Admixture mapping of growth related traits in F₂ mice dataset using ancestry informative markers

Most of the associated single nucleotide polymorphisms (SNPs) for genome wide association studies (GWAS) explain very little proportion of phenotypic variance in outbred populations. One reason is; large number of markers raises the problem of multiple hypothesis testing correction using conservative statistical tests in single marker models. Admixture mapping could be used as alternative model to detect the genes associated with quantitative traits by less number of ancestry informative markers. Ancestral genotypes of founder populations were available for the F₂ mice dataset for growth related traits. The objectives of this study were (1) to detect genomic signals by admixture mapping for growth related traits by ancestry informative markers and ancestral genotypes (2) to detect genomic signals for growth related traits by Bayes C(π) model and compare results with those obtained by use of admixture mapping. Bayes C(π) model detected more SNPs that has high ancestry informative markers. But due to stringent significance tests and small SNPs effects admixture model did not detect the same SNPs in Bayes C(π). As was expected higher ancestral informative markers lead to higher Z values in admixture model with a little variation. Admixture model could incorporate and use ancestral genomic information.