Harnessing exotic germplasm for red clover improvement: Tracking genomic introgression and deploying genomic selection

Abstract

Red clover ( Trifolium pratense L.) is a globally important temperate forage legume. Its symbiosis with soil‐borne rhizobia enables nitrogen fixation, and its ability to produce quality forage under diverse soil conditions enhances pasture productivity, particularly during water deficits. With increasing climate‐related stresses, harnessing adaptive traits absent in current cultivars is critical. Genebanks conserve diverse red clover germplasm, providing genetic variation for agronomic and adaptive traits. In this study, we introgressed novel germplasm into locally adapted cultivars to track the inheritance of allelic variants using genotyping‐by‐sequencing. Multi‐location, multi‐year trials evaluated half‐sib families (generation two [Gen 2]) two generations removed from the exotic germplasm (genereation zero [Gen 0]) against local cultivars. Several Gen 2 populations matched or outperformed local cultivars and exhibited a moderate family mean heritability ( h ²  > 0.40) for most traits. Integrating genomic, phenotypic, and environmental data, 77 bioclimatic‐associated single nucleotide polymorphisms (SNPs) were identified, of which 35 SNPs and 27 associated genes were significantly linked to trait expression. By using the original germplasm (Gen 0) as a training population and the derived half‐sib families (Gen 2) as a validation population, genomic prediction models were developed to calculate prediction accuracies for key agronomic traits. Biomass and plot density traits showed high predictive abilities and the highest prediction accuracies across generations. This study demonstrates a route by which genetic diversity from genebanks can be successfully incorporated into local populations, enabling evaluation and selection of key traits. The identified molecular markers and genomic prediction models provide a pathway to efficiently develop climate‐adaptive red clover cultivars.