Siavash Mirarab

Whole-genome analyses resolve early branches in the tree of life of modern birds

To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.

Phylotranscriptomic analysis of the origin and early diversification of land plants

Significance Early branching events in the diversification of land plants and closely related algal lineages remain fundamental and unresolved questions in plant evolutionary biology. Accurate reconstructions of these relationships are critical for testing hypotheses of character evolution: for example, the origins of the embryo, vascular tissue, seeds, and flowers. We investigated relationships among streptophyte algae and land plants using the largest set of nuclear genes that has been applied to this problem to date. Hypothesized relationships were rigorously tested through a series of analyses to assess systematic errors in phylogenetic inference caused by sampling artifacts and model misspecification. Results support some generally accepted phylogenetic hypotheses, while rejecting others. This work provides a new framework for studies of land plant evolution. Reconstructing the origin and evolution of land plants and their algal relatives is a fundamental problem in plant phylogenetics, and is essential for understanding how critical adaptations arose, including the embryo, vascular tissue, seeds, and flowers. Despite advances in molecular systematics, some hypotheses of relationships remain weakly resolved. Inferring deep phylogenies with bouts of rapid diversification can be problematic; however, genome-scale data should significantly increase the number of informative characters for analyses. Recent phylogenomic reconstructions focused on the major divergences of plants have resulted in promising but inconsistent results. One limitation is sparse taxon sampling, likely resulting from the difficulty and cost of data generation. To address this limitation, transcriptome data for 92 streptophyte taxa were generated and analyzed along with 11 published plant genome sequences. Phylogenetic reconstructions were conducted using up to 852 nuclear genes and 1,701,170 aligned sites. Sixty-nine analyses were performed to test the robustness of phylogenetic inferences to permutations of the data matrix or to phylogenetic method, including supermatrix, supertree, and coalescent-based approaches, maximum-likelihood and Bayesian methods, partitioned and unpartitioned analyses, and amino acid versus DNA alignments. Among other results, we find robust support for a sister-group relationship between land plants and one group of streptophyte green algae, the Zygnematophyceae. Strong and robust support for a clade comprising liverworts and mosses is inconsistent with a widely accepted view of early land plant evolution, and suggests that phylogenetic hypotheses used to understand the evolution of fundamental plant traits should be reevaluated.

ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes

Motivation: The estimation of species phylogenies requires multiple loci, since different loci can have different trees due to incomplete lineage sorting, modeled by the multi-species coalescent model. We recently developed a coalescent-based method, ASTRAL, which is statistically consistent under the multi-species coalescent model and which is more accurate than other coalescent-based methods on the datasets we examined. ASTRAL runs in polynomial time, by constraining the search space using a set of allowed ‘bipartitions’. Despite the limitation to allowed bipartitions, ASTRAL is statistically consistent. Results: We present a new version of ASTRAL, which we call ASTRAL-II. We show that ASTRAL-II has substantial advantages over ASTRAL: it is faster, can analyze much larger datasets (up to 1000 species and 1000 genes) and has substantially better accuracy under some conditions. ASTRAL’s running time is O(n2k|X|2), and ASTRAL-II’s running time is O(nk|X|2), where n is the number of species, k is the number of loci and X is the set of allowed bipartitions for the search space. Availability and implementation: ASTRAL-II is available in open source at https://github.com/smirarab/ASTRAL and datasets used are available at http://www.cs.utexas.edu/~phylo/datasets/astral2/. Contact: smirarab@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Data access for the 1,000 Plants (1KP) project

The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.

Statistical binning enables an accurate coalescent-based estimation of the avian tree

Introduction Reconstructing species trees for rapid radiations, as in the early diversification of birds, is complicated by biological processes such as incomplete lineage sorting (ILS) that can cause different parts of the genome to have different evolutionary histories. Statistical methods, based on the multispecies coalescent model and that combine gene trees, can be highly accurate even in the presence of massive ILS; however, these methods can produce species trees that are topologically far from the species tree when estimated gene trees have error. We have developed a statistical binning technique to address gene tree estimation error and have explored its use in genome-scale species tree estimation with MP-EST, a popular coalescent-based species tree estimation method. The statistical binning pipeline for estimating species trees from gene trees. Loci are grouped into bins based on a statistical test for combinabilty, before estimating gene trees. Rationale In statistical binning, phylogenetic trees on different genes are estimated and then placed into bins, so that the differences between trees in the same bin can be explained by estimation error (see the figure). A new tree is then estimated for each bin by applying maximum likelihood to a concatenated alignment of the multiple sequence alignments of its genes, and a species tree is estimated using a coalescent-based species tree method from these supergene trees. Results Under realistic conditions in our simulation study, statistical binning reduced the topological error of species trees estimated using MP-EST and enabled a coalescent-based analysis that was more accurate than concatenation even when gene tree estimation error was relatively high. Statistical binning also reduced the error in gene tree topology and species tree branch length estimation, especially when the phylogenetic signal in gene sequence alignments was low. Species trees estimated using MP-EST with statistical binning on four biological data sets showed increased concordance with the biological literature. When MP-EST was used to analyze 14,446 gene trees in the avian phylogenomics project, it produced a species tree that was discordant with the concatenation analysis and conflicted with prior literature. However, the statistical binning analysis produced a tree that was highly congruent with the concatenation analysis and was consistent with the prior scientific literature. Conclusions Statistical binning reduces the error in species tree topology and branch length estimation because it reduces gene tree estimation error. These improvements are greatest when gene trees have reduced bootstrap support, which was the case for the avian phylogenomics project. Because using unbinned gene trees can result in overestimation of ILS, statistical binning may be helpful in providing more accurate estimations of ILS levels in biological data sets. Thus, statistical binning enables highly accurate species tree estimations, even on genome-scale data sets. Gene tree incongruence arising from incomplete lineage sorting (ILS) can reduce the accuracy of concatenation-based estimations of species trees. Although coalescent-based species tree estimation methods can have good accuracy in the presence of ILS, they are sensitive to gene tree estimation error. We propose a pipeline that uses bootstrapping to evaluate whether two genes are likely to have the same tree, then it groups genes into sets using a graph-theoretic optimization and estimates a tree on each subset using concatenation, and finally produces an estimated species tree from these trees using the preferred coalescent-based method. Statistical binning improves the accuracy of MP-EST, a popular coalescent-based method, and we use it to produce the first genome-scale coalescent-based avian tree of life.

The Effects of Time Constraints on Test Case Prioritization: A Series of Controlled Experiments

Regression testing is an expensive process used to validate modified software. Test case prioritization techniques improve the cost-effectiveness of regression testing by ordering test cases such that those that are more important are run earlier in the testing process. Many prioritization techniques have been proposed and evidence shows that they can be beneficial. It has been suggested, however, that the time constraints that can be imposed on regression testing by various software development processes can strongly affect the behavior of prioritization techniques. If this is correct, a better understanding of the effects of time constraints could lead to improved prioritization techniques and improved maintenance and testing processes. We therefore conducted a series of experiments to assess the effects of time constraints on the costs and benefits of prioritization techniques. Our first experiment manipulates time constraint levels and shows that time constraints do play a significant role in determining both the cost-effectiveness of prioritization and the relative cost-benefit trade-offs among techniques. Our second experiment replicates the first experiment, controlling for several threats to validity including numbers of faults present, and shows that the results generalize to this wider context. Our third experiment manipulates the number of faults present in programs to examine the effects of faultiness levels on prioritization and shows that faultiness level affects the relative cost-effectiveness of prioritization techniques. Taken together, these results have several implications for test engineers wishing to cost-effectively regression test their software systems. These include suggestions about when and when not to prioritize, what techniques to employ, and how differences in testing processes may relate to prioritization cost--effectiveness.

Fast Coalescent-Based Computation of Local Branch Support from Quartet Frequencies

Species tree reconstruction is complicated by effects of incomplete lineage sorting, commonly modeled by the multi-species coalescent model (MSC). While there has been substantial progress in developing methods that estimate a species tree given a collection of gene trees, less attention has been paid to fast and accurate methods of quantifying support. In this article, we propose a fast algorithm to compute quartet-based support for each branch of a given species tree with regard to a given set of gene trees. We then show how the quartet support can be used in the context of the MSC to compute (1) the local posterior probability (PP) that the branch is in the species tree and (2) the length of the branch in coalescent units. We evaluate the precision and recall of the local PP on a wide set of simulated and biological datasets, and show that it has very high precision and improved recall compared with multi-locus bootstrapping. The estimated branch lengths are highly accurate when gene tree estimation error is low, but are underestimated when gene tree estimation error increases. Computation of both the branch length and local PP is implemented as new features in ASTRAL.

An empirical study of the effect of time constraints on the cost-benefits of regression testing

Regression testing is an expensive process used to validate modified software. Test case prioritization techniques improve the cost-effectiveness of regression testing by ordering test cases such that those that are more important are run earlier in the testing process. Many prioritization techniques have been proposed and evidence shows that they can be beneficial. It has been suggested, however, that the time constraints that can be imposed on regression testing by various software development processes can strongly affect the behavior of prioritization techniques. Therefore, we conducted an experiment to assess the effects of time constraints on the costs and benefits of prioritization techniques. Our results show that time constraints can indeed play a significant role in determining both the cost-effectiveness of prioritization, and the relative cost-benefit tradeoffs among techniques, with important implications for the use of prioritization in practice.

PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences

We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate--slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory.

The Interrelationships of Placental Mammals and the Limits of Phylogenetic Inference

Placental mammals comprise three principal clades: Afrotheria (e.g., elephants and tenrecs), Xenarthra (e.g., armadillos and sloths), and Boreoeutheria (all other placental mammals), the relationships among which are the subject of controversy and a touchstone for debate on the limits of phylogenetic inference. Previous analyses have found support for all three hypotheses, leading some to conclude that this phylogenetic problem might be impossible to resolve due to the compounded effects of incomplete lineage sorting (ILS) and a rapid radiation. Here we show, using a genome scale nucleotide data set, microRNAs, and the reanalysis of the three largest previously published amino acid data sets, that the root of Placentalia lies between Atlantogenata and Boreoeutheria. Although we found evidence for ILS in early placental evolution, we are able to reject previous conclusions that the placental root is a hard polytomy that cannot be resolved. Reanalyses of previous data sets recover Atlantogenata + Boreoeutheria and show that contradictory results are a consequence of poorly fitting evolutionary models; instead, when the evolutionary process is better-modeled, all data sets converge on Atlantogenata. Our Bayesian molecular clock analysis estimates that marsupials diverged from placentals 157–170 Ma, crown Placentalia diverged 86–100 Ma, and crown Atlantogenata diverged 84–97 Ma. Our results are compatible with placental diversification being driven by dispersal rather than vicariance mechanisms, postdating early phases in the protracted opening of the Atlantic Ocean.