Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease
Name
nihms-1688845.pdf
Description
Accepted version
Size
3.14 MB
Format
Adobe PDF
Checksum (MD5)
80a2a5cd17148c173fb8e5ec5edc4bd2
Author(s)
Kellis, Manolis
Date Issued
2021
Journal
Cell
Publisher
Elsevier BV
Citation
Kellis, Manolis. 2021. "Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease." Cell, 184 (10).
Version
Author's final manuscript
Abstract
Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.CELL.2021.03.050
