ADVANCES IN STATISTICAL-METHODS TO MAP QUANTITATIVE TRAIT LOCI IN OUTBRED POPULATIONS

Statistical methods to map quantitative trait loci (QTL) in outbred po pulations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identi fied. Simple and computationally inexpensive methods include (multiple ) linear regression of phenotype on marker genotypes and repression of squared phenotypic differences among relative pairs on estimated prop ortions of identity-by-descent at a locus. These methods are less suit ed for genetic parameter estimation in outbred populations but allow t he determination of test statistic distributions via simulation or dat a permutation; however, further inferences including confidence interv als of QTL location require the use of Monte Carlo or bootstrap sampli ng techniques. A method which is intermediate in computational require ments is residual maximum likelihood (REML) with a covariance matrix o f random QTL effects conditional on information from multiple linked m arkers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the d istribution of multilocus marker-QTL genotypes on a pedigree and permi t investigators to fit different models of variation at the QTL. The B ayesian analysis includes the number of QTLs on a chromosome as an unk nown.