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Detecting gene breakpoints in noisy genome sequences using position-annotated colored de-Bruijn graphs.

Lisa Fiedler1, Matthias Bernt2, Martin Middendorf3

  • 1Department of Computer Science, University Leipzig, Augustusplatz 10-11, 04109, Leipzig, Germany. lfiedler@informatik.uni-leipzig.de.

BMC Bioinformatics
|June 5, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces DeBBI, a new method for finding gene breakpoints in mitochondrial DNA sequences, even with high variation. DeBBI accurately detects evolutionary breakpoints, improving analysis of mitochondrial genome evolution.

Keywords:
Gene breakpointsGenomeMitochondriade-Bruijn graph

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Identifying gene breakpoints aids understanding evolutionary processes.
  • Mitochondrial genomes present challenges due to high variation in gene order and sequence inconsistencies.
  • Accurate breakpoint detection in nucleotide sequences is difficult with erroneous annotations or missing gene locations.

Purpose of the Study:

  • To present a novel method for detecting gene breakpoints in mitochondrial genome nucleotide sequences.
  • To develop a software package, DeBBI, for analyzing transposition- and inversion-based breakpoints.
  • To address challenges posed by high substitution rates and sequence inconsistencies.

Main Methods:

  • Developed the DeBBI software package utilizing a novel breakpoint detection method.
  • Employed a parallel program design for efficient analysis on multi-processor systems.
  • Constructed a position-annotated de-Bruijn graph and used a heuristic algorithm to find breakpoint-associated structures (bulges).

Main Results:

  • DeBBI demonstrates accurate results on synthetic datasets with varying sequence dissimilarities and breakpoint numbers.
  • Case studies confirm DeBBI's applicability to real-world data across diverse taxonomic groups.
  • DeBBI shows improved detection of gene breaks, particularly between short, poorly conserved tRNA genes, compared to some alignment tools.

Conclusions:

  • The proposed method effectively identifies gene breakpoints in mitochondrial nucleotide sequences.
  • DeBBI offers a robust and accurate approach for analyzing mitochondrial genome evolution.
  • The de-Bruijn graph and heuristic algorithm provide an efficient means to locate breakpoints.