In charlotte-ngs/lbgfs2020: Livestock Breeding and Genomics (Fall 2020)

knitr::opts_chunk$set(echo = FALSE, results = "asis")
knitr::knit_hooks$set(hook_convert_odg = rmdhelp::hook_convert_odg)

Introduction

• Proposed in 2001
• Widely adopted in 2007/2008
• Costs of breeding program reduced due to shorter generation intervals
• In cattle: young sire selection versus selection based on sire proofs
• In pigs: early selection among full sibbs
• Inbreeding must be considered

Terminology

• Genomic Selection: use of genomic Information for selection decisions
• Genomic Information is used to predict genomic breeding values

Benefits in Cattle

#rmdhelp::use_odg_graphic(ps_path = "odg/fig-benefit-geno-sel-cattle.odg")
knitr::include_graphics(path = "odg/fig-benefit-geno-sel-cattle.png")

Benefits in Pigs

#rmdhelp::use_odg_graphic(ps_path = "odg/fig-benefit-geno-sel-pig.odg")
knitr::include_graphics(path = "odg/fig-benefit-geno-sel-pig.png")

Genetic Model

• Recall: BLUP animal model is based on infinitesimal model
• Prediction of genomic breeding values is based on polygenic model
• In polygenic model: Single Nucleotide Polymorphisms (SNP) are used as markers
• Marker genotypes are expected to be associated with genotypes of Quantitative Trait Loci (QTL)

Polygenic Model

#rmdhelp::use_odg_graphic(ps_path = "odg/fig-polygenic-model.odg")
knitr::include_graphics(path = "odg/fig-polygenic-model.png")

Statistical Models

Two types of models are used

1. marker-effect models (MEM)
2. genomic-breeding-value based models (BVM)

MEM

• marker effects ($a$-values) are fitted using

  • a simple linear model $\rightarrow$ marker effects are fixed
  • a linear mixed effects model $\rightarrow$ marker effects are random

• Problem of finding which markers are associated to QTL

• With high number of SNP compared to number of genotyped animals: very large systems of equations to solve

BVM

• genomic breeding values as random effects
• similar to animal model
• genomic relationship matrix ($G$) instead of numerator relationship matrix ($A$)

MEM versus BVM

#rmdhelp::use_odg_graphic(ps_path = "odg/mem-vs-bvm.odg")
knitr::include_graphics(path = "odg/mem-vs-bvm.png")

Logistic Procedures

• Two Step:

  • use reference population to get marker effects using MEM
  • use marker effects to get to genomic breeding values

• Single Step

  • MEM or BVM in a single evaluation
  • difficulty how to combine animals with and without genotypes

Two Step Procedure

#rmdhelp::use_odg_graphic(ps_path = "odg/two-step-gs.odg")
knitr::include_graphics(path = "odg/two-step-gs.png")

charlotte-ngs/lbgfs2020 documentation built on Dec. 20, 2020, 5:39 p.m.