**3. Amino acid content**

In addition to GPC, improvement in the amino acid composition is important to meet the food demands of a growing global population. A major function of proteins in nutrition is to supply adequate amounts of required amino acids [59, 60]. Depending on requirement and availability in animal metabolic processes, essential amino acids cannot be synthesised by animals, but play a crucial role in metabolism [61]. Therefore, improving amino acid content in rice grain is an important objective. Several studies using the linkage mapping approach with various mapping populations have provided useful genetic information for improving the amino acid composition (AAC) in rice grains. Wang et al. [23] identified 18 chromosomal

*Agronomy - Climate Change and Food Security*

**42**

**Cross**

**Population** 

**No. of** 

**PVE range** 

**Chromosomes/**

**Marker intervals/nearest markers for major QTL (PVE)**

**References**

**chromosome arms**

**(additive** 

**effect** 

**QTLs)**

**total** 

**QTLs**

**type and** 

**size**

Indica cultivar (PSBRc82) x Korean

DH lines

GZn-8;

7.5–22.8; 9.4

2, 3, 6, 8, 11, 12; 4

2,140,834–2,147,095 (10.3), 13,048,465–13,057,679 (12.3),

[55]

8,803,052–8,832,534 (14.3), 6,025,827–6,047,367 (15.3),

606,341- id6006214 (16.1), 2,110,566-id2009463 (17.3),

2,783,884–2,785,595 (20.3), 10,858,811-id11000778 (22.8)

[GZn]

wd9002310–9,831,169 (10.3), 5,645,339–5,648,872 (11.5),

[56]

2,048,774–2,054,640 (12.2), 3,538,410–3,548,096 (12.2),

7,062,019–7,089,136 (12.6), 5,027,770–5,077,125 (18.4),

10,907,196-id11001107 (27.7) [GZn]

RM585-RM3 (25) [GZn]; RM2488-RM440 (64.1),

[57]

RM440-RM31 (95.2), RM440-RM31 (95.2), RM432-RM429

(95.2), RM566-RM434 (36.6) [GFe]

GFe-1

(130 and 97)

rice (Joryeongbyeo) and PSBRc82 x

Indica breeding line (IR69428)

Indica cultivar (IR64) × Breeding

DH lines

GZn-8

8.6–27.7

2, 3, 5, 7, 8, 9, 11

(111 and

146)

line (IR69428) and Indica cultivar

(BR29) × Breeding line (IR75862)

Indica rice (PAU201) x Indica rice

F4

GZn-1;

25;

6; 5, 7, 9

34.6–95.2

GFe-5

Population

(579)

(Palman)

**Table 1.** *List of QTLs identified for biofortification traits in rice.*

regions for 19 components of AAC in 2 years, viz. 2002 and 2004. They found a total of 10 QTL clusters in 2002 and 6 in 2004.

Interestingly, they also detected a wide coincidence between the QTLs and the loci involved in amino acid metabolism pathways, including N assimilation, transfer and protein biosynthesis. In a similar study, Zhong et al. [26] reported 48 and 64 QTLs, each contributing 4.0–43.7% to the total phenotypic variance, in 2004 and 2005, respectively. They also reported good coincidence between the detected QTL and the loci involved in amino acid metabolism pathways in nitrogen assimilation and transport, or protein biosynthesis. In another study, Zheng et al. [24] mapped a total of 10 QTLs explaining 12–35% of PVE for histidine on chromosomes 1, 2, 3, 6, 7, 10, 11, and 12 and 8 QTLs explaining 16–33% of PVE for arginine on chromosomes 2, 3, 5, 6, 7, 10, 11, and 12. All QTLs showed significant additive effects from the triploid endosperm and diploid maternal plant, while two QTLs for histidine and two for arginine content also showed significant dominant main effects from the triploid endosperm. Various interactions between QTLs and the environment were detected for five QTLs associated with histidine content and two QTLs associated with arginine contents. QTLs associated with amino acid contents and linked/flanking markers are summarised in **Table 1**. Recently, Yoo [27] mapped a total of six main-effect QTLs located on chromosome 3, contributing 10.2–12.4% PVE for the content of six amino acids. The QTL cluster (qAla3, qVal3, qPhe3, qIle3, and qLeu3) in the interval of markers id3015453 and id3016090 was found to be associated with the contents of five amino acids and accounted for PVE from 10.2 to 12.8%. Although they also detected 26 digenic interactions for the content of 7 amino acids, viz. Asp, Ser, His, Gly, Arg, Ala, and Tyr, involving 25 loci distributed on the 9 chromosomes, but they did not find any interaction for the other 9 amino acids. Therefore, these identified QTL results will be useful to find the candidate genes and favourable alleles for the enrichment of nutritional value in rice grain.

## **4. Zn and Fe contents in rice**

Zn deficiency in grown-up children and adolescent males causes retarded growth and dwarfism, retarded sexual development, impaired sense of taste and poor appetite, and mental lethargy [62]. Several roles of zinc are found to be involved in an abundant number of proteins in biological systems to maintain their structural stability function. It has been found that Zn is essential for gene regulation and expression under stress conditions and is therefore required for protection against infections and disease [63]. Likewise, iron has so many vital functions in the body like as a carrier of oxygen to the tissues from the lungs [64].

In last two decades, more than 80 QTLs have been identified and mapped on all 12 chromosomes of rice for zinc and iron contents using various mapping populations derived from different intraspecific and interspecific crosses. QTLs associated with zinc and iron contents and linked/flanking markers are summarised in **Table 1**. As per our knowledge, for the first time, Stangoulis et al. [18] mapped two QTLs for Zn and three QTLs for Fe on chromosomes 1, 2, 8, and 12 explaining 12.8–15% and 13.8–18.3% of PVE, respectively. Besides, Garcia- Oliveira et al. [17] detected one major effect QTL explaining the most significant proportion of PVE (11–19%) for zinc, flanking SSR marker RM152 on chromosome 8. In other various studies, several QTLs have been reported which explained a large amount of PVE either for zinc or for both iron and zinc contents [34, 48–52].

**45**

**Figure 2.**

*from HarvestPlus).*

*Breeding for Biofortification Traits in Rice: Means to Eradicate Hidden Hunger*

interactions for Zn, Cu, Mg, and Na in a double haploid population.

qZn9.1 showed highest mean grain Zn of 18.1 and 19.1 mg kg<sup>−</sup><sup>1</sup>

Furthermore, they identified several candidate genes near grain zinc QTL (OsNRAMP, OsNAS, OsZIP, OsYSL, OsFER, and OsZIFL family), which may be useful for marker-assisted breeding for this important trait. Recently in 2019, two critical studies were conducted; in the first study, Descalsota-Empleo et al. [55] phenotyped two DH populations at two seasons and genotyped with a 6 K SNP chip and identified a total of 15 QTLs for agronomic traits and 50 QTLs for grain element concentration including 8 QTLs explaining 8.6–27.7% PVE for grain zinc. They also analysed the combined effect of QTL in both populations. Among the single-QTL lines, those with

seasons, respectively. They reported an increase in the content of zinc with the increase

seasons, respectively, in four QTL lines (qZn2.1 + qZn5.1 + qZn5.1 + qZn11.1). Their results showed the possibility of QTL pyramiding for improving the zinc content in rice. In another study, Kumar et al. [57] detected one QTL for Zn and five QTLs for Fe having PVE 25% and 34.6–95.2%, respectively, using F4 population (579 individuals) derived from a cross between PAU 201 and Palman. These identified QTLs can significantly enhance the efficacy of breeding programs to improve the Zn and Fe density in

*Map showing countries where zinc-biofortified rice varieties are released and being tested (information taken* 

in number of QTLs and observed highest grain Zn of 28.2 and 24.3 mg kg<sup>−</sup><sup>1</sup>

rice. The Zinc fortified rice varieties are released globally (**Figure 2**).

in two consecutive

in two

Ishikawa et al. [53] mapped four QTLs on chromosomes 2, 9, and 10 explaining 15.0–21.9% of PVE for grain zinc content using backcross recombinant inbred lines (BRILs) derived from *O. sativa* 'Nipponbare' and *O. meridionalis* W1627. Further, they fine-mapped QTL (named qGZn9) present on chromosome 9 and identified two tightly linked loci, qGZn9a (candidate region-190 kb) and qGZn9b (950 kb). They also showed the association of wild chromosomal segment covering qGZn9a with fertility reduction, and hence they recommended the use of qGZn9b as a valuable allele for breeding rice with high Zn in the grains. In another study, Swamy et al. [55] identified 20 QTLs for agronomic traits and total 59 QTLs for several biofortification traits including 8 QTLs for grain zinc and one QTL for grain iron, mapped on chromosomes 2, 3, 4, 6, 8, 11, and 12. They also detected eight epistatic

*DOI: http://dx.doi.org/10.5772/intechopen.91144*

#### *Breeding for Biofortification Traits in Rice: Means to Eradicate Hidden Hunger DOI: http://dx.doi.org/10.5772/intechopen.91144*

Ishikawa et al. [53] mapped four QTLs on chromosomes 2, 9, and 10 explaining 15.0–21.9% of PVE for grain zinc content using backcross recombinant inbred lines (BRILs) derived from *O. sativa* 'Nipponbare' and *O. meridionalis* W1627. Further, they fine-mapped QTL (named qGZn9) present on chromosome 9 and identified two tightly linked loci, qGZn9a (candidate region-190 kb) and qGZn9b (950 kb). They also showed the association of wild chromosomal segment covering qGZn9a with fertility reduction, and hence they recommended the use of qGZn9b as a valuable allele for breeding rice with high Zn in the grains. In another study, Swamy et al. [55] identified 20 QTLs for agronomic traits and total 59 QTLs for several biofortification traits including 8 QTLs for grain zinc and one QTL for grain iron, mapped on chromosomes 2, 3, 4, 6, 8, 11, and 12. They also detected eight epistatic interactions for Zn, Cu, Mg, and Na in a double haploid population.

Furthermore, they identified several candidate genes near grain zinc QTL (OsNRAMP, OsNAS, OsZIP, OsYSL, OsFER, and OsZIFL family), which may be useful for marker-assisted breeding for this important trait. Recently in 2019, two critical studies were conducted; in the first study, Descalsota-Empleo et al. [55] phenotyped two DH populations at two seasons and genotyped with a 6 K SNP chip and identified a total of 15 QTLs for agronomic traits and 50 QTLs for grain element concentration including 8 QTLs explaining 8.6–27.7% PVE for grain zinc. They also analysed the combined effect of QTL in both populations. Among the single-QTL lines, those with qZn9.1 showed highest mean grain Zn of 18.1 and 19.1 mg kg<sup>−</sup><sup>1</sup> in two consecutive seasons, respectively. They reported an increase in the content of zinc with the increase in number of QTLs and observed highest grain Zn of 28.2 and 24.3 mg kg<sup>−</sup><sup>1</sup> in two seasons, respectively, in four QTL lines (qZn2.1 + qZn5.1 + qZn5.1 + qZn11.1). Their results showed the possibility of QTL pyramiding for improving the zinc content in rice. In another study, Kumar et al. [57] detected one QTL for Zn and five QTLs for Fe having PVE 25% and 34.6–95.2%, respectively, using F4 population (579 individuals) derived from a cross between PAU 201 and Palman. These identified QTLs can significantly enhance the efficacy of breeding programs to improve the Zn and Fe density in rice. The Zinc fortified rice varieties are released globally (**Figure 2**).

#### **Figure 2.**

*Agronomy - Climate Change and Food Security*

total of 10 QTL clusters in 2002 and 6 in 2004.

regions for 19 components of AAC in 2 years, viz. 2002 and 2004. They found a

Interestingly, they also detected a wide coincidence between the QTLs and the loci involved in amino acid metabolism pathways, including N assimilation, transfer and protein biosynthesis. In a similar study, Zhong et al. [26] reported 48 and 64 QTLs, each contributing 4.0–43.7% to the total phenotypic variance, in 2004 and 2005, respectively. They also reported good coincidence between the detected QTL and the loci involved in amino acid metabolism pathways in nitrogen assimilation and transport, or protein biosynthesis. In another study, Zheng et al. [24] mapped a total of 10 QTLs explaining 12–35% of PVE for histidine on chromosomes 1, 2, 3, 6, 7, 10, 11, and 12 and 8 QTLs explaining 16–33% of PVE for arginine on chromosomes 2, 3, 5, 6, 7, 10, 11, and 12. All QTLs showed significant additive effects from the triploid endosperm and diploid maternal plant, while two QTLs for histidine and two for arginine content also showed significant dominant main effects from the triploid endosperm. Various interactions between QTLs and the environment were detected for five QTLs associated with histidine content and two QTLs associated with arginine contents. QTLs associated with amino acid contents and linked/flanking markers are summarised in **Table 1**. Recently, Yoo [27] mapped a total of six main-effect QTLs located on chromosome 3, contributing 10.2–12.4% PVE for the content of six amino acids. The QTL cluster (qAla3, qVal3, qPhe3, qIle3, and qLeu3) in the interval of markers id3015453 and id3016090 was found to be associated with the contents of five amino acids and accounted for PVE from 10.2 to 12.8%. Although they also detected 26 digenic interactions for the content of 7 amino acids, viz. Asp, Ser, His, Gly, Arg, Ala, and Tyr, involving 25 loci distributed on the 9 chromosomes, but they did not find any interaction for the other 9 amino acids. Therefore, these identified QTL results will be useful to find the candidate genes and favourable alleles for the enrichment of nutritional

Zn deficiency in grown-up children and adolescent males causes retarded growth and dwarfism, retarded sexual development, impaired sense of taste and poor appetite, and mental lethargy [62]. Several roles of zinc are found to be involved in an abundant number of proteins in biological systems to maintain their structural stability function. It has been found that Zn is essential for gene regulation and expression under stress conditions and is therefore required for protection against infections and disease [63]. Likewise, iron has so many vital functions in the

In last two decades, more than 80 QTLs have been identified and mapped on all 12 chromosomes of rice for zinc and iron contents using various mapping populations derived from different intraspecific and interspecific crosses. QTLs associated with zinc and iron contents and linked/flanking markers are summarised in **Table 1**. As per our knowledge, for the first time, Stangoulis et al. [18] mapped two QTLs for Zn and three QTLs for Fe on chromosomes 1, 2, 8, and 12 explaining 12.8–15% and 13.8–18.3% of PVE, respectively. Besides, Garcia- Oliveira et al. [17] detected one major effect QTL explaining the most significant proportion of PVE (11–19%) for zinc, flanking SSR marker RM152 on chromosome 8. In other various studies, several QTLs have been reported which explained a large amount of PVE either for zinc or for both iron and zinc

body like as a carrier of oxygen to the tissues from the lungs [64].

**44**

contents [34, 48–52].

value in rice grain.

**4. Zn and Fe contents in rice**

*Map showing countries where zinc-biofortified rice varieties are released and being tested (information taken from HarvestPlus).*
