Genome Analysis Identified Novel Candidate Genes for Ascochyta Blight Resistance in Chickpea Using Whole Genome Re-sequencing Data

Abstract

Ascochyta blight (AB) is a fungal disease that can significantly reduce chickpea production in Australia and other regions of the world. In this study, 69 chickpea genotypes were sequenced using whole genome re-sequencing (WGRS) methods. They included 48 Australian varieties differing in their resistance ranking to AB, 16 advanced breeding lines from the Australian chickpea breeding program, four landraces, and one accession representing the wild chickpea species Cicer reticulatum. More than 800,000 single nucleotide polymorphisms (SNPs) were identified. Population structure analysis revealed relatively narrow genetic diversity amongst recently released Australian varieties and two groups of varieties separated by the level of AB resistance. Several regions of the chickpea genome were under positive selection based on Tajima’s D test. Both Fst genome- scan and genome-wide association studies (GWAS) identified a 100 kb region (AB4.1) on chromosome 4 that was significantly associated with AB resistance. The AB4.1 region co-located to a large QTL interval of 7 Mb∼30 Mb identified previously in three different mapping populations which were genotyped at relatively low density with SSR or SNP markers. The AB4.1 region was validated by GWAS in an additional collection of 132 advanced breeding lines from the Australian chickpea breeding program, genotyped with approximately 144,000 SNPs. The reduced level of nucleotide diversity and long extent of linkage disequilibrium also suggested the AB4.1 region may have gone through selective sweeps probably caused by selection of the AB resistance trait in breeding. In total, 12 predicted genes were located in the AB4.1 QTL region, including those annotated as: NBS-LRR receptor-like kinase, wall-associated kinase, zinc finger protein, and serine/threonine protein kinases. One significant SNP located in the conserved catalytic domain of a NBS-LRR receptor-like kinase led to amino acid substitution. Transcriptional analysis using qPCR showed that some predicted genes were significantly induced in resistant lines after inoculation compared to non-inoculated plants. This study demonstrates the power of combining WGRS data with relatively simple traits to rapidly develop “functional makers” for marker-assisted selection and genomic selection.

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

“…It is possible that the region identified by Li et al . () is different than the one identified in the current study as the two studies used different pathotypes of Ascochyta rabiei and different sources of resistance.…”

“…Ascochyta blight resistance QTLs have been reported on all chickpea chromosomes. However, most of these QTLs were identified using low‐density SSR marker‐based maps and the QTL interval varied from 0.3 to 30 Mb in CDC Frontier physical map (Li et al ., ; Sagi et al ., ). Genomic position of a few QTL flanking SSR markers was still undetected in the reference genome, and, hence, they were not used for comparative analysis in the present study.…”

mQTL-seq and classical mapping implicates the role of an AT-HOOK MOTIF CONTAINING NUCLEAR LOCALIZED (AHL ) family gene in Ascochyta blight resistance of chickpea

“…The presence of four pathotypes in A . rabiei is now accepted (Li, Ruperao, et al, ). The identified qABR4 .…”

“…Despite the presence of different pathotypes, many genetic studies have ignored the pathotype‐specific effect of QTLs, and only few have mentioned the A . rabiei pathotype in their genetic studies (Aryamanesh, Nelson, Yan, Clarke, & Siddique, ; Cho, Chen, & Muehlbauer, ; Li, Ruperao, et al, ; Udupa & Baum, ). Among the identified QTLs, two major ones (QTL AR1 and QTL AR2 ) have recurrently appeared in different crosses on linkage group IV (LGIV) (Cho et al, ; Iruela et al, ; Madrid et al, ; Sabbavarapu et al, ; Santra, Tekeoglu, Ratnaparkhe, Kaiser, & Muehlbauer, ; Stephens et al, ; Tekeoglu, Isik, & Muehlbauer, ; Udupa & Baum, ).…”

Adapting legume crops to climate change using genomic approaches

“…Examples of where LD mapping has been applied for identification of both novel and previously characterized genes responsible for agronomic traits include genome‐wide association studies (GWAS) in model legume Medicago truncatula (Stanton‐Geddes et al, ), common bean (Kamfwa, Cichy, & Kelly, ; Moghaddam et al, ), and soybean (Contreras‐Soto et al, ; Zhou et al, ). GWAS has also proven to be successful in identifying candidate genes for ascochyta blight resistance (Li et al, ) and heat and drought tolerant loci in chickpea (Thudi, Upadhyaya, et al, ), and Aphanomyces euteiches resistance in Medicago truncatula (Bonhomme et al, ). Applying GWAS in a population comprising 292 pigeonpea accessions using data over several years enabled identification of association between candidate genes and traits, including 100‐seed weight, days to 50% flowering, and plant height (Varshney et al, ).…”