**1. Introduction**

Chickpea (*Cicer arietinum* L.) is a diploid (2*n* = 16), self-pollinated plant which is grown in the cool season and has a genome size of 738 Mb [1]. It is the third most produced pulse crop in the world (13.73 million tons) after beans (26.52 million tons) and green pea (17.43 million tons) (FAOSTAT 2014). It is considered to be an ideal crop for the semiarid and arid regions as it exhibits an extensive tap root system. Chickpea seeds are an excellent source of nutrition as they contain ≈40% carbohydrates, ≈6% oil and 20–30% protein and good source of minerals and trace elements such as calcium, magnesium, phosphorus, iron and zinc [2]. Moreover, chickpea contributes to improvement of soil fertility since it has the capability to establish symbiotic association with *Mesorhizobium ciceri* that helps in fixing atmospheric nitrogen to the reduced nitrogen (NH3 ). Chickpea, through symbiotic nitrogen fixation (SNF), can fulfil up to 80% of its nitrogen requirement [3]. All these qualities make chickpea an economically important crop as it is an affordable source that can fulfil the dietary protein requirement of the masses.

**3. Legume genomics**

wilt has also been carried out [41–43].

SNP and InDel variations in chickpea [50].

developmental stages of an organism [34].

**4. Transcriptome**

With the advent of next-generation sequencing technologies, there has been a rapid increase in the efficiency of DNA and RNA sequencing and decrease in the cost involved. *Leguminosae* is a very important family known due to the economic and nutritional value of its members [18]. The recent years have witnessed a spurt in the number of studies utilizing genomic

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

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The advances in DNA sequencing have led to whole genome sequencing of important legumes such as *Glycine max* [19], *Medicago truncatula* [20], *Lotus japonicus* [21], *Cajanus cajan* [22], *Phaseolus vulgaris* [23], diploid ancestors of peanut *Arachis duranensis* and *Arachis ipaensis* [24] and *C. arietinum* [1, 25]. Moreover, whole genome resequencing has been carried out for soybean [26, 27], *Medicago* [28] and chickpea [1] in order to understand the genetic variability, evolution and domestication in greater depth. Simultaneously, in order to unravel the functional aspects of legume biology, several NGS-based studies of transcriptomes were carried out. These studies have made significant contributions towards understanding of gene expression, alternative splicing events and small RNA identification. Gene expression atlases have been developed for soybean [29, 30], *Medicago* [31], *L. japonicus* [32] and pigeon pea [33]. Moreover, in chickpea a number of transcriptome studies have been performed. These include exploring the overall transcriptome of various tissues [34–37], specifically understanding of the development of flower [38], seed [39] and root nodule [40]. Transcriptome analysis of chickpea under different abiotic and biotic stresses such as drought, desiccation, salinity, cold and *Fusarium*

Next-generation sequencing (NGS)-based plant genomics has also assisted in understanding of genetic variation within and between species mostly through identification of single-nucleotide polymorphisms (SNPs). In chickpea, a number of studies have been performed to identify SNPs and utilized for various applications such as construction of linkage maps, synteny analysis, anchoring of whole genome sequencing and quantitative trait loci (QTL) analysis [44–49]. A CicArVarDB has also been developed which includes

A cell undergoing a functional or developmental process has a specific set of genes undergoing transcription at a particular time and is collectively called the 'transcriptome'. Thus, a transcriptome represents up to an extant physical, biochemical and developmental status of a cell. A transcriptome represents a pool of protein coding as well as nonprotein-coding RNAs; moreover, there may be the presence of variants of genes originating from alternative splicing and RNA editing, making the transcriptome more complex than a genome. Study of transcriptome may reveal information regarding spatial and temporal expression patterns of genes, and therefore it is possible to generate global expression profiles of genes representing

approaches to understand the biology of several agronomic traits in legumes.
