The R-loop grammar predicts R-loop formation under different topological constraints

R-loops are transient three-stranded nucleic acids that form during transcription when the nascent RNA hybridizes with the template DNA, freeing the non-template strand of the DNA. There is growing evidence that R-loops play important roles in physiological processes such as the regulation of gene expression, and that they contribute to chromosomal instability and disease. It is known that R-loop formation is influenced by both the sequence and the topology of the DNA substrate, but many questions remain about how R-loops form and the three-dimensional structures that they adopt. Here we represent an R-loop as a word in a formal grammar, the R-loop grammar. We use the R-loop grammar to predict R-loop formation. We train the R-loop grammar on experimental data obtained by single-molecule R-loop footprinting and sequencing (SMRF-seq). Despite not explicitly encoding topological information, the R-loop grammar accurately predicts R-loop formation on plasmids with varying starting topologies and outperforms previous methods in R-loop prediction.

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Publication Details

Journal
PLoS Computational Biology
Published
2025-08-29
DOI
https://doi.org/10.1371/journal.pcbi.1013376
Citations
1
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.81

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The R-loop grammar predicts R-loop formation under different topological constraints

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The R-loop grammar predicts R-loop formation under different topological constraints

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article en
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Abstract

R-loops are transient three-stranded nucleic acids that form during transcription when the nascent RNA hybridizes with the template DNA, freeing the non-template strand of the DNA. There is growing evidence that R-loops play important roles in physiological processes such as the regulation of gene expression, and that they contribute to chromosomal instability and disease. It is known that R-loop formation is influenced by both the sequence and the topology of the DNA substrate, but many questions remain about how R-loops form and the three-dimensional structures that they adopt. Here we represent an R-loop as a word in a formal grammar, the R-loop grammar. We use the R-loop grammar to predict R-loop formation. We train the R-loop grammar on experimental data obtained by single-molecule R-loop footprinting and sequencing (SMRF-seq). Despite not explicitly encoding topological information, the R-loop grammar accurately predicts R-loop formation on plasmids with varying starting topologies and outperforms previous methods in R-loop prediction.

PLoS Computational BiologyVol. 21(8)
Rose–Hulman Institute of Technology (US), University of South Florida (US), University of Manitoba (CA), Clemson University (US), University of California, Davis (US)
National Science Foundation, W. M. Keck Foundation, Simons Foundation, Association for Women in Mathematics, University of Manitoba, National Institutes of Health, Directorate for Computer and Information Science and Engineering, Directorate for Mathematical and Physical Sciences, Natural Sciences and Engineering Research Council of Canada, National Institute of General Medical Sciences
Openalex Percentile: Top 24%
RNA and protein synthesis mechanisms
0.81
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