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Indirect identification of horizontal gene transfer.
Schaller, David; Lafond, Manuel; Stadler, Peter F; Wieseke, Nicolas; Hellmuth, Marc.
Afiliación
  • Schaller D; Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04109, Leipzig, Germany.
  • Lafond M; Bioinformatics Group, Department of Computer Science, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.
  • Stadler PF; Interdisciplinary Center of Bioinformatics, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.
  • Wieseke N; Department of Computer Science, Université de Sherbrooke, 2500 boul. de l'Université, Sherbrooke, QC, J1K 2R1, Canada.
  • Hellmuth M; Bioinformatics Group, Department of Computer Science, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.
J Math Biol ; 83(1): 10, 2021 07 03.
Article en En | MEDLINE | ID: mdl-34218334
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Transferencia de Gen Horizontal Tipo de estudio: Diagnostic_studies Idioma: En Revista: J Math Biol Año: 2021 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Transferencia de Gen Horizontal Tipo de estudio: Diagnostic_studies Idioma: En Revista: J Math Biol Año: 2021 Tipo del documento: Article País de afiliación: Alemania