Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.

ABSTRACT:

Background

Genomic prediction is an effective method for shortening breeding cycles and accelerating genetic gains. Traditionally, genomic prediction has focused on estimating 'additive' breeding values for individual genotypes. However, for many breeding programmes, predicting the cross-performance of parental combinations may provide greater value.

Results

We present the genomic predicted cross-performance (GPCP) tool, which utilizes a mixed linear model based on additive and directional dominance. This tool is available within the BreedBase environment and as an R package. We assessed its effectiveness against classical genomic estimated breeding values (GEBVs) using simulated traits that exhibit varying dominance effects and on four yam traits. The GPCP tool proved super

SUBMITTER: Nyaga C 

PROVIDER: S-EPMC12620651 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature