Transcriptome and genome interaction data of brain tissues from eight canines to understand the role of non-coding mutations during rapid adaptation of dogs
Evolutionary studies have aimed to unravel the genomic architecture of domestication by employing genomic and gene expression data to detect regions under selection. Some of those regions are located within exons, but most are potential regulatory mutations, whose biological significance often cannot properly be determined, leaving much of the phenotypic diversity unexplained. In this study we used the dog as a model system to investigate the significance of the cis-regulatory networks during early dog domestication. We performed RNA-seq and targeted chromosome conformation capture of the prefrontal cortex and hypothalamus in four Mongrel dogs and four wolves. We find 1282 differentially expressed genes between wolves and dogs, whose functions were enriched for processes relevant for neural function, in particular abnormal learning and synapse formation. To understand whether enhancer usage per promoter differed across the canines, we compared their enhancer-promoter interactions. Indeed, we find 727 genes that were interacting with different enhancers between wolves and dogs. These differentially interacting genes were enriched for neurodevelopmental functions and diseases. Our data reveals that human-mediated artificial selection has led to extensive cis-regulatory network changes, mediated by alternate enhancer usage in dogs and we provide evidence that they facilitate man's best friend's ability to respond differently to internal and external stimuli, shaping their genomic foundation for tameness, sociability and reduced fear upon changing the regulatory logic of the genes while maintaining steady-state levels of expression which is under strong selection. We also find that while differentially expressed genes tend be older, differentially interacting genes were enriched for younger genes. Our study illustrates, that illuminating the enhancer-promoter interaction network in combination with expression profiles is a powerful strategy to better capture the involvement of regulatory mutations in adaption phenotypes and discover genes and pathways involved in specific phenotypes. We further propose, that alternate enhancer usage is a wide-spread molecular mechanism for mammals to facilitate rapid adaptation in natural settings while assuring steady-state expression levels for genes.