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A high resolution gene expression atlas in Chickpea: Implications in crop improvement

Kudapa, H., Garg, V., Chitikineni, A. and Varshney, R.K.ORCID: 0000-0002-4562-9131 (2019) A high resolution gene expression atlas in Chickpea: Implications in crop improvement. In: Plant and Animal Genome (PAG ASIA) Conference 2019, 6 - 8 June 2019, Shenzhen, China.


Legumes are second to cereals in agricultural production accounting for approximately 27% of the world’s primary production. Grain legumes alone contribute to about one-third of the human dietary protein. Chickpea is one of the world’s largest cultivated food legume and is an excellent source of high-quality protein to the human diet. Plant growth and development are controlled by programmed expression of a suite of genes at the given time, stage and tissue. Understanding how the underlying genome sequence translates into specific plant phenotypes at key developmental stages, information on gene expression patterns is crucial. Here we present a comprehensive Cicer arietinum Gene Expression Atlas (CaGEA) across the plant developmental stages and organs covering the entire life cycle of chickpea. One of the widely used drought tolerant cultivar, ICC 4958 has been used to generate RNA-Seq data from 27 samples at five major developmental stages of the plant. A total of 816 million raw reads were generated and of these, 794 million filtered reads after QC were subjected to downstream analysis. A total of 15,947 unique number of differentially expressed genes across different pairwise tissue combinations were identified. Significant differences in gene expression patterns contributing in the process of flowering, nodulation, seed and root development were inferred in this study. Furthermore, four functionally relevant candidate genes on the effect of “QTL-hotspot” for drought tolerance in chickpea were identified. The gene expression atlas of chickpea would not only provide a global view of gene expression patterns in all major tissues and organ systems but also will serve as valuable resource for functional genomics and accelerate gene discovery in legumes.

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