QTL‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.). Issue 8 (7th February 2017)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Plant biotechnology journal. Volume 15:Issue 8(2017)
• Page Start: 927
• Page End: 941
• Publication Date: 2017-02-07
• Subjects: resequencing -- trait mapping -- QTL‐seq analysis -- candidate gene discovery -- diagnostic markers; Plant biotechnology -- Periodicals; Plant genetic engineering -- Periodicals; 630.272
• DOI: 10.1111/pbi.12686
• Languages: English
• ISSNs: 1467-7644

Abstract

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 (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNPs 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.