Multi-tissue integrative analysis of personal epigenomes

Rozowsky, J.; Drenkow, J.; Yang, Y.; Gursoy, G.; Galeev, T.; Borsari, B.; Epstein, C.; Xiong, K.; Xu, J.; Gao, J.; Yu, K.; Berthel, A.; Chen, Z.; Navarro, F.; Liu, J.; Sun, M.; Wright, J.; Chang, J.; Cameron, C.; Shoresh, N.; Gaskell, E.; Adrian, J.; Aganezov, S.; Balderrama-Gutierrez, G.; Banskota, S.; Corona, G.; Chee, S.; Chhetri, S.; Martins, G.; Danyko, C.; Davis, C.; Farid, D.; Farrell, N.; Gabdank, I.; Gofin, Y.; Gorkin, D.; Gu, M.; Hecht, V.; Hitz, B.; Issner, R.; Kirsche, M.; Kong, X.; Lam, B.; Li, S.; Li, B.; Li, T.; Li, X.; Lin, K.; Luo, R.; Mackiewicz, M.; Moore, J.; Mudge, J.; Nel

doi:10.1101/2021.04.26.441442

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bioRxiv · 10.1101/2021.04.26.441442

Multi-tissue integrative analysis of personal epigenomes

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Abstract

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.

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Rozowsky, J., Drenkow, J., Yang, Y., Gursoy, G., Galeev, T., Borsari, B., Epstein, C., Xiong, K., Xu, J., Gao, J., Yu, K., Berthel, A., Chen, Z., Navarro, F., Liu, J., Sun, M., Wright, J., Chang, J., Cameron, C., Shoresh, N., Gaskell, E., Adrian, J., Aganezov, S., Balderrama-Gutierrez, G., Banskota, S., Corona, G., Chee, S., Chhetri, S., Martins, G., Danyko, C., Davis, C., Farid, D., Farrell, N., Gabdank, I., Gofin, Y., Gorkin, D., Gu, M., Hecht, V., Hitz, B., Issner, R., Kirsche, M., Kong, X., Lam, B., Li, S., Li, B., Li, T., Li, X., Lin, K., Luo, R., Mackiewicz, M., Moore, J., Mudge, J., Nel. 2021-04-26. Multi-tissue integrative analysis of personal epigenomes. https://doi.org/10.1101/2021.04.26.441442

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