R-loopBase v2.0: species- and cell type-resolved quantitative R-loop maps and R-loop regulatory resources
4 affiliations
- 1State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Chemistry and Biomedicine Innovation Center (ChemBIC), ChemBioMed Interdisciplinary Research Center, Department of Laboratory Medicine at Nanjing Drum Tower Hospital, Nanjing University , Nanjing 210023 ,
- 2Center of Excellence for Leukemia Studies, Department of Pathology, St. Jude Children’s Research Hospital , Memphis, TN 38105 ,
- 3Nanchuang (Jiangsu) Institute of Chemistry and Health , Nanjing 210032 ,
- 4State Key Laboratory of Natural Medicines, China Pharmaceutical University , Nanjing 211198 ,
Abstract
R-loops are non-canonical nucleic acid structures implicated in diverse cellular processes and diseases. We previously developed R-loopBase to address the pressing challenges of inaccurate R-loop maps and the limited understanding of the R-loop regulatory network. However, R-loopBase provided only human R-loop maps with categorical confidence and did not account for cell type specificity. These limitations, coupled with the emerging R-loop profiling technologies and advances in R-loop regulatory mechanisms, have motivated the development of R-loopBase v2.0 (https://rloopbase.nju.edu.cn). After uniformly re-analysing 358 R-loop mapping datasets generated by 16 technologies, we introduce a quantitative R-loop scoring framework that assesses genome-wide R-loop confidence in human, demonstrating strong concordance with known R-loop biology. We further extend the framework to specific cell types and mouse, fruit fly, and yeast. In parallel, we substantially expand the collection of R-loop regulators across species, enabling the inference of changes in R-loop homeostasis. Building on these expanded datasets, we implement several new interactive features and analytical tools, including an expanded multi-species genome browser, deep learning-based R-loop prediction, R-loop homeostasis analysis, and a streamlined data download portal. We anticipate that R-loopBase v2.0 will serve as an enhanced, up-to-date one-stop resource for the R-loop research community.
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BibTeX
@article{gu2026rloopbase,
title = {{R-loopBase v2.0: species- and cell type-resolved quantitative R-loop maps and R-loop regulatory resources}},
author = {Rongchen Gu and Jiyun Hu and Yajie Gao and Hongbing Yang and Ruoyao Lin and Xiaoming Zhong and Kui-Xing Zhang and Wenjun Li and Qingxi Hu and Luojie Wei and Zetong Xing and Jia-Yu Chen},
journal = {Nucleic Acids Research},
year = {2026},
month = nov,
doi = {10.1093/nar/gkag1103},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1103/9012871},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - R-loopBase v2.0: species- and cell type-resolved quantitative R-loop maps and R-loop regulatory resources
AU - Rongchen Gu
AU - Jiyun Hu
AU - Yajie Gao
AU - Hongbing Yang
AU - Ruoyao Lin
AU - Xiaoming Zhong
AU - Kui-Xing Zhang
AU - Wenjun Li
AU - Qingxi Hu
AU - Luojie Wei
AU - Zetong Xing
AU - Jia-Yu Chen
PY - 2026
DA - 2026/11/05
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1103
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1103/9012871
AB - R-loops are non-canonical nucleic acid structures implicated in diverse cellular processes and diseases. We previously developed R-loopBase to address the pressing challenges of inaccurate R-loop maps and the limited understanding of the R-loop regulatory network. However, R-loopBase provided only human R-loop maps with categorical confidence and did not account for cell type specificity. These limitations, coupled with the emerging R-loop profiling technologies and advances in R-loop regulatory mechanisms, have motivated the development of R-loopBase v2.0 (https://rloopbase.nju.edu.cn). After uniformly re-analysing 358 R-loop mapping datasets generated by 16 technologies, we introduce a quantitative R-loop scoring framework that assesses genome-wide R-loop confidence in human, demonstrating strong concordance with known R-loop biology. We further extend the framework to specific cell types and mouse, fruit fly, and yeast. In parallel, we substantially expand the collection of R-loop regulators across species, enabling the inference of changes in R-loop homeostasis. Building on these expanded datasets, we implement several new interactive features and analytical tools, including an expanded multi-species genome browser, deep learning-based R-loop prediction, R-loop homeostasis analysis, and a streamlined data download portal. We anticipate that R-loopBase v2.0 will serve as an enhanced, up-to-date one-stop resource for the R-loop research community.
SN - 0305-1048
SN - 1362-4962
ER -