Basic Concepts of Linkage Analysis

Abstract

The goal of linkage analysis in human disease gene mapping is to assess whether an observed genetic marker locus is physically linked to the disease locus. This is equivalent to testing the null-hypothesis that the recombination fraction between the marker locus and the disease locus, θ, equals ½. In this case, we say the marker locus and the disease locus are unlinked. It is also possible to estimate θ, which can be used to provide an approximate idea of the location of the DSL relative to observed markers. In this chapter, we discuss the basic concepts of parametric linkage analysis. We explain how linkage between two genetic loci can be utilized to construct long-range mapping approaches that require only a small number of marker loci per chromosome to cover the entire human genome sufficiently. Using fully parameterized statistical models, parametric linkage describes the phenotype as a function of the genetic marker locus and its relative distance to the disease locus, i.e., the recombination fraction (Ott (1999)). The simplest case of parametric linkage analysis uses the method of direct counting, where θ can be estimated by directly counting recombinant and non-recombinant offspring haplotypes (Ott (1979)). Using the method of direct-counting, we outline the principles of parametric linkage analysis. Advanced topics such as non-parametric linkage analysis and multi-point analysis (Kruglyak et al. (1996)) are discussed in Appendix A. While the advanced topics that are included in Appendix A are necessary for a thorough grounding in linkage analysis, they are not required for an introduction to association analysis.