Integrative GWAS, transcriptomics, and genomic prediction identify loci and candidate genes for flowering time in alfalfa

Flowering time in alfalfa is a key agronomic trait that influences harvest scheduling and breeding strategies, with direct consequences for forage yield and quality. Despite its importance, the genetic basis underlying flowering time in alfalfa remains poorly understood. In this study, we evaluated flowering time under field conditions over three years using a diverse panel of 176 accessions and investigated its genetic architecture. Phenotypic analysis revealed substantial variation across years. Genome resequencing of the panel yielded 2,043,025 high-quality single-nucleotide polymorphisms (SNPs), which were used for genome-wide association studies (GWAS). GWAS identified 42 significant SNPs and implicated 210 candidate genes in close proximity to these loci. Integration of GWAS with RNA-seq data prioritized 10 candidate genes, and their involvement in flowering regulation was further supported by RT‒qPCR. Haplotype analysis indicated that the number of haplotypes associated with delayed flowering was positively correlated with later flowering time. Genomic prediction (GP) using the top 5,000 SNPs from GWAS achieved accuracies ranging from 0.72 to 0.91 across traits. These findings provide testable targets for elucidating the regulatory mechanisms of flowering time in alfalfa and establish a foundation for molecular design breeding to optimize this trait.