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Abstract
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.
Highlights
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
By using phenotyping data for 20 drought tolerance related traits collected in 1–7 seasons at 1–5 locations in India and genotyping data for 241 simple sequence repeat (SSR) loci on one intra-specific population (ICC 4958 × I CC 1882), we identified a “QTL-hotspot” region harbouring 12 QTLs for 12 drought tolerance related traits explaining up to 58.20% phenotypic variation[5]
These SNPs were further filtered, using the criteria of minimum allele frequency (MAF) of ≥ 0.20 and lines having ≥ 5% missing data being discarded, which resulted in 53,169 SNPs across 222 recombinant inbred line (RIL) being analysed
Summary
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. Recent advances in sequencing technology have provided a cost effective way to develop several thousand SNPs in a limited period of time in large mapping populations, by sequence-based genotyping[11,12] One such technique, GBS13, offers simultaneous SNP detection and scoring and is being used in several crops for diversity assessment, trait mapping, GWAS and genomic selection[14,15]. The SNPs identified using NGS technologies cannot be directly used for QTL studies as: i) generation sequencing (NGS) technologies are prone to small but unrecoverable sequencing errors and an individual SNP site cannot be used as a reliable marker for genotyping, ii) it is very difficult to score all SNP sites in an entire recombinant population, and iii) limitations of QTL analysis software to handle such a huge dataset To address these issues, a parent dependant sliding window approach was used to identify true recombination breakpoints and to construct a recombination bin map using SNP data of an entire recombinant population in rice[18]. Functional validation of these genes has provided the most promising candidate genes that are involved in regulation of drought tolerance in chickpea
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