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Title: R-loopDB: a database for R-loop forming sequences (RLFS) and R-loops
Authors: Jenjaroenpun, Piroon
Wongsurawat, Thidathip
Sutheeworapong, Sawannee
Kuznetsov, Vladimir A.
Keywords: Chromosomes
Issue Date: 2016
Source: Jenjaroenpun, P., Wongsurawat, T., Sutheeworapong, S., & Kuznetsov, V. A. (2017). R-loopDB: a database for R-loop forming sequences (RLFS) and R-loops. Nucleic Acids Research, 45(D1), D119-D127.
Series/Report no.: Nucleic Acids Research
Abstract: R-loopDB ( was originally constructed as a collection of computationally predicted R-loop forming sequences (RLFSs) in the human genic regions. The renewed R-loopDB provides updates, improvements and new options, including access to recent experimental data. It includes genome-scale prediction of RLFSs for humans, six other animals and yeast. Using the extended quantitative model of RLFSs (QmRLFS), we significantly increased the number of RLFSs predicted in the human genes and identified RLFSs in other organism genomes. R-loopDB allows searching of RLFSs in the genes and in the 2 kb upstream and downstream flanking sequences of any gene. R-loopDB exploits the Ensembl gene annotation system, providing users with chromosome coordinates, sequences, gene and genomic data of the 1 565 795 RLFSs distributed in 121 056 genic or proximal gene regions of the covered organisms. It provides a comprehensive annotation of Ensembl RLFS-positive genes including 93 454 protein coding genes, 12 480 long non-coding RNA and 7 568 small non-coding RNA genes and 7 554 pseudogenes. Using new interface and genome viewers of R-loopDB, users can search the gene(s) in multiple species with keywords in a single query. R-loopDB provides tools to carry out comparative evolution and genome-scale analyses in R-loop biology.
ISSN: 0305-1048
DOI: 10.1093/nar/gkw1054
Schools: School of Computer Science and Engineering 
Rights: © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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