**6. Using transcriptome analysis for studying biological processes in chickpea**

Extensive transcriptome analysis has been carried out in chickpea in order to gain insights into the numerous biological processes. Techniques, such as EST sequencing, SAGE and most importantly the NGS, have been used to analyse the transcriptomes of root, shoot, flower, seed and nodule tissues in order to understand the tissue-specific development and function. Several groups undertook EST sequencing, and till date (March 2017) 53,333 chickpea ESTs are reported in the NCBI database. In another earlier study of the root transcriptome, an EST library was constructed by subtractive suppressive hybridization (SSH) of two related chickpea varieties, ICC 4958 and Annigeri, as they show different root traits. Sequences of more than 2800 ESTs were reported and used to develop the 'Chickpea Root Expressed Sequence Tag Database' [54].

A major advancement in transcriptome analysis for understanding developmental and biological processes occurred with the advent of the NGS platform. Several large-scale NGS-based transcriptome analyses were carried out in chickpea [34–36]. In one of the first NGS-based studies, the Illumina sequencing of transcriptome of chickpea genotype ICC 4958 root and shoot followed by de novo assembly resulted in generation of 53,409 transcripts. Of these 34,676 transcripts were annotated, and 6577 transcripts were identified as transcription factors (TFs) belonging to 57 families. Another study by Garg et al. reported the Roche/454-based transcriptomes of 'shoot', 'root', 'mature leaf', 'flower bud' and 'young pod' of chickpea genotype ICC 4958 [34]. These sequence reads generated by the Roche/454 platform were merged with the Illumina reads from the previous study, and a hybrid assembly was generated [34], which resulted in 34,760 tentative consensus (TC) transcripts. Of these, 1851 transcripts were annotated as transcription factors belonging to 84 families. This analysis also led to the identification of 1132, 695, 513, 408 and 126 TCs specifically expressed in flower bud, young pod, shoot, root and mature leaf, respectively. The complete data were integrated leading to the development of the 'Chickpea Transcriptome Data Base' (CTDB) which provides a searchable interface to the chickpea transcriptome data [34]. Further, transcriptome analysis of the wild progenitor of chickpea, i.e. *Cicer reticulatum* PI489777, was also performed by Jhanwar et al. [37]. Moreover, transcriptomes of the kabuli, desi and wild chickpeas were compared [55] and used to create an improved version of the Chickpea Transcriptome Data Base V2.0 [56].

**5. Methods for transcriptome analysis**

248 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

**chickpea**

Transcriptome analysis was initiated with the generation of expressed sequence tags (ESTs) that are 200–800 nucleotide long cDNA sequences, synthesised from mRNA through reverse transcription. ESTs represent the expressed part of an organism's genome and hence are an excellent resource for the study of gene expression at a genome-wide level. Conventionally, EST resources have been developed through Sanger sequencing. Although this process is used to generate and sequence longer fragments of cDNA, it is tedious and labour intensive and offers poor coverage of the transcriptome. These limitations of EST-based transcriptome analysis inspired scientists to develop microarray and other tag-based methods for gene expression analysis. Therefore, tools such as microarrays and serial analysis of gene expression (SAGE) continued to be used for several years for analysis of global gene expression patterns. However, with the advent of NGS and the simultaneous development of in silico analytical tools, global genome and transcriptome analysis has become a standard practice for deriving information to relate genotype to phenotype. However, it is not possible to sequence the transcripts to the full length due to technological limitations. Transcriptome analysis is based on the principle that the depth of coverage of a sequence is proportional to the level of expression of the corresponding gene. Therefore, by mapping and counting the sequenced reads onto the given transcript, expression can be measured, thereby translating sequence information to some biologically significant information. A host of NGS technologies such as sequencing by synthesis (Illumina Inc., USA), SOLiD (ThermoFisher Scientific) and pyrosequencing (454 biosciences/Roche) has provided unprecedented opportunities for high-throughput functional genomic research [51–53]. Moreover, a number of technologies for transcriptome sequencing are emerging such as The Ion Torrent (ThermoFisher Scientific), single-molecule real time (SMRT) (Pacific Biosciences, USA) and Nanopore (Oxford Nanopore Technologies, UK).

**6. Using transcriptome analysis for studying biological processes in** 

Extensive transcriptome analysis has been carried out in chickpea in order to gain insights into the numerous biological processes. Techniques, such as EST sequencing, SAGE and most importantly the NGS, have been used to analyse the transcriptomes of root, shoot, flower, seed and nodule tissues in order to understand the tissue-specific development and function. Several groups undertook EST sequencing, and till date (March 2017) 53,333 chickpea ESTs are reported in the NCBI database. In another earlier study of the root transcriptome, an EST library was constructed by subtractive suppressive hybridization (SSH) of two related chickpea varieties, ICC 4958 and Annigeri, as they show different root traits. Sequences of more than 2800 ESTs were reported and used to develop the 'Chickpea Root Expressed Sequence Tag Database' [54]. A major advancement in transcriptome analysis for understanding developmental and biological processes occurred with the advent of the NGS platform. Several large-scale NGS-based transcriptome analyses were carried out in chickpea [34–36]. In one of the first NGS-based Flower development is an important and specialized process that takes place in angiosperms. Hence, in order to gain insights into the molecular mechanisms responsible for flower development in chickpea, transcriptome analysis was carried out using the Illumina sequencing platform [38]. Transcriptome sequencing of eight successive developing stages of flower (flower buds at sizes 4, 6, 8 and 8–10 mm and flowers with closed petals, partially opened petals, opened and faded petals and senescing petals) along with young leaf, germinating seedling and shoot apical meristem was carried out. Differential expression analysis revealed 1572 genes to be differentially expressed in at least one stage of flower development. A number of 1118 genes (908 upregulated and 201 downregulated) and 966 genes (857 upregulated and 109 downregulated) were found to be differentially regulated in flower bud and flower developmental stages, respectively [38]. The majority of the differentially expressed genes were found to be involved in various flower developmental pathways such as floral organ identity; development of corolla, androecium and gynoecium and gametophyte development. Moreover, genes related to cell wall development and transport were also found to be differentially expressed. In addition, 111 TF genes were found differentially expressed in floral bud and flower.

Chickpea is most valued for its seeds since they serve as a source of protein, especially for vegetarian population. Therefore, a thorough understanding of the transcriptional flux during seed development is important in order to get insights into the biological processes that define the seed. Towards this, an NGS-based deep transcriptome analysis of chickpea seed at four developmental stages, i.e. 10 days after anthesis (DAA), 20 DAA, 30 DAA and 40 DAA, was carried out [39]. The transcriptome was sequenced using the 454 pyrosequencing on the GS-FLX Titanium platform followed by its assembly into 51,099 transcripts. A gene ontology enrichment of seed-specific genes revealed genes related to reproductive structure development, fruit development and embryonic and post-embryonic development to be highly represented. Many metabolic pathways such as proteolysis, lipid metabolic process, regulation of RNA metabolic process, regulation of transcription, terpenoid metabolic process and gibberellin metabolic processes were also found to be significantly represented [39]. In another study, sequencing of ESTs from the chickpea embryo resulted in identification of 1480 unigenes expressed during embryo development [57]. The analysis also identified 12 genes encoding for F-box proteins, of which 2 F-box genes (*CarFbox\_PP2* and *CarF-box\_LysM*) were predicted to be involved in seed development [57].

genes to be differentially expressed in drought, cold and high-salinity stresses, respectively [62]. A SuperSAGE-based transcriptome analysis of chickpea drought stressed and control tissues gave rise to 17,493 unique transcripts (UniTags) of which 7532 were differentially expressed in drought stress [63]. Another SuperSAGE followed by 454 sequencing of root nodule transcriptome of salt-tolerant variety INRAT-93 identified 363 and 106 genes to be

Transcriptome Analysis in Chickpea (*Cicer arietinum* L.): Applications in Study of Gene...

http://dx.doi.org/10.5772/intechopen.69884

251

The more global view of stress response in chickpea was provided by the study of Garg et al. [41] in which the transcriptome of chickpea root and shoot under desiccation, salinity and cold stress was analysed. The Illumina sequencing-based transcriptome and comparison revealed 11,640 transcripts to be differentially expressed during at least one of the stresses. Seven hundred forty-five transcription factors (TFs) were also found to be differentially regulated in at least one stress condition. Moreover 3536 unannotated genes from the chickpea transcriptome were also identified [41]. A more detailed transcriptome analysis of drought-tolerant (ICC 4958), drought-sensitive (ICC 1882), salinity-tolerant (JG 62) and salinity-sensitive (ICCV2) chickpea varieties resulted in identification of 18,462 transcripts representing 13,964 unique loci in at least one sample/stress condition. The study also revealed 4954 and 5545 genes exclusively regulated in drought-tolerant and salinitytolerant varieties. A number of 775 TFs encoding genes belonging to 80 families were also found differentially regulated in stress conditions. Members of the bHLH, WRKY, NAC, AP2-EREBP and MYB were found among the top differentially expressed TFs in stress condition [42]. In order to understand the effect of cold stress, AFLP-based transcript profiling (cDNA-AFLP) approach was used [67], which showed that in cold-tolerant chickpea, 102 transcript-derived fragments (TDFs) were differentially expressed during cold stress. Moreover, transcriptome analysis of cold-tolerant chickpea ICC 16349 using cDNA differential display (DDRT-PCR) resulted in identification of 127 ESTs as differentially expressed

*Ascochyta* blight caused by *A. rabiei* and *Fusarium* wilt caused by *F. oxysporum* are major fungal diseases of chickpea. In order to understand the response of chickpea to *A. rabiei*, an EST library sequencing of blight-resistant chickpea variety ICC 3996 infected with *A. rabiei* was performed by Coram and Pang [68]. The study reported 516 genes of which 4% were related to defense and found to encode for lignin and phytoalexin biosynthesis enzymes, pathogenesisrelated proteins, signalling proteins and putative-defensive proteins [68]. For further identification of resistance-related genes, transcriptome analysis of four genotypes, *C. arietinum* ICC 3996, *C. arietinum* Lasseter, *C. arietinum* FLIP94-508C and *Cicer echinospermum* ILWC245, was performed using 756 featured microarrays. The study revealed 97 genes to be differentially expressed upon infection with *A. rabiei*. A comparison between resistant and susceptible varieties identified many genes such as pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein and Ca-binding protein, which might be responsible for imparting resistance to the tolerant varieties [69]. On the other hand, in order to identify genes involved in wilt resistance in chickpea, EST sequencing followed by microarray analysis of chickpea wilt susceptible genotype (JG-62) and resistant genotype (WR-315) was performed after infecting them with *F. oxysporum* 

upregulated and downregulated, respectively, in root and nodule tissues [64].

in anthers during cold stress conditions.

Another important distinctive feature of chickpea is its ability to form symbiotic relationship with *M. ciceri* which results in the formation of specialized structures called root nodules. These are formed by the host plant and protect the oxygen-sensitive, bacterial nitrogen fixing machinery. It is a complex phenomenon and a detailed understanding of the molecular pathways governing that the process of nodule development and nitrogen fixation would certainly help plant scientists in developing sustainable farming strategies for chickpea. Towards this, a DeepSuperSAGE-based transcriptome analysis led to the identification of 71 genes being differentially expressed in root nodules [58]. Further, in order to understand the root nodulation in greater depth, a deep transcriptome analysis of the chickpea root nodule at different developing stages was carried out using the 454 pyrosequencing [40]. Sequencing of transcriptomes of uninfected root and three developing stages of nodules followed by reference-based assembly resulted in 83,405 transcripts. Of these 3760 were found to be differentially expressed in at least one of the stages of nodule when compared to uninfected root. Also, 1606 transcripts were identified as transcription factors, of which 171 TFs were found to be differentially expressed during nodulation.
