Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters

Iersel, Leo van; Kelk, Steven; Rupp, Regula; Huson, Daniel H.

doi:10.1093/bioinformatics/btq202

Cited by 53 publications

(58 citation statements)

References 27 publications

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“…To address these obstacles, ad hoc methods simplify the search space of network structures: k-level, galled, tree-child, and tree-sibling networks. Although some of these methods cease to be NP-hard (19), all prioritize computational tractability over biological modeling (20). For example, galled tree networks minimize the number of inferred recombinations by ensuring that reticulation cycles share no nodes (21).…”

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confidence: 99%

Topology of viral evolution

Chan

Carlsson

Rabadán

2013

Proc. Natl. Acad. Sci. U.S.A.

223

189

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The tree structure is currently the accepted paradigm to represent evolutionary relationships between organisms, species or other taxa. However, horizontal, or reticulate, genomic exchanges are pervasive in nature and confound characterization of phylogenetic trees. Drawing from algebraic topology, we present a unique evolutionary framework that comprehensively captures both clonal and reticulate evolution. We show that whereas clonal evolution can be summarized as a tree, reticulate evolution exhibits nontrivial topology of dimension greater than zero. Our method effectively characterizes clonal evolution, reassortment, and recombination in RNA viruses. Beyond detecting reticulate evolution, we succinctly recapitulate the history of complex genetic exchanges involving more than two parental strains, such as the triple reassortment of H7N9 avian influenza and the formation of circulating HIV-1 recombinants. In addition, we identify recurrent, large-scale patterns of reticulate evolution, including frequent PB2-PB1-PA-NP cosegregation during avian influenza reassortment. Finally, we bound the rate of reticulate events (i.e., 20 reassortments per year in avian influenza). Our method provides an evolutionary perspective that not only captures reticulate events precluding phylogeny, but also indicates the evolutionary scales where phylogenetic inference could be accurate. n On the Origin of the Species in 1859, Darwin first proposed the phylogenetic tree as a structure to describe the evolution of phenotypic attributes. Since then, the advancement of modern sequencing has spurred development of a number of phylogenetic inference methods (1, 2). The tree structure effectively models vertical or clonal evolution, mediated by random mutations over multiple generations (Fig. 1A). Phylogenetic trees, however, cannot capture horizontal, or reticulate, events, which occur when distinct clades merge together to form a new hybrid lineage ( Fig. 1B and SI Appendix, Fig. S1). In nature, horizontal evolution can occur through species hybridization in eukaryotes, lateral gene transfer in bacteria, recombination and reassortment in viruses, viral integration in eukaryotes, and fusion of genomes of symbiotic species (e.g., mitochondria). These horizontal genetic exchanges create incompatibilities that mischaracterize the species tree (3). Doolittle (4) argued that molecular phylogeneticists have failed to identify the "true tree of life" because the history of living organisms cannot be understood as a tree. One may wonder what other mathematical structures beyond phylogeny can capture the richness of evolutionary processes.Current techniques that detect reticulate events can be divided into phylogenetic and nonphylogenetic methodologies. Phylogenetic methods detect incongruence in the tree structure of different segments (5-8). Nonphylogenetic methods probe for homoplasies (shared character traits independently arising in different lineages by convergent or parallel evolution) or similar inconsistencies in sequence alignment (9-...

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confidence: 99%

Topology of viral evolution

Chan

Carlsson

Rabadán

2013

Proc. Natl. Acad. Sci. U.S.A.

223

189

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“…com/site/cassalgorithm/data-sets) (van Iersel et al, 2010), and the results are summarized in Table 1 and Figure 1. The table shows the results of an application of QuickCass and BIMLR on several artificial datasets.…”

Section: Resultsmentioning

confidence: 99%

“…The Dendroscope program (Huson and Scornavacca, 2012) is an available tool for computing rooted phylogenetic networks. This tool contains a lot of methods, such as Cass (van Iersel et al, 2010), the galled network (Huson et al, 2009), and the cluster network (Huson and Rupp, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Here, the task is to construct a rooted phylogenetic network from a set of binary sequences. The third is horizontal gene transfer networks, where the goal is to explain the discrepancies between gene trees and a species tree (e.g., Gusfield et al, 2007;Semple, 2007;Nakleh, 2009;van Iersel et al, 2010). The fourth is the construction of rooted phylogenetic networks from triplets (van Iersel et al, 2008;van Iersel and Kelk, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, we invoke the parsimony principle to argue that the best network representing a set of clusters in the softwired sense is one that minimizes the number of clusters that are represented by the network on the premise of as few reticulate nodes as possible. The Cass algorithm, which was developed by van Iersel et al (2010), can construct a phyloge-netic network in the softwired sense. The phylogenetic network that is constructed by the Cass algorithm has fewer reticulate nodes than other methods.…”

Section: Introductionmentioning

confidence: 99%

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A new algorithm to construct phylogenetic networks from trees

Wang¹

2014

Genet. Mol. Res.

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ABSTRACT. Developing appropriate methods for constructing phylogenetic networks from tree sets is an important problem, and much research is currently being undertaken in this area. BIMLR is an algorithm that constructs phylogenetic networks from tree sets. The algorithm can construct a much simpler network than other available methods. Here, we introduce an improved version of the BIMLR algorithm, QuickCass. QuickCass changes the selection strategy of the labels of leaves below the reticulate nodes, i.e., the nodes with an indegree of at least 2 in BIMLR. We show that QuickCass can construct simpler phylogenetic networks than BIMLR. Furthermore, we show that QuickCass is a polynomialtime algorithm when the output network that is constructed by QuickCass is binary.

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Large-Scale Multiple Sequence Alignment and Phylogeny Estimation

Warnow

2013

Models and Algorithms for Genome Evolution

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With the advent of next generation sequencing technologies, alignment and phylogeny estimation of datasets with thousands of sequences is being attempted. To address these challenges, new algorithmic approaches have been developed that have been able to provide substantial improvements over standard methods. This paper focuses on new approaches for ultra-large tree estimation, including methods for co-estimation of alignments and trees, estimating trees without needing a full sequence alignment, and phylogenetic placement. While the main focus is on methods with empirical performance advantages, we also discuss the theoretical guarantees of methods under Markov models of evolution.Finally, we include a discussion of the future of large-scale phylogenetic analysis.

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Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters

Cited by 53 publications

References 27 publications

Topology of viral evolution

Topology of viral evolution

A new algorithm to construct phylogenetic networks from trees

Large-Scale Multiple Sequence Alignment and Phylogeny Estimation

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