Gene tree parsimony vs uninode coding for phylogenetic reconstruction

have suggested that there are important weaknesses of gene tree parsimony in reconstructing phylogeny in the face of gene duplication, weaknesses that are addressed by method of uninode coding. Here, we discuss Simmons and Freudenstein's criticisms and suggest a number of reasons why gene tree parsimony is preferable to uninode coding. During this discussion we introduce a number of recent developments of gene tree parsimony methods overlooked by Simmons and Freudenstein. Finally, we present a re-analysis of data from that produces a more reasonable phylogeny than that found by Simmons and Freudenstein, suggesting that gene tree parsimony outperforms uninode coding, at least on these data.     

Algorithms for efficient near-perfect phylogenetic tree reconstruction in theory and practice

We consider the problem of reconstructing near-perfect phylogenetic trees using binary character states (referred to as BNPP). A perfect phylogeny assumes that every character mutates at most once in the evolutionary tree, yielding an algorithm for binary character states that is computationally efficient but not robust to imperfections in real data. A near-perfect phylogeny relaxes the perfect phylogeny assumption by allowing at most a constant number of additional mutations. We develop two algorithms for constructing optimal near-perfect phylogenies and provide empirical evidence of their performance. The first simple algorithm is fixed parameter tractable when the number of additional mutations and the number of characters that share four gametes with some other character are constants. The second, more involved algorithm for the problem is fixed parameter tractable when only the number of additional mutations is fixed. We have implemented both algorithms and shown them to be extremely efficient in practice on biologically significant data sets. This work proves the BNPP problem fixed parameter tractable and provides the first practical phylogenetic tree reconstruction algorithms that find guaranteed optimal solutions while being easily implemented and computationally feasible for data sets of biologically meaningful size and complexity.     

Disk-covering, a fast-converging method for phylogenetic tree reconstruction.

The evolutionary history of a set of species is represented by a phylogenetic tree, which is a rooted, leaf-labeled tree, where internal nodes represent ancestral species and the leaves represent modern day species. Accurate (or even boundedly inaccurate) topology reconstructions of large and divergent trees from realistic length sequences have long been considered one of the major challenges in systematic biology. In this paper, we present a simple method, the Disk-Covering Method (DCM), which boosts the performance of base phylogenetic methods under various Markov models of evolution. We analyze the performance of DCM-boosted distance methods under the Jukes-Cantor Markov model of biomolecular sequence evolution, and prove that for almost all trees, polylogarithmic length sequences suffice for complete accuracy with high probability, while polynomial length sequences always suffice. We also provide an experimental study based upon simulating sequence evolution on model trees. This study confirms substantial reductions in error rates at realistic sequence lengths.     

On the repeat-annotated phylogenetic tree reconstruction problem.

A new problem in phylogenetic inference is presented, based on recent biological findings indicating a strong association between reversals (i.e., inversions) and repeats. These biological findings are formalized here in a new mathematical model, called repeat-annotated phylogenetic trees (RAPT). We show that, under RAPT, the evolutionary process--including both the tree-topology as well as internal node genome orders--is uniquely determined, a property that is of major significance both in theory and in practice. Furthermore, the repeats are employed to provide linear-time algorithms for reconstructing both the genomic orders and the phylogeny, which are NP-hard problems under the classical model of sorting by reversals (SBR).     

Assessment of protein distance measures and tree-building methods for phylogenetic tree reconstruction

Distance-based methods are popular for reconstructing evolutionary trees of protein sequences, mainly because of their speed and generality. A number of variants of the classical neighbor-joining (NJ) algorithm have been proposed, as well as a number of methods to estimate protein distances. We here present a large-scale assessment of performance in reconstructing the correct tree topology for the most popular algorithms. The programs BIONJ, FastME, Weighbor, and standard NJ were run using 12 distance estimators, producing 48 tree-building/distance estimation method combinations. These were evaluated on a test set based on real trees taken from 100 Pfam families. Each tree was used to generate multiple sequence alignments with the ROSE program using three evolutionary models. The accuracy of each method was analyzed as a function of both sequence divergence and location in the tree. We found that BIONJ produced the overall best results, although the average accuracy differed little between the tree-building methods (normally less than 1%). A noticeable trend was that FastME performed poorer than the rest on long branches. Weighbor was several orders of magnitude slower than the other programs. Larger differences were observed when using different distance estimators. Protein-adapted Jukes-Cantor and Kimura distance correction produced clearly poorer results than the other methods, even worse than uncorrected distances. We also assessed the recently developed Scoredist measure, which performed equally well as more complex methods.     

A short proof that phylogenetic tree reconstruction by maximum likelihood is hard

Maximum likelihood is one of the most widely used techniques to infer evolutionary histories. Although it is thought to be intractable, a proof of its hardness has been lacking. Here, we give a short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.     

Anchoring quartet-based phylogenetic distances and applications to species tree reconstruction

Background

Inferring species trees from gene trees using the coalescent-based summary methods has been the subject of much attention, yet new scalable and accurate methods are needed.

Results

We introduce DISTIQUE, a new statistically consistent summary method for inferring species trees from gene trees under the coalescent model. We generalize our results to arbitrary phylogenetic inference problems; we show that two arbitrarily chosen leaves, called anchors, can be used to estimate relative distances between all other pairs of leaves by inferring relevant quartet trees. This results in a family of distance-based tree inference methods, with running times ranging between quadratic to quartic in the number of leaves.

Conclusions

We show in simulated studies that DISTIQUE has comparable accuracy to leading coalescent-based summary methods and reduced running times.

     

Generalized neighbor-joining: more reliable phylogenetic tree reconstruction.

We have developed a phylogenetic tree reconstruction method that detects and reports multiple topologically distant low-cost solutions. Our method is a generalization of the neighbor-joining method of Saitou and Nei and affords a more thorough sampling of the solution space by keeping track of multiple partial solutions during its execution. The scope of the solution space sampling is controlled by a pair of user-specified parameters--the total number of alternate solutions and the number of alternate solutions that are randomly selected--effecting a smooth trade-off between run time and solution quality and diversity. This method can discover topologically distinct low-cost solutions. In tests on biological and synthetic data sets using either the least-squares distance or minimum-evolution criterion, the method consistently performed as well as, or better than, both the neighbor-joining heuristic and the PHYLIP implementation of the Fitch-Margoliash distance measure. In addition, the method identified alternative tree topologies with costs within 1% or 2% of the best, but with topological distances of 9 or more partitions from the best solution (16 taxa); with 32 taxa, topologies were obtained 17 (least-squares) and 22 (minimum-evolution) partitions from the best topology when 200 partial solutions were retained. Thus, the method can find lower-cost tree topologies and near-best tree topologies that are significantly different from the best topology.     

On a functional-morphological approach to phylogenetic reconstruction: A critique

A method of phylogenetic reconstruction as proposed by a number of scientists of the Senckenberg Research Institute is discussed. The method is based on functional-morphological studies, the evolutionary adaptation principle of Bock and Von Wahlert (1965) and so-called model reconstruction. It is argued in this paper that direction of the adaptation process cannot be determined because of lack of knowledge about particular selective forces and that theories of model reconstruction are not open to contradiction in the sense of Popperian falsification. Although it has been claimed that the method provides the only valid directional argument for morphoclines in cladistic studies, it remains unclear how to proceed when morphoclines show contradictory polarities. Moreover, it is doubtful whether polarities of morphoclines can be determined independently of phylogenetic hypotheses, and also whether the use of multistate morphoclines is methodologically valid. By relying on a particular evolutionary theory, i.e. the neo-Darwinian theory, and consequently assigning natural selection as the major agent of directional progress, the Senckenburg method of phylogenetic reconstruction restricts itself to microevolutionary change and, therefore, cannot be used when other hypotheses on the evolutionary process appear to explain the speciation process more plausibly, i.e. hypotheses on macroevolution. Furthermore, it is an unproved statement that evolution always proceeds according to the principle of economy.     

A hybrid micro-macroevolutionary approach to gene tree reconstruction.

Gene family evolution is determined by microevolutionary processes (e.g., point mutations) and macroevolutionary processes (e.g., gene duplication and loss), yet macroevolutionary considerations are rarely incorporated into gene phylogeny reconstruction methods. We present a dynamic program to find the most parsimonious gene family tree with respect to a macroevolutionary optimization criterion, the weighted sum of the number of gene duplications and losses. The existence of a polynomial delay algorithm for duplication/loss phylogeny reconstruction stands in contrast to most formulations of phylogeny reconstruction, which are NP-complete. We next extend this result to obtain a two-phase method for gene tree reconstruction that takes both micro- and macroevolution into account. In the first phase, a gene tree is constructed from sequence data, using any of the previously known algorithms for gene phylogeny construction. In the second phase, the tree is refined by rearranging regions of the tree that do not have strong support in the sequence data to minimize the duplication/lost cost. Components of the tree with strong support are left intact. This hybrid approach incorporates both micro- and macroevolutionary considerations, yet its computational requirements are modest in practice because the two-phase approach constrains the search space. Our hybrid algorithm can also be used to resolve nonbinary nodes in a multifurcating gene tree. We have implemented these algorithms in a software tool, NOTUNG 2.0, that can be used as a unified framework for gene tree reconstruction or as an exploratory analysis tool that can be applied post hoc to any rooted tree with bootstrap values. The NOTUNG 2.0 graphical user interface can be used to visualize alternate duplication/loss histories, root trees according to duplication and loss parsimony, manipulate and annotate gene trees, and estimate gene duplication times. It also offers a command line option that enables high-throughput analysis of a large number of trees.     

Uninode coding vs gene tree parsimony for phylogenetic reconstruction using duplicate genes

Two different methods of using paralogous genes for phylogenetic inference have been proposed: reconciled trees (or gene tree parsimony) and uninode coding. Gene tree parsimony suffers from 10 serious problems, including differential weighting of nucleotide and gap characters, undersampling which can be misinterpreted as synapomorphy, all of the characters not being allowed to interact, and conflict between gene trees being given equal weight, regardless of branch support. These problems are largely avoided by using uninode coding. The uninode coding method is elaborated to address multiple gene duplications within a single gene tree family and handle problems caused by lack of gene tree resolution. An example of vertebrate phylogeny inferred from nine genes is reanalyzed using uninode coding. We suggest that uninode coding be used instead of gene tree parsimony for phylogenetic inference from paralogous genes.     

A new sequence distance measure for phylogenetic tree construction

MOTIVATION: Most existing approaches for phylogenetic inference use multiple alignment of sequences and assume some sort of an evolutionary model. The multiple alignment strategy does not work for all types of data, e.g. whole genome phylogeny, and the evolutionary models may not always be correct. We propose a new sequence distance measure based on the relative information between the sequences using Lempel-Ziv complexity. The distance matrix thus obtained can be used to construct phylogenetic trees. RESULTS: The proposed approach does not require sequence alignment and is totally automatic. The algorithm has successfully constructed consistent phylogenies for real and simulated data sets. AVAILABILITY: Available on request from the authors.     

LZ complexity distance of DNA sequences and its application in phylogenetic tree reconstruction

DNA sequences can be treated as finite-length symbol strings over a four-letter alphabet （A, C, T, G）. As a universal and computable complexity measure, LZ complexity is valid to describe the complexity of DNA sequences. In this study, a concept of conditional LZ complexity between two sequences is proposed according to the principle of LZ complexity measure. An LZ complexity distance metric between two nonnull sequences is defined by utilizing conditional LZ complexity. Based on LZ complexity distance, a phylogenetic tree of 26 species of placental mammals （Eutheria） with three outgroup species was reconstructed from their complete mitochondrial genomes. On the debate that which two of the three main groups of placental mammals, namely Primates, Ferungulates, and Rodents, are more closely related, the phylogenetic tree reconstructed based on LZ complexity distance supports the suggestion that Primates and Ferungulates are more closely related.     

Performance comparison between k-tuple distance and four model-based distances in phylogenetic tree reconstruction

Phylogenetic tree reconstruction requires construction of a multiple sequence alignment (MSA) from sequences. Computationally, it is difficult to achieve an optimal MSA for many sequences. Moreover, even if an optimal MSA is obtained, it may not be the true MSA that reflects the evolutionary history of the underlying sequences. Therefore, errors can be introduced during MSA construction which in turn affects the subsequent phylogenetic tree construction. In order to circumvent this issue, we extend the application of the k-tuple distance to phylogenetic tree reconstruction. The k-tuple distance between two sequences is the sum of the differences in frequency, over all possible tuples of length k, between the sequences and can be estimated without MSAs. It has been traditionally used to build a fast ‘guide tree’ to assist the construction of MSAs. Using the 1470 simulated sets of sequences generated under different evolutionary scenarios, the neighbor-joining trees and BioNJ trees, we compared the performance of the k-tuple distance with four commonly used distance estimators including Jukes–Cantor, Kimura, F84 and Tamura–Nei. These four distance estimators fall into the category of model-based distance estimators, as each of them takes account of a specific substitution model in order to compute the distance between a pair of already aligned sequences. Results show that trees constructed from the k-tuple distance are more accurate than those from other distances most time; when the divergence between underlying sequences is high, the tree accuracy could be twice or higher using the k-tuple distance than other estimators. Furthermore, as the k-tuple distance voids the need for constructing an MSA, it can save tremendous amount of time for phylogenetic tree reconstructions when the data include a large number of sequences.     

Bayes estimators for phylogenetic reconstruction

Tree reconstruction methods are often judged by their accuracy, measured by how close they get to the true tree. Yet, most reconstruction methods like maximum likelihood (ML) do not explicitly maximize this accuracy. To address this problem, we propose a Bayesian solution. Given tree samples, we propose finding the tree estimate that is closest on average to the samples. This "median" tree is known as the Bayes estimator (BE). The BE literally maximizes posterior expected accuracy, measured in terms of closeness (distance) to the true tree. We discuss a unified framework of BE trees, focusing especially on tree distances that are expressible as squared euclidean distances. Notable examples include Robinson-Foulds (RF) distance, quartet distance, and squared path difference. Using both simulated and real data, we show that BEs can be estimated in practice by hill-climbing. In our simulation, we find that BEs tend to be closer to the true tree, compared with ML and neighbor joining. In particular, the BE under squared path difference tends to perform well in terms of both path difference and RF distances.     

A tree kernel to analyse phylogenetic profiles

MOTIVATION: The phylogenetic profile of a protein is a string that encodes the presence or absence of the protein in every fully sequenced genome. Because proteins that participate in a common structural complex or metabolic pathway are likely to evolve in a correlated fashion, the phylogenetic profiles of such proteins are often 'similar' or at least 'related' to each other. The question we address in this paper is the following: how to measure the 'similarity' between two profiles, in an evolutionarily relevant way, in order to develop efficient function prediction methods? RESULTS: We show how the profiles can be mapped to a high-dimensional vector space which incorporates evolutionarily relevant information, and we provide an algorithm to compute efficiently the inner product in that space, which we call the tree kernel. The tree kernel can be used by any kernel-based analysis method for classification or data mining of phylogenetic profiles. As an application a Support Vector Machine (SVM) trained to predict the functional class of a gene from its phylogenetic profile is shown to perform better with the tree kernel than with a naive kernel that does not include any information about the phylogenetic relationships among species. Moreover a kernel principal component analysis (KPCA) of the phylogenetic profiles illustrates the sensitivity of the tree kernel to evolutionarily relevant variations.     

基于k-mer组分信息的系统发生树构建方法

随着越来越多基因组的测序完成,基于全基因组的非比对的系统发生分析已成为研究热点。不同的生物物种或个体基因组之间的核酸组分不完全相同。遗传语言-DNA序列的信息很大程度上反映在其k—mer频数中。基于基因组序列k-mer频数的系统发生树则从新的角度为我们提供物种之间的亲缘关系。本文定义基于k-mer,频数的信息参数,并用它表征基因组序列,计算不同基因组之间信息参数的距离,用邻接法对84个病毒构建了系统发生树,发现构建的系统发生树很大程度上与已有的系统发生树相吻合。     

Interactive visualization software for exploring phylogenetic trees and clades

Summary: The Summary Tree Explorer (STE) is a Java applicationfor interactively exploring sets of phylogenetic trees usingtwo coupled representations: a node-and-link diagram and a textuallist of common clades. Selection, pruning, filtering or re-rootingin one representation is immediately reflected in the other.While summary trees are more effective at showing the relationshipamong clades, they can only show a consistent subset of thosethat appear in the textual list. Working with both representationsmitigates the disadvantages of having to choose just one. Availability: STE, along with several sample datasets, is availableat http://cityscape.inf.cs.cmu.edu/phylogeny/ Contact: mad{at}cs.cmu.edu Associate Editor: Martin Bishop