Frontiers in Plant Science (Oct 2024)

Leveraging trait and QTL covariates to improve genomic prediction of resistance to Fusarium head blight in Central European winter wheat

  • Laura Morales,
  • Laura Morales,
  • Deniz Akdemir,
  • Anne-Laure Girard,
  • Anton Neumayer,
  • Vinay Kumar Reddy Nannuru,
  • Fahimeh Shahinnia,
  • Fahimeh Shahinnia,
  • Melanie Stadlmeier,
  • Lorenz Hartl,
  • Josef Holzapfel,
  • Julio Isidro-Sánchez,
  • Hubert Kempf,
  • Morten Lillemo,
  • Franziska Löschenberger,
  • Sebastian Michel,
  • Hermann Buerstmayr

DOI
https://doi.org/10.3389/fpls.2024.1454473
Journal volume & issue
Vol. 15

Abstract

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Fusarium head blight (FHB) is a devastating disease of wheat, causing yield losses, reduced grain quality, and mycotoxin contamination. Breeding can mitigate the severity of FHB epidemics, especially with genomics-assisted methods. The mechanisms underlying resistance to FHB in wheat have been extensively studied, including phenological traits and genome-wide markers associated with FHB severity. Here, we aimed to improve genomic prediction for FHB resistance across breeding programs by incorporating FHB-correlated traits and FHB-associated loci as model covariates. We combined phenotypic data on FHB severity, anthesis date, and plant height with genome-wide marker data from five Central European winter wheat breeding programs for genome-wide association studies (GWAS) and genomic prediction. Within all populations, FHB was correlated with anthesis date and/or plant height, and a marker linked to the semi-dwarfing locus Rht-D1 was detected with GWAS for FHB. Including the Rht-D1 marker, anthesis date, and/or plant height as covariates in genomic prediction modeling improved prediction accuracy not only within populations but also in cross-population scenarios.

Keywords