Biallelic non-productive enhancer-promoter interactions precede imprinted expression of Kcnk9 during mouse neural commitment

It is only partially understood how constitutive allelic methylation at imprinting control regions (ICRs) interacts with other regulation levels to drive timely parental allele-specific expression along large imprinted domains. The Peg13-Kcnk9 domain is an imprinted domain with important brain functions. To gain insights into its regulation during neural commitment, we performed an integrative analysis of its allele-specific epigenetic, transcriptomic, and cis-spatial organization using a mouse stem cell-based corticogenesis model that recapitulates the control of imprinted gene expression during neurodevelopment. We found that, despite an allelic higher-order chromatin structure associated with the paternally CTCF-bound Peg13 ICR, enhancer-Kcnk9 promoter contacts occurred on both alleles, although they were productive only on the maternal allele. This observation challenges the canonical model in which CTCF binding isolates the enhancer and its target gene on either side and suggests a more nuanced role for allelic CTCF binding at some ICRs.

Genome-wide prediction of functional gene-gene interactions inferred from patterns of genetic differentiation in mice and men

The human genome encodes a limited number of genes yet contributes to individual differences in a vast array of heritable traits. A possible explanation for the capacity our genome to generate this virtually unlimited range of phenotypic variation in complex traits is to assume functional interactions between genes. Therefore we searched two mammalian genomes to identify potential epistatic interactions by looking for co-adapted genes marked by excess two-locus genetic differentiation between populations/lineages using publicly available SNP genotype data. The practical motivation for this effort is to reduce the number of pair-wise tests that need to be performed in genome-wide association studies aimed at detecting G×G interactions, by focusing on pairs predicted to be more likely to jointly affect variation in complex traits. Hence, this approach generates a list of candidate interactions that can be empirically tested. In both the mouse and human data we observed two-locus genetic differentiation in excess of what can be expected from chance alone based on simulations. In an attempt to validate our hypothesis that pairs of genes showing excess genetic divergence represent potential functional interactions, we selected a small set of gene combinations postulated to be interacting based on our analyses and looked for a combined effect of the selected genes on variation in complex traits in both mice and man. In both cases the individual effect of the genes were not significant, instead we observed marginally significant interaction effects. These results show that genome wide searches for gene-gene interactions based on population genetic data are feasible and can generate interesting candidate gene pairs to be further tested for their contribution to phenotypic variation in complex traits.