Gen Htr : a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing
Abstract Background: Microevolution is the study of short-term changes of alleles within a population and their effects on the phenotype of organisms. The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural varia...
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description | Abstract Background: Microevolution is the study of short-term changes of alleles within a population and their effects on the phenotype of organisms. The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural variations. Heterogeneity analysis is thus essential to our understanding of how selective and neutral forces shape bacterial populations over a short period of time. The Solexa Genome Analyzer, a next-generation sequencing platform, allows millions of short sequencing reads to be obtained with great accuracy, allowing for the ability to study the dynamics of the bacterial population at the whole genome level. The tool referred to as GenHtr was developed for genome-wide heterogeneity analysis. Results: For particular bacterial strains, GenHtr relies on a set of Solexa short reads on given bacteria pathogens and their isogenic reference genome to identify heterogeneity sites, the chromosomal positions with multiple variants of genes in the bacterial population, and variations that occur in large gene families. GenHtr accomplishes this by building and comparatively analyzing genome-wide heterogeneity genotypes for both the newly sequenced genomes (using massive short-read sequencing) and their isogenic reference (using simulated data). As proof of the concept, this approach was applied to SRX007711, the Solexa sequencing data for a newly sequenced Staphylococcus aureus subsp. USA300 cell line, and demonstrated that it could predict such multiple variants. They include multiple variants of genes critical in pathogenesis, e.g. genes encoding a LysR family transcriptional regulator, 23 S ribosomal RNA, and DNA mismatch repair protein MutS. The heterogeneity results in non-synonymous and nonsense mutations, leading to truncated proteins for both LysR and MutS. Conclusion: GenHtr was developed for genome-wide heterogeneity analysis. Although it is much more time-consuming when compared to Maq, a popular tool for SNP analysis, GenHtr is able to predict potential multiple variants that pre-exist in the bacterial population as well as SNPs that occur in the highly duplicated gene families. It is expected that, with the proper experimental design, this analysis can improve our understanding of the molecular mechanism underlying the dynamics and the evolution of drug-resistant bacterial pathogens. |
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The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural variations. Heterogeneity analysis is thus essential to our understanding of how selective and neutral forces shape bacterial populations over a short period of time. The Solexa Genome Analyzer, a next-generation sequencing platform, allows millions of short sequencing reads to be obtained with great accuracy, allowing for the ability to study the dynamics of the bacterial population at the whole genome level. The tool referred to as GenHtr was developed for genome-wide heterogeneity analysis. Results: For particular bacterial strains, GenHtr relies on a set of Solexa short reads on given bacteria pathogens and their isogenic reference genome to identify heterogeneity sites, the chromosomal positions with multiple variants of genes in the bacterial population, and variations that occur in large gene families. GenHtr accomplishes this by building and comparatively analyzing genome-wide heterogeneity genotypes for both the newly sequenced genomes (using massive short-read sequencing) and their isogenic reference (using simulated data). As proof of the concept, this approach was applied to SRX007711, the Solexa sequencing data for a newly sequenced Staphylococcus aureus subsp. USA300 cell line, and demonstrated that it could predict such multiple variants. They include multiple variants of genes critical in pathogenesis, e.g. genes encoding a LysR family transcriptional regulator, 23 S ribosomal RNA, and DNA mismatch repair protein MutS. The heterogeneity results in non-synonymous and nonsense mutations, leading to truncated proteins for both LysR and MutS. Conclusion: GenHtr was developed for genome-wide heterogeneity analysis. Although it is much more time-consuming when compared to Maq, a popular tool for SNP analysis, GenHtr is able to predict potential multiple variants that pre-exist in the bacterial population as well as SNPs that occur in the highly duplicated gene families. It is expected that, with the proper experimental design, this analysis can improve our understanding of the molecular mechanism underlying the dynamics and the evolution of drug-resistant bacterial pathogens.</description><identifier>ISSN: 1471-2105</identifier><identifier>EISSN: 1471-2105</identifier><identifier>DOI: 10.1186/1471-2105-11-508</identifier><language>eng</language><publisher>London: BioMed Central</publisher><subject>Bacteria ; Drug resistance ; Experimental design ; Genes ; Genotypes ; Heterogeneity ; Microbiology ; Pathogens ; Streptococcus infections ; Subpopulations</subject><ispartof>BMC bioinformatics, 2010-10, Vol.11 (1), p.508, Article 508</ispartof><rights>2010 Yu; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1578-88adb7789fb6204799c98fa0baecd21f79834ff4213c3b78aeb29352d885a7d3</citedby><cites>FETCH-LOGICAL-c1578-88adb7789fb6204799c98fa0baecd21f79834ff4213c3b78aeb29352d885a7d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27903,27904</link.rule.ids></links><search><creatorcontrib>Yu, GongXin</creatorcontrib><title>Gen Htr : a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing</title><title>BMC bioinformatics</title><description>Abstract Background: Microevolution is the study of short-term changes of alleles within a population and their effects on the phenotype of organisms. The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural variations. Heterogeneity analysis is thus essential to our understanding of how selective and neutral forces shape bacterial populations over a short period of time. The Solexa Genome Analyzer, a next-generation sequencing platform, allows millions of short sequencing reads to be obtained with great accuracy, allowing for the ability to study the dynamics of the bacterial population at the whole genome level. The tool referred to as GenHtr was developed for genome-wide heterogeneity analysis. Results: For particular bacterial strains, GenHtr relies on a set of Solexa short reads on given bacteria pathogens and their isogenic reference genome to identify heterogeneity sites, the chromosomal positions with multiple variants of genes in the bacterial population, and variations that occur in large gene families. GenHtr accomplishes this by building and comparatively analyzing genome-wide heterogeneity genotypes for both the newly sequenced genomes (using massive short-read sequencing) and their isogenic reference (using simulated data). As proof of the concept, this approach was applied to SRX007711, the Solexa sequencing data for a newly sequenced Staphylococcus aureus subsp. USA300 cell line, and demonstrated that it could predict such multiple variants. They include multiple variants of genes critical in pathogenesis, e.g. genes encoding a LysR family transcriptional regulator, 23 S ribosomal RNA, and DNA mismatch repair protein MutS. The heterogeneity results in non-synonymous and nonsense mutations, leading to truncated proteins for both LysR and MutS. Conclusion: GenHtr was developed for genome-wide heterogeneity analysis. Although it is much more time-consuming when compared to Maq, a popular tool for SNP analysis, GenHtr is able to predict potential multiple variants that pre-exist in the bacterial population as well as SNPs that occur in the highly duplicated gene families. It is expected that, with the proper experimental design, this analysis can improve our understanding of the molecular mechanism underlying the dynamics and the evolution of drug-resistant bacterial pathogens.</description><subject>Bacteria</subject><subject>Drug resistance</subject><subject>Experimental design</subject><subject>Genes</subject><subject>Genotypes</subject><subject>Heterogeneity</subject><subject>Microbiology</subject><subject>Pathogens</subject><subject>Streptococcus 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Htr : a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing</title><author>Yu, GongXin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1578-88adb7789fb6204799c98fa0baecd21f79834ff4213c3b78aeb29352d885a7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Bacteria</topic><topic>Drug resistance</topic><topic>Experimental design</topic><topic>Genes</topic><topic>Genotypes</topic><topic>Heterogeneity</topic><topic>Microbiology</topic><topic>Pathogens</topic><topic>Streptococcus infections</topic><topic>Subpopulations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, GongXin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Computer and 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, GongXin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gen Htr : a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing</atitle><jtitle>BMC bioinformatics</jtitle><date>2010-10-12</date><risdate>2010</risdate><volume>11</volume><issue>1</issue><spage>508</spage><pages>508-</pages><artnum>508</artnum><issn>1471-2105</issn><eissn>1471-2105</eissn><abstract>Abstract Background: Microevolution is the study of short-term changes of alleles within a population and their effects on the phenotype of organisms. The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural variations. Heterogeneity analysis is thus essential to our understanding of how selective and neutral forces shape bacterial populations over a short period of time. The Solexa Genome Analyzer, a next-generation sequencing platform, allows millions of short sequencing reads to be obtained with great accuracy, allowing for the ability to study the dynamics of the bacterial population at the whole genome level. The tool referred to as GenHtr was developed for genome-wide heterogeneity analysis. Results: For particular bacterial strains, GenHtr relies on a set of Solexa short reads on given bacteria pathogens and their isogenic reference genome to identify heterogeneity sites, the chromosomal positions with multiple variants of genes in the bacterial population, and variations that occur in large gene families. GenHtr accomplishes this by building and comparatively analyzing genome-wide heterogeneity genotypes for both the newly sequenced genomes (using massive short-read sequencing) and their isogenic reference (using simulated data). As proof of the concept, this approach was applied to SRX007711, the Solexa sequencing data for a newly sequenced Staphylococcus aureus subsp. USA300 cell line, and demonstrated that it could predict such multiple variants. They include multiple variants of genes critical in pathogenesis, e.g. genes encoding a LysR family transcriptional regulator, 23 S ribosomal RNA, and DNA mismatch repair protein MutS. The heterogeneity results in non-synonymous and nonsense mutations, leading to truncated proteins for both LysR and MutS. Conclusion: GenHtr was developed for genome-wide heterogeneity analysis. Although it is much more time-consuming when compared to Maq, a popular tool for SNP analysis, GenHtr is able to predict potential multiple variants that pre-exist in the bacterial population as well as SNPs that occur in the highly duplicated gene families. It is expected that, with the proper experimental design, this analysis can improve our understanding of the molecular mechanism underlying the dynamics and the evolution of drug-resistant bacterial pathogens.</abstract><cop>London</cop><pub>BioMed Central</pub><doi>10.1186/1471-2105-11-508</doi><oa>free_for_read</oa></addata></record> |
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subjects | Bacteria Drug resistance Experimental design Genes Genotypes Heterogeneity Microbiology Pathogens Streptococcus infections Subpopulations |
title | Gen Htr : a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing |
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