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

Content Provider	Springer Nature : BioMed Central
Author	Fiedler, Lisa Bernt, Matthias Middendorf, Martin Stadler, Peter F.
Abstract	Background Identifying the locations of gene breakpoints between species of different taxonomic groups can provide useful insights into the underlying evolutionary processes. Given the exact locations of their genes, the breakpoints can be computed without much effort. However, often, existing gene annotations are erroneous, or only nucleotide sequences are available. Especially in mitochondrial genomes, high variations in gene orders are usually accompanied by a high degree of sequence inconsistencies. This makes accurately locating breakpoints in mitogenomic nucleotide sequences a challenging task. Results This contribution presents a novel method for detecting gene breakpoints in the nucleotide sequences of complete mitochondrial genomes, taking into account possible high substitution rates. The method is implemented in the software package DeBBI. DeBBI allows to analyze transposition- and inversion-based breakpoints independently and uses a parallel program design, allowing to make use of modern multi-processor systems. Extensive tests on synthetic data sets, covering a broad range of sequence dissimilarities and different numbers of introduced breakpoints, demonstrate DeBBI ’s ability to produce accurate results. Case studies using species of various taxonomic groups further show DeBBI ’s applicability to real-life data. While (some) multiple sequence alignment tools can also be used for the task at hand, we demonstrate that especially gene breaks between short, poorly conserved tRNA genes can be detected more frequently with the proposed approach. Conclusion The proposed method constructs a position-annotated de-Bruijn graph of the input sequences. Using a heuristic algorithm, this graph is searched for particular structures, called bulges, which may be associated with the breakpoint locations. Despite the large size of these structures, the algorithm only requires a small number of graph traversal steps.
Related Links	https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-023-05371-4.pdf
Ending Page	29
Page Count	29
Starting Page	1
File Format	HTM / HTML
ISSN	14712105
DOI	10.1186/s12859-023-05371-4
Journal	BMC Bioinformatics
Issue Number	1
Volume Number	24
Language	English
Publisher	BioMed Central
Publisher Date	2023-06-05
Access Restriction	Open
Subject Keyword	Bioinformatics Microarrays Computational Biology Computer Appl. in Life Sciences Algorithms Gene breakpoints de-Bruijn graph Genome Mitochondria Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biochemistry Computer Science Applications Applied Mathematics Structural Biology
Journal Impact Factor	2.9/2023
5-Year Journal Impact Factor	3.6/2023

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