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

Natasha H. Johansen; Andrea Bellucci; Pernille B. Hansen; Petter Marum; Helga Amdahl; Kristin H. Gylstrøm; Odd Arne Rognli; Vilma Kemešytė; Gintaras Brazauskas; Morten Greve; Christer Persson; Mika Isolahti; Áslaug Helgadóttir; Rene Aavola; Torben Asp; Guillaume P. Ramstein
Theoretical and Applied Genetics · Vol. 138, Issue 11 · 2025

Abstract

Key Message Perennial ryegrass shows extensive genotype x environment interactions at the limit of its ecological niche. Accounting for GxE may improve prediction even when environmental and genetic samples are highly diverse. Background In 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). Methods The 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 under environmental conditions experienced in Nordic and Baltic regions at the limit of the species distribution. Two different approaches to modelling GxE were tested and validated under three different breeding scenarios. Results Our analysis documented the presence of significant GxE for all traits. 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 Quantitative Trait Loci (QTL) whose effects were adaptive under specific environmental conditions while neutral or deleterious under different environmental conditions. Conclusion This study demonstrates the usefulness and limitations of genomic prediction models for predicting GxE in highly diverse samples and describes the extent of GxE at the limit of species distribution for perennial ryegrass. Our study points towards adaptive variation which may enhance persistence of perennial ryegrass populations in Nordic and Baltic growing conditions.

Bibliographic Information

JournalTheoretical and Applied Genetics
PublisherSpringer
Publication Date2025-11-01
Publication Year2025
Volume138
Issue11
Document TypeJournal Article
Print ISSN0040-5752
eISSN1432-2242
DOI10.1007/s00122-025-05064-x

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NARA Access Coverage1929-01-01~Current
Journal Homepagehttps://www.springer.com/journal/122
Publisher PageOpen Publisher Page
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