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Genome wide association studies and QTL mapping in chickpeas for resistance to Ascochyta Blight and Pythium Ultimum

Agarwal, C., Vandemark, G.J., Chen, W. and Varshney, R.K.ORCID: 0000-0002-4562-9131 (2019) Genome wide association studies and QTL mapping in chickpeas for resistance to Ascochyta Blight and Pythium Ultimum. In: 2019 ASA-CSSA-SSSA International Annual Meeting: Embracing the Digital Environment, 10 - 13 Vov. 2019, San Antonio, TX.


Ascochyta blight, caused by Ascochyta rabiei, is globally the most destructive disease of chickpea. Chickpeas also suffer from emerging diseases, including seed rot and damping-off caused by Pythium ultimum. The objectives of this study were to detect molecular markers associated with resistance in chickpea to these two diseases. Plant materials included 177 chickpea recombinant inbred lines derived from an interspecific cross [C. reticulatum (PI 599072) x C. arietinum (FLIP 84-92C)] and 209 chickpea accessions representing an ICRISAT ‘mini-core’ collection. Disease screenings were conducted in a growth chamber (Pythium) or greenhouse (Ascochyta) in repeated experiments. A linkage map was developed for the C. reticulatum x C. arietinum population that included 1032 single nucleotide polymorphisms (SNPs) across eight linkage groups covering 965cM. Recombinant inbred lines were evaluated for reaction to seed rot and pre-emergence damping-off caused by metalaxyl resistant P. ultimum. A single significant QTL was detected on LG4 by composite interval mapping that explained 41.8 % of total phenotypic variation for disease reaction. Conversely, a genome wide association study (GWAS) approach was used to detect markers associated with resistance in the ICRISAT mini-core collection to Pythium seed rot and Ascochyta blight. A total of 302,902 single nucleotide polymorphisms (SNPs) equally distributed across the chickpea genome were examined with ADMIXTURE to determine population structure. Genomic regions were evaluated separately to establish marker-trait associations by employing FarmCPU and multiple loci mixed linear models (MMLM). For Pythium disease resistance, a total of 15 significant SNPs were detected and three candidate genes identified. One candidate gene and a total of 10 and 18 significant SNPs were detected for resistance to A. rabiei pathotype 1 (AR19) and pathotype 2 (AR628), respectively. SNPs and candidate genes identified in this study can be used for marker-assisted selection to develop superior chickpea varieties with improved disease resistance.

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