Mutant alleles (MAs) that have been classically recognised have large effects on phenotype and tend to be deleterious to traits and fitness. Is this the case for mutations with small effects? We infer MAs for 8 million sequence variants in 113k cattle and quantify the effects of MA on 37 complex traits. Heterozygosity for variants at genomic sites conserved across 100 vertebrate species increase fertility, stature, and milk production, positively associating these traits with fitness. MAs decrease stature and fat and protein concentration in milk, but increase gestation length and somatic cell count in milk (the latter indicative of mastitis). However, the frequency of MAs decreasing stature and fat and protein concentration, increasing gestation length and somatic cell count were lower than the frequency of MAs with the opposite effect. These results suggest bias in the mutations direction of effect (e.g. towards reduced protein in milk), but selection operating to reduce the frequency of these MAs. Taken together, our results imply two classes of genomic sites subject to long-term selection: sites conserved across vertebrates show hybrid vigour while sites subject to less long-term selection show a bias in mutation towards undesirable alleles.

Context Functional genomics studies have highlighted genomic regions with regulatory and evolutionary significance. Such information independent of association analysis may benefit fine-mapping and genomic selection of economically important traits. However, systematic evaluation of the use of functional information in mapping, and genomic selection of cattle traits, is lacking. Also, single-nucleotide polymorphisms (SNPs) from the high-density (HD) panel are known to tag informative variants, but the performance of genomic prediction using HD SNPs together with variants supported by different functional genomics is unknown. Aims We selected six sets of functionally important variants and modelled each set together with HD SNPs in Bayesian models to map and predict protein, fat and milk yield as well as mastitis, somatic cell count and temperament of dairy cattle. Methods Two models were used, namely (1) BayesR, which includes priors of four distribution of variant effects, and (2) BayesRC, which includes additional priors of different functional classes of variants. Bayesian models were trained in three breeds of 28 000 cows of Holstein, Jersey and Australian Red and predicted into 2600 independent bulls. Key results Adding functionally important variants significantly increased the enrichment of genetic variance explained for mapped variants, suggesting improved genome-wide mapping precision. Such improvement was significantly higher when the same set of variants was modelled by BayesRC than by BayesR. Combining functional variant sets with HD SNPs improves genomic prediction accuracy in the majority of the cases and such improvement was more common and stronger for non-Holstein breeds and traits such as mastitis, somatic cell count and temperament. In contrast, adding a large number of random sequence variants to HD SNPs reduces mapping precision and has a worse or similar prediction accuracy, compared with using HD SNPs alone to map or predict. While BayesRC tended to have better genomic prediction accuracy than did BayesR, the overall difference in prediction accuracy between the two models was insignificant. Conclusions Our findings demonstrated the usefulness of functional data in genomic mapping and prediction. Implications We have highlighted the need for effective tools exploiting complex functional datasets to improve genomic prediction.

Classical mutations tend to be deleterious to traits and fitness. Is this the case for mutations with polygenic effects? Here, we infer ancestral and mutant alleles (MAs) for 8 million sequence variants in 113k cattle and quantify the effects of MA on 37 complex traits. Heterozygosity at sites conserved across 100 vertebrates increase fertility, stature, and milk production, positively associating these traits with fitness. MAs decrease fat and protein concentration in milk and stature but increase gestation length and somatic cell count in milk indicative of mastitis. However, the frequency of MAs that decrease fat and protein concentration and stature and increase gestation length and somatic cell count is lower than the frequency of MAs with the opposite effect. These results suggest bias in the direction of effect of mutation (e.g. towards reduced protein in milk), but selection operating to reduce the frequency of these MAs. MAs with a large-effect decrease protein and milk yield, while small-effect MAs increase the two traits. These results imply two classes of genomic sites subject to long-term selection: sites conserved across vertebrates show hybrid vigour while sites subject to less long-term selection show a bias in mutation towards alleles that are selected against.