DASHR 2.0: integrated database of human small non-coding RNA genes and mature products.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
15 03 2019
Historique:
received: 27 10 2017
revised: 31 05 2018
accepted: 20 08 2018
pubmed: 23 1 2019
medline: 1 1 2020
entrez: 23 1 2019
Statut: ppublish

Résumé

Small non-coding RNAs (sncRNAs, <100 nts) are highly abundant RNAs that regulate diverse and often tissue-specific cellular processes by associating with transcription factor complexes or binding to mRNAs. While thousands of sncRNA genes exist in the human genome, no single resource provides searchable, unified annotation, expression and processing information for full sncRNA transcripts and mature RNA products derived from these larger RNAs. Our goal is to establish a complete catalog of annotation, expression, processing, conservation, tissue-specificity and other biological features for all human sncRNA genes and mature products derived from all major RNA classes. DASHR (Database of small human non-coding RNAs) v2.0 database is the first that integrates human sncRNA gene and mature products profiles obtained from multiple RNA-seq protocols. Altogether, 185 tissues/cell types and sncRNA annotations and >800 curated experiments from ENCODE and GEO/SRA across multiple RNA-seq protocols for both GRCh38/hg38 and GRCh37/hg19 assemblies are integrated in DASHR. Moreover, DASHR is the first to contain both known and novel, previously un-annotated sncRNA loci identified by unsupervised segmentation (13 times more loci with 1 678 800 total). Additionally, DASHR v2.0 adds >3 200 000 annotations for non-small RNA genes and other genomic features (long-noncoding RNAs, mRNAs, promoters, repeats). Furthermore, DASHR v2.0 introduces an enhanced user interface, interactive experiment-by-locus table view, sncRNA locus sorting and filtering by biological features. All annotation and expression information directly downloadable and accessible as UCSC genome browser tracks. DASHR v2.0 is freely available at https://lisanwanglab.org/DASHRv2. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 30668832
pii: 5078466
doi: 10.1093/bioinformatics/bty709
pmc: PMC6419920
doi:

Substances chimiques

RNA, Long Noncoding 0
RNA, Small Untranslated 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1033-1039

Subventions

Organisme : NIA NIH HHS
ID : U54 AG052427
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM099962
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG032984
Pays : United States
Organisme : NIA NIH HHS
ID : T32 AG000255
Pays : United States
Organisme : NIA NIH HHS
ID : UF1 AG047133
Pays : United States
Organisme : NIA NIH HHS
ID : U24 AG041689
Pays : United States

Informations de copyright

© The Author(s) 2018. Published by Oxford University Press.

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Auteurs

Pavel P Kuksa (PP)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.

Alexandre Amlie-Wolf (A)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.
Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Živadin Katanić (Ž)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.

Otto Valladares (O)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.

Li-San Wang (LS)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.
Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Yuk Yee Leung (YY)

Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine.

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Classifications MeSH