Inferring horizontal gene transfer.

Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can there...

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Main Authors: Matt Ravenhall, Nives Škunca, Florent Lassalle, Christophe Dessimoz
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-05-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1004095
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spelling doaj-67cc5dff41b241f8bc2a3f2531befc502021-04-21T15:00:25ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-05-01115e100409510.1371/journal.pcbi.1004095Inferring horizontal gene transfer.Matt RavenhallNives ŠkuncaFlorent LassalleChristophe DessimozHorizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events.https://doi.org/10.1371/journal.pcbi.1004095
collection DOAJ
language English
format Article
sources DOAJ
author Matt Ravenhall
Nives Škunca
Florent Lassalle
Christophe Dessimoz
spellingShingle Matt Ravenhall
Nives Škunca
Florent Lassalle
Christophe Dessimoz
Inferring horizontal gene transfer.
PLoS Computational Biology
author_facet Matt Ravenhall
Nives Škunca
Florent Lassalle
Christophe Dessimoz
author_sort Matt Ravenhall
title Inferring horizontal gene transfer.
title_short Inferring horizontal gene transfer.
title_full Inferring horizontal gene transfer.
title_fullStr Inferring horizontal gene transfer.
title_full_unstemmed Inferring horizontal gene transfer.
title_sort inferring horizontal gene transfer.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2015-05-01
description Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events.
url https://doi.org/10.1371/journal.pcbi.1004095
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