Functional enrichment analysis of marker effects from genomic prediction models in soybean

Abstract

Genomic selection is a promising tool that can increase the efficiency of crop breeding, being particularly useful for improvement of quantitative traits. Th is approach is based on prediction of plant performances by estimation of breeding values using simultaneously effects of molecular markers across the genome. Even though all available genome-wide markers are used for selection, it could be expected that markers located near genes responsible for particular biological function will have higher effects on final breeding value. This work aimed to estimate marker effects for soybean yield by developing prediction model and to perform functional annotation and enrichment in order to reveal the differences in marker effects related to different biological functions on yield prediction. Training population of 230 lines from the existing breeding program of Institute of Field and Vegetable Crops, was analysed using genotyping-by-sequencing and evaluated for yield in field trails over three growing seasons.