Average semivariance directly yields accurate estimates of the genomic variance in complex trait analyses.

ABSTRACT: Many important traits in plants, animals, and microbes are polygenic and challenging to improve through traditional marker-assisted selection. Genomic prediction addresses this by incorporating all genetic data in a mixed model framework. The primary method for predicting breeding values is genomic best linear unbiased prediction, which uses the realized genomic relationship or kinship matrix (K) to connect genotype to phenotype. Genomic relationship matrices share information among entries to estimate the observed entries' genetic values and predict unobserved entries' genetic values. One of the main parameters of such models is genomic variance (σg2), or the variance of a trait associated with a genome-wide sample of DNA polymorphisms, and genomic heritability (hg2); however, the seminal

SUBMITTER: Feldmann MJ 

PROVIDER: S-EPMC9157152 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature