Open AccessQTL ‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut ( A rachis hypogaea L .)
Author(s) -
Pandey Manish K.,
Khan Aamir W.,
Singh Vikas K.,
Vishwakarma Manish K.,
Shasidhar Yaduru,
Kumar Vinay,
Garg Vanika,
Bhat Ramesh S.,
Chitikineni Annapurna,
Janila Pasupuleti,
Guo Baozhu,
Varshney Rajeev K.
Publication year - 2017
Publication title -
plant biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.525
H-Index - 115
eISSN - 1467-7652
pISSN - 1467-7644
DOI - 10.1111/pbi.12686
Subject(s) - biology , quantitative trait locus , rust (programming language) , genetics , single nucleotide polymorphism , candidate gene , snp genotyping , snp , plant disease resistance , variants of pcr , snp array , expressed sequence tag , genome , allele , gene , genotype , computer science , programming language
Summary Rust and late leaf spot ( LLS ) are the two major foliar fungal diseases in groundnut, and their co‐occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS , whole‐genome resequencing ( WGRS )‐based approach referred as ‘ QTL ‐seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS . Sequence analysis of bulks for rust and LLS with reference‐guided resistant parent assembly identified 3136 single‐nucleotide polymorphisms ( SNP s) for rust and 66 SNP s for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNP s affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNP s affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNP s for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population ( TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL ‐seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.