2003/07/22 by Ina Hoeschele · 2 citations
Biochemistry, Genetics and Molecular Biology · Agricultural and Biological Sciences · #Genetic Mapping and Diversity in Plants and Animals #Genetic and phenotypic traits in livestock #Genetics and Plant Breeding
paper · doi:10.1002/0470022620.bbc17
openalex publication_date 2003/07/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/05/21
Abstract In this chapter, we present statistical methods for mapping quantitative trait loci (QTLs) in outbred or complex pedigrees. Such pedigrees exist primarily in livestock populations, also in human populations, and occasionally in experimental animal or plant populations. The main focus of this chapter is on linkage mapping, but methods for linkage disequilibrium (LD) and combined linkage/LD mapping are also outlined. The latter are very recent proposals and are at the time of writing less developed than linkage methods. We describe least‐squares and maximum likelihood (ML) methods for estimating QTL effects, and variance components analysis by approximate (residual) ML for estimating QTL variance contributions. We describe Bayesian QTL mapping, its prior distributions and other distributional assumptions, its implementation via Markov chain Monte Carlo (MCMC) algorithms, its inferences, and contrast it with frequentist methodology. Genotype sampling algorithms using genotypic peeling, allelic peeling, or descent graphs are described. Genotype samplers are a critical component of MCMC algorithms implementing ML and Bayesian analyses for complex pedigrees. Lastly, fine‐mapping methods including chromosome dissection and linkage disequilibrium mapping using current and historical recombinations, respectively, are outlined, and initial method developments combining linkage disequilibrium and linkage are presented.