Reticulate evolutionary history and extensive introgression in mosquito species revealed by phylogenetic network analysis

The role of hybridization and subsequent introgression has been demonstrated in an increasing number of species. Recently, Fontaine et al. (Science, 347, 2015, 1258524) conducted a phylogenomic analysis of six members of the Anopheles gambiae species complex. Their analysis revealed a reticulate evolutionary history and pointed to extensive introgression on all four autosomal arms. The study further highlighted the complex evolutionary signals that the co-occurrence of incomplete lineage sorting (ILS) and introgression can give rise to in phylogenomic analyses. While tree-based methodologies were used in the study, phylogenetic networks provide a more natural model to capture reticulate evolutionary histories. In this work, we reanalyse the Anopheles data using a recently devised framework that combines the multispecies coalescent with phylogenetic networks. This framework allows us to capture ILS and introgression simultaneously, and forms the basis for statistical methods for inferring reticulate evolutionary histories. The new analysis reveals a phylogenetic network with multiple hybridization events, some of which differ from those reported in the original study. To elucidate the extent and patterns of introgression across the genome, we devise a new method that quantifies the use of reticulation branches in the phylogenetic network by each genomic region. Applying the method to the mosquito data set reveals the evolutionary history of all the chromosomes. This study highlights the utility of ‘network thinking’ and the new insights it can uncover, in particular in phylogenomic analyses of large data sets with extensive gene tree incongruence

Bayesian Inference of Phylogenetic Networks

The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under the MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We devised a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devised a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under the MSNC. Given the reticulate evolutionary histories for the whole genome, we devised a method to quantify introgression which would elucidate how each gene evolves. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation

WenNakhleh-SI

Supplementary Informatio

Data from: Coestimating reticulate phylogenies and gene trees from multilocus sequence data

The multispecies network coalescent (MSNC) is a stochastic process that captures how gene trees grow within the branches of a phylogenetic network. Coupling the MSNC with a stochastic mutational process that operates along the branches of the gene trees gives rise to a generative model of how multiple loci from within and across species evolve in the presence of both incomplete lineage sorting (ILS) and reticulation (e.g., hybridization). We report on a Bayesian method for sampling the parameters of this generative model, including the species phylogeny, gene trees, divergence times, and population sizes, from DNA sequences of multiple independent loci. We demonstrate the utility of our method by analyzing simulated data and reanalyzing an empirical data set. Our results demonstrate the significance of not only co-estimating species phylogenies and gene trees, but also accounting for reticulation and ILS simultaneously. In particular, we show that when gene flow occurs, our method accurately estimates the evolutionary histories, coalescence times, and divergence times. Tree inference methods, on the other hand, underestimate divergence times and overestimate coalescence times when the evolutionary history is reticulate. While the MSNC corresponds to an abstract model of ``intermixture," we study the performance of the model and method on simulated data generated under a gene flow model. We show that the method accurately infers the most recent time at which gene flow occurs. Finally, we demonstrate the application of the new method to a 106-locus yeast data set

Data from: Bayesian inference of reticulate phylogenies under the multispecies network coalescent

The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We report on a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devise a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under MSNC. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation

Iridium-Catalyzed Asymmetric Ring-Opening of Oxabenzonorbornadienes with N-Substituted Piperazine Nucleophiles

Iridium-catalyzed asymmetric ring-opening of oxabenzonorbornadienes with N-substituted piperazines was described. The reaction afforded the corresponding ring-opening products in high yields and moderate enantioselectivities in the presence of 2.5 mol % [Ir(COD)Cl]2 and 5.0 mol % (S)-p-Tol-BINAP. The effects of various chiral bidentate ligands, catalyst loading, solvent, and temperature on the yield and enantioselectivity were also investigated. A plausible mechanism was proposed to account for the formation of the corresponding trans-ring opened products based on the X-ray structure of product 2i

Data from: Bayesian inference of reticulate phylogenies under the multispecies network coalescent

The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We report on a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devise a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under MSNC. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation

Phylogenetic history of the bread wheat.

<p>(<b>A</b>–<b>C</b>) The three phylogenetic networks that comprise the 95% credible set, (<b>D</b>) and a plausible summary of the three networks that is consistent with the model of phylogenetic history of bread wheat (Fig 3 in [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006006#pgen.1006006.ref029" target="_blank">29</a>]).</p

The seven moves that the MCMC sampler utilizes can be classified into ones that do not modify the topology of the phylogenetic network (moves 1 and 2), ones that modify the topology but do not change the model’s dimensions (moves 3, 4, and 5), and ones that modify the topology and model’s dimensions (moves 6 and 7).

<p>The current-state phylogenetic network is shown at the center in dark blue, and the resulting next-state phylogenetic network after each moves is show in black lines. Moves 1 and 2 modify branch lengths and inheritance probabilities, respectively. Moves 3–5 relocate one of the children of a tree node, relocate the head of a reticulation edge, and reverse the direction of a reticulation edge, respectively. Moves 6 and 7 add and remove a reticulation edge, respectively. The probabilities <i>κ</i> and <i>ω</i> determine which of the three groups of moves is selected in an iteration. Within each group, an edge is selected and a move is selected uniformly at random among all the ones that are applicable to the selected edge within that group.</p

PGENETICS-D-15-02479R1-DATA

This directory contains four input files on which PhyloNet can be run to conduct the Bayesian analyses reported in the paper for the four data sets (the wheat data set, the mouse data set, the mosquito autosome data set, and the mosquito X chromosome data set)