PrimerSNP: a web tool for whole-genome selection of allele-specific and common primers of phylogenetically-related bacterial genomic sequences

<p>Abstract</p> <p>Background</p> <p>The increasing number of genomic sequences of bacteria makes it possible to select unique SNPs of a particular strain/species at the whole genome level and thus design specific primers based on the SNPs. The high similarity of genomi...

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Bibliographic Details
Main Authors: Lemos Eliana, Francis Martha, Doddapaneni Harshavardhan, Lin Hong, Van Deynze Allen, Yao Jiqiang, Civerolo Edwin L
Format: Article
Language:English
Published: BMC 2008-10-01
Series:BMC Microbiology
Online Access:http://www.biomedcentral.com/1471-2180/8/185
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Summary:<p>Abstract</p> <p>Background</p> <p>The increasing number of genomic sequences of bacteria makes it possible to select unique SNPs of a particular strain/species at the whole genome level and thus design specific primers based on the SNPs. The high similarity of genomic sequences among phylogenetically-related bacteria requires the identification of the few loci in the genome that can serve as unique markers for strain differentiation. PrimerSNP attempts to identify reliable strain-specific markers, on which specific primers are designed for pathogen detection purpose.</p> <p>Results</p> <p>PrimerSNP is an online tool to design primers based on strain specific SNPs for multiple strains/species of microorganisms at the whole genome level. The allele-specific primers could distinguish query sequences of one strain from other homologous sequences by standard PCR reaction. Additionally, PrimerSNP provides a feature for designing common primers that can amplify all the homologous sequences of multiple strains/species of microorganisms. PrimerSNP is freely available at <url>http://cropdisease.ars.usda.gov/~primer</url>.</p> <p>Conclusion</p> <p>PrimerSNP is a high-throughput specific primer generation tool for the differentiation of phylogenetically-related strains/species. Experimental validation showed that this software had a successful prediction rate of 80.4 – 100% for strain specific primer design.</p>
ISSN:1471-2180