Additive Genetic Variability and the Bayesian Alphabet

摘要: The use of all available molecular markers in statistical models for prediction quantitative traits has led to what could be termed a genomic-assisted selection paradigm animal and plant breeding. This article provides critical review some theoretical concepts the context genetic evaluation animals crops. First, relationships between (Bayesian) variance marker effects regression additive are examined under standard assumptions. Second, connection genotypes resemblance relatives is explored, linkages marker-based model infinitesimal reviewed. Third, issues associated with Bayesian marker-assisted selection, focus on role priors, from angle. sensitivity specification that been proposed (called “Bayes A”) respect priors illustrated simulation. Methods can solve potential shortcomings these procedures discussed briefly.