Accounting for overlapping annotations as biological priors in genomic prediction models of complex traits

It is now widespread in farm animal and plant breeding to use genotyping data to predict phenotypes with genomic prediction models. Functional genomic annotations (e.g., the accessibility of chromatin or methylation status in relevant tissues), have the potential to provide valuable insight into the location and effect size of causal genetic variants underlying complex traits. Developing and validating genomic prediction models able to fully leverage such complex functional annotations for improved accuracy and interpretability was one of the aims of the H2020 GENE-SWitCH project. To this end, we defined and implemented a flexible framework for genomic prediction called BayesRCO to simultaneously take advantage of the availability of multiple functional genomic annotations. In this talk, I’ll describe the intuition behind our proposed model and discuss some of our key take-away messages from early results.

October 13, 2023

9:30 AM – 10:10 AM

Edinburgh, UK