Including marker x environment interactions improves genomic prediction in red clover ( Trifolium pratense L.).

Autor:	Skøt L; Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom., Nay MM; Division of Plant Breeding, Fodder Plant Breeding, Agroscope, Zurich, Switzerland., Grieder C; Division of Plant Breeding, Fodder Plant Breeding, Agroscope, Zurich, Switzerland., Frey LA; Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland., Pégard M; INRAE P3F, Lusignan, France., Öhlund L; Lantmännen Lantbruk, Svalöv, Sweden., Amdahl H; Graminor Breeding Ltd., Bjørke Forsøksgård, Norway., Radovic J; Institute for Forage Crops (IKBKS), Kruševac, Serbia., Jaluvka L; DLF Seeds, Hladké Životice, Czechia., Palmé A; The Nordic Genetic Resource Centre, Plant Section, Alnarp, Sweden., Ruttink T; Plant Sciences Unit, Flanders Research Institute for Agriculture, Fisheries and Food, Melle, Belgium.; Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium., Lloyd D; Germinal Horizon, Plas Gogerddan, Aberystwyth, United Kingdom., Howarth CJ; Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom., Kölliker R; Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Jazyk:	angličtina
Zdroj:	Frontiers in plant science [Front Plant Sci] 2024 Jun 10; Vol. 15, pp. 1407609. Date of Electronic Publication: 2024 Jun 10 (Print Publication: 2024).
DOI:	10.3389/fpls.2024.1407609
Abstrakt:	Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of plants. However, in the last decade, prediction models including marker x environment (MxE) interaction have been developed. We evaluated the potential of genomic prediction in red clover ( Trifolium pratense L.) using field trial data from five European locations, obtained in the Horizon 2020 EUCLEG project. Three models were compared: (1) single environment (SingleEnv), (2) across environment (AcrossEnv), (3) marker x environment interaction (MxE). Annual dry matter yield (DMY) gave the highest predictive ability (PA). Joint analyses of DMY from years 1 and 2 from each location varied from 0.87 in Britain and Switzerland in year 1, to 0.40 in Serbia in year 2. Overall, crude protein (CP) was predicted poorly. PAs for date of flowering (DOF), however ranged from 0.87 to 0.67 for Britain and Switzerland, respectively. Across the three traits, the MxE model performed best and the AcrossEnv worst, demonstrating that including marker x environment effects can improve genomic prediction in red clover. Leaving out accessions from specific regions or from specific breeders' material in the cross validation tended to reduce PA, but the magnitude of reduction depended on trait, region and breeders' material, indicating that population structure contributed to the high PAs observed for DMY and DOF. Testing the genomic estimated breeding values on new phenotypic data from Sweden showed that DMY training data from Britain gave high PAs in both years (0.43-0.76), while DMY training data from Switzerland gave high PAs only for year 1 (0.70-0.87). The genomic predictions we report here underline the potential benefits of incorporating MxE interaction in multi-environment trials and could have perspectives for identifying markers with effects that are stable across environments, and markers with environment-specific effects. Competing Interests: Author HA was employed by the company Graminor Breeding Ltd and author LJ was employed by the company DLF Seeds. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision. (Copyright © 2024 Skøt, Nay, Grieder, Frey, Pégard, Öhlund, Amdahl, Radovic, Jaluvka, Palmé, Ruttink, Lloyd, Howarth and Kölliker.)
Databáze:	MEDLINE
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