Dataset Information

Detecting microsatellites within genomes: significant variation among algorithms.

ABSTRACT:

Background

Microsatellites are short, tandemly-repeated DNA sequences which are widely distributed among genomes. Their structure, role and evolution can be analyzed based on exhaustive extraction from sequenced genomes. Several dedicated algorithms have been developed for this purpose. Here, we compared the detection efficiency of five of them (TRF, Mreps, Sputnik, STAR, and RepeatMasker).

Results

Our analysis was first conducted on the human X chromosome, and microsatellite distributions were characterized by microsatellite number, length, and divergence from a pure motif. The algorithms work with user-defined parameters, and we demonstrate that the parameter values chosen can strongly influence microsatellite distributions. The five algorithms were then compared by fixing parameters settings, and the analysis was extended to three other genomes (Saccharomyces cerevisiae, Neurospora crassa and Drosophila melanogaster) spanning a wide range of size and structure. Significant differences for all characteristics of microsatellites were observed among algorithms, but not among genomes, for both perfect and imperfect microsatellites. Striking differences were detected for short microsatellites (below 20 bp), regardless of motif.

Conclusion

Since the algorithm used strongly influences empirical distributions, studies analyzing microsatellite evolution based on a comparison between empirical and theoretical size distributions should therefore be considered with caution. We also discuss why a typological definition of microsatellites limits our capacity to capture their genomic distributions.

SUBMITTER: Leclercq S

PROVIDER: S-EPMC1876248 | biostudies-literature | 2007 Apr

REPOSITORIES: biostudies-literature

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Publications

Detecting microsatellites within genomes: significant variation among algorithms.

Leclercq Sébastien S Rivals Eric E Jarne Philippe P

BMC bioinformatics 20070418

<h4>Background</h4>Microsatellites are short, tandemly-repeated DNA sequences which are widely distributed among genomes. Their structure, role and evolution can be analyzed based on exhaustive extraction from sequenced genomes. Several dedicated algorithms have been developed for this purpose. Here, we compared the detection efficiency of five of them (TRF, Mreps, Sputnik, STAR, and RepeatMasker).<h4>Results</h4>Our analysis was first conducted on the human X chromosome, and microsatellite dist ...[more]

PMID: 17442102

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Project description:BACKGROUND: The Ralstonia solanacearum species complex includes thousands of strains pathogenic to an unusually wide range of plant species. These globally dispersed and heterogeneous strains cause bacterial wilt diseases, which have major socio-economic impacts. Pathogenicity is an ancestral trait in R. solanacearum and strains with high genetic variation can be subdivided into four phylotypes, correlating to isolates from Asia (phylotype I), the Americas (phylotype IIA and IIB), Africa (phylotype III) and Indonesia (phylotype IV). Comparison of genome sequences strains representative of this phylogenetic diversity can help determine which traits allow this bacterium to be such a pathogen of so many different plant species and how the bacteria survive in many different habitats. RESULTS: The genomes of three tomato bacterial wilt pathogens, CFBP2957 (phy. IIA), CMR15 (phy. III) and PSI07 (phy. IV) were sequenced and manually annotated. These genomes were compared with those of three previously sequenced R. solanacearum strains: GMI1000 (tomato, phy. I), IPO1609 (potato, phy. IIB), and Molk2 (banana, phy. IIB). The major genomic features (size, G+C content, number of genes) were conserved across all of the six sequenced strains. Despite relatively high genetic distances (calculated from average nucleotide identity) and many genomic rearrangements, more than 60% of the genes of the megaplasmid and 70% of those on the chromosome are syntenic. The three new genomic sequences revealed the presence of several previously unknown traits, probably acquired by horizontal transfers, within the genomes of R. solanacearum, including a type IV secretion system, a rhi-type anti-mitotic toxin and two small plasmids. Genes involved in virulence appear to be evolving at a faster rate than the genome as a whole. CONCLUSIONS: Comparative analysis of genome sequences and gene content confirmed the differentiation of R. solanacearum species complex strains into four phylotypes. Genetic distances between strains, in conjunction with CGH analysis of a larger set of strains, revealed differences great enough to consider reclassification of the R. solanacearum species complex into three species. The data are still too fragmentary to link genomic classification and phenotypes, but these new genome sequences identify a pan-genome more representative of the diversity in the R. solanancearum species complex.

Dataset Information

Detecting microsatellites within genomes: significant variation among algorithms.

Background

Results

Conclusion

Publications

Detecting microsatellites within genomes: significant variation among algorithms.

Similar Datasets

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