Detection and use of single gene effects in large animal populations

Unbiased estimation of single gene effects can only be achieved by estimating them simultaneously with other environmental and polygenic effects. As in large animal populations the vast majority of animals are however not genotyped, missing genotypes have to be estimated. Currently used methods are unpractical for large datasets. Recently an alternative method to estimate missing gene content, defined as the number of copies of a particular allele was developed. Unknown gene content is approximated from known genotypes based on the additive relationships between animals. This method was tested for the detection of candidate gene effects for bovine transmembrane GHR on first lactation milk, fat and protein test-day yields in Holsteins where 961 mostly recent sires out of 2,755,041 animals were genotyped. The GHR gene was estimated to show moderate to small effects of 295 g/day for milk, -8.14 g/day for fat yield and-1.83 g/day for protein yield (phenylalanine replaced by tyrosine, frequency 23.3%. The accuracy of the procedure was estimated by doing 15 simulations using gene dropping and adjustment of the observed 12,858,741 records using the estimated values. The new method proved functional and accurate as relative bias in the estimation of allele frequency was very low (0.2%) as were the bases for moderate effects (milk %; 3.3%). Bias was larger for small effect on protein (55.3%).