Genomic prediction and allele mining of agronomic and morphological traits in pea (Pisum sativum) germplasm collections.

ABSTRACT: Well-performing genomic prediction (GP) models for polygenic traits and molecular marker sets for oligogenic traits could be useful for identifying promising genetic resources in germplasm collections, setting core collections, and establishing molecular variety distinction. This study aimed at (i) defining GP models and key marker sets for predicting 15 agronomic or morphological traits in germplasm collections, (ii) verifying the GP model usefulness also for selection in breeding programs, (iii) investigating the consistency between molecular and phenotypic diversity patterns, and (iv) identifying genomic regions associated with to the target traits. The study was based on phenotyping data and over 41,000 genotyping-by-sequencing-generated SNP markers of 220 landraces or old cultivars be

SUBMITTER: Crosta M 

PROVIDER: S-EPMC10766761 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature