A rooted phylogenetic network is a directed acyclic graph with a single root, whose sinks correspond to a set of species. As such networks are useful for representing the evolution of species that have undergone reticulate evolution, there has been great interest in developing the theory behind and algorithms for constructing them. However, unlike evolutionary trees, these networks can be highly non-planar, which can make them difficult to visualise and interpret. Here we investigate properties of planar rooted phylogenetic networks and algorithms for deciding whether or not rooted networks have certain special planarity properties. In particular, we introduce three natural subclasses of planar rooted phylogenetic networks and show that they form a hierarchy. In addition, for the well-known level- k networks, we show that level-1, -2, -3 networks are always outer, terminal, and upward planar, respectively, and that level-4 networks are not necessarily planar. Finally, we show that a regular network is terminal planar if and only if it is pyramidal. Our results make use of the highly developed field of planar digraphs, and we believe that the link between phylogenetic networks and planar graphs should prove useful in future for developing new approaches to both construct and visualise phylogenetic networks.

RNA molecules are single-stranded analogues of DNA that can fold into various structures which influence their biological function within the cell. RNA structures can be modeled combinatorially in terms of a certain type of graph called an RNA diagram. In this paper we introduce a new poset of RNA diagrams ${\mathcal B}^r_{f,k}$, $r\ge 0$, $k \ge 1$, and $f \ge 3$, which we call the Penner--Waterman poset, and, using results from the theory of multitriangulations, we show that this is a pure poset of rank $k(2f-2k+1)+r-f-1$, whose geometric realization is the join of a simplicial sphere of dimension $k(f-2k)-1$ and an $\left((f+1)(k-1)-1\right)$-simplex in case $r=0$. As a corollary for the special case $k=1$, we obtain a result due to Penner and Waterman concerning the topology of the space of RNA secondary structures. These results could eventually lead to new ways to study landscapes of RNA $k$-noncrossing structures.

Summary: Split-networks are a generalization of phylogenetic trees that have proven to be a powerful tool in phylogenetics. Various ways have been developed for computing such networks, including split-decomposition, NeighborNet, QNet and FlatNJ. Some of these approaches are implemented in the user-friendly SplitsTree software package. However, to give the user the option to adjust and extend these approaches and to facilitate their integration into analysis pipelines, there is a need for robust, open-source implementations of associated data structures and algorithms. Here, we present SPECTRE, a readily available, open-source library of data structures written in Java, that comes complete with new implementations of several pre-published algorithms and a basic interactive graphical interface for visualizing planar split networks. SPECTRE also supports the use of longer running algorithms by providing command line interfaces, which can be executed on servers or in High Performance Computing environments. Availability and implementation: Full source code is available under the GPLv3 license at: https://github.com/maplesond/SPECTRE. SPECTRE's core library is available from Maven Central at: https://mvnrepository.com/artifact/uk.ac.uea.cmp.spectre/core. Documentation is available at: http://spectre-suite-of-phylogenetic-tools-for-reticulate-evolution.readthedocs.io/en/latest/. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Binets and trinets are phylogenetic networks with two and three leaves, respectively. Here we consider the problem of deciding if there exists a binary level-1 phylogenetic network displaying a given set $$\mathbb {T}$$ of binary binets or trinets over a taxon set X, and constructing such a network whenever it exists. We show that this is NP-hard for trinets but polynomial-time solvable for binets. Moreover, we show that the problem is still polynomial-time solvable for inputs consisting of binets and trinets as long as the cycles in the trinets have size three. Finally, we present an $$O(3^{|X|} poly(|X|))$$ time algorithm for general sets of binets and trinets. The latter two algorithms generalise to instances containing level-1 networks with arbitrarily many leaves, and thus provide some of the first supernetwork algorithms for computing networks from a set of rooted phylogenetic networks.

MOTIVATION: Distance methods are well suited for constructing massive phylogenetic trees. However, the computational complexity for Rzhetsky and Nei's minimum evolution (ME) approach, one of the earliest methods for constructing a phylogenetic tree from a distance matrix, remains open. RESULTS: We show that Rzhetsky and Nei's ME problem is NP-complete, and so probably computationally intractable. We do this by linking the ME problem to a graph clustering problem called the quasi-clique decomposition problem, which has recently also been shown to be NP-complete. We also discuss how this link could potentially open up some useful new connections between phylogenetics and graph clustering.

In evolutionary biology, biologists often face the problem of constructing a phylogenetic tree on a set $X$ of species from a multiset $\Pi$ of partitions corresponding to various attributes of these species. One approach that is used to solve this problem is to try instead to associate a tree (or even a network) to the multiset $\Sigma_{\Pi}$ consisting of all those bipartitions $\{A,X-A\}$ with $A$ a part of some partition in $\Pi$. The rationale behind this approach is that a phylogenetic tree with leaf set $X$ can be uniquely represented by the set of bipartitions of $X$ induced by its edges. Motivated by these considerations, given a multiset $\Sigma$ of bipartitions corresponding to a phylogenetic tree on $X$, in this paper we introduce and study the set $\mathbb{P}(\Sigma)$ consisting of those multisets of partitions $\Pi$ of $X$ with $\Sigma_{\Pi}=\Sigma$. More specifically, we characterize when $\mathbb{P}(\Sigma)$ is nonempty and also identify some partitions in $\mathbb{P}(\Sigma)$ that are of maximum and minimum size. We also show that it is NP-complete to decide when $\mathbb{P}(\Sigma)$ is nonempty in the case when $\Sigma$ is an arbitrary multiset of bipartitions of $X$. Ultimately, we hope that by gaining a better understanding of the mapping that takes an arbitrary partition system $\Pi$ to the multiset $\Sigma_{\Pi}$, we will obtain new insights into the use of median networks and, more generally, split networks, to visualize sets of partitions.

Tree rearrangement operations typically induce a metric on the space of phylogenetic trees. One important property of these metrics is the size of the neighborhood, that is, the number of trees exactly one operation from a given tree. We present an exact expression for the size of the TBR (tree bisection and reconnection) neighborhood, thus answering a question first posed by Allen and Steel . In addition, we also obtain a characterization of the extremal trees whose TBR neighborhoods are maximized and minimized.

Evolutionary history of protein-protein interaction (PPI) networks provides valuable insight into molecular mechanisms of network growth. In this paper, we study how to infer the evolutionary history of a PPI network from its protein duplication relationship. We show that for a plausible evolutionary history of a PPI network, its relative quality, measured by the so-called loss number, is independent of the growth parameters of the network and can be computed efficiently. This finding leads us to propose two fast maximum likelihood algorithms to infer the evolutionary history of a PPI network given the duplication history of its proteins. Simulation studies demonstrated that our approach, which takes advantage of protein duplication information, outperforms NetArch, the first maximum likelihood algorithm for PPI network history reconstruction. Using the proposed method, we studied the topological change of the PPI networks of the yeast, fruitfly, and worm.

INTRODUCTION: A gene tree for a gene family is often discordant with the containing species tree because of its complex evolutionary course during which gene duplication, gene loss and incomplete lineage sorting events might occur. Hence, it is of great challenge to infer the containing species tree from a set of gene trees. One common approach to this inference problem is through gene tree and species tree reconciliation. RESULTS: In this paper, we generalize the traditional least common ancestor (LCA) reconciliation to define a reconciliation between a gene tree and species tree under the tree homomorphism framework. We then study the structural properties of the space of all reconciliations between a gene tree and a species tree in terms of the gene duplication, gene loss or deep coalescence costs. As application, we show that the LCA reconciliation is the unique one that has the minimum deep coalescence cost, provide a novel characterization of the reconciliations with the optimal duplication cost, and present efficient algorithms for enumerating (nearly-)optimal reconciliations with respect to each cost. CONCLUSIONS: This work provides a new graph-theoretic framework for studying gene tree and species tree reconciliations.

Given a set X of taxa, a phylogenetic X-tree T that is only partially resolved, and a collection of characters on X, we consider the problem of finding a resolution (refinement) of T that minimizes the parsimony score of the given characters. Previous work has shown that this problem has a polynomial time solution provided certain strong constraints are imposed on the input. In this paper we provide a new algorithm for this problem, and show that it is fixed parameter tractable under more general conditions.