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Indirect identification of horizontal gene transfer
Several implicit methods to infer horizontal gene transfer (HGT) focus on pairs of genes that have diverged only after the divergence of the two species in which the genes reside. This situation defines the edge set of a graph, the later-divergence-time (LDT) graph, whose vertices correspond to gene...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254804/ https://www.ncbi.nlm.nih.gov/pubmed/34218334 http://dx.doi.org/10.1007/s00285-021-01631-0 |
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author | Schaller, David Lafond, Manuel Stadler, Peter F. Wieseke, Nicolas Hellmuth, Marc |
author_facet | Schaller, David Lafond, Manuel Stadler, Peter F. Wieseke, Nicolas Hellmuth, Marc |
author_sort | Schaller, David |
collection | PubMed |
description | Several implicit methods to infer horizontal gene transfer (HGT) focus on pairs of genes that have diverged only after the divergence of the two species in which the genes reside. This situation defines the edge set of a graph, the later-divergence-time (LDT) graph, whose vertices correspond to genes colored by their species. We investigate these graphs in the setting of relaxed scenarios, i.e., evolutionary scenarios that encompass all commonly used variants of duplication-transfer-loss scenarios in the literature. We characterize LDT graphs as a subclass of properly vertex-colored cographs, and provide a polynomial-time recognition algorithm as well as an algorithm to construct a relaxed scenario that explains a given LDT. An edge in an LDT graph implies that the two corresponding genes are separated by at least one HGT event. The converse is not true, however. We show that the complete xenology relation is described by an rs-Fitch graph, i.e., a complete multipartite graph satisfying constraints on the vertex coloring. This class of vertex-colored graphs is also recognizable in polynomial time. We finally address the question “how much information about all HGT events is contained in LDT graphs” with the help of simulations of evolutionary scenarios with a wide range of duplication, loss, and HGT events. In particular, we show that a simple greedy graph editing scheme can be used to efficiently detect HGT events that are implicitly contained in LDT graphs. |
format | Online Article Text |
id | pubmed-8254804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82548042021-07-20 Indirect identification of horizontal gene transfer Schaller, David Lafond, Manuel Stadler, Peter F. Wieseke, Nicolas Hellmuth, Marc J Math Biol Article Several implicit methods to infer horizontal gene transfer (HGT) focus on pairs of genes that have diverged only after the divergence of the two species in which the genes reside. This situation defines the edge set of a graph, the later-divergence-time (LDT) graph, whose vertices correspond to genes colored by their species. We investigate these graphs in the setting of relaxed scenarios, i.e., evolutionary scenarios that encompass all commonly used variants of duplication-transfer-loss scenarios in the literature. We characterize LDT graphs as a subclass of properly vertex-colored cographs, and provide a polynomial-time recognition algorithm as well as an algorithm to construct a relaxed scenario that explains a given LDT. An edge in an LDT graph implies that the two corresponding genes are separated by at least one HGT event. The converse is not true, however. We show that the complete xenology relation is described by an rs-Fitch graph, i.e., a complete multipartite graph satisfying constraints on the vertex coloring. This class of vertex-colored graphs is also recognizable in polynomial time. We finally address the question “how much information about all HGT events is contained in LDT graphs” with the help of simulations of evolutionary scenarios with a wide range of duplication, loss, and HGT events. In particular, we show that a simple greedy graph editing scheme can be used to efficiently detect HGT events that are implicitly contained in LDT graphs. Springer Berlin Heidelberg 2021-07-03 2021 /pmc/articles/PMC8254804/ /pubmed/34218334 http://dx.doi.org/10.1007/s00285-021-01631-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Schaller, David Lafond, Manuel Stadler, Peter F. Wieseke, Nicolas Hellmuth, Marc Indirect identification of horizontal gene transfer |
title | Indirect identification of horizontal gene transfer |
title_full | Indirect identification of horizontal gene transfer |
title_fullStr | Indirect identification of horizontal gene transfer |
title_full_unstemmed | Indirect identification of horizontal gene transfer |
title_short | Indirect identification of horizontal gene transfer |
title_sort | indirect identification of horizontal gene transfer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254804/ https://www.ncbi.nlm.nih.gov/pubmed/34218334 http://dx.doi.org/10.1007/s00285-021-01631-0 |
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