A holistic view of mouse enhancer architectures reveals analogous pleiotropic effects and correlation with human disease.
Author
Sethi, SiddharthVorontsov, Ilya E
Kulakovskiy, Ivan V
Greenaway, Simon
Williams, John
Makeev, Vsevolod J
Brown, Steve D M
Simon, Michelle M
Mallon, Ann-Marie
Publication date
2020-11-02Subject
Genetics
Metadata
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Background: Efforts to elucidate the function of enhancers in vivo are underway but their vast numbers alongside differing enhancer architectures make it difficult to determine their impact on gene activity. By systematically annotating multiple mouse tissues with super- and typical-enhancers, we have explored their relationship with gene function and phenotype. Results: Though super-enhancers drive high total- and tissue-specific expression of their associated genes, we find that typical-enhancers also contribute heavily to the tissue-specific expression landscape on account of their large numbers in the genome. Unexpectedly, we demonstrate that both enhancer types are preferentially associated with relevant 'tissue-type' phenotypes and exhibit no difference in phenotype effect size or pleiotropy. Modelling regulatory data alongside molecular data, we built a predictive model to infer gene-phenotype associations and use this model to predict potentially novel disease-associated genes. Conclusion: Overall our findings reveal that differing enhancer architectures have a similar impact on mammalian phenotypes whilst harbouring differing cellular and expression effects. Together, our results systematically characterise enhancers with predicted phenotypic traits endorsing the role for both types of enhancers in human disease and disorders.Citation
Sethi S, Vorontsov IE, Kulakovskiy IV, Greenaway S, Williams J, Makeev VJ, Brown SDM, Simon MM, Mallon AM. A holistic view of mouse enhancer architectures reveals analogous pleiotropic effects and correlation with human disease. BMC Genomics. 2020 Nov 2;21(1):754. doi: 10.1186/s12864-020-07109-5Type
ArticleAdditional Links
https://bmcgenomics.biomedcentral.com/PMID
33138777Journal
BMC GenomicsPublisher
BioMed Centralae974a485f413a2113503eed53cd6c53
10.1186/s12864-020-07109-5