Exact p-values for large-scale single step genome-wide association, with an application for birth weight in American Angus

BACKGROUND: Single Step GBLUP (SSGBLUP) is the most comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for Genome Wide Association Studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for GWAS studies in the ssGBLUP framework, showing algorithms, computational procedures, and an application to a large beef cattle population. METHODS: P-values were obtained based on the prediction error (co)variance for SNP, which uses the inverse of the coefficient matrix and formulas to compute SNP effects. RESULTS: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation was observed. The SNP passing the Bonferroni threshold of 5.9 in the -log10 scale were the same as those that explained the highest proportion of additive genetic variance, but the latter was penalized (as GWAS signal) by low allele frequency. CONCLUSION: The exact p-value for SSGWAS is a very general and efficient strategy for QTL detection and testing. It can be used in complex data sets such as used in animal breeding, where only a proportion of pedigreed animals are genotyped.