Genome wide association studies (GWASs) commonly used to search for genetic variants associated with
quantitative traits. Pleiotropic effect of genes may cause the observed correlations among different phenotypes. This study proposed a
two stage multilocus model for pleiotropic GWAS using a Bayesian mixture model to take into account of both small and major gene
effects. The objectives of this study were to investigate if the two-stage model was useful for detecting pleiotropic genes using a
simulated data set and to investigate existence of pleiotropic genes for testis weight and testis gene expression levels in house mouse.
The analyses included relative testis weight and testis gene expression traits. The results showed that two stage model had higher power
to detect the pleiotropic QTL than the single marker model. It was also noted the possible economical impact of sampling informative
individuals for the GWAS analyses by observing genomic trends in the simulated dataset. Two stage model detected 50 and 53 major
SNP effects using first and the second principal components. Additive genetic variation explained by chromosome X was found to be
4% for the testis weight.
Primary Language | English |
---|---|
Subjects | Veterinary Surgery |
Journal Section | Research Article |
Authors | |
Publication Date | November 9, 2018 |
Published in Issue | Year 2018Volume: 65 Issue: 4 |