Exploration and analysis of R-loop mapping data with RLBase.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
06 01 2023
06 01 2023
Historique:
accepted:
17
08
2022
received:
29
06
2022
pubmed:
31
8
2022
medline:
12
1
2023
entrez:
30
8
2022
Statut:
ppublish
Résumé
R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current R-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explore R-loop consensus regions, (iii) analyze user-supplied data and (iv) download standardized and reprocessed datasets. RLBase is directly accessible via the following URL: https://gccri.bishop-lab.uthscsa.edu/shiny/rlbase/.
Identifiants
pubmed: 36039757
pii: 6678868
doi: 10.1093/nar/gkac732
pmc: PMC9825527
doi:
Substances chimiques
DNA
9007-49-2
RNA
63231-63-0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
D1129-D1137Subventions
Organisme : NCI NIH HHS
ID : R01 CA241554
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM139549
Pays : United States
Organisme : NIA NIH HHS
ID : F31 AG072902
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA054174
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA152063
Pays : United States
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.
Références
Mol Cell. 2012 Mar 30;45(6):814-25
pubmed: 22387027
F1000Res. 2017 Jun 29;6:1025
pubmed: 28751969
Nucleic Acids Res. 2022 Jul 22;50(13):7260-7286
pubmed: 35758606
DNA Repair (Amst). 2021 Oct;106:103182
pubmed: 34303066
Bioinformatics. 2014 Apr 1;30(7):1003-5
pubmed: 24227676
Nature. 2018 Mar 15;555(7696):387-391
pubmed: 29513652
Mol Cell Oncol. 2018 May 29;5(4):e1465014
pubmed: 30250915
Nucleic Acids Res. 2019 May 7;47(8):e47
pubmed: 30783653
Genome Res. 2002 Jun;12(6):996-1006
pubmed: 12045153
Plant Cell. 2020 Apr;32(4):888-903
pubmed: 32075864
Nucleic Acids Res. 2017 Jan 4;45(D1):D119-D127
pubmed: 27899586
Cancers (Basel). 2020 Apr 11;12(4):
pubmed: 32290418
Cell Rep. 2018 May 8;23(6):1891-1905
pubmed: 29742442
Genome Res. 2013 Oct;23(10):1590-600
pubmed: 23868195
Nucleic Acids Res. 2020 Jun 4;48(10):5639-5655
pubmed: 32352519
J Biol Chem. 2020 Apr 3;295(14):4684-4695
pubmed: 32107311
Nucleic Acids Res. 2022 Jan 7;50(D1):D303-D315
pubmed: 34792163
Nat Methods. 2017 Apr;14(4):417-419
pubmed: 28263959
Nucleic Acids Res. 2015 Jul 1;43(W1):W527-34
pubmed: 25883153
Nat Rev Mol Cell Biol. 2020 Mar;21(3):167-178
pubmed: 32005969
Nature. 2020 Sep;585(7824):298-302
pubmed: 32669707