dc.contributor.author
Seiler, Enrico
dc.contributor.author
Trappe, Kathrin
dc.contributor.author
Renard, Bernhard Y.
dc.date.accessioned
2019-09-03T07:28:43Z
dc.date.available
2019-09-03T07:28:43Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/25409
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-4113
dc.description.abstract
Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data.
en
dc.format.extent
26 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
gene transfer
en
dc.subject
metagenomic analysis tools
en
dc.subject
horizontal gene transfer
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.subject.ddc
000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::000 Informatik, Informationswissenschaft, allgemeine Werke
dc.title
Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e1007208
dcterms.bibliographicCitation.doi
10.1371/journal. pcbi.1007208
dcterms.bibliographicCitation.journaltitle
PLoS Computational Biology
dcterms.bibliographicCitation.number
7
dcterms.bibliographicCitation.volume
15
dcterms.bibliographicCitation.url
https://doi.org/10.1371/journal. pcbi.1007208
refubium.affiliation
Mathematik und Informatik
refubium.affiliation.other
Institut für Informatik

refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
1553-734X
dcterms.isPartOf.eissn
1553-7358
refubium.resourceType.provider
WoS-Alert