| Literature DB >> 33499903 |
Alvaro N Barbeira1, Rodrigo Bonazzola1, Eric R Gamazon2,3,4,5, Yanyu Liang1, YoSon Park6,7, Sarah Kim-Hellmuth8,9,10, Gao Wang11, Zhuoxun Jiang1, Dan Zhou2, Farhad Hormozdiari12,13, Boxiang Liu14, Abhiram Rao14, Andrew R Hamel12,15, Milton D Pividori1, François Aguet12, Lisa Bastarache16,17, Daniel M Jordan18,19,20, Marie Verbanck18,19,20,21, Ron Do18,19,20, Matthew Stephens11, Kristin Ardlie12, Mark McCarthy22, Stephen B Montgomery23,24, Ayellet V Segrè12,15, Christopher D Brown6, Tuuli Lappalainen9,10, Xiaoquan Wen25, Hae Kyung Im26.
Abstract
The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.Entities:
Mesh：
Year: 2021 PMID： 33499903 PMCID： PMC7836161 DOI： 10.1186/s13059-020-02252-4
Source DB: PubMed Journal: Genome Biol ISSN： 1474-7596 Impact factor: 17.906