Phenotypic and genomic insights into alfalfa diversity: Identifying critical loci for enhanced resilience

TL;DR

This study explores how genetic and phenotypic diversity in alfalfa relates, identifying key traits and genes that could help breed more resilient crops.

Contribution

The study identifies specific genomic regions and traits linked to genetic differentiation in alfalfa, offering new targets for crop improvement.

Findings

Nine phenotypic groups were identified, with anthracnose resistance and lodging susceptibility as key traits.

Genome scans revealed candidate regions for disease resistance, abiotic stress, and reproductive traits.

Phenotypic and genetic clustering only showed moderate correspondence (Mantel r = 0.17, p = 0.001).

Abstract

Alfalfa (Medicago sativa L.) is a globally important forage crop, yet the relationship between its phenotypic variation and underlying genetic structure remains poorly resolved. In this study, we combined spatially adjusted, multiyear phenotyping with high‐density single‐nucleotide polymorphism genotyping in a panel of 395 cultivated accessions to (i) characterize the structure of phenotypic diversity across a broad range of agronomic traits, (ii) quantify the correspondence between phenotypic and genetic structure, and (iii) identify specific traits and genomic regions associated with genetic differentiation. Phenotypic data were collected across multiple locations and years, while genotypic data were obtained using genotyping by sequencing. Multivariate and feature selection analyses revealed nine phenotypic groups, with 78 traits confirmed as important, especially anthracnose resistance and lodging susceptibility. However, phenotypic clustering showed only moderate correspondence with genetic structure (Mantel r = 0.17, p = 0.001). Genome‐wide scans for genetic groups differentiation (F
ST) identified discrete genomic regions enriched for candidate genes linked to disease resistance, stress tolerance, and reproductive processes, including loci potentially involved in self‐incompatibility. These results highlight the complexity of genotype–phenotype relationships in alfalfa and pinpoint specific genomic targets for future breeding efforts aiming to enhance resilience, productivity, and adaptability.

American and European accessions spanned phenotypic groups, while most Chinese ones clustered in a single group.Genetic groups showed broad within‐group phenotypic diversity, with wide variation among accessions.Anthracnose resistance and lodging susceptibility are key phenotypic drivers of genetic group differentiation.Genome scans revealed candidate regions for disease resistance, abiotic stress, and reproductive traits.

American and European accessions spanned phenotypic groups, while most Chinese ones clustered in a single group.

Genetic groups showed broad within‐group phenotypic diversity, with wide variation among accessions.

Anthracnose resistance and lodging susceptibility are key phenotypic drivers of genetic group differentiation.

Genome scans revealed candidate regions for disease resistance, abiotic stress, and reproductive traits.

Alfalfa (Medicago sativa) is one of the most widely grown forage crops worldwide. In this study, we examined 395 cultivated accessions across two sites and 3 years, measuring a wide range of agronomic traits such as yield, forage quality, and disease resistance. These data were combined with genome‐wide deoxyribonucleic acid markers to better understand the relationship between genetic background and observable traits. Results reveal nine phenotypic groups and 78 traits linked to genetic structure, with anthracnose resistance and lodging susceptibility playing key roles, although genetic and phenotypic clustering only partly overlapped. The study also identified genomic regions linked to disease resistance, stress tolerance, and reproduction processes. The findings provide useful targets for breeding programs aimed at developing varieties with higher productivity, stronger resistance to disease, and improved adaptation to different environments.

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