lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Journal: Scientific data
PMID: 33020484

Abstract

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,199 human lncRNA (224,286 transcripts). The user-friendly knowledgebase covers a comprehensive breadth and depth of lncRNA annotation. lncRNAKB is a compendium of expression patterns, derived from analysis of RNA-seq data in thousands of samples across 31 solid human normal tissues (GTEx). Thousands of co-expression modules identified via network analysis and pathway enrichment to delineate lncRNA function are also accessible. Millions of expression quantitative trait loci (cis-eQTL) computed using whole genome sequence genotype data (GTEx) can be downloaded at lncRNAKB that also includes tissue-specificity, phylogenetic conservation and coding potential scores. Tissue-specific lncRNA-trait associations encompassing 323 GWAS (UK Biobank) are also provided. LncRNAKB is accessible at http://www.lncrnakb.org/ , and the data are freely available through Open Science Framework ( https://doi.org/10.17605/OSF.IO/RU4D2 ).

Authors

  • Fayaz Seifuddin
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Komudi Singh
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Abhilash Suresh
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Jennifer T Judy
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Yun-Ching Chen
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Vijender Chaitankar
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Ilker Tunc
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Xiangbo Ruan
    Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Ping Li
    Department of Gastroenterology, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
  • Yi Chen
    Department of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Haiming Cao
    Cardiovascular Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Richard S Lee
    Department of Psychiatry & Behavioral Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
  • Fernando S Goes
    Department of Psychiatry & Behavioral Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
  • Peter P Zandi
    Department of Psychiatry & Behavioral Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
  • M Saleet Jafri
    School of Systems Biology, George Mason University, Manassas, VA, 20110, USA.
  • Mehdi Pirooznia
    Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA. mehdi.pirooznia@nih.gov.

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