Species Tree Inference Research Articles

DISCO: Species Tree Inference using Multicopy Gene Family Tree Decomposition.

Species tree inference from gene family trees is a significant problem in computational biology. However, gene tree heterogeneity, which can be caused by several factors including gene duplication and loss, makes the estimation of species trees very challenging. While there have been several species tree estimation methods introduced in recent years to specifically address gene tree heterogeneity due to gene duplication and loss (such as DupTree, FastMulRFS, ASTRAL-Pro, and SpeciesRax), many incur high cost in terms of both running time and memory. We introduce a new approach, DISCO, that decomposes the multi-copy gene family trees into many single copy trees, which allows for methods previously designed for species tree inference in a single copy gene tree context to be used. We prove that using DISCO with ASTRAL (i.e., ASTRAL-DISCO) is statistically consistent under the GDL model, provided that ASTRAL-Pro correctly roots and tags each gene family tree. We evaluate DISCO paired with different methods for estimating species trees from single copy genes (e.g., ASTRAL, ASTRID, and IQ-TREE) under a wide range of model conditions, and establish that high accuracy can be obtained even when ASTRAL-Pro is not able to correctly roots and tags the gene family trees. We also compare results using MI, an alternative decomposition strategy from Yang Y. and Smith S.A. (2014), and find that DISCO provides better accuracy, most likely as a result of covering more of the gene family tree leafset in the output decomposition. [Concatenation analysis; gene duplication and loss; species tree inference; summary method.]

Bayesian-Weighted Triplet and Quartet Methods for Species Tree Inference

Inference of the evolutionary histories of species, commonly represented by a species tree, is complicated by the divergent evolutionary history of different parts of the genome. Different loci on the genome can have different histories from the underlying species tree (and each other) due to processes such as incomplete lineage sorting (ILS), gene duplication and loss, and horizontal gene transfer. The multispecies coalescent is a commonly used model for performing inference on species and gene trees in the presence of ILS. This paper introduces Lily-T and Lily-Q, two new methods for species tree inference under the multispecies coalescent. We then compare them to two frequently used methods, SVDQuartets and ASTRAL, using simulated and empirical data. Both methods generally showed improvement over SVDQuartets, and Lily-Q was superior to Lily-T for most simulation settings. The comparison to ASTRAL was more mixed-Lily-Q tended to be better than ASTRAL when the length of recombination-free loci was short, when the coalescent population parameter [Formula: see text] was small, or when the internal branch lengths were longer.

Rapid Radiation and Rampant Reticulation: Phylogenomics of South American Liolaemus Lizards.

Understanding the factors that cause heterogeneity among gene trees can increase the accuracy of species trees. Discordant signals across the genome are commonly produced by incomplete lineage sorting (ILS) and introgression, which in turn can result in reticulate evolution. Species tree inference using the multispecies coalescent is designed to deal with ILS and is robust to low levels of introgression, but extensive introgression violates the fundamental assumption that relationships are strictly bifurcating. In this study, we explore the phylogenomics of the iconic Liolaemus subgenus of South American lizards, a group of over 100 species mostly distributed in and around the Andes mountains. Using mitochondrial DNA (mtDNA) and genome-wide restriction site-associated DNA sequencing (RADseq; nDNA hereafter), we inferred a time-calibrated mtDNA gene tree, nDNA species trees, and phylogenetic networks. We found high levels of discordance between mtDNA and nDNA, which we attribute in part to extensive ILS resulting from rapid diversification. These data also reveal extensive and deep introgression, which combined with rapid diversification, explain the high level of phylogenetic discordance. We discuss these findings in the context of Andean orogeny and glacial cycles that fragmented, expanded, and contracted species distributions. Finally, we use the new phylogeny to resolve long-standing taxonomic issues in one of the most studied lizard groups in the New World.[Andes; ddRADSeq; introgression; lizards; mtDNA; reptiles; SNPs.].

Evolutionary Rate Variation among Lineages in Gene Trees has a Negative Impact on Species-Tree Inference.

Phylogenetic analyses of genomic data provide a powerful means of reconstructing the evolutionary relationships among organisms, yet such analyses are often hindered by conflicting phylogenetic signals among loci. Identifying the signals that are most influential to species-tree estimation can help to inform the choice of data for phylogenomic analysis. We investigated this in an analysis of 30 phylogenomic data sets. For each data set, we examined the association between several branch-length characteristics of gene trees and the distance between these gene trees and the corresponding species trees. We found that the distance of each gene tree to the species tree inferred from the full data set was positively associated with variation in root-to-tip distances and negatively associated with mean branch support. However, no such associations were found for gene-tree length, a measure of the overall substitution rate at each locus. We further explored the usefulness of the best-performing branch-based characteristics for selecting loci for phylogenomic analyses. We found that loci that yield gene trees with high variation in root-to-tip distances have a disproportionately distant signal of tree topology compared with the complete data sets. These results suggest that rate variation across lineages should be taken into consideration when exploring and even selecting loci for phylogenomic analysis.[Branch support; data filtering; nucleotide substitution model; phylogenomics; substitution rate; summary coalescent methods.]

Species Tree Inference Methods Intended to Deal with Incomplete Lineage Sorting Are Robust to the Presence of Paralogs.

Many recent phylogenetic methods have focused on accurately inferring species trees when there is gene tree discordance due to incomplete lineage sorting (ILS). For almost all of these methods, and for phylogenetic methods in general, the data for each locus are assumed to consist of orthologous, single-copy sequences. Loci that are present in more than a single copy in any of the studied genomes are excluded from the data. These steps greatly reduce the number of loci available for analysis. The question we seek to answer in this study is: what happens if one runs such species tree inference methods on data where paralogy is present, in addition to or without ILS being present? Through simulation studies and analyses of two large biological data sets, we show that running such methods on data with paralogs can still provide accurate results. We use multiple different methods, some of which are based directly on the multispecies coalescent model, and some of which have been proven to be statistically consistent under it. We also treat the paralogous loci in multiple ways: from explicitly denoting them as paralogs, to randomly selecting one copy per species. In all cases, the inferred species trees are as accurate as equivalent analyses using single-copy orthologs. Our results have significant implications for the use of ILS-aware phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci. This will greatly increase the amount of data that can be used for phylogenetic inference.[Gene duplication and loss; incomplete lineage sorting; multispecies coalescent; orthology; paralogy.]

Concordance-Based Approaches for the Inference of Relationships and Molecular Rates with Phylogenomic Data Sets.

Gene tree conflict is common and finding methods to analyze and alleviate the negative effects that conflict has on species tree analysis is a crucial part of phylogenomics. This study aims to expand the discussion of inferring species trees and molecular branch lengths when conflict is present. Conflict is typically examined in two ways: inferring its prevalence and inferring the influence of the individual genes (how strongly one gene supports any given topology compared to an alternative topology). Here, we examine a procedure for incorporating both conflict and the influence of genes in order to infer evolutionary relationships. All supported relationships in the gene trees are analyzed and the likelihood of the genes constrained to these relationships is summed to provide a likelihood for the relationship. Consensus tree assembly is conducted based on the sum of likelihoods for a given relationship and choosing relationships based on the most likely relationship assuming it does not conflict with a relationship that has a higher likelihood score. If it is not possible for all most likely relationships to be combined into a single bifurcating tree then multiple trees are produced and a consensus tree with a polytomy is created. This procedure allows for more influential genes to have a greater influence on an inferred relationship, does not assume conflict has arisen from any one source and does not force the data set to produce a single bifurcating tree. Using this approach, on three empirical data sets, we examine and discuss the relationship between influence and prevalence of gene tree conflict. We find that in one of the data sets, assembling a bifurcating consensus tree solely composed of the most likely relationships is impossible. To account for conflict in molecular rate analysis we also introduce a concordance-based approach to the summary and estimation of branch lengths suitable for downstream comparative analyses. We demonstrate through simulation that even under high levels of stochastic conflict, the mean and median of the concordant rates recapitulate the true molecular rate better than using a supermatrix approach. Using a large phylogenomic data set, we examine rate heterogeneity across concordant genes with a focus on the branch subtending crown angiosperms. Notably, we find highly variable rates of evolution along the branch subtending crown angiosperms. The approaches outlined here have several limitations, but they also represent some alternative methods for harnessing the complexity of phylogenomic data sets and enrich our inferences of both species relationships and evolutionary processes.[Branch length estimation; consensus tree; gene tree conflict; gene tree filtering; phylogenetics; phylogenomics.].

Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model.

MotivationThe classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis.ResultsIn this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal.Supplementary information Supplementary data are available at Bioinformatics online.

Genome-wide SNPs redefines species boundaries and conservation units in the freshwater mussel genus Cyprogenia of North America

Detailed information on species delineation and population genetic structure is a prerequisite for designing effective restoration and conservation strategies for imperiled organisms. Phylogenomic and population genomic analyses based on genome-wide double digest restriction-site associated DNA sequencing (ddRAD-Seq) data has identified three allopatric lineages in the North American freshwater mussel genus Cyprogenia. Cyprogenia stegaria is restricted to the Eastern Highlands and displays little genetic structuring within this region. However, two allopatric lineages of C. aberti in the Ozark and Ouachita highlands exhibit substantial levels (mean uncorrected FST = 0.368) of genetic differentiation and each warrants recognition as a distinct evolutionary lineage. Lineages of Cyprogenia in the Ouachita and Ozark highlands are further subdivided reflecting structuring at the level of river systems. Species tree inference and species delimitation in a Bayesian framework using single nucleotide polymorphisms (SNP) data supported results from phylogenetic analyses, and supports three species of Cyprogenia over the currently recognized two species. A comparison of SNPs generated from both destructively and non-destructively collected samples revealed no significant difference in the SNP error rate, quality and amount of ddRAD sequence reads, indicating that nondestructive or trace samples can be effectively utilized to generate SNP data for organisms for which destructive sampling is not permitted.

Statistical inconsistency of the unrooted minimize deep coalescence criterion.

Species trees, which describe the evolutionary relationships between species, are often inferred from gene trees, which describe the ancestral relationships between sequences sampled at different loci from the species of interest. A common approach to inferring species trees from gene trees is motivated by supposing that gene tree variation is due to incomplete lineage sorting, also known as deep coalescence. One of the earliest methods motivated by deep coalescence is to find the species tree that minimizes the number of deep coalescent events needed to explain discrepancies between the species tree and input gene trees. This minimize deep coalescence (MDC) criterion can be applied in both rooted and unrooted settings. where either rooted or unrooted gene trees can be used to infer a rooted species tree. Previous work has shown that MDC is statistically inconsistent in the rooted setting, meaning that under a probabilistic model for deep coalescence, the multispecies coalescent, for some species trees, increasing the number of input gene trees does not make the method more likely to return a correct species tree. Here, we obtain analogous results in the unrooted setting, showing conditions leading to inconsistency of the MDC criterion using the multispecies coalescent model with unrooted gene trees for four taxa and five taxa.

A multitiered sequence capture strategy spanning broad evolutionary scales: Application for phylogenetic and phylogeographic studies of orchids.

With over 25,000 species, the drivers of diversity in the Orchidaceae remain to be fully understood. Here, we outline a multitiered sequence capture strategy aimed at capturing hundreds of loci to enable phylogenetic resolution from subtribe to subspecific levels in orchids of the tribe Diurideae. For the probe design, we mined subsets of 18 transcriptomes, to give five target sequence sets aimed at the tribe (Sets 1 & 2), subtribe (Set 3), and within subtribe levels (Sets 4 & 5). Analysis included alternative de novo and reference-guided assembly, before target sequence extraction, annotation and alignment, and application of a homology-aware k-mer block phylogenomic approach, prior to maximum likelihood and coalescence-based phylogenetic inference. Our evaluation considered 87 taxa in two test data sets: 67 samples spanning the tribe, and 72 samples involving 24 closely related Caladenia species. The tiered design achieved high target loci recovery (>89%), with the median number of recovered loci in Sets 1-5 as follows: 212, 219, 816, 1024, and 1009, respectively. Interestingly, as a first test of the homologous k-mer approach for targeted sequence capture data, our study revealed its potential for enabling robust phylogenetic species tree inferences. Specifically, we found matching, and in one case improved phylogenetic resolution within species complexes, compared to conventional phylogenetic analysis involving target gene extraction. Our findings indicate that a customized multitiered sequence capture strategy, in combination with promising yet underutilized phylogenomic approaches, will be effective for groups where interspecific divergence is recent, but information on deeper phylogenetic relationships is also required.

SODA: multi-locus species delimitation using quartet frequencies.

Species delimitation, the process of deciding how to group a set of organisms into units called species, is one of the most challenging problems in computational evolutionary biology. While many methods exist for species delimitation, most based on the coalescent theory, few are scalable to very large datasets, and methods that scale tend to be not accurate. Species delimitation is closely related to species tree inference from discordant gene trees, a problem that has enjoyed rapid advances in recent years. In this article, we build on the accuracy and scalability of recent quartet-based methods for species tree estimation and propose a new method called SODA for species delimitation. SODA relies heavily on a recently developed method for testing zero branch length in species trees. In extensive simulations, we show that SODA can easily scale to very large datasets while maintaining high accuracy. The code and data presented here are available on https://github.com/maryamrabiee/SODA. Supplementary data are available at Bioinformatics online.

Collapsing dubiously resolved gene-tree branches in phylogenomic coalescent analyses

In two-step coalescent analyses of phylogenomic data, gene-tree topologies are treated as fixed prior to species-tree inference. Although all gene-tree conflict is assumed to be caused by lineage sorting when applying these methods, in empirical datasets much of the conflict can be caused by estimation error. Weakly supported and even arbitrarily resolved clades are important sources of this estimation error for gene trees inferred from few informative characters relative to the number of sampled terminals, and the resulting extraneous conflict among gene trees can negatively impact species-tree inference. In this study, we quantified the relative severity of alternative methods for collapsing gene-tree branches for seven empirical datasets and quantified their effects on species-tree inference. The branch-collapsing methods that we employed were based on the strict consensus of optimal topologies, various bootstrap thresholds, and 0% approximate likelihood ratio test (SH-like aLRT) support. Up to 86% of internal gene-tree branches are dubiously or arbitrarily resolved in reanalyses of these published phylogenomic datasets, and collapsing these branches increased inferred species-tree coalescent branch lengths by up to 455%. For two datasets, the longer inferred branch lengths sometimes impacted inference of anomaly-zone conditions. Although branch-collapsing methods did not consistently affect the species-tree topology, they often increased branch support. The more severe and clearly justified gene-tree branch-collapsing methods, which we recommend be broadly applied for two-step coalescent analyses, are use of the strict consensus in parsimony analyses and the collapse clades with 0% SH-like aLRT support in likelihood analyses. Collapsing dubiously or arbitrarily resolved branches in gene trees sometimes improved congruence between coalescent-based results and concatenation trees. In such cases, we contend that the resolution provided by concatenation should be preferred and that incomplete lineage sorting is a poor explanation for the initial conflict between phylogenetic approaches.

Consensus of All Solutions for Intractable Phylogenetic Tree Inference.

Solving median tree problems is a classic approach for inferring species trees from a collection of discordant gene trees. Median tree problems are typically NP-hard and dealt with by local search heuristics. Unfortunately, such heuristics generally lack provable correctness and precision. Algorithmic advances addressing this uncertainty have led to exact dynamic programming formulations suitable to solve a well-studied group of median tree problems for smaller phylogenetic analyses. However, these formulations allow computing only very few optimal species trees out of possibly many such trees, and phylogenetic studies often require the analysis of all optimal solutions through their consensus tree. Here, we describe a significant algorithmic modification of the dynamic programming formulations that compute the cluster counts of all optimal species trees from which various types of consensus trees can be efficiently computed. Through experimental studies, we demonstrate that our parallel implementation of the modified dynamic programming formulation is more efficient than a previous implementation of the original formulation. Finally, we show that the parallel implementation can rapidly identify novel reassorted influenza A viruses potentially facilitating pandemic preparedness efforts.

Target-capture phylogenomics provide insights on gene and species tree discordances in Old World treefrogs (Anura: Rhacophoridae).

Genome-scale data have greatly facilitated the resolution of recalcitrant nodes that Sanger-based datasets have been unable to resolve. However, phylogenomic studies continue to use traditional methods such as bootstrapping to estimate branch support; and high bootstrap values are still interpreted as providing strong support for the correct topology. Furthermore, relatively little attention has been given to assessing discordances between gene and species trees, and the underlying processes that produce phylogenetic conflict. We generated novel genomic datasets to characterize and determine the causes of discordance in Old World treefrogs (Family: Rhacophoridae)-a group that is fraught with conflicting and poorly supported topologies among major clades. Additionally, a suite of data filtering strategies and analytical methods were applied to assess their impact on phylogenetic inference. We showed that incomplete lineage sorting was detected at all nodes that exhibited high levels of discordance. Those nodes were also associated with extremely short internal branches. We also clearly demonstrate that bootstrap values do not reflect uncertainty or confidence for the correct topology and, hence, should not be used as a measure of branch support in phylogenomic datasets. Overall, we showed that phylogenetic discordances in Old World treefrogs resulted from incomplete lineage sorting and that species tree inference can be improved using a multi-faceted, total-evidence approach, which uses the most amount of data and considers results from different analytical methods and datasets.

Hybrid capture of 964 nuclear genes resolves evolutionary relationships in the mimosoid legumes and reveals the polytomous origins of a large pantropical radiation.

PREMISETargeted enrichment methods facilitate sequencing of hundreds of nuclear loci to enhance phylogenetic resolution and elucidate why some parts of the “tree of life” are difficult (if not impossible) to resolve. The mimosoid legumes are a prominent pantropical clade of ~3300 species of woody angiosperms for which previous phylogenies have shown extensive lack of resolution, especially among the species‐rich and taxonomically challenging ingoids.METHODSWe generated transcriptomes to select low‐copy nuclear genes, enrich these via hybrid capture for representative species of most mimosoid genera, and analyze the resulting data using de novo assembly and various phylogenomic tools for species tree inference. We also evaluate gene tree support and conflict for key internodes and use phylogenetic network analysis to investigate phylogenetic signal across the ingoids.RESULTSOur selection of 964 nuclear genes greatly improves phylogenetic resolution across the mimosoid phylogeny and shows that the ingoid clade can be resolved into several well‐supported clades. However, nearly all loci show lack of phylogenetic signal for some of the deeper internodes within the ingoids.CONCLUSIONSLack of resolution in the ingoid clade is most likely the result of hyperfast diversification, potentially causing a hard polytomy of six or seven lineages. The gene set for targeted sequencing presented here offers great potential to further enhance the phylogeny of mimosoids and the wider Caesalpinioideae with denser taxon sampling, to provide a framework for taxonomic reclassification, and to study the ingoid radiation.

The Perfect Storm: Gene Tree Estimation Error, Incomplete Lineage Sorting, and Ancient Gene Flow Explain the Most Recalcitrant Ancient Angiosperm Clade, Malpighiales.

The genomic revolution offers renewed hope of resolving rapid radiations in the Tree of Life. The development of the multispecies coalescent model and improved gene tree estimation methods can better accommodate gene tree heterogeneity caused by incomplete lineage sorting (ILS) and gene tree estimation error stemming from the short internal branches. However, the relative influence of these factors in species tree inference is not well understood. Using anchored hybrid enrichment, we generated a data set including 423 single-copy loci from 64 taxa representing 39 families to infer the species tree of the flowering plant order Malpighiales. This order includes 9 of the top 10 most unstable nodes in angiosperms, which have been hypothesized to arise from the rapid radiation during the Cretaceous. Here, we show that coalescent-based methods do not resolve the backbone of Malpighiales and concatenation methods yield inconsistent estimations, providing evidence that gene tree heterogeneity is high in this clade. Despite high levels of ILS and gene tree estimation error, our simulations demonstrate that these two factors alone are insufficient to explain the lack of resolution in this order. To explore this further, we examined triplet frequencies among empirical gene trees and discovered some of them deviated significantly from those attributed to ILS and estimation error, suggesting gene flow as an additional and previously unappreciated phenomenon promoting gene tree variation in Malpighiales. Finally, we applied a novel method to quantify the relative contribution of these three primary sources of gene tree heterogeneity and demonstrated that ILS, gene tree estimation error, and gene flow contributed to 10.0$\%$, 34.8$\%$, and 21.4$\%$ of the variation, respectively. Together, our results suggest that a perfect storm of factors likely influence this lack of resolution, and further indicate that recalcitrant phylogenetic relationships like the backbone of Malpighiales may be better represented as phylogenetic networks. Thus, reducing such groups solely to existing models that adhere strictly to bifurcating trees greatly oversimplifies reality, and obscures our ability to more clearly discern the process of evolution. [Coalescent; concatenation; flanking region; hybrid enrichment, introgression; phylogenomics; rapid radiation, triplet frequency.].

A phylogenomic study of Steganinae fruit flies (Diptera: Drosophilidae): strong gene tree heterogeneity and evidence for monophyly

BackgroundThe Drosophilidae family is traditionally divided into two subfamilies: Drosophilinae and Steganinae. This division is based on morphological characters, and the two subfamilies have been treated as monophyletic in most of the literature, but some molecular phylogenies have suggested Steganinae to be paraphyletic. To test the paraphyletic-Steganinae hypothesis, here, we used genomic sequences of eight Drosophilidae (three Steganinae and five Drosophilinae) and two Ephydridae (outgroup) species and inferred the phylogeny for the group based on a dataset of 1,028 orthologous genes present in all species (> 1,000,000 bp). This dataset includes three genera that broke the monophyly of the subfamilies in previous works. To investigate possible biases introduced by small sample sizes and automatic gene annotation, we used the same methods to infer species trees from a set of 10 manually annotated genes that are commonly used in phylogenetics.ResultsMost of the 1,028 gene trees depicted Steganinae as paraphyletic with distinct topologies, but the most common topology depicted it as monophyletic (43.7% of the gene trees). Despite the high levels of gene tree heterogeneity observed, species tree inference in ASTRAL, in PhyloNet, and with the concatenation approach strongly supported the monophyly of both subfamilies for the 1,028-gene dataset. However, when using the concatenation approach to infer a species tree from the smaller set of 10 genes, we recovered Steganinae as a paraphyletic group. The pattern of gene tree heterogeneity was asymmetrical and thus could not be explained solely by incomplete lineage sorting (ILS).ConclusionsSteganinae was clearly a monophyletic group in the dataset that we analyzed. In addition to ILS, gene tree discordance was possibly the result of introgression, suggesting complex branching processes during the early evolution of Drosophilidae with short speciation intervals and gene flow. Our study highlights the importance of genomic data in elucidating contentious phylogenetic relationships and suggests that phylogenetic inference for drosophilids based on small molecular datasets should be performed cautiously. Finally, we suggest an approach for the correction and cleaning of BUSCO-derived genomic datasets that will be useful to other researchers planning to use this tool for phylogenomic studies.

MSCquartets 1.0: quartet methods for species trees and networks under the multispecies coalescent model in R.

MSCquartets is an R package for species tree hypothesis testing, inference of species trees and inference of species networks under the Multispecies Coalescent model of incomplete lineage sorting and its network analog. Input for these analyses are collections of metric or topological locus trees which are then summarized by the quartets displayed on them. Results of hypothesis tests at user-supplied levels are displayed in a simplex plot by color-coded points. The package implements the QDC and WQDC algorithms for topological and metric species tree inference, and the NANUQ algorithm for level-1 topological species network inference, all of which give statistically consistent estimators under the model. MSCquartets is available through the Comprehensive R Archive Network: https://CRAN.R-project.org/package=MSCquartets.

Exact median-tree inference for unrooted reconciliation costs

BackgroundSolving median tree problems under tree reconciliation costs is a classic and well-studied approach for inferring species trees from collections of discordant gene trees. These problems are NP-hard, and therefore are, in practice, typically addressed by local search heuristics. So far, however, such heuristics lack any provable correctness or precision. Further, even for small phylogenetic studies, it has been demonstrated that local search heuristics may only provide sub-optimal solutions. Obviating such heuristic uncertainties are exact dynamic programming solutions that allow solving tree reconciliation problems for smaller phylogenetic studies. Despite these promises, such exact solutions are only suitable for credibly rooted input gene trees, which constitute only a tiny fraction of the readily available gene trees. Standard gene tree inference approaches provide only unrooted gene trees and accurately rooting such trees is often difficult, if not impossible.ResultsHere, we describe complex dynamic programming solutions that represent the first nonnaïve exact solutions for solving the tree reconciliation problems for unrooted input gene trees. Further, we show that the asymptotic runtime of the proposed solutions does not increase when compared to the most time-efficient dynamic programming solutions for rooted input trees.ConclusionsIn an experimental evaluation, we demonstrate that the described solutions for unrooted gene trees are, like the solutions for rooted input gene trees, suitable for smaller phylogenetic studies. Finally, for the first time, we study the accuracy of classic local search heuristics for unrooted tree reconciliation problems.

Machine learning based imputation techniques for estimating phylogenetic trees from incomplete distance matrices

BackgroundWith the rapid growth rate of newly sequenced genomes, species tree inference from genes sampled throughout the whole genome has become a basic task in comparative and evolutionary biology. However, substantial challenges remain in leveraging these large scale molecular data. One of the foremost challenges is to develop efficient methods that can handle missing data. Popular distance-based methods, such as NJ (neighbor joining) and UPGMA (unweighted pair group method with arithmetic mean) require complete distance matrices without any missing data.ResultsWe introduce two highly accurate machine learning based distance imputation techniques. These methods are based on matrix factorization and autoencoder based deep learning architectures. We evaluated these two methods on a collection of simulated and biological datasets. Experimental results suggest that our proposed methods match or improve upon the best alternate distance imputation techniques. Moreover, these methods are scalable to large datasets with hundreds of taxa, and can handle a substantial amount of missing data.ConclusionsThis study shows, for the first time, the power and feasibility of applying deep learning techniques for imputing distance matrices. Thus, this study advances the state-of-the-art in phylogenetic tree construction in the presence of missing data. The proposed methods are available in open source form at https://github.com/Ananya-Bhattacharjee/ImputeDistances.