Phenetic Comparison of Prokaryotic Genomes Using k-mers.
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Auteurs : Maxime Déraspe [Canada] ; Frédéric Raymond [Canada] ; Sébastien Boisvert [Canada] ; Alexander Culley [Canada] ; Paul H. Roy [Canada] ; François Laviolette [Canada] ; Jacques Corbeil [Canada]Source :
- Molecular biology and evolution [ 1537-1719 ] ; 2017.
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Abstract
Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets.
DOI: 10.1093/molbev/msx200
PubMed: 28957508
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Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28957508</PMID><DateCompleted><Year>2017</Year><Month>11</Month><Day>29</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1537-1719</ISSN><JournalIssue CitedMedium="Internet"><Volume>34</Volume><Issue>10</Issue><PubDate><Year>2017</Year><Month>10</Month><Day>01</Day></PubDate></JournalIssue><Title>Molecular biology and evolution</Title><ISOAbbreviation>Mol. Biol. Evol.</ISOAbbreviation></Journal><ArticleTitle>Phenetic Comparison of Prokaryotic Genomes Using k-mers.</ArticleTitle><Pagination><MedlinePgn>2716-2729</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/molbev/msx200</ELocationID><Abstract><AbstractText>Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets.</AbstractText><CopyrightInformation>© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Déraspe</LastName><ForeName>Maxime</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Centre de Recherche en Infectiologie, CHU de Québec-Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centre de Recherche en Données Massives de l'Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Département de Médecine Moléculaire, Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Raymond</LastName><ForeName>Frédéric</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Centre de Recherche en Infectiologie, CHU de Québec-Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centre de Recherche en Données Massives de l'Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Boisvert</LastName><ForeName>Sébastien</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Gydle Inc., Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Culley</LastName><ForeName>Alexander</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Département de Biochimie, Microbiologie et Bio-informatique, Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Roy</LastName><ForeName>Paul H</ForeName><Initials>PH</Initials><AffiliationInfo><Affiliation>Centre de Recherche en Infectiologie, CHU de Québec-Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Département de Biochimie, Microbiologie et Bio-informatique, Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Laviolette</LastName><ForeName>François</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Centre de Recherche en Données Massives de l'Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Département d'Informatique et de Génie Logiciel, Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Corbeil</LastName><ForeName>Jacques</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Centre de Recherche en Infectiologie, CHU de Québec-Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centre de Recherche en Données Massives de l'Université Laval, Quebec City, QC, Canada.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Département de Médecine Moléculaire, Université 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