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.

Department of Plant Biotechnology and Bioinformatics Ghent University Ghent Belgium

Division of Plant Breeding Fodder Plant Breeding Agroscope Zurich Switzerland

DLF Seeds Hladké Životice Czechia

Germinal Horizon Plas Gogerddan Aberystwyth United Kingdom

Graminor Breeding Ltd Bjørke Forsøksgård Norway

INRAE P3F Lusignan France

Institute for Forage Crops Kruševac Serbia

Institute of Biological Environmental and Rural Sciences Aberystwyth University Aberystwyth United Kingdom

Lantmännen Lantbruk Svalöv Sweden

Molecular Plant Breeding Institute of Agricultural Sciences ETH Zurich Zurich Switzerland

Plant Sciences Unit Flanders Research Institute for Agriculture Fisheries and Food Melle Belgium

The Nordic Genetic Resource Centre Plant Section Alnarp Sweden

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