Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes.
Xiang G., He X., Giardine BM., Weaver KJ., Taylor DJ., McCoy RC., Jansen C., Keller CA., Wixom AQ., Cockburn A., Miller A., Qi Q., He Y., Li Y., Lichtenberg J., Heuston EF., Anderson SM., Luan J., Vermunt MW., Yue F., Sauria MEG., Schatz MC., Taylor J., Göttgens B., Hughes JR., Higgs DR., Weiss MJ., Cheng Y., Blobel GA., Bodine D., Zhang Y., Li Q., Mahony S., Hardison RC.
Knowledge of locations and activities of cis -regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult across species. In contrast, we conducted a cross-species study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable across species. This study used integrative modeling of eight epigenetic features jointly in human and mouse in our V al i dated S ystematic I ntegrati on (VISION) Project. The contribution of each epigenetic state in cCREs to gene regulation was estimated from a multivariate regression against gene expression across cell types. We used these values to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which are useful for visualizing and categorizing dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar across species. Genetic variants associated with blood cell phenotypes were highly and specifically enriched in the catalog of human VISION cCREs, supporting its utility for understanding impacts of noncoding genetic variants on blood cell-related traits. A cross-species comparison of cCREs, based on the joint modeling, revealed both conserved and lineage-specific patterns of epigenetic evolution, even in the absence of genomic sequence alignment. We provide these resources through tools and browsers at http://usevision.org .