Mapping multiple linked quantitative trait loci in non-obese diabetic mice using a stepwise regression strategy

Abstract

A simple regression strategy for mapping multiple linked quantitative trait loci (QTLs) in inbred populations is proposed and applied to data from a non-obese diabetic (NOD) mouse backcross. The method involves adding and deleting markers from a linear model in a stepwise manner, allowing the association with a particular marker to be examined once associations with other (in particular neighbouring) markers have been taken into account. This approach has the advantage of using programs available in standard statistical packages while still allowing adequate separation of possible multiple linked effects. For the mouse backcross, using these methods, at least two and possibly three diabetogenic loci are detected on each of chromosomes 1 and 3. Some evidence for epistasis is seen between the loci on chromosome 1, with a possible additional epistatic interaction between the loci on chromosome 3. Congenic strain analysis of the chromosome regions in NOD diabetes suggests that although the true type I error rate may be larger than that suggested by the nominal P values, our results nevertheless correspond well with those disease loci and interactions detected using a congenic approach, indicating that the regression method may be a powerful strategy for the detection and characterization of QTLs in inbred populations.