPK* activity, and subsequently wound-induced modifications in the transcriptome, proteome and defensive secondary metabolites [74, 75]. Insect egg ovipositional fluids have also been shown to induce plant defences [76, 77]. Moreover, insect egg deposition on one leaf could induce volatile emission in the other eggfree leaves [77], suggesting that SAR could be involved after detection of insect eggs' associated molecules. An interesting example was reported in the oviposition by *Pieris brassicae*, which triggered SA accumulation and the subsequent induction of PAMP responsive gene expression associated with lectin-domain RK (*LecRK*), *LecRK-I* [78]. Correspondingly, expression of the defence gene *PR-1,* which requires *EDS1*, *SID2* and *NPR1*, was also detected, implicating the SA pathway downstream of the insect egg recognition.

Another mechanism that is closely related to the PAMP receptors in plant resistance to insects is the *Mi-1* gene in tomato. The induction of *Mi-1* confers resistance to *Macrosiphum euphor‐ biae* [79]. A receptor-like kinase gene *OsLecRK* in rice, which confers basal resistance to *Nilaparvata lugens*, was recently suggested to be a PRR that recognizes molecules secreted by these insects [80]. A similar mechanism was demonstrated in aphid infestation of *Arabidopsis* in which the immune response was apparently triggered by infiltration of aphid saliva [81]. Consistent with this, infiltration of whole aphid extract from *M. persicae* was reported to activate PTI-like responses in *Arabidopsis* [69, 82].

This notwithstanding, the insect HAMP-receptor binding phenomenon that allows plants to detect insects still remains less clear as to whether these responses are exclusively due to the specific perception of herbivores or due to different damage patterns or both.

#### *3.1.1.6. Infection self-perception DAMPs*

act as PAMPs, which trigger PTI and RNA interference (RNAi). However, PTI is typically a form of innate immunity, whereas RNAi induces a form of adaptive immunity. Thus, it is clear

Molecular recognition via ligand-receptor binding phenomena is increasingly becoming important in insect-plant interactions [69]. As reported earlier, the concept of PAMPS has been expanded to include herbivore-associated molecular patterns or damaged-self compounds produced after insect attack [70]. HAMPs isolated and characterized to date include compo‐ nents found in insect oral secretions (proteins, fatty acid-amino acid conjugates (FACs), sulphur-containing fatty acids, as well as plant-derived molecules generated following insect herbivory, including degradation products of ATP synthase and cell walls [71, 72]. The insect oral secretion molecules are released by chewing insects and have been reported to induce ion imbalances, variations in membrane potential, changes in Ca2+ fluxes and the generation of reactive oxygen species (ROS), which stimulate downstream signalling events in plants [73]. Ca2+ influx is obviously preceded by the opening of calcium channels, and it is likely that these channels are associated with plant receptors tuned to insect elicitors. Recently, a mechanism similar to PTI was reported in Arabidopsis in which LRR-RK *BAK1* was shown to contribute to innate immunity against aphids [69]. Moreover, application of synthetic FACs on wounded *N. attenuate* leaves strongly induced *MAPK* activity, and subsequently wound-induced modifications in the transcriptome, proteome and defensive secondary metabolites [74, 75]. Insect egg ovipositional fluids have also been shown to induce plant defences [76, 77]. Moreover, insect egg deposition on one leaf could induce volatile emission in the other eggfree leaves [77], suggesting that SAR could be involved after detection of insect eggs' associated molecules. An interesting example was reported in the oviposition by *Pieris brassicae*, which triggered SA accumulation and the subsequent induction of PAMP responsive gene expression associated with lectin-domain RK (*LecRK*), *LecRK-I* [78]. Correspondingly, expression of the defence gene *PR-1,* which requires *EDS1*, *SID2* and *NPR1*, was also detected, implicating the

Another mechanism that is closely related to the PAMP receptors in plant resistance to insects is the *Mi-1* gene in tomato. The induction of *Mi-1* confers resistance to *Macrosiphum euphor‐ biae* [79]. A receptor-like kinase gene *OsLecRK* in rice, which confers basal resistance to *Nilaparvata lugens*, was recently suggested to be a PRR that recognizes molecules secreted by these insects [80]. A similar mechanism was demonstrated in aphid infestation of *Arabidopsis* in which the immune response was apparently triggered by infiltration of aphid saliva [81]. Consistent with this, infiltration of whole aphid extract from *M. persicae* was reported to

This notwithstanding, the insect HAMP-receptor binding phenomenon that allows plants to detect insects still remains less clear as to whether these responses are exclusively due to the

specific perception of herbivores or due to different damage patterns or both.

that a lot remains to be discovered to prove that virus-derived molecules trigger PTI.

*3.1.1.5. Plant perception of insect PAMPs*

238 Plant Genomics

SA pathway downstream of the insect egg recognition.

activate PTI-like responses in *Arabidopsis* [69, 82].

As discussed before, plants can also sense self-molecules called damage-associated molecular patterns that are available for recognition only after cell/tissue damage. The striking similari‐ ties of DAMP perception in animals and plants have been reviewed [83]. A perfect example that was discussed earlier is the *Arabidopsis* plasma membrane LRR receptor kinase (LRR-RK), designated *PEPR1*/*PEPR2*, which perceives *AtPep* peptides derived from propeptide (Pro‐ PEPs) encoded by a seven-member multigenic family (*Pep1-Pep7*). Both *PEPR1* and *PEPR2* were reported to be transcriptionally induced by wounding, treatment with methyl jasmonate, *Pep* peptides and pathogen-associated molecular patterns [64, 84]. Moreover, *AtPep* perception is part of a PTI amplification loop and is important for the induction of systemic immunity [85]. In another example, hydroxyproline-containing glycopeptides (*HypSys*) and rapid alkaliniza‐ tion factor (*RALF*) peptides have been shown to induce an *MAPK* cascade in tomato cells [86]. The precursors of *HypSys* and *RALF* are constitutively present in the plant cell walls [14]. Microbial proteases or intracellular proteases release these peptides upon cell injury, making then to act as DAMPs.

Cell wall components derived from the enzymatic activity of highly specific microbial homogalacturonan (HGA) is another good example of DAMPs [87]. The enhanced production of oligogalacturonic acid (OGA) fragments from plant cell walls potentially acts as DAMP, which are perceived by receptors such as *RLK THESEUS1* (*THE1*), *ER* and *WAK1*. Plants may also rely on the recognition of cell wall degrading enzymes (CWDEs) by LRR-RLPs receptors, e.g., *RBPG1* and *LeEIX1-2* [88]. A decisive role of the composition and structure of plant cell wall polysaccharides, specifically of side chains of pectic polysaccharides, in elicitation of plant defence has also been described in tomato interaction with a bacterial pathogen, *R. solanacea‐ rum* [89, 90, 203]. Thus, studying the expression of endogenous molecules and microbial cell wall degrading enzymes and their inhibitors, e.g., polygalacturonases (PGs) and polygalac‐ turonase-inhibiting proteins (PGIPs) [204] is a valuable approach to understanding the dynamics of plant-pathogen interactions as well as to develop a strategy to improve plant protection using induced plant endogenous molecules.

#### **3.2. Effector-triggered immunity (ETI)**

ETI (formerly called *R*-gene-mediated or vertical resistance) is based on the highly specific, direct or indirect interaction of pathogen effectors and the products of plant *R* genes according to the gene-for-gene theory [14]. As discussed before, R genes encode proteins of the intracel‐ lular nucleotide-binding leucine-rich repeat (NB-LRR) class [10]. The NB-LRR consist of Nterminal effector domain, central NB domain and C-terminal LRR domain, which largely vary in plants [91]. Two major subgroups that have distinct N-terminal domains are generally recognized: (1) one group with a Toll–interleukin 1 receptor (*TIR*) domain are called TNLs, and (2) those with a coiled-coil (CC) domain are called CNLs [92].

In Arabidopsis, the CNLs functionally interact with the glycosylphosphatidylinositol (GPI) anchored protein—*NON-RACE SPECIFIC DISEASE RESISTANCE 1* (*NDR1*), a positive regulator of SA accumulation, for signalling [93, 94]. Indeed, an *ndr1* mutation compromises resistance conferred by the CC-NBS-LRR proteins *RPS2*, *RPM1* or *RPS5* to *P. syringae* express‐ ing the avirulence effectors *avrRpt2*, *avrB* and *avrRpm1*, or *avrPph3*, respectively [95]. In contrast, multiple TNLs functionally associate with *ENHANCED DISEASE SUCEPTIBILITY 1* (*EDS1*) and *PHYTOALEXIN DEFICIENT 4* (*PAD4*) for signalling. For instance, resistance conferred by the TIR–NBS–LRR protein *RPS4*, which recognizes *avrRps4* in *P. syringae* is compromised in *eds1* mutants [96]. However, resistance mediated by some R genes is inde‐ pendent of *EDS1/PAD4* and *NDR1* or require additional co-activating proteins, suggesting existence of additional components for signal transmission during plant-pathogen interaction. Some of the regulatory components functionally associated with R genes for an effective HR mediated resistance include *RAR1* (required for *Mla12* resistance) and *SGT1* (suppressor of the G2 allele of *skp1*) proteins [97]. *RAR1* interacts with the N-terminal half of *HSP90* that contains the ATPase domain. *HSP90* also specifically interacts with *SGT1* that contains a tetratricopep‐ tide repeat motif and a domain with similarity to the co-chaperone *p23* [98]. These observations suggest that R proteins require several co-activating proteins, although distinct downstream signalling pathways could be involved. There are also some NLRs containing N terminus other than the classical TIR and CC, either because their protein structures are not validated or due to lack of significant homology; they are referred to as non-TIR-type NLRs (nTNLs) or generally referred to as NLRs. Further work on non-sequenced genomes is likely to expand the number of NLRs, and probably refine functional difference associated with NLR reper‐ toires.

receptor and *ATR1* alleles from *Hpa* strains can be diverse. This diversity contributes to a spectrum of resistance phenotypes and effectors. For instance, the recognition specificity of *RPP1-WsB* (from the Wassilewskija ecotype) and *RPP1-NdA* (from the Niederzenz ecotype) vary. The *RPP1-NdA* recognizes a small subset of the *ATR1* alleles recognized by *RPP1-WsB*, while the *RPP1-WsB* associates with the cognate *Hpa* effector protein, *Atr1*, through its LRR domain in a recognition-specific manner [105]. Another example is the Arabidopsis NLR *RRS1*, a domain with sequence similarity to *WRKY* TFs, positioned after the LRR. The cognate effectors *AvrRps4* and *PopP2* directly interact with this *WRKY-*like domain to activate the

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Together, the different R proteins have functional domains that can occupy different positions in NLRs. The functional domain positioning differences could be the reason behind several R genes that have been identified in plants. For instance, in rice more than 100 NLRs encoding genes have been described to confer resistance to strains of *Magnaporthe oryzae*[107]. However, only few R proteins encoded by these genes have been characterized, which limits their deployment. A well-known structure for the recognition of *M. oryzae* effectors is that of *AVR-Piz-t*, which adopts a six-stranded β-sandwich structure and contains a single disulphide bond [108]. The *AVR-Pia* and *AVR1-CO39* have also been reported to be recognized by the *R GENE ANALOGs (RGA4*/*RGA5)* NLR pair [109, 110] through direct binding to a Heavy-Metal Associated domain (HMA; also known as RATX1) integrated into *RGA5* after the LRR position. *RGA4*/*RGA5* physically interact to prevent cell death mediated by *RGA4* in the absence of *AVR-Pia*; the presence of the effector relieves this suppression, and induces cell death response, a mechanism that could also be described as indirect NLR surveilance. More recently, Maqbool et al. [111] also found that recognition of *AVR-Pik* by *Pik* is by direct binding to the *HMA* domain of *Pik-1*. However, the positioning of the *HMA* domain between the CC and NB-ARC region of *Pik-1* and after the LRR in *RGA5* is a striking difference between *Pik-1* and *RGA5.* These conformational changes underlying direct effector binding could be causing immunity-related signalling differences. However, the intra- and/or inter-molecular complexes mediating

During indirect recognition, the NLR guards the host protein by recognizing (monitoring) the modifications caused by the pathogen effector on the guarded protein [10]. The guarded protein can either be the actual effector virulence target or a decoy inviting modification by the pathogen. An example of the indirect recognition of effectors by NLRs was demonstrated in the conserved Arabidopsis protein *RPM1*-interacting protein 4 (*RIN4*). *RIN4* is targeted by multiple bacterial effectors, e.g., *AvrRpt2*, *AvrRpm1* and *AvrB*, and is monitored for effectorinduced modification by two plasma membrane CNL receptors, *RPM1* (resistance to *P. syringae* pv. *maculicola 1*) and *RPS2* (*resistance to P. syringae 2*) [112]. *AvrB*-induced phosphor‐ ylation and cis/trans isomerization coupled with conformational changes in *RIN4* are sensed by *RPM1* to activate immune signalling [112, 113]. *AvrRpt2*, being a cysteine protease, cleaves *RIN4* and induces *RIN4* degradation. In the absence of *RPM1* and *RPS2*, *RIN4* acts as a negative regulator of basal resistance, and in that capacity appears to be targeted for manipulation by

downstream resistance components [106].

output may be conserved [111].

multiple bacterial effectors [114].

*3.2.2. Indirect NLR surveillance of effector activities*

Regardless of the NLR class, NB-ARC domain is the core nucleotide-binding fold in NB-LRR proteins. Four distinct subdomains constitute the NB-ARC domain, including nucleotidebinding (NB) fold and *ARC1, -2* and *-3* subdomains. *ARC1* is a four-helix bundle, *ARC2* is a winged-helix fold and *ARC3* is a helical bundle [99]. *ARC1* and *ARC2* are conserved in *Caenorhabditis elegans CED-4*, and plant NB-LRR R proteins, whereas *ARC3* is absent [99]. Throughout the NB-ARC domain in R proteins, numerous conserved motifs (e.g., *hhGRExE*, Walker A or P-loop, Walker B, GxP, *RNBS-A* to *D* and *MHD*) have been reported [100]. A mutation in these conserved motifs has shown their functional importance in the NB-LRR proteins [101], and is apparently a critical factor determining R gene functional effector recognition pattern differences. Generally, pathogen effector recognition by NLR and NLR expression are broadly characterized into (1) direct NLR-Effector interaction or (2) indirect NLR indirect surveillance of effector activities.

#### *3.2.1. Direct NLR-effector interaction*

NLRs maintain an ADP-binding inactive state in the absence of effectors. The binding of effectors induces conformational changes in NLRs, which allow ADP/ATP exchange. Conse‐ quently, the exchange of nucleotides triggers a second conformational change that activates the NB-LRRs' N-terminus (TIR or CC) to interact with and trigger downstream target processes [102]. However, there is no substantial evidence on direct NLR-effector interaction that underlies resistance specificity in the NLR-effector combinations, apart from the yeast twohybrid (Y2H) and *in vitro* interaction assays [103, 104]. A few examples that attempt to show the NLR-effector interaction include the Arabidopsis NLR *RPP1* recognition of the oomycete effector *ATR1* leading to *Hyaloperonospora arabidopsidis (Hpa)* resistance [104]. Both the *RPP1* receptor and *ATR1* alleles from *Hpa* strains can be diverse. This diversity contributes to a spectrum of resistance phenotypes and effectors. For instance, the recognition specificity of *RPP1-WsB* (from the Wassilewskija ecotype) and *RPP1-NdA* (from the Niederzenz ecotype) vary. The *RPP1-NdA* recognizes a small subset of the *ATR1* alleles recognized by *RPP1-WsB*, while the *RPP1-WsB* associates with the cognate *Hpa* effector protein, *Atr1*, through its LRR domain in a recognition-specific manner [105]. Another example is the Arabidopsis NLR *RRS1*, a domain with sequence similarity to *WRKY* TFs, positioned after the LRR. The cognate effectors *AvrRps4* and *PopP2* directly interact with this *WRKY-*like domain to activate the downstream resistance components [106]. cognatepositioning

Together, the different R proteins have functional domains that can occupy different positions in NLRs. The functional domain positioning differences could be the reason behind several R genes that have been identified in plants. For instance, in rice more than 100 NLRs encoding genes have been described to confer resistance to strains of *Magnaporthe oryzae*[107]. However, only few R proteins encoded by these genes have been characterized, which limits their deployment. A well-known structure for the recognition of *M. oryzae* effectors is that of *AVR-Piz-t*, which adopts a six-stranded β-sandwich structure and contains a single disulphide bond [108]. The *AVR-Pia* and *AVR1-CO39* have also been reported to be recognized by the *R GENE ANALOGs (RGA4*/*RGA5)* NLR pair [109, 110] through direct binding to a Heavy-Metal Associated domain (HMA; also known as RATX1) integrated into *RGA5* after the LRR position. *RGA4*/*RGA5* physically interact to prevent cell death mediated by *RGA4* in the absence of *AVR-Pia*; the presence of the effector relieves this suppression, and induces cell death response, a mechanism that could also be described as indirect NLR surveilance. More recently, Maqbool et al. [111] also found that recognition of *AVR-Pik* by *Pik* is by direct binding to the *HMA* domain of *Pik-1*. However, the positioning of the *HMA* domain between the CC and NB-ARC region of *Pik-1* and after the LRR in *RGA5* is a striking difference between *Pik-1* and *RGA5.* These conformational changes underlying direct effector binding could be causing immunity-related signalling differences. However, the intra- and/or inter-molecular complexes mediating output may be conserved [111]. *AVR1-CO39*interact *RGA5.*effector and/or 

#### *3.2.2. Indirect NLR surveillance of effector activities*

ing the avirulence effectors *avrRpt2*, *avrB* and *avrRpm1*, or *avrPph3*, respectively [95]. In contrast, multiple TNLs functionally associate with *ENHANCED DISEASE SUCEPTIBILITY 1* (*EDS1*) and *PHYTOALEXIN DEFICIENT 4* (*PAD4*) for signalling. For instance, resistance conferred by the TIR–NBS–LRR protein *RPS4*, which recognizes *avrRps4* in *P. syringae* is compromised in *eds1* mutants [96]. However, resistance mediated by some R genes is inde‐ pendent of *EDS1/PAD4* and *NDR1* or require additional co-activating proteins, suggesting existence of additional components for signal transmission during plant-pathogen interaction. Some of the regulatory components functionally associated with R genes for an effective HR mediated resistance include *RAR1* (required for *Mla12* resistance) and *SGT1* (suppressor of the G2 allele of *skp1*) proteins [97]. *RAR1* interacts with the N-terminal half of *HSP90* that contains the ATPase domain. *HSP90* also specifically interacts with *SGT1* that contains a tetratricopep‐ tide repeat motif and a domain with similarity to the co-chaperone *p23* [98]. These observations suggest that R proteins require several co-activating proteins, although distinct downstream signalling pathways could be involved. There are also some NLRs containing N terminus other than the classical TIR and CC, either because their protein structures are not validated or due to lack of significant homology; they are referred to as non-TIR-type NLRs (nTNLs) or generally referred to as NLRs. Further work on non-sequenced genomes is likely to expand the number of NLRs, and probably refine functional difference associated with NLR reper‐

Regardless of the NLR class, NB-ARC domain is the core nucleotide-binding fold in NB-LRR proteins. Four distinct subdomains constitute the NB-ARC domain, including nucleotidebinding (NB) fold and *ARC1, -2* and *-3* subdomains. *ARC1* is a four-helix bundle, *ARC2* is a winged-helix fold and *ARC3* is a helical bundle [99]. *ARC1* and *ARC2* are conserved in *Caenorhabditis elegans CED-4*, and plant NB-LRR R proteins, whereas *ARC3* is absent [99]. Throughout the NB-ARC domain in R proteins, numerous conserved motifs (e.g., *hhGRExE*, Walker A or P-loop, Walker B, GxP, *RNBS-A* to *D* and *MHD*) have been reported [100]. A mutation in these conserved motifs has shown their functional importance in the NB-LRR proteins [101], and is apparently a critical factor determining R gene functional effector recognition pattern differences. Generally, pathogen effector recognition by NLR and NLR expression are broadly characterized into (1) direct NLR-Effector interaction or (2) indirect

NLRs maintain an ADP-binding inactive state in the absence of effectors. The binding of effectors induces conformational changes in NLRs, which allow ADP/ATP exchange. Conse‐ quently, the exchange of nucleotides triggers a second conformational change that activates the NB-LRRs' N-terminus (TIR or CC) to interact with and trigger downstream target processes [102]. However, there is no substantial evidence on direct NLR-effector interaction that underlies resistance specificity in the NLR-effector combinations, apart from the yeast twohybrid (Y2H) and *in vitro* interaction assays [103, 104]. A few examples that attempt to show the NLR-effector interaction include the Arabidopsis NLR *RPP1* recognition of the oomycete effector *ATR1* leading to *Hyaloperonospora arabidopsidis (Hpa)* resistance [104]. Both the *RPP1*

toires.

240 Plant Genomics

NLR indirect surveillance of effector activities.

*3.2.1. Direct NLR-effector interaction*

During indirect recognition, the NLR guards the host protein by recognizing (monitoring) the modifications caused by the pathogen effector on the guarded protein [10]. The guarded protein can either be the actual effector virulence target or a decoy inviting modification by the pathogen. An example of the indirect recognition of effectors by NLRs was demonstrated in the conserved Arabidopsis protein *RPM1*-interacting protein 4 (*RIN4*). *RIN4* is targeted by multiple bacterial effectors, e.g., *AvrRpt2*, *AvrRpm1* and *AvrB*, and is monitored for effectorinduced modification by two plasma membrane CNL receptors, *RPM1* (resistance to *P. syringae* pv. *maculicola 1*) and *RPS2* (*resistance to P. syringae 2*) [112]. *AvrB*-induced phosphor‐ ylation and cis/trans isomerization coupled with conformational changes in *RIN4* are sensed by *RPM1* to activate immune signalling [112, 113]. *AvrRpt2*, being a cysteine protease, cleaves *RIN4* and induces *RIN4* degradation. In the absence of *RPM1* and *RPS2*, *RIN4* acts as a negative regulator of basal resistance, and in that capacity appears to be targeted for manipulation by multiple bacterial effectors [114]. effector effectors, acts manipulation

The functioning of NLRs as genetically tightly linked pairs to deliver disease resistance was also recently reported [115]. Moreover, Williams et al. [116] demonstrated, by coupling crystal structure and functional analyses, that *RPS4* and *RESISTANT TO RALSTONIA SOLANACEA‐ RUM 1* (*RRS1*) TIR domains form homo- and hetero-dimers through a common conserved interface that includes a core serine-histidine (SH) motif. Transient expression assays in tobacco revealed that the *RPS4* TIR domain triggers an effector-independent cell death, which is dependent on the SH motif. Co-expression of the *RRS1* TIR domain and *RPS4* TIR impedes the auto-active cell death caused by *RPS4* TIR, and this was found to be dependent on the *RRS1* SH motif. This suggests that an inactive *RRS1/RPS4* TIR hetero-dimer and the formation of an active *RPS4* TIR homo-dimer compete to modulate signalling. As discussed before, Cesari et al. [109] investigated the mode of action of *RGA 4* and *5* that associate through their coiled-coil domains. *RGA4* and *RGA5* are tightly linked rice CC-NLRs, which functionally interact to modulate resistance to the rice pathogen *M. oryzae*. *RGA5* modulates an effector independent cell death constitutively induced by *RGA4* signalling. *RGA5* domain on the C-terminus has a heavy-metal-associated domain, which is related to the cytoplasmic copper chaperone *ATX1* from *Saccharomyces cerevisiae* (*RATX1* domain). This domain is an *AVR-Pia* effector interacting domain in *RGA5*. Thus, the formation of the *RGA4/RGA5* hetero-complex is crucial to regulate *RGA4* activity in the absence of pathogen in rice. Hence, *RGA4* acts as a signalling component regulated by its interaction with *RGA5* that acts both as a repressor and a receptor that directly binds the *AVR-Pia* proteins. The apparent striking similarity between the *RPS4/RRS1* and the *RGA4/RGA5* functional models suggests that similarities are likely to be frequent between the different R genes present in dicots and monocots.

#### *3.2.3. Patterns of NLRs signalling in plant defence*

Most NLRs respond to the presence of proteins (effectors) delivered by adapted pathogens/ parasites. Using suppressor screens, Gabriels et al. [117], identified *NRC1* (*NLR protein required for HR-associated cell death 1*) as a component of fungal resistance modulated by the tomato plasma membrane receptor-like resistance protein *Cf-4* (*C. fulvum 4*). *NRC1* mediates resistance and cell death induced by both membrane receptors and intracellular NLRs. This indicates that *NRC1* is probably a downstream convergence point in ETI initiated at various cell locations. Indeed, silencing of *NRC1* in *N. benthamiana* impairs the HR mediated by several other R proteins including two NLRs, *Rx* and *Mi*. Members of a conserved class of noncanonical CNLs also function in ETI, downstream of NLR effector recognition and have been designated as helper NLRs [118]. Characterization of these non-canonical CNLs is required in order to track their interaction networks.

The downstream components of ETI signalling events partially overlap with PTI response, including activation of *MAPK* cascade and activation of TFs such as *WRKYs* [119]. In Arabi‐ dopsis, three CNLs—*activated disease resistance 1* (*ADR1*), *ADR1-L1* and *ADR1-L2*—transduce signals that lead to SA accumulation and induction of downstream *WRKYs* modulated resistance [118]. In rice, the CNL receptor, *panicle blast 1* (*Pb1*), also appears to mediate resistance against rice blast in a mechanism involving interaction with *WRKY45*, a TF involved in induced resistance via SA signalling pathway [120]. Some CNLs directly translocate or localize in the nucleus to activate defence [121], e.g., *barley mildew A 10* (*MLA10*) and Arabi‐ dopsis *RPS4* and *RPS6*. In the nucleus, *MLA10* interacts with *Hordeum vulgare* (Hv) *WRKY1/2*, which are suppressors of basal defence, during incompatible interaction with powdery mildew fungus. A CNL designated as *MLA1,* also from barley, functions in Arabi‐ dopsis against *Blumeria graminis* f. sp. *hordei* (*Bgh*) [122]. The *MLA1*-triggered immunity, including host cell death response and disease resistance, is fully retained in Arabidopsis mutant plants that are simultaneously impaired in well-characterized defence-phytohormone pathways (ET, JA and SA). Similar to *MLA1*, co-acting Arabidopsis TNL pair, *RPS4* and *RRS1* (which encodes a WRKY DNA binding domain), confers resistance in cucumber, *N. benthami‐ ana*, and tomato [122].

The functioning of NLRs as genetically tightly linked pairs to deliver disease resistance was also recently reported [115]. Moreover, Williams et al. [116] demonstrated, by coupling crystal structure and functional analyses, that *RPS4* and *RESISTANT TO RALSTONIA SOLANACEA‐ RUM 1* (*RRS1*) TIR domains form homo- and hetero-dimers through a common conserved interface that includes a core serine-histidine (SH) motif. Transient expression assays in tobacco revealed that the *RPS4* TIR domain triggers an effector-independent cell death, which is dependent on the SH motif. Co-expression of the *RRS1* TIR domain and *RPS4* TIR impedes the auto-active cell death caused by *RPS4* TIR, and this was found to be dependent on the *RRS1* SH motif. This suggests that an inactive *RRS1/RPS4* TIR hetero-dimer and the formation of an active *RPS4* TIR homo-dimer compete to modulate signalling. As discussed before, Cesari et al. [109] investigated the mode of action of *RGA 4* and *5* that associate through their coiled-coil domains. *RGA4* and *RGA5* are tightly linked rice CC-NLRs, which functionally interact to modulate resistance to the rice pathogen *M. oryzae*. *RGA5* modulates an effector independent cell death constitutively induced by *RGA4* signalling. *RGA5* domain on the C-terminus has a heavy-metal-associated domain, which is related to the cytoplasmic copper chaperone *ATX1* from *Saccharomyces cerevisiae* (*RATX1* domain). This domain is an *AVR-Pia* effector interacting domain in *RGA5*. Thus, the formation of the *RGA4/RGA5* hetero-complex is crucial to regulate *RGA4* activity in the absence of pathogen in rice. Hence, *RGA4* acts as a signalling component regulated by its interaction with *RGA5* that acts both as a repressor and a receptor that directly binds the *AVR-Pia* proteins. The apparent striking similarity between the *RPS4/RRS1* and the *RGA4/RGA5* functional models suggests that similarities are likely to be frequent between the

Most NLRs respond to the presence of proteins (effectors) delivered by adapted pathogens/ parasites. Using suppressor screens, Gabriels et al. [117], identified *NRC1* (*NLR protein required for HR-associated cell death 1*) as a component of fungal resistance modulated by the tomato plasma membrane receptor-like resistance protein *Cf-4* (*C. fulvum 4*). *NRC1* mediates resistance and cell death induced by both membrane receptors and intracellular NLRs. This indicates that *NRC1* is probably a downstream convergence point in ETI initiated at various cell locations. Indeed, silencing of *NRC1* in *N. benthamiana* impairs the HR mediated by several other R proteins including two NLRs, *Rx* and *Mi*. Members of a conserved class of noncanonical CNLs also function in ETI, downstream of NLR effector recognition and have been designated as helper NLRs [118]. Characterization of these non-canonical CNLs is required in

The downstream components of ETI signalling events partially overlap with PTI response, including activation of *MAPK* cascade and activation of TFs such as *WRKYs* [119]. In Arabi‐ dopsis, three CNLs—*activated disease resistance 1* (*ADR1*), *ADR1-L1* and *ADR1-L2*—transduce signals that lead to SA accumulation and induction of downstream *WRKYs* modulated resistance [118]. In rice, the CNL receptor, *panicle blast 1* (*Pb1*), also appears to mediate resistance against rice blast in a mechanism involving interaction with *WRKY45*, a TF involved in induced resistance via SA signalling pathway [120]. Some CNLs directly translocate or

different R genes present in dicots and monocots.

*3.2.3. Patterns of NLRs signalling in plant defence*

242 Plant Genomics

order to track their interaction networks.

Another example supporting our understanding of the NLR nuclear activity is the interaction of N immune receptor with the TF *SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 6* (*SPL6*) in *N. benthamiana* [123]. The N immune receptor is present in the nucleus, and confers resistance to tobacco mosaic virus (TMV) infection. N receptor associates with *SPL6* at the subnuclear bodies only when the cognate effector, *p50*, is present in the cell. A genetic requirement for *SPL6* was not only shown in *N. benthamiana* for N-mediated disease resistance using the yeast two-hybrid system, but also in *A. thaliana* for *RPS4* immune receptor mediated defence against *P. syringae* pv. *tomato* expressing *AvrRps4* effector. Moreover, a number of *RPS4* mediated defence responsive genes were differentially regulated upon *AtSPL6* silencing, including some of the previously characterized defence responsive genes such as *PAD4*, *PR1*, *ALD1*, *AIG1*, *NUDT6* and *FMO1*. Additional evidence has been shown in Arabidopsis *RPW8* resistance protein, which encodes truncated CNL-like proteins conferring resistance to powdery mildews in *N. tabacum* and *N. benthamiana* as in Arabidopsis. *RPW8* requires SA, *EDS1*, *NPR1* and *PAD4* to be effective. The functional role of *RPW8* is typically similar to a TNL *ADR1*, a close homolog of *N Requirement Gene 1* (*NRG1*), which functions in and beyond innate immunity [124]. These findings present a unique opportunity to further understand how effector-activated immune receptors directly associate with TFs in the nucleus to activate immune responses. Overall, a resistance signalling framework appears to have emerged for plants in which certain specificity-determining (sensor) NLRs initiate the immune response and either auto-activate and contribute to defence or compliment with other signalling NLRs to contribute to defence by conveying or amplifying the signal.

#### **4. Phytohormones in plant defence response to pathogens and insects**

Plant defence against pathogen/herbivore attack involves many signal transduction pathways that are mediated by a network of phytohormones. Phytohormones also play a critical role in regulating plant growth and development. Three most reported plant defence response phytohormones against pathogens/insects include salicylic acid (SA), jasmonic acid (JA) and ethylene (ET) [125]. Salicylic acid, a benzoic acid derivative, is an extensively studied important phytohormone in the regulation of plant defence [13]. In Arabidopsis, activation of the SA pathway has been shown to be important in both basal and R gene mediated biotrophic and hemibiotrophic pathogen defence [126, 127]. As discussed before, *NDR1* and *EDS1* act upstream of SA, while the downstream pathway is modulated by *NONEXPRESSOR OF PR GENES 1* (*NPR1*), and *WRKY45* in rice. *NPR1* is a transcriptional co-activator of a large set of defence-related genes downstream of SA, and it can conditionally regulate *PDF1.2* expression following treatment of plants with SA and MeJA [128]. SA also contributes to the HR-associated resistance via mechanisms that interact with *RBOHD*, a catalyst in ROS generation and cell death [128]. In tobacco, SA significantly increases in resistant plants infected with TMV [129]. A similar response was observed in Ny-1-resistant potatoes after infection with Potato virus Y (PVY) [130].

In response to insect attack, SA regulates plant defence signalling against aphids by modulat‐ ing the activity of *PAD4*. Indeed, *pad4* mutants, with compromised SA signalling, have increased susceptibility to *Myzus persicae*. Correspondingly, there is a correlation between *pad4* susceptibility and a delay in aphid-induced senescence [131], indicating that SA defence pathways are compromised in *pad4* mutants. Basal SA defences have also been shown to decrease *M. euphorbiae* longevity in tomato. Moreover, SA is necessary for *Mi1.2*-mediated resistance to potato aphids [132]. SA is also a key derivative of SAR in plants. SAR is a 'wholeplant' broad-spectrum resistance response that occurs following an earlier localized exposure to a pathogen [133]. It is well known that ETI can trigger SAR through both local and systemic synthesis of SA, resulting in transcriptional reprogramming of a battery of genes encoding PR proteins [133, 134]. The reports published so far point to different compounds as potential SAR signals [135]. A change in amino acid homeostasis is one of the suggested components in SAR mediated by ETI [136]. Moreover, amino acids have been reported to be precursors of a large array of plant secondary metabolites involved in defence, including signal SA, cell wall components and anthocyanins. Further evidence on the involvement of amino acid homeo‐ stasis in plant defence was reported in Arabidopsis *agd2*-*like defence response protein 1* (*ald1*) mutants. Characterization of the Arabidopsis *ald1* suggested that an amino acid–derived defence signal was generated upstream of SA synthesis [135]. These findings reveal that plants likely employ amino acids and their derivatives to rapidly reprogram SA synthesis and cellular transcription in order to cope with pathogen invasion, even though it appears to be at the expense of growth and development.

SA also interacts with other phytohormones either synergistically or antagonistically [137– 138]. There is an obvious cross-talk between JA and SA signalling pathways in pepper to control thionin synthesis as part of the PR response and other defence pathways [139]. Other synergistic examples include the treatment of *N. benthamiana* plants with JA or SA, which was shown to enhance systemic resistance to TMV [140]; Ellis et al. [141] have also shown that SAand JA-signalling pathways are required to accomplish the defence response necessary to avert pathogen attack. More recently, Arabidopsis mutants with constitutive SA responses were reported to require JA and ethylene signalling for SA mediated resistance [142]. A dominant mutant named *suppressor of SA insensitivity* (*ssi1*), which has constitutive expression of *PR*genes and is resistant to *P. syringae*, was also shown to constitutively express *PDF1.2* and accumulate elevated levels of SA [143]. Although this finding may be intriguing, because SA does not normally induce *PDF1.2* in wild-type plants, it suggests the existence of an intricate signalling network involving SA and JA. Another mutant named *constitutive PR 5 (cpr5*) was shown to have SA-mediated *NPR1*-independent resistance, which apparently required components of the JA and ET signal pathways [144]. The pre-treatment of plants with JA followed by SA was also shown to remarkably enhance resistance more than otherwise. Moreover, plants impaired in the JA pathway fail to accumulate SA in the leaves or phloem and become highly susceptible to TMV [145]. Conversely, impairing the SA pathway does not affect JA levels, although increased susceptibility is observed [141, 146]. During infection by the pathogen *P. syringae* pv. *tomato* (Pst) DC3000/*AvrRpm1*, JA as a systemic signal for SAR, increases significantly 6 hours after infection and returns to normal 11 hours after infection [147], which suggests that JA may be transiently required for SA accumulation. Further evidence indicates that SAR is compro‐ mised in JA-insensitive mutants, *sgt1b/jai4*, *opr3* (JA-biosynthesis mutant) and *jin1* (JAresponse mutant). The JA-biosynthesis mutants *dde2* and *opr3* as well as the downstream signalling mutants *coi1*, *jar1* and *jin1*, though intact in SAR, partially require JA biosynthesis for an effective resistance response [148]. Thus, it is possible that JA probably modulates early components of the SA biosynthetic or signalling pathway. However, it seems likely that the synergistic mechanisms may require not only SA and JA, but also ethylene [149, 150], consid‐ ering that *cpr5* phenotype is suppressed by the *ethylene-insensitive* (*ein2)* mutation*.*

upstream of SA, while the downstream pathway is modulated by *NONEXPRESSOR OF PR GENES 1* (*NPR1*), and *WRKY45* in rice. *NPR1* is a transcriptional co-activator of a large set of defence-related genes downstream of SA, and it can conditionally regulate *PDF1.2* expression following treatment of plants with SA and MeJA [128]. SA also contributes to the HR-associated resistance via mechanisms that interact with *RBOHD*, a catalyst in ROS generation and cell death [128]. In tobacco, SA significantly increases in resistant plants infected with TMV [129]. A similar response was observed in Ny-1-resistant potatoes after infection with Potato virus

In response to insect attack, SA regulates plant defence signalling against aphids by modulat‐ ing the activity of *PAD4*. Indeed, *pad4* mutants, with compromised SA signalling, have increased susceptibility to *Myzus persicae*. Correspondingly, there is a correlation between *pad4* susceptibility and a delay in aphid-induced senescence [131], indicating that SA defence pathways are compromised in *pad4* mutants. Basal SA defences have also been shown to decrease *M. euphorbiae* longevity in tomato. Moreover, SA is necessary for *Mi1.2*-mediated resistance to potato aphids [132]. SA is also a key derivative of SAR in plants. SAR is a 'wholeplant' broad-spectrum resistance response that occurs following an earlier localized exposure to a pathogen [133]. It is well known that ETI can trigger SAR through both local and systemic synthesis of SA, resulting in transcriptional reprogramming of a battery of genes encoding PR proteins [133, 134]. The reports published so far point to different compounds as potential SAR signals [135]. A change in amino acid homeostasis is one of the suggested components in SAR mediated by ETI [136]. Moreover, amino acids have been reported to be precursors of a large array of plant secondary metabolites involved in defence, including signal SA, cell wall components and anthocyanins. Further evidence on the involvement of amino acid homeo‐ stasis in plant defence was reported in Arabidopsis *agd2*-*like defence response protein 1* (*ald1*) mutants. Characterization of the Arabidopsis *ald1* suggested that an amino acid–derived defence signal was generated upstream of SA synthesis [135]. These findings reveal that plants likely employ amino acids and their derivatives to rapidly reprogram SA synthesis and cellular transcription in order to cope with pathogen invasion, even though it appears to be at the

SA also interacts with other phytohormones either synergistically or antagonistically [137– 138]. There is an obvious cross-talk between JA and SA signalling pathways in pepper to control thionin synthesis as part of the PR response and other defence pathways [139]. Other synergistic examples include the treatment of *N. benthamiana* plants with JA or SA, which was shown to enhance systemic resistance to TMV [140]; Ellis et al. [141] have also shown that SAand JA-signalling pathways are required to accomplish the defence response necessary to avert pathogen attack. More recently, Arabidopsis mutants with constitutive SA responses were reported to require JA and ethylene signalling for SA mediated resistance [142]. A dominant mutant named *suppressor of SA insensitivity* (*ssi1*), which has constitutive expression of *PR*genes and is resistant to *P. syringae*, was also shown to constitutively express *PDF1.2* and accumulate elevated levels of SA [143]. Although this finding may be intriguing, because SA does not normally induce *PDF1.2* in wild-type plants, it suggests the existence of an intricate signalling network involving SA and JA. Another mutant named *constitutive PR 5 (cpr5*) was shown to

Y (PVY) [130].

244 Plant Genomics

expense of growth and development.

The negative crosstalk between SA and JA/ET pathways is probably modulated by *TGA1A*-*RELATED GENE* (*TGA*) factors. *TGA* class of *bZIP* TFs are repressed by plant-specific gluta‐ redoxins (e.g., *ROXY19*), which are in turn induced by SA. Co-expression of *ROXY19* with *OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF-domain protein 59* (*ORA59*) and *ETHYLENE INSENSITVE 3* (*EIN3*) complex suppresses *ORA59* promoter activity. Moreover, a study by Van der Does et al. [137] indicated that SA negatively regulates *ORA59* protein accumulation in *35S:ORA59-GFP* overexpressing plants. *ORA59* is a transcriptional regulator of JA/ET-induced defence genes and is activated by either JA or ET and suppressed by SA. More recently, *TGA2*, *TGA5* and *TGA6* were shown to activate the SA-suppression of ETinducible defence by regulating *ORA59* expression [150]. This suggests that SA-suppresses JA/ ET-inducible defence by interfering with *ORA59* activity through regulation of *ROXY*-*TGA* interaction. Conversely, evidence of SA positive regulation of ET was proposed by Guan et al. [151]. These authors have shown that in Arabidopsis, SA modules ET by potentiating MITO‐ GEN-ACTIVATED PROTEIN KINASE6 (MPK6) and MPK3, and involves two 1-aminocyclo‐ propane-1-carboxylic acid synthase (*ACS*; *ACS2* and *ACS6*) isoforms, which are downstream components o MPK signalling pathway. This finding adds another level of complexity to the phytohormones regulatory network and will probably require further elucidation on how this pathway differs from the ORA59 regulated pathway.

On the other hand, most ET dependent defenses are positively modulated by JA. The *JASMONATE ZIM-DOMAIN* (*JAZ*) protein, which directly binds *EIN3*/*EIL1* and recruits *HISTONE DEACETYLASE 6* (*HDA6*) to repress ET responsive transcription, is repressed in the presence of JA. Thus, accumulation of JA degrades *JAZ* and allows the binding of *EIN3* to the *ERF1* promoter resulting in the transcription of *ERF1* [142, 152]. *EIN3* also directly activates the promoter of *ORA59* that regulates JA/ET-activated defence pathway. Studies on microarray analysis of Arabidopsis plants infected with *Alternaria brassicicola* revealed that nearly half of the genes induced by ET are also induced by JA [153]. This was substantiated by Lorenzo et al. [154] who reported that JA and ET pathways indeed converge in the transcriptional activation of *ERF1*, which encodes a TF that regulates the expression of pathogen response genes. *ERF* TFs have been reported to exhibit different regulatory roles depending on the species. For instance, in wheat *ERF* gene *TaPIEP1/TaPIE1,* which belongs to the B3 subgroup within the *ERF* subfamily, confers enhanced resistance to the fungal pathogens, *Bipolaris sorokiniana* and *R. cerealis*, when overexpressed in transgenic wheat [155], whereas in cotton GhERF of group IX, which includes *ORA59*, confer resistance to *Xanthomonas campestris pv. malvacearum*. Because *ERF1* integrates signals from the JA and ET defence signalling pathways, the constitutive expression of *ERF* family members activates the expression of several JA/ETdependent defence genes and induces resistance against necrotrophic pathogens. For instance, expression of several *PR genes* which confer resistance against several necrotrophs (e.g., *PR3* and *PR5d* and *PDF1.2*) is modulated by *ERFs*. These defence genes possess a GCC box in their promoters, which is a direct target for the action of *ERFs* [156].

Although ET has been shown to regulate plant defence responses against fungi and bacteria, ET is probably not essential in plant resistance against viruses. Recently, 1-aminocyclopro‐ pane-1- carboxylic acid (ACC) was shown to enhance *TMVcg* accumulation in treated plants [157], which increased susceptibility, suggesting that ET is required for viral infection.

Other phytohormones, such as ABA, gibberellins (GBs), auxins, brassinosteroids and cytoki‐ nins (CKs), have recently emerged as defence regulators [158]. ABA, a sesquiterpene com‐ pound resulting from the cleavage of γ-carotene, regulates numerous developmental processes and adaptive stress responses in plants. ABA can positively regulate plant defence at the early stages of infection by mediating stomatal closure against invaders, or inducing callose deposition if the pathogen evades the first line of defence [159]. If activated at later stages, ABA can suppress ROS induction and SA or JA signal transduction, thereby negating defences controlled by these two pathways [160].

Cytokinins promote cell division, and are known to play a role in the synthesis and mainte‐ nance of chlorophyll and chloroplast development and metabolism. CKs are also involved in the modulation of defence mechanisms, including the induction of resistance against viruses [161, 162], but are known to suppress HR [163]. Cytokinins can however act synergistically with SA signalling [164]. CKs activate the transcriptional regulator *ARABIDOPSIS RESPONSE REGULATOR 2* (*ARR2*), which positively modulates SA signalling by interacting with the SAresponsive factor *TGA3* [165]. *TGA3* induces the binding of *ARR2* to the promoters of *PR-1* and *PR-2* to induce cytokinin-dependent gene transcription. Correspondingly, the *npr1-1* or *NahG* mutants fail to modulate the induction of *ARR2* when treated with CK, indicating that CK modulates signaling components downstream of SA. Moreover, increased transcription of genes involved in SA-biosynthesis and signalling (e.g., *SID1*, *SID2*, *PR-1* and *PR-5*) is observed in *ARR2* over-expressing mutants challenged with *P. syringae* pv. *tomato* (*Pst DC3000*). Thus, CKs synergistically interacts not only with the SA signaling pathway to boost SA dependent induction of plant defence genes but also modulates SA biosynthesis. Cytokinins have also been shown to enhance the production of two antimicrobial phytoalexins, scopoletin and capsidiol in tobacco plants challenged with *P. syringae* pv*. tabaci* (*Pst*) independent of SA signalling [166]. Moreover, cytokinins induce the expression of cell wall invertase, a key sucrose cleaving enzyme required for carbohydrates supply through an apoplasmic pathway [167]. Invertase is required for plant defence against pathogens, including *Pst*. The glucose target of rapamycin (*TOR*) signalling pathway involved in autophagy apparently modulates the transcriptional dynamics associated with cytokinin-invertase-induced defence pathway by providing the required energy, metabolites and the cell cycle machinery required for cytokinin signal transduction [168]. The link between autophagy and cytokinin signalling was previously suggested [169], but the cytokinin-induced defence system in this interplay is probably a protective mechanism to maintain plant growth and proliferation despite pathogen challenge [170].

Brassinosteroids (BRs) are a class of polyhydroxysteroids that affect many cellular processes including elongation, proliferation, differentiation, membrane polarization and proton pumping [171]. BRs are increasingly becoming important in plant defence against pathogens. The mechanism underlying BR signalling involves the direct binding of BRs such as BL and castasterone to the LRR-RLK (*BRI1*). This interaction is reported to unlock *BRI1* from the negative regulator *BKI1*, followed by heterodimerization of *BRI1* with a co-receptor *BAK1* and phosphorylation of the *BRI1*-interacting signalling kinase (*BSK1*). Other events include the activation of the protein phosphatase *BSU1*. These biochemical changes inhibit the shaggy-like kinase *BIN2*, which culminates into the activation of the homologous TFs, *BZR1* and *BES1*/ *BZR2* [172]. These TFs translocate to the nucleus, interact with BR-responsive promoters, and cause transcriptional changes that eventually lead to defence response. BRs have been demonstrated to enhance plant defence against pathogens. In potato, BRs have been shown to be effective against viral infection from the starting planting materials to the second tuber generation [173]. Furthermore, application of BRs on tobacco plants decreases TMV viral load and restricts infection by other biotrophs [174]. The same authors reported that *BAK1* is essential for plant basal immunity during compatible interactions with RNA viruses. The *BAK1* mutants, *bak1-4* and *bak1-5*, accumulate *turnip crinkle virus* (TCV), *oilseed rape mosaic virus* (ORMV) and TMV to higher levels compared to the WT plants [174]. Thus, *BAK1* could probably be a general regulator of plant defence against biotrophs and hemibiotrophs. BRs have also been reported to interact with other phytohormones, such as GA and auxins, but independent of SA [175]. For details on auxin- and cytokinin-modulated immunity, and GA/BR interaction, the reader is referred to excellent reviews [176, 177]. Furthermore, details on the interaction of BRs and SA, including their effect on SAR marker genes (e.g., *PR-1*, *PR-2* and *PR-5*) can be found in [178].

Taken together, the intricate cross-talk among hormones to cooperate with other signals and to coordinate appropriate induction of defences against pathogens and/or insect pests depends on the pathogen type, physiological stage and environmental and probably circadian regula‐ tions.

#### **5. RNAi-mediated plant defence**

al. [154] who reported that JA and ET pathways indeed converge in the transcriptional activation of *ERF1*, which encodes a TF that regulates the expression of pathogen response genes. *ERF* TFs have been reported to exhibit different regulatory roles depending on the species. For instance, in wheat *ERF* gene *TaPIEP1/TaPIE1,* which belongs to the B3 subgroup within the *ERF* subfamily, confers enhanced resistance to the fungal pathogens, *Bipolaris sorokiniana* and *R. cerealis*, when overexpressed in transgenic wheat [155], whereas in cotton GhERF of group IX, which includes *ORA59*, confer resistance to *Xanthomonas campestris pv. malvacearum*. Because *ERF1* integrates signals from the JA and ET defence signalling pathways, the constitutive expression of *ERF* family members activates the expression of several JA/ETdependent defence genes and induces resistance against necrotrophic pathogens. For instance, expression of several *PR genes* which confer resistance against several necrotrophs (e.g., *PR3* and *PR5d* and *PDF1.2*) is modulated by *ERFs*. These defence genes possess a GCC box in their

Although ET has been shown to regulate plant defence responses against fungi and bacteria, ET is probably not essential in plant resistance against viruses. Recently, 1-aminocyclopro‐ pane-1- carboxylic acid (ACC) was shown to enhance *TMVcg* accumulation in treated plants [157], which increased susceptibility, suggesting that ET is required for viral infection.

Other phytohormones, such as ABA, gibberellins (GBs), auxins, brassinosteroids and cytoki‐ nins (CKs), have recently emerged as defence regulators [158]. ABA, a sesquiterpene com‐ pound resulting from the cleavage of γ-carotene, regulates numerous developmental processes and adaptive stress responses in plants. ABA can positively regulate plant defence at the early stages of infection by mediating stomatal closure against invaders, or inducing callose deposition if the pathogen evades the first line of defence [159]. If activated at later stages, ABA can suppress ROS induction and SA or JA signal transduction, thereby negating

Cytokinins promote cell division, and are known to play a role in the synthesis and mainte‐ nance of chlorophyll and chloroplast development and metabolism. CKs are also involved in the modulation of defence mechanisms, including the induction of resistance against viruses [161, 162], but are known to suppress HR [163]. Cytokinins can however act synergistically with SA signalling [164]. CKs activate the transcriptional regulator *ARABIDOPSIS RESPONSE REGULATOR 2* (*ARR2*), which positively modulates SA signalling by interacting with the SAresponsive factor *TGA3* [165]. *TGA3* induces the binding of *ARR2* to the promoters of *PR-1* and *PR-2* to induce cytokinin-dependent gene transcription. Correspondingly, the *npr1-1* or *NahG* mutants fail to modulate the induction of *ARR2* when treated with CK, indicating that CK modulates signaling components downstream of SA. Moreover, increased transcription of genes involved in SA-biosynthesis and signalling (e.g., *SID1*, *SID2*, *PR-1* and *PR-5*) is observed in *ARR2* over-expressing mutants challenged with *P. syringae* pv. *tomato* (*Pst DC3000*). Thus, CKs synergistically interacts not only with the SA signaling pathway to boost SA dependent induction of plant defence genes but also modulates SA biosynthesis. Cytokinins have also been shown to enhance the production of two antimicrobial phytoalexins, scopoletin and capsidiol in tobacco plants challenged with *P. syringae* pv*. tabaci* (*Pst*) independent of SA signalling [166]. Moreover, cytokinins induce the expression of cell wall invertase, a key

promoters, which is a direct target for the action of *ERFs* [156].

246 Plant Genomics

defences controlled by these two pathways [160].

RNA interference or silencing is one of the emergent crop improvement strategies that involve sequence-specific gene regulation by small non-coding RNAs, which mainly belong to two categories, i.e., small interfering RNA (siRNA) and microRNA (miRNA). Though these sRNAs differ in biogenesis [179], both regulate the target gene repression through ribonucleoprotein silencing complexes. Plant RNA silencing involves four basic steps, which include introduction of double-stranded RNA (dsRNA) into the cell, processing of dsRNA into 18–25-nt small RNA (sRNA), sRNA 2-O-methylation and sRNA incorporation into effector complexes that interact with target RNA or DNA [180]. The formation of RNA-induced silencing complex (*RISC*) and its incorporation into the antisense strand of siRNAs, which interacts with Argonaute and other effector proteins, precedes the cleavage of the target mRNA. For details about the formation of *RISC* and cleavage of the target mRNA, the reader is referred to comprehensive reviews [179, 181]. For sRNA to meet the target mRNA, it has to move from the point of initiation to the target. Thus, two main movement categories include cell-to-cell (short-range; symplastic movement through the plasmodesmata) and systemic (long-range; through the vascular phloem) movement. These mobile silencing strategies use sRNAs to target mRNA in a nucleotide sequence specific manner. By use of fluorescently labelled 21 and 24-nt siRNAs, Dunoyer et al. [182] demonstrated the movement of siRNAs from cell to cell and over long distances. Such systematic movements enhance systemic silencing of viruses as reported in *N. benthamiana* [183]. Similar systemic movements have been reported in the phloem sap of oilseed rape [184] and pumpkin [185]. Endogenous 21-nt miRNAs (miR399) were also reported to be mobile within the roots [186], and between shoots and roots of rapeseed and pumpkin [187]. Thus, sRNAs can be targeted to most active plant tissues, with transcription activity, to achieve a desirable consequence.

of the virus coat protein has also been successfully engineered into plants to induce resistance against viruses. For instance, transgenic tobacco plants expressing the CP gene of TMV are resistant to TMV. The resistance of *N. benthamiana* to *Cucumber Green Mottle Mosaic Virus* (CGMMV); and that of *Prunus domestica* to *Plum Pox virus* (PPV) are other examples docu‐

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In functional biology studies, virus-induced gene silencing (VIGS) has emerged to be one of the most powerful RNA-mediated post-transcriptional gene silencing (PTGS), not only in plant protection against viruses, but also for gene knockouts in functional genomic studies [195, 196].

Although RNAi has the potential to contribute to increased crop productivity, by generating crops with improved resistance against pests and diseases, it would be even better if interaction between sRNAs and their targets is validated in several backgrounds. This would provide valuable insight into mechanisms of post-transcriptional gene regulation and multiple molecular pathways controlling plant stress responses. However, the danger of unintentional silencing of genes with regions of homology to the intended target, and target mutations leading to easier escape from miRNA-directed silencing are still ethical issues. Certain biosafety concerns on the use of RNAi transgenics, especially transcriptional gene silencing by chromatin modification is even a more sensitive and contentious issue, as it is rumoured to lead to hereditary changes associated with adverse effects. Thus, the underlying mechanisms associated with RNAi require further investigations using well-controlled experiments.

**6. Modern approaches for improving biotic stress tolerance in plants**

Conventional breeding methods still play an important role in the selection of new varieties. However, emerging tools in biotechnology are much needed to maximize the probability of success. One area of biotechnology, molecular marker assisted breeding (MAB), has already made significant impact in improving efficiency of conventional breeding. There are, however, major gaps in the improvement of traits controlled by a large number of small effects, epistatic QTLs displaying significant genotype × environment (G × E) interactions. Thus, accurate indirect selections based on genomic tools that have emerged over the last few decades are continuously being employed to improve the breeding efficiency for such traits. The advantage is that, to date, the genome sequences for more than 55 plant species have been produced and many more are being sequenced [197]. The genome sequence information available enables the identification and development of genomewide markers. Availability of markers covering the whole genomic regions has already shown promise in the development of special popu‐ lations, such as recombinant inbred lines (RILs), near isogenic lines (NILs), introgression lines (ILs) or chromosome segment substitution lines (CSSLs). Recently, heterogeneous inbred family (HIFs) and multi-parent advanced generation inter-cross (MAGIC) populations, which can serve the dual purpose of permanent mapping populations for precise QTL mapping and for direct or indirect use in variety development, have shown promise in plant breeding. Also, genomewide association (GWA) analysis has been successfully applied to rice, maize, barley, wheat, sesame and other plants. GWA has also been adapted to the "breeding by design"

mented; for review see [179].

Several RNAi strategies have shown success in plant improvement against biotic stresses. Arabidopsis *miR393* was the first sRNA implicated in bacterial PTI [188], and enhanced *miR393* accumulation was found during sRNA profiling in Arabidopsis challenged with *Pst* [189]. The mechanism of *miR393-*induced resistance involves repression of auxin signalling by negatively regulating the F-box auxin receptors like *transport inhibitor response 1* (*TIR1*). This process restricts *Pst* infection, and, indeed, plants overexpressing *miR393* exhibit effective resistance against *Pst* [188].

RNAi in plant resistance to fungi has also shown promise. For instance, RNAi-mediated suppression of a rice gene *OsSSI2* enhances resistance towards *M. oryzae* and *X. oryzae* [189]. Moreover, RNAi suppression of *OsFAD7* and *OsFAD8,* the two genes encoding for *Ω-*3 fatty acid desaturase, also enhances resistance against *M. oryzae* [190]. RNAi targeting of lignin production pathway genes aimed at reducing lignin content has also been shown to enhance resistance against *Sclerotinia sclerotiorum* in soybean [191]. Increased resistance to *Blumeria graminis* f. sp. *tritici* in wheat was also demonstrated through RNAi using 24 miRNAs [192]. Nevertheless, the performance of these approaches under environmental conditions has often been unsatisfactory and environmental influences in expression of resistance often remain unpredictable [205].

In response to virus infection, several cases have shown successful crop improvement. For instance, resistance to *African Cassava Mosaic Virus* (CMV) was achieved in transgenic cassava plants producing dsRNA against PSTVd sequences [193]. A similar strategy was successful in transgenic tomato resistance against *Potato Spindle Tuber Viroid* (PSTVd) [194]. RNAi targeting of the virus coat protein has also been successfully engineered into plants to induce resistance against viruses. For instance, transgenic tobacco plants expressing the CP gene of TMV are resistant to TMV. The resistance of *N. benthamiana* to *Cucumber Green Mottle Mosaic Virus* (CGMMV); and that of *Prunus domestica* to *Plum Pox virus* (PPV) are other examples docu‐ mented; for review see [179].

categories, i.e., small interfering RNA (siRNA) and microRNA (miRNA). Though these sRNAs differ in biogenesis [179], both regulate the target gene repression through ribonucleoprotein silencing complexes. Plant RNA silencing involves four basic steps, which include introduction of double-stranded RNA (dsRNA) into the cell, processing of dsRNA into 18–25-nt small RNA (sRNA), sRNA 2-O-methylation and sRNA incorporation into effector complexes that interact with target RNA or DNA [180]. The formation of RNA-induced silencing complex (*RISC*) and its incorporation into the antisense strand of siRNAs, which interacts with Argonaute and other effector proteins, precedes the cleavage of the target mRNA. For details about the formation of *RISC* and cleavage of the target mRNA, the reader is referred to comprehensive reviews [179, 181]. For sRNA to meet the target mRNA, it has to move from the point of initiation to the target. Thus, two main movement categories include cell-to-cell (short-range; symplastic movement through the plasmodesmata) and systemic (long-range; through the vascular phloem) movement. These mobile silencing strategies use sRNAs to target mRNA in a nucleotide sequence specific manner. By use of fluorescently labelled 21 and 24-nt siRNAs, Dunoyer et al. [182] demonstrated the movement of siRNAs from cell to cell and over long distances. Such systematic movements enhance systemic silencing of viruses as reported in *N. benthamiana* [183]. Similar systemic movements have been reported in the phloem sap of oilseed rape [184] and pumpkin [185]. Endogenous 21-nt miRNAs (miR399) were also reported to be mobile within the roots [186], and between shoots and roots of rapeseed and pumpkin [187]. Thus, sRNAs can be targeted to most active plant tissues, with transcription activity, to achieve

Several RNAi strategies have shown success in plant improvement against biotic stresses. Arabidopsis *miR393* was the first sRNA implicated in bacterial PTI [188], and enhanced *miR393* accumulation was found during sRNA profiling in Arabidopsis challenged with *Pst* [189]. The mechanism of *miR393-*induced resistance involves repression of auxin signalling by negatively regulating the F-box auxin receptors like *transport inhibitor response 1* (*TIR1*). This process restricts *Pst* infection, and, indeed, plants overexpressing *miR393* exhibit effective resistance

RNAi in plant resistance to fungi has also shown promise. For instance, RNAi-mediated suppression of a rice gene *OsSSI2* enhances resistance towards *M. oryzae* and *X. oryzae* [189]. Moreover, RNAi suppression of *OsFAD7* and *OsFAD8,* the two genes encoding for *Ω-*3 fatty acid desaturase, also enhances resistance against *M. oryzae* [190]. RNAi targeting of lignin production pathway genes aimed at reducing lignin content has also been shown to enhance resistance against *Sclerotinia sclerotiorum* in soybean [191]. Increased resistance to *Blumeria graminis* f. sp. *tritici* in wheat was also demonstrated through RNAi using 24 miRNAs [192]. Nevertheless, the performance of these approaches under environmental conditions has often been unsatisfactory and environmental influences in expression of resistance often remain

In response to virus infection, several cases have shown successful crop improvement. For instance, resistance to *African Cassava Mosaic Virus* (CMV) was achieved in transgenic cassava plants producing dsRNA against PSTVd sequences [193]. A similar strategy was successful in transgenic tomato resistance against *Potato Spindle Tuber Viroid* (PSTVd) [194]. RNAi targeting

a desirable consequence.

248 Plant Genomics

against *Pst* [188].

unpredictable [205].

In functional biology studies, virus-induced gene silencing (VIGS) has emerged to be one of the most powerful RNA-mediated post-transcriptional gene silencing (PTGS), not only in plant protection against viruses, but also for gene knockouts in functional genomic studies [195, 196].

Although RNAi has the potential to contribute to increased crop productivity, by generating crops with improved resistance against pests and diseases, it would be even better if interaction between sRNAs and their targets is validated in several backgrounds. This would provide valuable insight into mechanisms of post-transcriptional gene regulation and multiple molecular pathways controlling plant stress responses. However, the danger of unintentional silencing of genes with regions of homology to the intended target, and target mutations leading to easier escape from miRNA-directed silencing are still ethical issues. Certain biosafety concerns on the use of RNAi transgenics, especially transcriptional gene silencing by chromatin modification is even a more sensitive and contentious issue, as it is rumoured to lead to hereditary changes associated with adverse effects. Thus, the underlying mechanisms associated with RNAi require further investigations using well-controlled experiments.

#### **6. Modern approaches for improving biotic stress tolerance in plants**

Conventional breeding methods still play an important role in the selection of new varieties. However, emerging tools in biotechnology are much needed to maximize the probability of success. One area of biotechnology, molecular marker assisted breeding (MAB), has already made significant impact in improving efficiency of conventional breeding. There are, however, major gaps in the improvement of traits controlled by a large number of small effects, epistatic QTLs displaying significant genotype × environment (G × E) interactions. Thus, accurate indirect selections based on genomic tools that have emerged over the last few decades are continuously being employed to improve the breeding efficiency for such traits. The advantage is that, to date, the genome sequences for more than 55 plant species have been produced and many more are being sequenced [197]. The genome sequence information available enables the identification and development of genomewide markers. Availability of markers covering the whole genomic regions has already shown promise in the development of special popu‐ lations, such as recombinant inbred lines (RILs), near isogenic lines (NILs), introgression lines (ILs) or chromosome segment substitution lines (CSSLs). Recently, heterogeneous inbred family (HIFs) and multi-parent advanced generation inter-cross (MAGIC) populations, which can serve the dual purpose of permanent mapping populations for precise QTL mapping and for direct or indirect use in variety development, have shown promise in plant breeding. Also, genomewide association (GWA) analysis has been successfully applied to rice, maize, barley, wheat, sesame and other plants. GWA has also been adapted to the "breeding by design"

**Figure 2.** Principle of genomic selection. Two steps are involved; developing a training population to provide pheno‐ typic and genotypic data; effects are estimated for all molecular markers. The second step involves genotyping untest‐ ed populations and selecting superior genotypes based on their expected phenotypes according to the estimates obtained from the marker effects on the training population (bottom).

transcriptomics, proteomics, metabolomics, epigenetics and physiological and biochemical methods (Figure 3) will remarkably provide novel possibilities to understand the biology of

**Figure 3.** Supportive omic tools for increasing plant breeding efficiency against biotic stresses. Sky blue lines indicate interactions; largest bold black lines indicate epigenetic regulation; red lines indicate regulation; and blue line indicates

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The recent advent of genotyping by sequencing (GBS) approach that minimizes ascertainment biases and the need for prior genome sequence information associated with traditional techniques has also enabled single nucleotide polymorphism marker detection, exposition of QTLs and the discovery of candidate genes controlling stress tolerance. Thus, genome/ transcript profiling when combined with genome variation analysis is a potential area which could prove useful for breeders in the near future [205, 209]. Another newly developed approach, which combines genetical genomics and bulk segregant analysis (BSA) to identify markers linked to genes, shows the possibility of coupling BSA to high throughput sequencing methods. Although there are shortcomings, including errors introduced during NGS proce‐ dures, this method has proven to be useful in identifying stress tolerance genomic regions in crop plants. A more recent modification that exploits the power of deep sequencing of targetenriched SNP markers to increase the efficiency of BSA analysis is called target-enriched TEX-QTL mapping [197]. The authors propose that by combining a large F2 population size, deeply sequenced markers, and 10–20% bulk size, most QTLs can be identified within two genera‐ tions. Although it does not currently detect very closely linked QTL, TEX-QTL method is

plants and consequently to precisely develop stress tolerant crop varieties.

metabolic reactions.

approach, often referred to as genome selection (Figure 2), which predicts the outcome of a set of crosses on the basis of molecular markers information.

Recently, a combination of different approaches has been used to develop new rice cultivars referred to as 'Green Super Rice', possessing resistance to multiple insects and diseases, high nutrient efficiency and drought resistance. If fully exploited, the integration of a similar approach with breeding by design or genome selection would help to design new plant types with not only a few selected major loci, but nearly all the functional loci of the genome controlling key desirable traits in commercial cultivars.

Expression studies also present a major area of interest for breeders. Among them, the NGS technologies have become the mainstay of studying complex traits, as direct sequencing of genomes and comparison with reference sequences is increasingly becoming more feasible. Re-sequencing has been performed for model species, e.g., *Arabidopsis*, to understand the whole genome sequence variation, and ultimately discover single nucleotide polymorphisms (SNPs). Similar re-sequencing efforts have been applied in rice, maize, soybean, grape and poplar. Combining re-sequencing with the recent developments in omic biology, including

**Figure 3.** Supportive omic tools for increasing plant breeding efficiency against biotic stresses. Sky blue lines indicate interactions; largest bold black lines indicate epigenetic regulation; red lines indicate regulation; and blue line indicates metabolic reactions.

transcriptomics, proteomics, metabolomics, epigenetics and physiological and biochemical methods (Figure 3) will remarkably provide novel possibilities to understand the biology of plants and consequently to precisely develop stress tolerant crop varieties.

approach, often referred to as genome selection (Figure 2), which predicts the outcome of a set

**Figure 2.** Principle of genomic selection. Two steps are involved; developing a training population to provide pheno‐ typic and genotypic data; effects are estimated for all molecular markers. The second step involves genotyping untest‐ ed populations and selecting superior genotypes based on their expected phenotypes according to the estimates

Recently, a combination of different approaches has been used to develop new rice cultivars referred to as 'Green Super Rice', possessing resistance to multiple insects and diseases, high nutrient efficiency and drought resistance. If fully exploited, the integration of a similar approach with breeding by design or genome selection would help to design new plant types with not only a few selected major loci, but nearly all the functional loci of the genome

Expression studies also present a major area of interest for breeders. Among them, the NGS technologies have become the mainstay of studying complex traits, as direct sequencing of genomes and comparison with reference sequences is increasingly becoming more feasible. Re-sequencing has been performed for model species, e.g., *Arabidopsis*, to understand the whole genome sequence variation, and ultimately discover single nucleotide polymorphisms (SNPs). Similar re-sequencing efforts have been applied in rice, maize, soybean, grape and poplar. Combining re-sequencing with the recent developments in omic biology, including

of crosses on the basis of molecular markers information.

obtained from the marker effects on the training population (bottom).

250 Plant Genomics

controlling key desirable traits in commercial cultivars.

The recent advent of genotyping by sequencing (GBS) approach that minimizes ascertainment biases and the need for prior genome sequence information associated with traditional techniques has also enabled single nucleotide polymorphism marker detection, exposition of QTLs and the discovery of candidate genes controlling stress tolerance. Thus, genome/ transcript profiling when combined with genome variation analysis is a potential area which could prove useful for breeders in the near future [205, 209]. Another newly developed approach, which combines genetical genomics and bulk segregant analysis (BSA) to identify markers linked to genes, shows the possibility of coupling BSA to high throughput sequencing methods. Although there are shortcomings, including errors introduced during NGS proce‐ dures, this method has proven to be useful in identifying stress tolerance genomic regions in crop plants. A more recent modification that exploits the power of deep sequencing of targetenriched SNP markers to increase the efficiency of BSA analysis is called target-enriched TEX-QTL mapping [197]. The authors propose that by combining a large F2 population size, deeply sequenced markers, and 10–20% bulk size, most QTLs can be identified within two genera‐ tions. Although it does not currently detect very closely linked QTL, TEX-QTL method is potentially a useful development in plant breeding. It is envisaged that BSA, by genotyping pooled-segregant sequencing, is likely to increase the reliability and reduce the time required to map all QTL defining the trait of interest and to identify causative superior alleles that can subsequently be used for crop improvement by targeted genetic engineering.

Desirable alleles are also being identified using functional genomic tools, including transfor‐ mation, insertional mutagenesis, RNAi, the screening of either mutant or natural germ‐ plasm collections by means of targeting induced local lesions in genomes (TILLING) or ecotype TILLING (EcoTILLING) methodologies. These strategies enable plant scientists to predict gene functions and allow efficient prediction of the phenotype associated with a given gene, the so-called reverse genetics approach. The availability of a large volume of sequen‐ ces generated through NGS technologies is significantly increasing the number and quality of candidates for TILLING and EcoTILLING studies. Thus, a number of crops have benefit‐ ed from these technologies, including Arabidopsis, lotus, barley, maize, pea, melon and rice, for review see [198].

The use of improved recombinant DNA techniques to introduce new traits in early phases of cultivar selection is also currently gaining momentum in plant biology. Techniques such as oligonucleotide-directed mutagenesis (oDM) as well as those based on zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALeN) and clustered regularly inter‐ spaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system are all capable of specifically modifying a given target sequence leading to genotypes not substan‐ tially different from those obtained through traditional mutagenesis. The practical use of these techniques in developing countries and the performance of the germplasm developed through them under environmental conditions [206, 207, 208] is yet to be fully demonstrated.

#### **7. Conclusion and perspective**

Plant resistance to biotic stresses is jointly controlled by the plants' anatomy, physiology, biochemistry, genetics, development and evolution. Efforts to understand these mechanisms have generated a lot of data on candidate genes, quantitative trait loci (QTLs), proteins and metabolites associated with plant defences. This chapter has reviewed most of these aspects to provide a reader with background information on the diverse plant defence patterns. Some of the genes and methods that hold promise for improving plant defences are also discussed. Certainly, plant-pathogen/insect interaction is a complex phenomenon that involves various signalling pathways tracking and regulating the pathogens/insect ingress. The interactions leading to effective defence apparently involve activation of both innate and systemic acquired resistance, and require both direct and indirect pathways to rapidly limit the entry or prolif‐ eration of biotic agents in the plant. Identifying and harmonizing an efficient defence signalling pathway, which leads to activation of an effective defence strategy, is still a challenge, considering the large number of genes and proteins often expressed in most plant-pathogen/ insect interaction studies. However, there are some resistance components that have shown promise, although further studies would be necessary to clarify the signalling patterns in which such components are involved. Important examples include LRR-RK *BAK1*, which features in several signalling networks leading to plant resistance against a diversity of pathogens and insects, and *NRC1* which mediates resistance and cell death induced by both membrane receptors and intracellular NLRs. *BAK1* forms heteromeric complexes with other receptors, which indicates that BAK1 is a multifaceted receptor capable of PAMP detection, while *NRC1* is probably a downstream convergence point in ETI initiated at various cell locations. Thus, *BAK1* and *NRC1* could probably contribute to effective plant resistance to a diversity of pathogens and insects. However, identification of additional effective receptors will be necessary to counter the stealthy tendencies of most pathogens and insects, and to guarantee the transmission of signals to the downstream components. More studies on adaptability of defence genes or QTLs to changing biotic agents and climatic conditions also need to be conducted in order to limit boom and bust incidences frequently observed in pathosystems.

#### **Acknowledgements**

potentially a useful development in plant breeding. It is envisaged that BSA, by genotyping pooled-segregant sequencing, is likely to increase the reliability and reduce the time required to map all QTL defining the trait of interest and to identify causative superior alleles that can

Desirable alleles are also being identified using functional genomic tools, including transfor‐ mation, insertional mutagenesis, RNAi, the screening of either mutant or natural germ‐ plasm collections by means of targeting induced local lesions in genomes (TILLING) or ecotype TILLING (EcoTILLING) methodologies. These strategies enable plant scientists to predict gene functions and allow efficient prediction of the phenotype associated with a given gene, the so-called reverse genetics approach. The availability of a large volume of sequen‐ ces generated through NGS technologies is significantly increasing the number and quality of candidates for TILLING and EcoTILLING studies. Thus, a number of crops have benefit‐ ed from these technologies, including Arabidopsis, lotus, barley, maize, pea, melon and rice,

The use of improved recombinant DNA techniques to introduce new traits in early phases of cultivar selection is also currently gaining momentum in plant biology. Techniques such as oligonucleotide-directed mutagenesis (oDM) as well as those based on zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALeN) and clustered regularly inter‐ spaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system are all capable of specifically modifying a given target sequence leading to genotypes not substan‐ tially different from those obtained through traditional mutagenesis. The practical use of these techniques in developing countries and the performance of the germplasm developed through

them under environmental conditions [206, 207, 208] is yet to be fully demonstrated.

Plant resistance to biotic stresses is jointly controlled by the plants' anatomy, physiology, biochemistry, genetics, development and evolution. Efforts to understand these mechanisms have generated a lot of data on candidate genes, quantitative trait loci (QTLs), proteins and metabolites associated with plant defences. This chapter has reviewed most of these aspects to provide a reader with background information on the diverse plant defence patterns. Some of the genes and methods that hold promise for improving plant defences are also discussed. Certainly, plant-pathogen/insect interaction is a complex phenomenon that involves various signalling pathways tracking and regulating the pathogens/insect ingress. The interactions leading to effective defence apparently involve activation of both innate and systemic acquired resistance, and require both direct and indirect pathways to rapidly limit the entry or prolif‐ eration of biotic agents in the plant. Identifying and harmonizing an efficient defence signalling pathway, which leads to activation of an effective defence strategy, is still a challenge, considering the large number of genes and proteins often expressed in most plant-pathogen/ insect interaction studies. However, there are some resistance components that have shown promise, although further studies would be necessary to clarify the signalling patterns in

subsequently be used for crop improvement by targeted genetic engineering.

for review see [198].

252 Plant Genomics

**7. Conclusion and perspective**

This publication was supported by Erfurt University of Applied Sciences.

#### **Author details**

Geoffrey Onaga1 and Kerstin Wydra2\*


2 Erfurt University of Applied Sciences, Faculty of Landscape Architecture, Horticulture and Forestry, Erfurt, Germany

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tomato against *Ralstonia solanacearum.* Physiological and Molecular Plant Pathology 81, 1-12

**Chapter 11**

**Genomics of Salinity Tolerance in Plants**

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/63361

**Abstract**

Trait loci

**1. Introduction**

Abdul Qayyum Rao, Salah ud Din, Sidra Akhtar, Muhammad Bilal Sarwar,

Uzma Qaisar, Ahmad Ali Shahid, Idrees Ahmad Nasir and Tayyab Husnain

Plants are frequently exposed to wide range of harsh environmental factors, such as drought, salinity, cold, heat, and insect attack. Being sessile in nature, plants have devel‐ oped different strategies to adapt and grow under rapidly changing environments. These strategies involve rearrangements at the molecular level starting from transcription, regu‐ lation of mRNA processing, translation, and protein modification or its turnover. Plants show stress-specific regulation of transcription that affects their transcriptome under stress conditions. The transcriptionally regulated genes have different roles under stress response. Generally, seedling and reproductive stages are more susceptible to stress. Thus, stress response studies during these growth stages reveal novel differentially regu‐ lated genes or proteins with important functions in plant stress adaptation. Exploiting the functional genomics and bioinformatics studies paved the way in understanding the rela‐ tionship between genotype and phenotype of an organism suffering from environmental stress. Future research programs can be focused on the development of transgenic plants with enhanced stress tolerance in field conditions based upon the outcome of genomic

approaches and knowing the mystery of nucleotides sequences hidden in cells.

**Keywords:** Salt tolerant genes, Salt Tolerance, Transgenic Plants, MicroRNA, Quantative

Nature's rage influencesplants inthe formofvarious biotic andabiotic stresses.Extreme abiotic stress conditions, such as salinity, flooding, heat, drought, and cold, as well as heavy metal toxicity and oxidative stress affect plants in many different ways. Human activities exacer‐ bate these stress conditions to a greater extent. All the abiotic and biotic stresses, including

and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

Mukhtar Ahmed, Bushra Rashid, Muhammad Azmat Ullah Khan,

