Testing for polytomies in phylogenetic species trees using quartet frequencies

Phylogenetic species trees typically represent the speciation history as a bifurcating tree. Speciation events that simultaneously create more than two descendants, thereby creating polytomies in the phylogeny, are possible. Moreover, the inability to resolve relationships is often shown as a (soft) polytomy. Both types of polytomies have been traditionally studied in the context of gene tree reconstruction from sequence data. However, polytomies in the species tree cannot be detected or ruled out without considering gene tree discordance. In this paper, we describe a statistical test based on properties of the multi-species coalescent model to test the null hypothesis that a branch in an estimated species tree should be replaced by a polytomy. On both simulated and biological datasets, we show that the null hypothesis is rejected for all but the shortest branches, and in most cases, it is retained for true polytomies. The test, available as part of the ASTRAL package, can help systematists decide whether their datasets are sufficient to resolve specific relationships of interest

New methods for inferring, assessing, and using phylogenetic trees from genomic and microbiome data

Phylogenies are trees showing the evolutionary relationship among species, and reconstructing phylogenies using molecular data can be framed as an optimization problem. Recent advances in DNA sequencing have resulted in extensive application of phylogenetic inference to (meta)genomic data. However, the scale and the complexity of the data has presented researchers with new algorithmic and statistical challenges, in particular, difficulties in noise reduction and statistical support estimation. This dissertation addresses these challenges.A significant challenge in using genomic data for phylogenetics (phylogenomics) is inconsistencies between evolutionary histories across different parts of the genome. Thus, phylogenomics methods need to consider these inconsistencies. One scalable solution is using summary methods, where a tree is first inferred for each gene, and then gene trees are summarized to build the species tree. Chapter 2 of this dissertation is dedicated to presenting a scalable and accurate summary method called DISTIQUE for reconstructing species trees from gene trees.A major challenge in phylogenomics is the interpretation of inferred phylogenies, especially in the presence of noise and gene-tree inconsistencies. Biologists rely on measures of statistical support for interpreting branches of the phylogeny. Chapter 3 introduces a highly scalable and reliable Bayesian measure of support, localPP, and Chapter 4 introduces a frequentist version of localPP for performing hypothesis testing.When using any summary method, the quality of the inferred species tree is highly impacted by the quality of gene phylogenies. In Chapter 5, we identify one factor that reduces the gene tree accuracy (gene fragmentation) and introduce a filtering strategy that effectively reduces error in gene trees and species trees. Further, Chapter 6 introduces a visualization framework, DiscoVista, to assist biologists in interpreting potentially discordant phylogenetic results.The final chapter focuses on the use of phylogenies in microbiome studies, where the goal is analyzing genetic material from environmental samples and to infer associations of genotype to phenotypical properties of samples. A main challenge in microbiome analyses is the huge variability across samples and small sample sizes. Chapter 7 introduces TADA, a new phylogeny-based method of data augmentation that improves the accuracy of classification methods applied to microbiome data

Additional file 1 of Anchoring quartet-based phylogenetic distances and applications to species tree reconstruction

Supplementary.pdf. The Supplementary Material for the paper. (PDF 426 KB

ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees

Abstract Background Evolutionary histories can be discordant across the genome, and such discordances need to be considered in reconstructing the species phylogeny. ASTRAL is one of the leading methods for inferring species trees from gene trees while accounting for gene tree discordance. ASTRAL uses dynamic programming to search for the tree that shares the maximum number of quartet topologies with input gene trees, restricting itself to a predefined set of bipartitions. Results We introduce ASTRAL-III, which substantially improves the running time of ASTRAL-II and guarantees polynomial running time as a function of both the number of species (n) and the number of genes (k). ASTRAL-III limits the bipartition constraint set (X) to grow at most linearly with n and k. Moreover, it handles polytomies more efficiently than ASTRAL-II, exploits similarities between gene trees better, and uses several techniques to avoid searching parts of the search space that are mathematically guaranteed not to include the optimal tree. The asymptotic running time of ASTRAL-III in the presence of polytomies is O(nk)1.726D $O\left ((nk)^{1.726} D \right)$ where D=O(nk) is the sum of degrees of all unique nodes in input trees. The running time improvements enable us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations, we show that removing branches with very low support (e.g., below 10%) improves accuracy while overly aggressive filtering is harmful. We observe on a biological avian phylogenomic dataset of 14K genes that contracting low support branches greatly improve results. Conclusions ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species. With ASTRAL-III, low support branches can be removed, resulting in improved accuracy

Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction

<div><p>Phylogenetic trees inferred using commonly-used models of sequence evolution are unrooted, but the root position matters both for interpretation and downstream applications. This issue has been long recognized; however, whether the potential for discordance between the species tree and gene trees impacts methods of rooting a phylogenetic tree has not been extensively studied. In this paper, we introduce a new method of rooting a tree based on its branch length distribution; our method, which minimizes the variance of root to tip distances, is inspired by the traditional midpoint rerooting and is justified when deviations from the strict molecular clock are random. Like midpoint rerooting, the method can be implemented in a linear time algorithm. In extensive simulations that consider discordance between gene trees and the species tree, we show that the new method is more accurate than midpoint rerooting, but its relative accuracy compared to using outgroups to root gene trees depends on the size of the dataset and levels of deviations from the strict clock. We show high levels of error for all methods of rooting estimated gene trees due to factors that include effects of gene tree discordance, deviations from the clock, and gene tree estimation error. Our simulations, however, did not reveal significant differences between two equivalent methods for species tree estimation that use rooted and unrooted input, namely, STAR and NJst. Nevertheless, our results point to limitations of existing scalable rooting methods.</p></div

Running time of MP and MV.

<p>A: comparison of our implementation of MV/MP with the implementation of MP in Dendropy, which employs a quadratic algorithm, on datasets D1, D2, and D3 with up to 5,000 leaves; B: Linear time scaling of our implementation, tested on the RNASim dataset with up to 200,000 leaves.</p

Species tree estimation accuracy using rooted and unrooted gene trees.

<p>Species tree estimation accuracy using rooted and unrooted gene trees.</p

Rooting error above ideal rooting on 30-taxon dataset.

<p>Top: delta triplet error with both true and estimated gene trees for (A) medium divergence from the clock and varying R/C ratios and (B) R/C = 1 and varying levels of divergence from the clock. C: Delta triplet error versus gene tree estimation error, measured by RF distance, shown for high, medium, and low divergence from the clock; each point is an average of all gene trees in all replicates that had an identical RF gene tree error. A loess regression is fitted to the data using R.</p