**7. Using transcriptome analysis for study of stress response in chickpea**

Transcriptome analysis has been utilized exclusively to study different abiotic and biotic stress responses in chickpea. Drought and salinity are the major factors that limit the growth and productivity of the plants. Terminal drought is thought to be a major constraint affecting productivity of chickpea as it can lower the yield of chickpea by about 50% [59]. Cold stress also affects susceptible chickpea mainly at the reproductive stage where it leads to pollen sterility and flower abortion [60]. Thus, it is important to study the response of chickpea under these stress conditions in order to devise strategies for development of stress-tolerant chickpea. Earlier studies based on EST sequencing, SAGE and microarray provided preliminary evidence for drought responses of chickpea at transcriptome level [61–66]. An EST sequencing-based study of drought and salinity stress in chickpea resulted in generation of 20,162 ESTs, of which 105 were found to have differential expression during one of the stresses [65]. In another comparison between ESTs generated from chickpea, ICC 4958 (drought tolerant) and ICC 1882 (drought resistant) varieties resulted in identification of 5494 drought-responsive ESTs [61]. A microarray-based transcriptome analysis of root and leaf of chickpea under drought stress resulted in identification of 4815 differentially expressed genes. Approximately 2623 and 3969 genes were found to be differentially expressed, whereas 88 and 52 genes were found to be specifically expressed during drought stress in root and leaf tissues, respectively [66]. Another microarray analysis in chickpea revealed 109, 210 and 386 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 upregulated and downregulated, respectively, in root and nodule tissues [64].

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

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

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

**7. Using transcriptome analysis for study of stress response in chickpea**

Transcriptome analysis has been utilized exclusively to study different abiotic and biotic stress responses in chickpea. Drought and salinity are the major factors that limit the growth and productivity of the plants. Terminal drought is thought to be a major constraint affecting productivity of chickpea as it can lower the yield of chickpea by about 50% [59]. Cold stress also affects susceptible chickpea mainly at the reproductive stage where it leads to pollen sterility and flower abortion [60]. Thus, it is important to study the response of chickpea under these stress conditions in order to devise strategies for development of stress-tolerant chickpea. Earlier studies based on EST sequencing, SAGE and microarray provided preliminary evidence for drought responses of chickpea at transcriptome level [61–66]. An EST sequencing-based study of drought and salinity stress in chickpea resulted in generation of 20,162 ESTs, of which 105 were found to have differential expression during one of the stresses [65]. In another comparison between ESTs generated from chickpea, ICC 4958 (drought tolerant) and ICC 1882 (drought resistant) varieties resulted in identification of 5494 drought-responsive ESTs [61]. A microarray-based transcriptome analysis of root and leaf of chickpea under drought stress resulted in identification of 4815 differentially expressed genes. Approximately 2623 and 3969 genes were found to be differentially expressed, whereas 88 and 52 genes were found to be specifically expressed during drought stress in root and leaf tissues, respectively [66]. Another microarray analysis in chickpea revealed 109, 210 and 386

development [57].

be differentially expressed during nodulation.

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 in anthers during cold stress conditions.

*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*  *ciceri*. The analysis resulted in identification of 257 differentially expressed genes associated with the early signalling pathway [70]. In order to understand the differential response of susceptible and tolerant/resistant chickpea varieties to *F. oxysporum*, transcriptomes of wilt susceptible (JG62) and wilt-tolerant/wilt-resistant (ICCV2, K850 and WR315) chickpea varieties were analysed using the Illumina platform. Comparison among the transcriptomes led to identification of 303 polymorphic SSRs, 14,462 SNPs and 1864 insertions/deletions (InDels). Moreover, a large number of SNPs and/or InDels were found to be present in defence-related genes [43].

in diverse cellular processes including protein turnover and modification, metabolism, transcriptional regulation and signal transduction [78]. A similar kind of study performed in leaf and flower tissue resulted in the prediction of 96 highly conserved miRNAs belonging to 38 miRNA families and 20 novel miRNAs belonging to 17 miRNA families in chickpea [80]. In addition to identification of miRNA from different tissues, studies were also conducted for characterization of miRNA in response to different biotic and abiotic stresses. In one such kind of study, three libraries were sequenced for small RNA identification [79]. Libraries were constructed from fungal-infected (*F. oxysporum* f.sp*. ciceris*), salt-treated and untreated seedlings of chickpea and were sequenced using the Illumina GAIIx platform. The analysis identified 122 conserved miRNAs belonging to 25 different families along with 59 novel miRNAs. miR156, miR396 and miR319 were upregulated in response to salt stress. miR156 and miR396 expression was found to be 1.5 times upregulated in both wilt and salt stresses, indicating a common mechanism implied by chickpea involving these miRNAs to cope up with both the stresses. miR530 was found to be significantly upregulated during wilt stress and may be involved in defence to fungal infection. Three legume-specific miRNAs, miR2111, miR2118 and miR5213, were also indicated to play a critical role in defence to pathogen attack. Targets of miR2111 include F-box protein and TIR (Toll/Interleukin-1 Receptor) domain-containing NBS-LRR disease-resistance proteins, and miR2118 and miR5213 also target the same class of R genes. Interestingly, miR2118 is upregulated following wilt infection and downregulated

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

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

253

Long intergenic non-coding (linc) RNAs belong to a class of non-coding transcripts which have a length of at least 200bp lacking coding potential and are transcribed from intergenic region of protein coding genes [81, 82]. Linc RNAs control gene regulation at transcriptional and post-transcriptional level by mechanisms including chromatin modification, promoter binding complex attachment and shielding mRNA degradation by acting as sponge against miRNA [83–85]. RNA-seq data from 11 different tissues of chickpea were used for mining linc-RNA [86]. RNA-seq data were processed using TopHat2 and Cufflinks program using chickpea genome as the reference. From 32,984 transcripts obtained, 5782 putative intergenic transcripts were extracted out and subjected to the optimized pipeline for identification of linc-RNA. After removing potential coding transcripts and transcripts having similarity to protein domains, finally a total of 2248 transcripts were retained as putative chickpea linc-RNAs. About 79%, i.e. 1790 linc-RNAs, could be assigned a putative function. Through expression profiling it was evident that a large number of linc-RNAs have tissue-specific expression in distinct tissues. Along with this several linc-RNAs were found to be targets of miRNAs and

were involved in various developmental and reproductive processes [86].

**9. Expanding transcriptome data to aid development of molecular** 

A DNA-based molecular marker is a DNA sequence with an identifiable location on the genome that can be transmitted from one generation to the next following the standard laws

following salt stress [79].

**markers**

In order to identify common genes between biotic and abiotic responses in chickpea, Mantri et al. [71] performed microarray analysis of chickpea ICC 3996 under three abiotic stresses (drought, cold and high salinity) and biotic stress (infection with *A. rabiei*). This analysis revealed 46, 54, 266 and 51 genes to be differentially regulated in drought, cold, high salinity and *A. rabiei* stresses, respectively. *A. rabiei* stress response was found to be more similar to that of high-salinity stress [71].
