The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.
Cell
; 186(7): 1493-1511.e40, 2023 03 30.
Article
en En
| MEDLINE
| ID: mdl-37001506
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 1,635 open-access datasets from four donors (â¼30 tissues × â¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Sitios de Carácter Cuantitativo
/
Epigenoma
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Cell
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos