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RecGraph: recombination-aware alignment of sequences to variation graphs.

Jorge Avila Cartes1, Paola Bonizzoni1, Simone Ciccolella1

  • 1Department of Informatics, Systems and Communication, University of Milano - Bicocca. Viale Sarca 336, Milano 20126, Italy.

Bioinformatics (Oxford, England)
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Summary
This summary is machine-generated.

This study introduces RecGraph, a novel computational tool for bacterial sequence alignment that accounts for homologous recombination. RecGraph accurately aligns recombinant bacterial sequences, improving genomic analysis.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Bacterial genomes exhibit high variability and mosaic structures due to homologous recombination, challenging standard linear alignment tools.
  • Existing pangenomic approaches represent species variability but lack explicit methods for sequence-to-graph alignment that capture recombination events.

Purpose of the Study:

  • To extend sequence-to-graph alignment to variation graphs incorporating recombination.
  • To develop and implement a dynamic programming approach for aligning sequences with at most one recombination event.

Main Methods:

  • Introduced a novel sequence-to-graph alignment concept for variation graphs with recombination.
  • Developed RecGraph, a dynamic programming algorithm for sequences with at most one recombination.
  • Modeled recombination as a new path in the variation graph formed by combining existing paths.

Main Results:

  • RecGraph accurately aligns simulated recombinant bacterial sequences with a single recombination event.
  • The method provides evidence for the presence of recombination events in bacterial genomes.
  • Demonstrated the utility of sequence-to-graph alignment in capturing complex genomic variations.

Conclusions:

  • RecGraph offers an accurate method for aligning bacterial sequences with recombination.
  • The developed approach enhances the analysis of bacterial genome variability and evolution.
  • Sequence-to-graph alignment is a promising direction for understanding mosaic genome structures.