TREECON: A software package for the construction and drawing of evolutionary trees

A package of programs (run by a management program called TREECON)was developed for the construction and drawing of evolutionarytrees. The program MATRIX calculates dissimilarity values andcan perform bootstrap analysis on nucleic acid sequences. TREEimplements different evolutionary tree constructing methodsbased on distance matrices. Because some of these methods produceunrooted evolutionary trees, a program ROOT places a root onthe tree. Finally, the program DRAW draws the evolutionary tree,changes its size or topology, and produces drawings suitablefor publication. Whereas MATRIX is suited only for nucleic acids,the modules TREE, ROOT and DRAW are applicable to any kind ofdissimilarity matrix. The programs run on IBM-compatible microcomputersusing the DOS operating system.     

A practical method for calculating evolutionary trees from sequence data

In a previous paper (Klotz et a1., 1979) we described a method for determining evolutionary trees from sequence data when rates of evolution of the sequences might differ greatly. It was shown theoretically that the method always gave the correct topology and root when the exact number of mutation differences between sequences and from their common ancestor was known. However, the method is impractical to use in most situations because it requires some knowledge of the ancestor. In this present paper we describe another method, related to the previous one, in which a present-day sequence can serve temporarily as an ancestor for purposes of determining the evolutionary tree regardless of the rates of evolution of the sequences involved. This new method can be carried out with high precision without the aid of a computer, and it does not increase in difficulty rapidly as the number of sequences involved in the study increases, unlike other methods.     

Progress with methods for constructing evolutionary trees

Evolutionists dream of a tree-reconstruction method that is efficient (fast), powerful, consistent, robust and falsifiable. These criteria are at present conflicting in that the fastest methods are weak (in their use of information in the sequences) and inconsistent (even with very long sequences they may lead to an incorrect tree). But there has been exciting progress in new approaches to tree inference, in understanding general properties of methods, and in developing ideas for estimating the reliability of trees. New phylogenetic invariant methods allow selected parameters of the underlying model to be estimated directly from sequences. There is still a need for more theoretical understanding and assistance in applying what is already known.     

A conflict between two evolutionary levels in trees

Due to the lack of germ line segregation in plants, it is possible to consider plant evolution (but not the evolution of most animals) as being composed of two evolutionary levels: 1. Intra-organism, in which the replicating unit is a part of the tree (e.g. a branch), reproduction is asexual, mutations are somatic, and selection operates only upon traits relevant to vegetative growth. 2. Inter-organism, in which the replicating unit is the whole tree, reproduction is sexual, and selection operates upon all the traits. In this work, a case of a conflict between these two levels is studied. The dynamics of a mutation, which is advantageous on the branch level but harmful for the whole tree, are discussed for a one-locus two-allele model. Several cases are considered: dominant, partially dominant, and haploid. Necessary and sufficient conditions for fixation of such a mutation are found. The model predicts that as the longevity of a tree species increases, the trees are expected to be more strongly shifted from their optimal growth-to-reproduction ratio towards growth, and resource allocation between branches and other tree parts is expected to be shifted in favor of the branches. Traditional approach, considering the second level only, is justified as a limit case for short longevity.     

QDist--quartet distance between evolutionary trees

SUMMARY: QDist is a program for computing the quartet distance between two unrooted trees, i.e. the number of quartet topology differences between the trees, where a quartet topology is the topological subtree induced by four species. The program is based on an algorithm with running time O(n log2 n), which makes it practical to compare large trees. Available under GNU license. AVAILABILITY: http://www.birc.dk/Software/QDist     

Estimation of evolutionary distance for reconstructing molecular phylogenetic trees

The most commonly used measure of evolutionary distance in molecular phylogenetics is the number of nucleotide substitutions per site. However, this number is not necessarily most efficient for reconstructing a phylogenetic tree. In order to evaluate the accuracy of evolutionary distance, D(t), for obtaining the correct tree topology, an accuracy index, A(t), was proposed. This index is defined as D'(t)/square root of[D(t)], where D'(t) is the first derivative of D(t) with respect to evolutionary time and V[D(t)] is the sampling variance of evolutionary distance. Using A(t), namely, finding the condition under which A(t) gives the maximum value, we can obtain an evolutionary distance which is efficient for obtaining the correct topology. Under the assumption that the transversional changes do not occur as frequently as the transitional changes, we obtained the evolutionary distances which are expected to give the correct topology more often than are the other distances.      

Estimating the reliability of evolutionary trees

Six protein sequences from the same 11 mammalian taxa were used to estimate the accuracy and reliability of phylogenetic trees using real, rather than simulated, data. A tree comparison metric was used to measure the increase in similarity of minimal trees as larger, randomly selected subsets of nucleotide positions were taken. The ratio of the observed to the expected number of incompatibilities for each nucleotide position (character) is a good predictor of the number of changes required at that position on the minimal (most-parsimonious) tree. This allows a higher weighting of nucleotide positions that have changed more slowly and should result in the minimal length tree converging to the correct tree as more sequences are obtained. An estimate was made of the smallest subset of trees that need to be considered to include the actual historical tree for a given set of data. It was concluded that it is possible to give a reasonable estimate of the reliability of the final tree, at least when several sequences are combined. With the present data, resolving the rodent- primate-lagomorph (rabbit) trichotomy is the least certain aspect of the final tree, followed then by establishing the position of dog. In our opinion, it is unreasonable to publish an evolutionary tree derived from sequence data without giving an idea of the reliability of the tree.      

A program for at-risk high school students informed by evolutionary science

Improving the academic performance of at-risk high school students has proven difficult, often calling for an extended day, extended school year, and other expensive measures. Here we report the results of a program for at-risk 9th and 10th graders in Binghamton, New York, called the Regents Academy that takes place during the normal school day and year. The design of the program is informed by the evolutionary dynamics of cooperation and learning, in general and for our species as a unique product of biocultural evolution. Not only did the Regents Academy students outperform their comparison group in a randomized control design, but they performed on a par with the average high school student in Binghamton on state-mandated exams. All students can benefit from the social environment provided for at-risk students at the Regents Academy, which is within the reach of most public school districts.     

Variant evolutionary trees under phenotypic variance

Evolutionary branching, which is a coevolutionary phenomenon of the development of two or more distinctive traits from a single trait in a population, is the issue of recent studies on adaptive dynamics. In previous studies, it was revealed that trait variance is a minimum requirement for evolutionary branching, and that it does not play an important role in the formation of an evolutionary pattern of branching. Here we demonstrate that the trait evolution exhibits various evolutionary branching paths starting from an identical initial trait to different evolutional terminus traits as determined by only changing the assumption of trait variance. The key feature of this phenomenon is the topological configuration of equilibria and the initial point in the manifold of dimorphism from which dimorphic branches develop. This suggests that the existing monomorphic or polymorphic set in a population is not an unique inevitable consequence of an identical initial phenotype.     

Haplotype fine mapping by evolutionary trees

To refine the location of a disease gene within the bounds provided by linkage analysis, many scientists use the pattern of linkage disequilibrium between the disease allele and alleles at nearby markers. We describe a method that seeks to refine location by analysis of "disease" and "normal" haplotypes, thereby using multivariate information about linkage disequilibrium. Under the assumption that the disease mutation occurs in a specific gap between adjacent markers, the method first combines parsimony and likelihood to build an evolutionary tree of disease haplotypes, with each node (haplotype) separated, by a single mutational or recombinational step, from its parent. If required, latent nodes (unobserved haplotypes) are incorporated to complete the tree. Once the tree is built, its likelihood is computed from probabilities of mutation and recombination. When each gap between adjacent markers is evaluated in this fashion and these results are combined with prior information, they yield a posterior probability distribution to guide the search for the disease mutation. We show, by evolutionary simulations, that an implementation of these methods, called "FineMap," yields substantial refinement and excellent coverage for the true location of the disease mutation. Moreover, by analysis of hereditary hemochromatosis haplotypes, we show that FineMap can be robust to genetic heterogeneity.     

A simple computer program for calculating, modifying and drawing circular restriction maps.

An HPL program is described which constructs and draws circular restriction maps given a set of cleavage sites, together with deletion of insertion data if required. This program is of great use in the routine interpretation of restriction patterns for the analysis of recombinant DNA molecules.     

BEAST: Bayesian evolutionary analysis by sampling trees

Background  

The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented.     

Quantitative aspects of the estimation of evolutionary trees

Various approaches to the estimation of evolutionary trees are reviewed, with emphasis on recent developments. It is argued that no approach is 'model-free', that is, without some assumptions about the processes of evolutionary change. A statistical approach provides a general framework and it is accepted that cladistic methodology represents a special case within this framework. The idea of evolutionary convergence is examined in the light of recent discussion of the existence of convergence in molecular evolution. It is concluded that attempts to estimate evolutionary trees are justifiable at least on the grounds that, despite present shortcomings, they are the most appropriate way to analyse comparative data. There are good prospects for further progress.     

Ancestral maximum likelihood of evolutionary trees is hard

Maximum likelihood (ML) (Neyman, 1971) is an increasingly popular optimality criterion for selecting evolutionary trees. Finding optimal ML trees appears to be a very hard computational task--in particular, algorithms and heuristics for ML take longer to run than algorithms and heuristics for maximum parsimony (MP). However, while MP has been known to be NP-complete for over 20 years, no such hardness result has been obtained so far for ML. In this work we make a first step in this direction by proving that ancestral maximum likelihood (AML) is NP-complete. The input to this problem is a set of aligned sequences of equal length and the goal is to find a tree and an assignment of ancestral sequences for all of that tree's internal vertices such that the likelihood of generating both the ancestral and contemporary sequences is maximized. Our NP-hardness proof follows that for MP given in (Day, Johnson and Sankoff, 1986) in that we use the same reduction from Vertex Cover; however, the proof of correctness for this reduction relative to AML is different and substantially more involved.