Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

ABSTRACT: We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBL

SUBMITTER: Da Y 

PROVIDER: S-EPMC3907568 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature