Increased genomic predictive ability in mango using GWAS-preselected variants and fixed-effect SNPs.

ABSTRACT: Genomic selection (GS) using whole-genome sequencing (WGS) data has potential to improve breeding value accuracy in fruit trees, but previous studies have reported limited gains compared to high-density marker sets. Incorporating preselected variants identified through genome-wide association studies (GWAS) is a promising strategy to enhance the predictive power of WGS data. We investigated whether incorporating GWAS-preselected variants and fixed-effect markers into genomic best linear unbiased prediction (GBLUP) models improves predictive ability for fruit blush color (FBC), average fruit weight (AFW), fruit firmness (FF), and trunk circumference (TC) in mango (Mangifera indica L.). The study used 225 gene pool accessions from the Queensland Department of Primary Industries in Aus

SUBMITTER: Munyengwa N 

PROVIDER: S-EPMC12605043 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature