tRFtarget: a database for transfer RNA-derived fragment targets.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
08 01 2021
Historique:
accepted: 17 09 2020
revised: 10 09 2020
received: 15 08 2020
pubmed: 10 10 2020
medline: 21 1 2021
entrez: 9 10 2020
Statut: ppublish

Résumé

Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs and play important roles in biological and physiological processes. Prediction of tRF target genes and binding sites is crucial in understanding the biological functions of tRFs in the molecular mechanisms of human diseases. We developed a publicly accessible web-based database, tRFtarget (http://trftarget.net), for tRF target prediction. It contains the computationally predicted interactions between tRFs and mRNA transcripts using the two state-of-the-art prediction tools RNAhybrid and IntaRNA, including location of the binding sites on the target, the binding region, and free energy of the binding stability with graphic illustration. tRFtarget covers 936 tRFs and 135 thousand predicted targets in eight species. It allows researchers to search either target genes by tRF IDs or tRFs by gene symbols/transcript names. We also integrated the manually curated experimental evidence of the predicted interactions into the database. Furthermore, we provided a convenient link to the DAVID® web server to perform downstream functional pathway analysis and gene ontology annotation on the predicted target genes. This database provides useful information for the scientific community to experimentally validate tRF target genes and facilitate the investigation of the molecular functions and mechanisms of tRFs.

Identifiants

pubmed: 33035346
pii: 5920434
doi: 10.1093/nar/gkaa831
pmc: PMC7779015
doi:

Substances chimiques

RNA, Messenger 0
RNA, Small Untranslated 0
RNA, Transfer 9014-25-9

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

D254-D260

Subventions

Organisme : NIAAA NIH HHS
ID : K01 AA023321
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States
Organisme : National Science Foundation
ID : DMS1916246
Pays : International
Organisme : National Science Foundation
ID : ACI-1548562
Pays : International

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Auteurs

Ningshan Li (N)

SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.

Nayang Shan (N)

Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.
Center for Statistical Science, Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.

Lingeng Lu (L)

Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT 06520, USA.

Zuoheng Wang (Z)

SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.

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Classifications MeSH