Back to Search Start Over

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models

Authors :
Joel Rozowsky
Jorg Drenkow
Yucheng T Yang
Gamze Gursoy
Timur Galeev
Beatrice Borsari
Charles B Epstein
Kun Xiong
Jinrui Xu
Jiahao Gao
Keyang Yu
Ana Berthel
Zhanlin Chen
Fabio Navarro
Jason Liu
Maxwell S Sun
James Wright
Justin Chang
Christopher JF Cameron
Noam Shoresh
Elizabeth Gaskell
Jessika Adrian
Sergey Aganezov
François 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
Melanie Kirsche
Xiangmeng Kong
Bonita R Lam
Shantao Li
Bian Li
Tianxiao Li
Xiqi Li
Khine Zin Lin
Ruibang Luo
Mark Mackiewicz
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
Roderic Guigó
Bradley E Bernstein
Thomas R Gingeras
Mark Gerstein
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

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.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........f293c3be99001dfcca0596fbe318c048