Genetic evaluations in dairy cattle incorporating an epigenetic source of information

The extended use of genomic selection over the last decade has doubled the rate of genetic gain in livestock populations, enabling a consistent and sustained enhancement of animal phenotypes associated with economic traits.<br/>Nowadays, not only genomic information is available, but intermediary omics features can also be obtained at an affordable price. Here, we simulated the methylation profile of 13,183 genotyped animals using the methylome pattern obtained from 6 dairy cows sequenced with Nanopore Technology. Then, a multiomic model (GOBLUP) was proposed to determine the impact of adding this epigenetic information into genomic evaluations. The heritability recovered by the GOBLUP for the methylation windows agreed to the simulated one for the different scenarios (h2 of methylation of 0.1, 0.3 and 0.8). Contrarily, the variances for milk yield retrieved by the traditional model, did not capture the effect of the methylation on the phenotype, and thus, the heritability estimate for milk yield captured part of the genetic variance from the methylation genomic windows. The traditional and epigenetic breeding values showed a Pearson correlation of 0.99. Multiomic models may provide a comprehensive decomposition of the heritability estimates by accurately differentiating genetic and epigenetic variance. This enables more informed breeding decisions, optimize selection under specific management or environments that had a differential impact in the animal epigenetics<br/>