Year: 2019
Type: preprint
Abstract: Long non-coding RNA (lncRNA) genes are known to have diverse impacts on gene regulation. However, it is still a major challenge to distinguish functional lncRNAs from those that are byproducts of surrounding transcriptional activity. To systematically identify hallmarks of biological function, we used the GTEx v8 data to profile the expression, regulation, network relationships and trait associations of lncRNA genes across 49 tissues encompassing 87 distinct traits. In addition to revealing widespread differences in regulatory patterns between lncRNA and protein-coding genes, we identified novel disease-associated lncRNAs, such as C6orf3 for psoriasis and LINC01475 / RP11-129J12.1 for ulcerative colitis. This work provides a comprehensive resource to interrogate lncRNA genes of interest and annotate cell type and human trait relevance. One Sentence Summary lncRNA genes have distinctive regulatory patterns and unique trait associations compared to protein-coding genes.
DOI: 10.1101/793091
Institutions: Stanford University, Stanford Medicine, Broad Institute, University of Chicago, New York Genome Center, Columbia University, Max Planck Society, Max Planck Institute of Psychiatry, University of Pennsylvania, Washington University in St. Louis, Johns Hopkins University, University of Michigan, Stanford Cardiovascular Institute
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, National Institutes of Health, School of Medicine, Stanford University, Horizon 2020 Framework Programme, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Institute on Drug Abuse, National Human Genome Research Institute, NIH Office of the Director, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, Common Fund
Awards: Methods for high-resolution analysis of genetic effects on gene expression, Identification and validation of cell specific eQTLs by Bayesian modeling, Predicted Gene Expression: High Power, Mechanism, and Direction of Effect, Integrative analysis of genetic variation and transcription factor networks to elucidate mechanisms of mental health disorders, New York Center for Collaborative Research in Common Disease Genomics, Integration of omics data to improve interpretation of genetic risk variants in lung disease, Decoding the regulatory architecture of the human genome across cell types, individuals and disease, G4478373029, G4715193760, G5097752872, Mechanism of the Coronary Heart Disease Association at Chromosome 6q23.2, Predicting causal non-coding variants in a founder population, Single-nucleotide resolution mapping of allelic protein-RNA interactions and splicing-regulatory variants, G6944544953, Integrative multi-omics in whole genome studies of HLBS disorders, Regulatory modifiers of coding variant penetrance via haplotype epistasis in human populations and diseases, Identification of causal coronary heart disease variation in smooth muscle cells, G7859997503, G7871733508, Center for Multi- and Trans-ethnic Mapping of Mendelian and Complex Diseases, 3/3 Building integrative CNS networks for genomic analysis of autism, Network-based algorithms for target identification and drug repositioning from genetic associations, G8858395165, A portal and integrative collaborative analysis platform for GTEx, Causal variant association mechanisms in TCF21 binding coronary disease loci, The SMAD3 signaling network in coronary artery disease risk, Diabetes Research and Training Center
OpenAlex ID: W2979238127