BIN301 Genomic and Pedigree-Based Prediction of Genetic Value

Prediction of genetic value using mixed model theory - use of genomic data - use of pedigree data, primarily by use of an animal model, also with more than one random effect and, in addition, multivariate models. Motivation of models used for survival, modelling of categorical data (e.g, for diseases or number of lambs born), longitudinal models, in addition to modelling of genotype by environment interaction. Prediction errors will be calculated.

Introduction to estimation of variance components for random variables.

Examples from plant and animal breeding.

Students will have an overview over state-of-the-art predictions of genetic value for animal and plant populations, and their relevance in breeding programs.

After the course students should be able to predict genetic values, and thus phenotypes, based on genomic and family information (SNP- and G-BLUP, and pedigree based BLUP), with a focus to animal models. Model bias is covered and prediction errors will be calculated. The students will construct mixed model equations for animal models with more than one random effect (which in addition to animal and error might contain permanent environment of animal, litter, or non-additive (gene) effects), in multivariate models, and being introduced to modeling of survival, categorical data (e.g, for diseases or number of lambs born), longitudinal models, in addition to modelling of genotype by environment interaction.

The weekly assignments will be programmed in R, but students will learn commercial software (ASReml), to calculate breeding values, and to estimate variance components, in the most simple models.