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Key message: Major QTL for Phytophthora root rot resistance have been identified in three mapping populations with independent sources of resistance contributed by C. echinospermum and C. arietinum. Phytophthora root rot (PRR) caused by the oomycete Phytophthora medicaginis is a major soil-borne disease of chickpea in Australia. With no economic in-crop control of PRR, a genetic approach to improve resistance is the most practical management option. Moderate field resistance has been incorporated in the cultivated C. arietinum variety, Yorker, and a higher level of resistance has been identified in a derivative of wild chickpea (C. echinospermum, interspecific breeding line 04067-81-2-1-1). These genotypes and two other released varieties were used to develop one intra-specific and two interspecific F6-derived recombinant inbred line mapping populations for genetic analysis of resistance. The Yorker × Genesis114 (YG), Rupali × 04067-81-2-1-1 (RB) and Yorker × 04067-81-2-1-1 (YB) populations were genotyped using genotyping-by-sequencing and phenotyped for PRR under three field environments with a mixture of 10 P. medicaginis isolates. Whole-genome QTL analysis identified major QTL QRBprrsi01, QYBprrsi01, QRBprrsi03 and QYBprrsi02 for PRR resistance on chromosomes 3 and 6, in RB and YB populations, respectively, with the resistance source derived from the wild Cicer species. QTL QYGprrsi02 and QYGprrsi03 were also identified on chromosomes 5 and 6 in YG population from C. arietinum. Aligning QTL regions to the corresponding chickpea reference genome suggested that the resistance source from C. arietinum and C. echinospermum may be different. The findings from this study provide tools for marker-assisted selection in chickpea breeding and information to assist the development of populations suitable for fine-mapping of resistance loci to determine the molecular basis for PRR resistance in chickpea. [ABSTRACT FROM AUTHOR]

Achieving yield potential in chickpea (Cicer arietinum L.) is limited by many constraints that include biotic and abiotic stresses. Combining next-generation sequencing technology with advanced statistical modeling has the potential to increase genetic gain efficiently. Whole genome resequencing data was obtained from 315 advanced chickpea breeding lines from the Australian chickpea breeding program resulting in more than 298,000 single nucleotide polymorphisms (SNPs) discovered. Analysis of population structure revealed a distinct group of breeding lines with many alleles that are absent from recently released Australian cultivars. Genome-wide association studies (GWAS) using these Australian breeding lines identified 20 SNPs significantly associated with grain yield in multiple field environments. A reduced level of nucleotide diversity and extended linkage disequilibrium suggested that some regions in these chickpea genomes may have been through selective breeding for yield or other traits. A large introgression segment that introduced from C. echinospermum for phytophthora root rot resistance was identified on chromosome 6, yet it also has unintended consequences of reducing yield due to linkage drag. We further investigated the effect of genotype by environment interaction on genomic prediction of yield. We found that the training set had better prediction accuracy when phenotyped under conditions relevant to the targeted environments. We also investigated the effect of SNP functional annotation on prediction accuracy using different subsets of SNPs based on their genomic locations: regulatory regions, exome, and alternative splice sites. Compared with the whole SNP dataset, a subset of SNPs did not significantly decrease prediction accuracy for grain yield despite consisting of a smaller number of SNPs., (© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)