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  Alignment-free detection of local similarity among viral and bacterial genomes

Domazet-Lošo, M., & Haubold, B. (2011). Alignment-free detection of local similarity among viral and bacterial genomes. Bioinformatics, 27(11), 1466-1472. doi:10.1093/bioinformatics/btr176.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-D3B7-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-D3B8-8
Genre: Journal Article

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Domazet-Lose_2011.pdf (Publisher version), 436KB
 
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Domazet-Lošo, Mirjana1, Author              
Haubold, Bernhard1, Author              
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1Research Group Bioinformatics, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society, escidoc:1445644              

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 Abstract: Motivation: Bacterial and viral genomes are often affected by horizontal gene transfer observable as abrupt switching in local homology. In addition to the resulting mosaic genome structure, they frequently contain regions not found in close relatives, which may play a role in virulence mechanisms. Due to this connection to medical microbiology, there are numerous methods available to detect horizontal gene transfer. However, these are usually aimed at individual genes and viral genomes rather than the much larger bacterial genomes. Here, we propose an efficient alignment-free approach to describe the mosaic structure of viral and bacterial genomes, including their unique regions. Results: Our method is based on the lengths of exact matches between pairs of sequences. Long matches indicate close homology, short matches more distant homology or none at all. These exact match lengths can be looked up efficiently using an enhanced suffix array. Our program implementing this approach, alfy (ALignment-Free local homologY), efficiently and accurately detects the recombination break points in simulated DNA sequences and among recombinant HIV-1 strains. We also apply alfy to Escherichia coli genomes where we detect new evidence for the hypothesis that strains pathogenic in poultry can infect humans.

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Language(s): eng - English
 Dates: 2011-06-01
 Publication Status: Published in print
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 Identifiers: eDoc: 564941
DOI: 10.1093/bioinformatics/btr176
Other: 2840/S 39183
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Title: Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 27 (11) Sequence Number: - Start / End Page: 1466 - 1472 Identifier: ISSN: 1367-4803 (print)
ISSN: 0266-706 (print)
ISSN: 1367-4811 (online)
ISSN: 1460-2059 (online)