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

Margherita Maria Ferrari1, Svetlana Poznanović2, Manda Riehl3

  • 1Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada.

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|August 29, 2025
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Summary
This summary is machine-generated.

This study introduces a novel R-loop grammar to predict R-loop formation, a key nucleic acid structure involved in gene regulation and disease. The grammar accurately forecasts R-loop occurrences, even without explicit topological data.

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Area of Science:

  • Molecular Biology
  • Genetics
  • Bioinformatics

Background:

  • R-loops are three-stranded nucleic acid structures formed during transcription.
  • They play critical roles in gene expression regulation.
  • R-loop formation is influenced by DNA sequence and topology, but mechanisms remain unclear.

Purpose of the Study:

  • To develop a predictive model for R-loop formation.
  • To represent R-loops using formal grammar.
  • To investigate the influence of DNA topology on R-loop prediction.

Main Methods:

  • Development of the R-loop grammar.
  • Training the grammar on experimental data from single-molecule R-loop footprinting and sequencing (SMRF-seq).
  • Testing predictive accuracy on plasmids with varying topologies.

Main Results:

  • The R-loop grammar accurately predicts R-loop formation.
  • The model performs well even without explicit topological information.
  • The R-loop grammar outperforms previous prediction methods.

Conclusions:

  • A formal grammar can effectively model and predict R-loop formation.
  • This approach offers a new tool for studying R-loop dynamics.
  • The R-loop grammar has implications for understanding gene regulation and disease pathogenesis.