An application of Bayesian QTL mapping to early development in double haploid lines of rainbow trout including environmental effects.

Abstract

A Bayesian model and variable dimensional parameter estimation based on Markov chain Monte Carlo was applied to map quantitative trait loci (QTLs) in a doubled haploid mapping population of rainbow trout. To increase power, the analysis was performed using the multiple-QTL model, which simultaneously accounted for all the environmental and genetic main effects that influence the expression of early development life history traits. By doing so we obtained the posterior estimated effects for the environmental factors as well as the number, positions, and the effects for the QTLs. The analyses revealed QTLs for time at hatching, embryonic length and weight at swim-up stage. The posterior expectation of the number of QTLs in different linkage groups shows that at least four QTLs are needed to explain the observed differences in early development between the clonal lines. The Bayesian method effectively combined all the information available to accurately position these QTLs in the rainbow trout genome.