Genomic prediction of agronomic traits in perennial ryegrass (Lolium perenne L.) and genotype x environment interactions at the limit of the species distribution

Johansen, N. H.; Bellucci, A.; Hansen, P. B.; Marum, P.; Amdahl, H.; Gylstrom, K. H.; Rognli, O. A.; Kemesyte, V.; Brazauskas, G.; Greve, M.; Persson, C.; Isolahti, M.; Helgadottir, A.; Aavola, R.; Asp, T.; Ramstein, G.

doi:10.1101/2025.03.18.642199

bioRxiv · 10.1101/2025.03.18.642199

Genomic prediction of agronomic traits in perennial ryegrass (Lolium perenne L.) and genotype x environment interactions at the limit of the species distribution

Johansen, N. H.·Bellucci, A.·Hansen, P. B.·Marum, P.·Amdahl, H.·Gylstrom, K. H.·Rognli, O. A.·Kemesyte, V.·Brazauskas, G.·Greve, M.·Persson, C.·Isolahti, M.·Helgadottir, A.·Aavola, R.·Asp, T.·Ramstein, G.

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Abstract

BackgroundIn breeding the aim is to identify and accumulate beneficial variants. However, detection of these variants may be challenging in the presence of extensive genotype x environment interactions (GxE), as variant effects will be conditional on environment. MethodsThe study assesses the performance of 264 diploid perennial ryegrass accessions in a multi-environment field trial. We investigate the extent of GxE, for yield (total dry matter) and persistence traits, i.e. winter kill and spring cover, under environmental conditions experienced in Nordic and Baltic regions at the limit of the species distribution. Two different approaches to modelling GxE were tested: reaction norm and envirotyping, and the models were validated under three different breeding scenarios. ResultsOur analysis documented the presence of significant GxE interaction for all traits investigated in the study. Validation showed improvements in prediction accuracy when accounting for GxE: up to 4% for yield when predicting in unobserved environments, and up to 22% and 9% for spring cover and winter kill, respectively when predicting unobserved germplasm. Genome-wide-association-studies (GWAS) were utilized to detect genetic variants with marginal effects (environment-independent effect) and conditional effects (environment-dependent effects). Results showed the presence of large-effect genetic variants with marginal effects, in addition to few QTL whose effects were adaptive under specific environmental conditions while neutral or deleterious under different environmental conditions. ConclusionThis study demonstrates the usefulness and limitations of genomic prediction models for predicting GxE in highly diverse samples, and describes the extent of GxE interactions at the limit of species distribution for perennial ryegrass. Finally, our study points toward adaptive variation, which may enhance persistence of perennial ryegrass populations in Nordic and Baltic growing conditions.

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Johansen, N. H., Bellucci, A., Hansen, P. B., Marum, P., Amdahl, H., Gylstrom, K. H., Rognli, O. A., Kemesyte, V., Brazauskas, G., Greve, M., Persson, C., Isolahti, M., Helgadottir, A., Aavola, R., Asp, T., Ramstein, G.. 2025-03-19. Genomic prediction of agronomic traits in perennial ryegrass (Lolium perenne L.) and genotype x environment interactions at the limit of the species distribution. https://doi.org/10.1101/2025.03.18.642199

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