How can maximum likelihood methods reveal candidate gene effects on a quantitative trait?

Different maximum likelihood approaches were used to explore the role of candidate genes in the variability of quantitative trait Q1 while accounting for the effects of age, Q2, and Q3. Segregation analysis, under the class D regressive model, provides evidence for a Mendelian gene effect on the adjusted trait Q1. Results of gene mapping through lod-score analyses remain puzzling. Pairwise lod scores indicate a possible linkage with the candidate gene C5 which is excluded when using tightly linked informative marker loci. Finally, our combined segregation and linkage analysis clearly shows that a C5 linked gene is involved in Q1 variability. However, given the lod-score results within the C5 region, we postulate a more complex mechanism for Q1 than a single di-allelic C5 linked gene. The knowledge of the true model (C5 is MG1 and has three alleles) permits a partial explanation of our results. This study demonstrates the advantages of using complementary approaches to reveal the role of candidate genes in complex traits, and the value of simultaneous estimation of linkage and segregation parameters.