New loci and candidate genes in spring two-rowed barley detected through meta-analysis of a field trial European network

Francesc Montardit-Tarda, Ana Maria Casas, William Thomas, Florian Schnaithmann, Rajiv Sharma, Salar Shaaf, Chiara Campoli, Joanne Russell, Luke Ramsay, Stefano Delbono, Marko Jääskeläinen, Maitry Paul, Frederick L Stoddard, Andrea Visioni, Andrew J Flavell, Klaus Pillen, Benjamin Kilian, Andreas Graner, Laura Rossini, Robbie WaughLuigi Cattivelli, Alan H. Schulman, Alessandro Tondelli, Ernesto Igartua (Lead / Corresponding author)

Research output: Working paper/PreprintPreprint

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Abstract

This study contributes new knowledge on quantitative trait loci (QTLs) and candidate genes for adaptive traits and yield in two-rowed spring barley. A meta-analysis of a network of field trials, varying in latitude and sowing date, with 151 cultivars across several European countries, increased QTL detection power compared to single-trial analyses. The traits analysed were heading date (HD), plant height (PH), thousand-grain weight (TGW), and grain yield (GY). Breaking down the analysis by the main genotype-by-environment trends revealed QTLs and candidate genes specific to conditions like sowing date and latitude. A historical look on the evolution of QTL frequencies revealed that early selection focused on PH and TGW, likely due to their high heritability. GY selection occurred later, facilitated by reduced variance in other traits. The study observed that favourable alleles for plant height were often fixed before those for grain yield and TGW. Some regions showed linkage in repulsion, suggesting targets for future breeding. Several candidate genes were identified, including known genes and new candidates based on orthology with rice. Remarkably, the deficiens allele of gene Vrs1, appears associated to higher GY. These findings provide valuable insights for barley breeders aiming to improve yield, and other agronomic traits.
Original languageEnglish
PublisherBioRxiv
DOIs
Publication statusPublished - 7 Sept 2024

Keywords

  • agronomic traits
  • barley
  • breeding history
  • GWAS
  • meta-analysis
  • Vrs1

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