QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Abstract

Whole-genome sequencing-based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next-generation sequencing (NGS)-based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR-01 and CPR-02. Eleven QTLs in CPR-01 and six QTLs in CPR-02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR-01 using conventional biparental mapping approach were used to compare the efficiency of NGS-based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR-01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS-based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR-02 population. This study demonstrated the efficiency of NGS-based BSA as a rapid and cost-effective method to identify QTLs associated with ascochyta blight in chickpea.

Next‐generation sequencing identified genomic region and diagnostic markers for resistance to bacterial wilt on chromosome B02 in peanut (Arachis hypogaea L.)

“…The QTL‐seq approach only requires WGRS data of extreme bulks and parents of mapping population, making it cost‐effective and fast (Takagi et al ., ). This approach has been proved to be very successful with RIL populations in several crops including rice (Takagi et al ., ), peanut (Pandey et al ., ), cucumber (Wei et al ., ), chickpea (Deokar et al ., ) and pigeonpea (Singh et al ., ). The present study successfully applied the QTL‐seq approach (Figure ) to identify genomic regions and candidate genes for BWR using the sequencing data of parental genotypes and pooled samples of RIL population (Yuanza 9102 × Xuzhou 68‐4).…”

“…In order to increase the reliability of identified genomic regions and candidate genes, we used resistant as well as susceptible parent separately as reference parent in the QTL-seq approach. According to the original QTL-seq approach (Takagi et al, 2013), only one parent was required to be used as reference to analyse the reads of two extreme bulks, and previous reports followed this principle in multiple crops (Deokar et al, 2018;Hua et al, 2016;Pandey et al, 2017;Singh et al, 2016). Recently, in our one such study for shelling percentage in peanut, we found that when both parents were sequenced and used to analyse the reads of two extreme bulks in parallel, the comparative analysis of the two sets of results generated by QTL-seq increased the mapping efficiency and accuracy of shelling percentage in peanut (Luo et al, 2018).…”

“…This approach required resequencing of three samples, that is two bulks segregating for trait of interest and one parent of the mapping population, and is therefore cost-effective and more precise (Takagi et al, 2013). This approach has been proven very successful in identification of genomic regions for resistance to Fusarium wilt and sterility mosaic disease in pigeonpea , resistance to rust and late leaf spot in peanut and resistance to ascochyta blight in chickpea (Deokar et al, 2018). The present study reports deployment of sequencing-based trait mapping approach, QTL-seq, that helped in successful discovery of genomic regions, candidate genes and diagnostic markers for BWR in a RIL population developed from the cross of Yuanza 9102 9 Xuzhou 68-4.…”

Quantitative Trait Loci for Cold Tolerance in Chickpea

“…This could be due to species difference, or the linkage map density in this chickpea QTL study may be an issue (Mallikarjuna et al, 2017;Supplemental Fig. S2) compared with high-density chickpea maps (Deokar et al, 2018). We hypothesize that the two enzymes, PstI/MspI, of the Poland et al (2012) GBS were not the best combination for chickpea, since only 747 SNPs were identified.…”

Ethylene‐responsive factor 4 is associated with the desirable rind hardness trait conferring cracking resistance in fresh fruits of watermelon

“…After the release of the watermelon genome (Guo et al , ), watermelon has become an ideal model crop for research on traits such as fruit cracking, size, shape, rind colour, and flesh texture due to being an annual and thus having a shorter life cycle than other perennial fruit crops. With the advancement of next‐generation sequencing (NGS) technology, sequencing‐based gene mining strategies, such as bulk segregant analysis (BSA), genetic mapping and genome‐wide association study (GWAS), have been widely used as affordable, efficient and routine approaches to dissect crop traits in rice (Wang et al , ) tomato (Chapman et al , ; Soyk et al , ), cucumber(Li et al , ; Xu et al , ), peanut(Luo et al , ), chickpea(Deokar et al , ),spinach(She et al , ), apple(Jia et al , ) and melon (Hu et al , ). Recently, genes or QTLs related to sugar transporter (Ren et al , ), dwarfism (Dong et al , ) and lobed leaves (Wei et al , ) have been reported in watermelon.…”