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Identification of compositionally distinct regions in genomes using the centroid method
Issaac Rajan1, Sarang Aravamuthan, Sharmila S Mande
1Life Sciences Research, Advanced Technology Centre, Tata Consultancy Services, Hyderabad 500 081, Andhra Pradesh, India.
Bioinformatics (Oxford, England)
|August 29, 2007
Summary
The centroid approach identifies distinct genomic regions by analyzing m-mer compositions. This method successfully detected embedded sequences and revealed genes related to pathogenicity islands in bacterial genomes.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Genomic regions of interest, such as horizontally acquired sequences and genomic islands, exhibit distinct word (m-mer) compositions.
- Previous studies primarily focused on di- and tri-nucleotide compositions for analyzing these regions.
Purpose of the Study:
- To introduce a novel computational method, the centroid approach, for analyzing genomic sequence composition.
- To enable the analysis of composition for any given word (m-mer) size.
Main Methods:
- The centroid approach was developed to identify compositionally distinct regions within genomic sequences.
- The method was applied to analyze the m-mer composition of genomic data.
Main Results:
- The centroid approach was successfully applied to 50 bacterial genomes, identifying embedded sequences of varying lengths from diverse organisms.
- Analysis of distinct regions in four selected organisms revealed frequent presence of pathogenicity island (PAI) components and genes encoding strain-specific proteins.
Conclusions:
- The centroid approach is effective in detecting compositionally distinct genomic regions across various word sizes.
- The identified regions are often associated with horizontally acquired elements like pathogenicity islands and strain-specific genes, offering insights into genome evolution and function.
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