Classes of explicit phylogenetic networks and their biological and mathematical significance

Kong, Sungsik; Pons, Joan Carles; Kubatko, Laura; Wicke, Kristina

doi:10.1007/s00285-022-01746-y

Cited by 34 publications

(36 citation statements)

References 127 publications

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“…As we have seen, even in the presence of ILS and GDL, a tree is a reasonable model for the evolutionary relationships between the species. However, some biological processes, such as gene flow, horizontal gene transfer and species hybridization, may require graphical models of evolution called 'explicit phylogenetic networks' [98][99][100] that are not purely tree-like. For example, in a hybridization network, a hybrid species will have two parents rather than one, while in a network representing evolutionary relationships that include HGT events, there will be two types of edges: those depicting vertical transmission and those depicting HGT events.…”

Section: Discussionmentioning

confidence: 99%

Recent progress on methods for estimating and updating large phylogenies

Zaharias

Warnow

2022

Phil. Trans. R. Soc. B

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With the increased availability of sequence data and even of fully sequenced and assembled genomes, phylogeny estimation of very large trees (even of hundreds of thousands of sequences) is now a goal for some biologists. Yet, the construction of these phylogenies is a complex pipeline presenting analytical and computational challenges, especially when the number of sequences is very large. In the past few years, new methods have been developed that aim to enable highly accurate phylogeny estimations on these large datasets, including divide-and-conquer techniques for multiple sequence alignment and/or tree estimation, methods that can estimate species trees from multi-locus datasets while addressing heterogeneity due to biological processes (e.g. incomplete lineage sorting and gene duplication and loss), and methods to add sequences into large gene trees or species trees. Here we present some of these recent advances and discuss opportunities for future improvements. This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’.

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Section: Discussionmentioning

confidence: 99%

Recent progress on methods for estimating and updating large phylogenies

Zaharias

Warnow

2022

Phil. Trans. R. Soc. B

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“…Although phylogenetic networks have critical value in biology and beyond (Kong et al. 2022), their widespread use has been hindered by computational challenges that arise when using data to estimate them (Hejase and Liu 2016). In brief, the performance of current methods degrades as dataset size or the complexity of the network increases (i.e., lacks scalability).…”

Section: Figurementioning

confidence: 99%

Digest: Frequent hybridization in Darevskia rarely leads to the evolution of asexuality

Kong

2022

Evolution

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Asexuality in vertebrates is often generated via hybridization, but is it a rare product of pervasive hybridization or a common product of rare hybridization? Freitas et al. show that hybridization is frequent among the sexual species of Darevskia, although the crossings between parents of the asexual hybrids are undetected. This study illustrates that hybridization is not extraordinary in nature, and thus scalable phylogenetic network inference methods, rather than phylogenetic trees, are needed to accurately represent the true evolutionary history.

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“…An even more restrictive class of networks that is often considered are binary networks [12,24,43]: Definition 3.3. A network is binary if every tree vertex v is either a leaf or has outdeg(v) = 2, and every hybrid vertex v satisfies indeg(v) = 2 and outdeg(v) = 1.…”

Section: Basic Conceptsmentioning

confidence: 99%

“…A broad array of different types of networks have been studied in the literature in order to model different modes of non-tree-like evolution such as horizontal gene transfer, recombination, or hybridization, see [43] for a current review. Naturally, the question arises how much information about the structure of N is contained in the clustering system C N .…”

Section: Introductionmentioning

confidence: 99%

Clustering Systems of Phylogenetic Networks

Hellmuth¹,

Schaller²,

Stadler³

2022

Preprint

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Rooted acyclic graphs appear naturally when the phylogenetic relationship of a set X of taxa involves not only speciations but also recombination, horizontal transfer, or hybridization, that cannot be captured by trees. A variety of classes of such networks have been discussed in the literature, including phylogenetic, level-1, tree-child, tree-based, galled tree, regular, or normal networks as models of different types of evolutionary processes. Clusters arise in models of phylogeny as the sets C(v) of descendant taxa of a vertex v. The clustering system C N comprising the clusters of a network N conveys key information on N itself. In the special case of rooted phylogenetic trees, T is uniquely determined by its clustering system C T . Although this is no longer true for networks in general, it is of interest to relate properties of N and C N . Here, we systematically investigate the relationships of several well-studied classes of networks and their clustering systems. The main results are correspondences of classes of networks and clustering system of the following form: If N is a network of type X, then C N satisfies Y, and conversely if C is a clustering system satisfying Y then there is network N of type X such that C ⊆ C N .This, in turn, allows us to investigate the mutual dependencies between the distinct types of networks in much detail.

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Classes of explicit phylogenetic networks and their biological and mathematical significance

Cited by 34 publications

References 127 publications

Recent progress on methods for estimating and updating large phylogenies

Recent progress on methods for estimating and updating large phylogenies

Digest: Frequent hybridization in Darevskia rarely leads to the evolution of asexuality

Clustering Systems of Phylogenetic Networks

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