Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

Abstract

Summary: Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

Keywords

• deep learning
• functional conservation
• human
• pig
• complex trait
• gene expression