Prioritization of candidate genes in “QTL-hotspot” region for drought tolerance in chickpea (Cicer arietinum L.)

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作者
Sandip M Kale
Deepa Jaganathan
Pradeep Ruperao
Charles Chen
Ramu Punna
Himabindu Kudapa
Mahendar Thudi
Manish Roorkiwal
Mohan AVSK Katta
Dadakhalandar Doddamani
Vanika Garg
P B Kavi Kishor
Pooran M Gaur
Henry T Nguyen
Jacqueline Batley
David Edwards
Tim Sutton
Rajeev K Varshney
机构
[1] International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),Department of Genetics
[2] Center of Excellence in Genomics (CEG),Department of Biochemistry and Molecular Biology
[3] Osmania University,National Center for Soybean Biotechnology and Division of Plant Sciences
[4] The University of Western Australia,undefined
[5] School of Plant Biology and the Institute of Agriculture,undefined
[6] University of Queensland,undefined
[7] School of Agriculture and Food Science,undefined
[8] Oklahoma State University,undefined
[9] Cornell University,undefined
[10] Biotechnology Building,undefined
[11] University of Missouri,undefined
[12] South Australian Research and Development Institute,undefined
[13] University of Adelaide,undefined
[14] Australia and School of Agriculture,undefined
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摘要
A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.
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