Linking Genomic and Phenotypic Variation in Cattle Using Intermediate Phenotypes

Identification of causal mutations which affect complex traits in cattle, especially those affecting key traits in dairy and beef production, could improve accuracy of genomic estimated breeding values, particularly across breeds and with greater persistency of accuracy across time.  Identification of these causal mutations would also provide insights into the biology underlying such traits.  A significant proportion of the genomic variation in cattle, for Bos Taurus breeds at least, has been identified.  The 1000 bull genomes project now includes whole genome sequences from 1682 cattle of 55 breeds, from which 67.3 million variants (64.8 million SNP, 2.5 million indel) have been identified.  Some progress has also been made in identifying structural variants from these genomes.  The challenge is now to determine which variants affect complex traits.  This challenge is magnified by the fact that the size of effects of causal mutations are likely to be small, given the large number of mutations typically affecting complex traits.  One strategy for identifying such causal mutations is to use intermediate phenotypes, such as gene expression and protein abundance, where mutation effect is much larger than on the complex trait phenotype, Several examples identifying potential causal mutations affecting protein content of milk from dairy cattle are given.  The results highlight the need for better annotation of the bovine genome – many of the most significant mutations are in poorly annotated genomic regions, likely regions regulating gene expression.   The functional annotation of animal genomes (FAANG) consortium will greatly improve this situation.