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

Authors :
Laura Morales
Deniz Akdemir
Anne-Laure Girard
Anton Neumayer
Vinay Kumar Reddy Nannuru
Fahimeh Shahinnia
Melanie Stadlmeier
Lorenz Hartl
Josef Holzapfel
Julio Isidro-Sánchez
Hubert Kempf
Morten Lillemo
Franziska Löschenberger
Sebastian Michel
Hermann Buerstmayr
Source :
Frontiers in Plant Science, Vol 15 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

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.

Details

Language :
English
ISSN :
1664462X
Volume :
15
Database :
Directory of Open Access Journals
Journal :
Frontiers in Plant Science
Publication Type :
Academic Journal
Accession number :
edsdoj.7a1b05dd4424ea8bb9321e1f1238993
Document Type :
article
Full Text :
https://doi.org/10.3389/fpls.2024.1454473