The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models
Joel Rozowsky, Jiahao Gao, Beatrice Borsari, Yucheng T. Yang, Timur Galeev, Gamze Gürsoy, Charles B. Epstein, Kun Xiong, Jinrui Xu, Tianxiao Li, Jason Liu, Keyang Yu, Ana Berthel, Zhanlin Chen, Fabio Navarro, Maxwell S. Sun, James Wright, Justin Chang, Christopher J.F. Cameron, Noam Shoresh, Elizabeth Gaskell, Jorg Drenkow, Jessika Adrian, Sergey Aganezov, Francois Aguet, Gabriela Balderrama-Gutierrez, Samridhi Banskota, Guillermo Barreto Corona, Sora Chee, Surya B. Chhetri, Gabriel Conte Cortez Martins, Cassidy Danyko, Carrie A. Davis, Daniel Farid, Nina P. Farrell, Idan Gabdank, Yoel Gofin, David U. Gorkin, Mengting Gu, Vivian Hecht, Benjamin C. Hitz, Robbyn Issner, Yunzhe Jiang, Melanie Kirsche, Xiangmeng Kong, Bonita R. Lam, Shantao Li, Bian Li, Xiqi Li, Khine Zin Lin, Ruibang Luo, Mark Mackiewicz, Ran Meng, Jill E. Moore, Jonathan Mudge, Nicholas Nelson, Chad Nusbaum, Ioann Popov, Henry E. Pratt, Yunjiang Qiu, Srividya Ramakrishnan, Joe Raymond, Leonidas Salichos, Alexandra Scavelli, Jacob M. Schreiber, Fritz J. Sedlazeck, Lei Hoon See, Rachel M. Sherman, Xu Shi, Minyi Shi, Cricket Alicia Sloan, J Seth Strattan, Zhen Tan, Forrest Y. Tanaka, Anna Vlasova, Jun Wang, Jonathan Werner, Brian Williams, Min Xu, Chengfei Yan, Lu Yu, Christopher Zaleski, Jing Zhang, Kristin Ardlie, J Michael Cherry, Eric M. Mendenhall, William S. Noble, Zhiping Weng, Morgan E. Levine, Alexander Dobin, Barbara Wold, Ali Mortazavi, Bing Ren, Jesse Gillis, Richard M. Myers, Michael P. Snyder, Jyoti Choudhary, Aleksandar Milosavljevic, Michael C. Schatz, Bradley E. Bernstein, Roderic Guigó, Thomas R. Gingeras, and Mark Gerstein.
- Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for ∼25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.