Genome‐wide association mapping of Hagberg falling number, protein content, test weight and grain yield in UK wheat

Jon White, Rajiv Sharma, David Balding, James Cockram, Ian J. Mackay

Research output: Contribution to journalArticlepeer-review

Abstract

Association mapping using crop varieties allows identification of genetic loci of direct relevance tobreeding. Here, 150 UK wheat varieties genotyped with 23,288 single nucleotide polymorphisms(SNPs) were used for genome-wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number, test weight and grain yield. Power calculationsindicated experimental design would enable detection of quantitative trait loci (QTL) explaining≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNPwith an R2≥0.5 with the same QTL. GWAS identified marker-trait associations for all four traits. ForHagberg falling number (h2=0.89), six QTL were identified, including a major locus on chromosome7B explaining 49% PVE and reducing Hagberg falling number by 44 seconds. For protein content(h2=0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B and 6B, together explaining 48.9%PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 lociwere identified for grain yield (h2=0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1%PVE), of which five were located within 16 Mbp of genetic regions previously identified as underbreeder selection in European wheat. Our study demonstrates the utility of exploiting historical cropdatasets, identifying genomic targets for independent validation, and ultimately for wheat geneticimprovement.
Original languageEnglish
JournalCrop Science
Early online date28 Dec 2021
DOIs
Publication statusFirst published - 28 Dec 2021

Keywords

  • Agronomy and Crop Science

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