A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events.
Identifieur interne : 000735 ( PubMed/Corpus ); précédent : 000734; suivant : 000736A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events.
Auteurs : Magali Jaillard ; Leandro Lima ; Maud Tournoud ; Pierre Mahé ; Alex Van Belkum ; Vincent Lacroix ; Laurent JacobSource :
- PLoS genetics [ 1553-7404 ] ; 2018.
English descriptors
- KwdEn :
- Computer Graphics, DNA, Bacterial (genetics), Databases, Genetic, Drug Resistance, Bacterial (genetics), Genetic Variation, Genome, Bacterial, Genome-Wide Association Study (methods), Genome-Wide Association Study (statistics & numerical data), Interspersed Repetitive Sequences, Models, Genetic, Mycobacterium tuberculosis (drug effects), Mycobacterium tuberculosis (genetics), Phenotype, Pseudomonas aeruginosa (drug effects), Pseudomonas aeruginosa (genetics), Sequence Analysis, DNA, Software, Staphylococcus aureus (drug effects), Staphylococcus aureus (genetics).
- MESH :
- chemical , genetics : DNA, Bacterial.
- drug effects : Mycobacterium tuberculosis, Pseudomonas aeruginosa, Staphylococcus aureus.
- genetics : Drug Resistance, Bacterial, Mycobacterium tuberculosis, Pseudomonas aeruginosa, Staphylococcus aureus.
- methods : Genome-Wide Association Study.
- statistics & numerical data : Genome-Wide Association Study.
- Computer Graphics, Databases, Genetic, Genetic Variation, Genome, Bacterial, Interspersed Repetitive Sequences, Models, Genetic, Phenotype, Sequence Analysis, DNA, Software.
Abstract
Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.
DOI: 10.1371/journal.pgen.1007758
PubMed: 30419019
Links to Exploration step
pubmed:30419019Le document en format XML
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<front><div type="abstract" xml:lang="en">Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.</div>
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<Abstract><AbstractText>Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.</AbstractText>
</Abstract>
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<AffiliationInfo><Affiliation>EPI ERABLE - Inria Grenoble, Rhône-Alpes, France.</Affiliation>
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</MeshHeading>
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</MeshHeading>
<MeshHeading><DescriptorName UI="D009169" MajorTopicYN="N">Mycobacterium tuberculosis</DescriptorName>
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<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
</MeshHeading>
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<MeshHeading><DescriptorName UI="D011550" MajorTopicYN="N">Pseudomonas aeruginosa</DescriptorName>
<QualifierName UI="Q000187" MajorTopicYN="N">drug effects</QualifierName>
<QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName>
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<MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName>
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<CoiStatement>I have read the journal’s policy and the authors of this manuscript have the following competing interests: MJ, MT, PM and AvB are employees of bioMérieux, a company that develops and sells diagnostic tests in the field of infectious diseases. However, the study was designed and executed in an open manner and the presented method as well as all data generated have been deposited in the public domain, also resulting in the current publication.</CoiStatement>
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<ReferenceList><Reference><Citation>Elife. 2018 Jun 13;7:null</Citation>
<ArticleIdList><ArticleId IdType="pubmed">29897334</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Expert Rev Mol Diagn. 2017 Mar;17(3):257-269</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28093921</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2018 Jan 4;46(D1):D851-D860</Citation>
<ArticleIdList><ArticleId IdType="pubmed">29112715</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2015 Nov 15;31(22):3691-3</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26198102</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Med. 2015 May 27;7(1):51</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26019726</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Rep. 2014 Nov 12;4:6874</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25387525</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2008 May;18(5):810-20</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18340039</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>FEMS Microbiol Lett. 1994 Jan 15;115(2-3):297-304</Citation>
<ArticleIdList><ArticleId IdType="pubmed">8138142</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2017 Jan 4;45(D1):D535-D542</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27899627</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Antimicrob Agents Chemother. 2009 Dec;53(12):4961-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19721075</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J R Soc Med. 2002;95 Suppl 41:22-6</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12216271</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2017 Jan 4;45(D1):D158-D169</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27899622</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Ann N Y Acad Sci. 2015 Sep;1354:12-31</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26190223</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2008 May;18(5):821-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18349386</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2017 Jan 4;45(D1):D574-D580</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27899569</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Microbiol Mol Biol Rev. 2010 Dec;74(4):621-41</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21119020</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2011 Mar 15;27(6):764-70</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21217122</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Clin Microbiol. 2014 Apr;52(4):1182-91</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24501024</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Commun. 2016 Sep 16;7:12797</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27633831</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>MBio. 2015 Nov 24;6(6):e01796-15</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26604259</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Genet. 2013 Oct;45(10):1255-60</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23995137</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Microbiol. 2016 Apr 04;1:16041</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27572646</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2016 Jun 15;32(12):i201-i208</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27307618</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Antimicrob Chemother. 2012 Nov;67(11):2640-4</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22782487</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2017 May;27(5):665-676</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28360232</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Gigascience. 2016 Feb 11;5:9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26870323</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Antimicrob Agents Chemother. 1995 Feb;39(2):369-73</Citation>
<ArticleIdList><ArticleId IdType="pubmed">7726500</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2017 May;27(5):835-848</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28396522</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS Genet. 2014 Aug 07;10(8):e1004547</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25101644</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Genet. 2013 Oct;45(10):1183-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23995135</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Int J Tuberc Lung Dis. 2000 May;4(5):441-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">10815738</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Int J Antimicrob Agents. 2017 Aug;50(2):210-218</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28554735</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Genet. 2012 Jan 08;44(2):226-32</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22231483</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Med. 2014 Nov 22;6(11):109</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25593593</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nucleic Acids Res. 2013 Jan;41(Database issue):D36-42</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23193287</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2016 Feb 03;11(2):e0148367</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26841043</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2014 Oct 15;30(20):2959-61</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24990603</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Methods. 2014 Apr;11(4):407-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24531419</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS Comput Biol. 2018 Feb 5;14(2):e1005958</Citation>
<ArticleIdList><ArticleId IdType="pubmed">29401456</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>FEMS Microbiol Rev. 2017 May 1;41(3):354-373</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28369307</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2009 Nov 13;4(11):e7740</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19936230</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Am J Respir Crit Care Med. 2016 Sep 1;194(5):621-30</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26910495</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Proc Natl Acad Sci U S A. 2013 Jul 16;110(29):11923-7</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23818615</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Antibiotics (Basel). 2014 Jul 02;3(3):317-40</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27025748</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet Infect Dis. 2016 Feb;16(2):161-8</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26603172</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>BMC Bioinformatics. 2014 Apr 14;15:107</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24731071</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Biol. 2016 Jun 20;17(1):132</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27323842</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Res. 2017 May;27(5):768-777</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28232478</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Proc Natl Acad Sci U S A. 2001 Aug 14;98(17):9748-53</Citation>
<ArticleIdList><ArticleId IdType="pubmed">11504945</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2010 Aug 18;5(8):e12245</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20805881</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Genome Biol Evol. 2014 Apr 30;6(5):1174-85</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24787619</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Commun. 2015 Dec 21;6:10063</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26686880</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Antimicrob Agents Chemother. 2014;58(1):212-20</Citation>
<ArticleIdList><ArticleId IdType="pubmed">24145532</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Bioinformatics. 2016 Jan 15;32(2):309-11</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26415722</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Rep. 2016 Jun 14;6:27930</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27297683</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Antimicrob Agents Chemother. 2015 Jan;59(1):427-36</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25367914</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Rev Microbiol. 2015 Jan;13(1):42-51</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25435309</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Rev Genet. 2017 Jan;18(1):41-50</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27840430</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Int J Tuberc Lung Dis. 2000 May;4(5):481-4</Citation>
<ArticleIdList><ArticleId IdType="pubmed">10815743</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>BMC Bioinformatics. 2009 Dec 15;10:421</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20003500</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Trends Microbiol. 2006 Aug;14(8):353-5</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16782339</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Rev Genet. 2006 Oct;7(10):781-91</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16983374</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PLoS One. 2011 Mar 14;6(3):e17915</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21423806</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Nat Genet. 2012 Jun 17;44(7):821-4</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22706312</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Clin Invest. 2003 May;111(9):1265-73</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12727914</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Sci Rep. 2017 Sep 12;7(1):11262</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28900144</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Int J Genomics. 2014;2014:123058</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25184130</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Zentralbl Bakteriol. 1998 May;287(4):277-314</Citation>
<ArticleIdList><ArticleId IdType="pubmed">9638861</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
</record>
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