Exact multipoint quantitative-trait linkage analysis in pedigrees by variance components

Methods based on variance components are powerful tools for linkage analysi s of quantitative traits, because they allow simultaneous consideration of all pedigree members. The central idea is to identify loci making a signifi cant contribution to the population variance of a trait, by use of allele-s haring probabilities derived from genotyped marker loci. The technique is o nly as powerful as the methods used to infer these probabilities, but, to d ate, no implementation has made full use of the inheritance information in mapping data. Here we present a new implementation that uses an exact multi point algorithm to extract the full probability distribution of allele shar ing at every point in a mapped region. At each locus in the region, the pro gram fits a model that partitions total phenotypic variance into components due to environmental factors, a major gene at the locus, and other unlinke d genes. Numerical methods are used to derive maximum-likelihood estimates of the variance components, under the assumption of multivariate normality A likelihood-ratio test is then applied to detect any significant effect of the hypothesized major gene. Simulations show the method to have greater p ower than does traditional sib-pair analysis. The method is freely availabl e in a new release of the software package GENEHUNTER.