Exploring the relationship between sequence similarity and accurate phylogenetic trees

We have characterized the relationship between accurate phylogenetic reconstruction and sequence similarity, testing whether high levels of sequence similarity can consistently produce accurate evolutionary trees. We generated protein families with known phylogenies using a modified version of the PAML/EVOLVER program that produces insertions and deletions as well as substitutions. Protein families were evolved over a range of 100-400 point accepted mutations; at these distances 63% of the families shared significant sequence similarity. Protein families were evolved using balanced and unbalanced trees, with ancient or recent radiations. In families sharing statistically significant similarity, about 60% of multiple sequence alignments were 95% identical to true alignments. To compare recovered topologies with true topologies, we used a score that reflects the fraction of clades that were correctly clustered. As expected, the accuracy of the phylogenies was greatest in the least divergent families. About 88% of phylogenies clustered over 80% of clades in families that shared significant sequence similarity, using Bayesian, parsimony, distance, and maximum likelihood methods. However, for protein families with short ancient branches (ancient radiation), only 30% of the most divergent (but statistically significant) families produced accurate phylogenies, and only about 70% of the second most highly conserved families, with median expectation values better than 10(-60), produced accurate trees. These values represent upper bounds on expected tree accuracy for sequences with a simple divergence history; proteins from 700 Giardia families, with a similar range of sequence similarities but considerably more gaps, produced much less accurate trees. For our simulated insertions and deletions, correct multiple sequence alignments did not perform much better than those produced by T-COFFEE, and including sequences with expressed sequence tag-like sequencing errors did not significantly decrease phylogenetic accuracy. In general, although less-divergent sequence families produce more accurate trees, the likelihood of estimating an accurate tree is most dependent on whether radiation in the family was ancient or recent. Accuracy can be improved by combining genes from the same organism when creating species trees or by selecting protein families with the best bootstrap values in comprehensive studies.     

Assessing the performance of single-copy genes for recovering robust phylogenies

Phylogenies involving nonmodel species are based on a few genes, mostly chosen following historical or practical criteria. Because gene trees are sometimes incongruent with species trees, the resulting phylogenies may not accurately reflect the evolutionary relationships among species. The increase in availability of genome sequences now provides large numbers of genes that could be used for building phylogenies. However, for practical reasons only a few genes can be sequenced for a wide range of species. Here we asked whether we can identify a few genes, among the single-copy genes common to most fungal genomes, that are sufficient for recovering accurate and well-supported phylogenies. Fungi represent a model group for phylogenomics because many complete fungal genomes are available. An automated procedure was developed to extract single-copy orthologous genes from complete fungal genomes using a Markov Clustering Algorithm (Tribe-MCL). Using 21 complete, publicly available fungal genomes with reliable protein predictions, 246 single-copy orthologous gene clusters were identified. We inferred the maximum likelihood trees using the individual orthologous sequences and constructed a reference tree from concatenated protein alignments. The topologies of the individual gene trees were compared to that of the reference tree using three different methods. The performance of individual genes in recovering the reference tree was highly variable. Gene size and the number of variable sites were highly correlated and significantly affected the performance of the genes, but the average substitution rate did not. Two genes recovered exactly the same topology as the reference tree, and when concatenated provided high bootstrap values. The genes typically used for fungal phylogenies did not perform well, which suggests that current fungal phylogenies based on these genes may not accurately reflect the evolutionary relationships among species. Analyses on subsets of species showed that the phylogenetic performance did not seem to depend strongly on the sample. We expect that the best-performing genes identified here will be very useful for phylogenetic studies of fungi, at least at a large taxonomic scale. Furthermore, we compare the method developed here for finding genes for building robust phylogenies with previous ones and we advocate that our method could be applied to other groups of organisms when more complete genomes are available.     

Phylogenomics using low‐depth whole genome sequencing: A case study with the olive tribe

Species trees have traditionally been inferred from a few selected markers, and genome‐wide investigations remain largely restricted to model organisms or small groups of species for which sampling of fresh material is available, leaving out most of the existing and historical species diversity. The genomes of an increasing number of species, including specimens extracted from natural history collections, are being sequenced at low depth. While these data sets are widely used to analyse organelle genomes, the nuclear fraction is generally ignored. Here we evaluate different reference‐based methods to infer phylogenies of large taxonomic groups from such data sets. Using the example of the Oleeae tribe, a worldwide‐distributed group, we build phylogenies based on single nucleotide polymorphisms (SNPs) obtained using two reference genomes (the olive and ash trees). The inferred phylogenies are overall congruent, yet present differences that might reflect the effect of distance to the reference on the amount of missing data. To limit this issue, genome complexity was reduced by using pairs of orthologous coding sequences as the reference, thus allowing us to combine SNPs obtained using two distinct references. Concatenated and coalescence trees based on these combined SNPs suggest events of incomplete lineage sorting and/or hybridization during the diversification of this large phylogenetic group. Our results show that genome‐wide phylogenetic trees can be inferred from low‐depth sequence data sets for eukaryote groups with complex genomes, and histories of reticulate evolution. This opens new avenues for large‐scale phylogenomics and biogeographical analyses covering both the extant and the historical diversity stored in museum collections.     

A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis

Background  

To date, most fungal phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increase in fungal genome sequencing presents an opportunity to reconstruct evolutionary events using entire genomes. As a tool for future comparative, phylogenomic and phylogenetic studies, we used both supertrees and concatenated alignments to infer relationships between 42 species of fungi for which complete genome sequences are available.     

A comprehensive vertebrate phylogeny using vector representations of protein sequences from whole genomes

We recently developed a method for producing comprehensive gene and species phylogenies from unaligned whole genome data using singular value decomposition (SVD) to analyze character string frequencies. This work provides an integrated gene and species phylogeny for 64 vertebrate mitochondrial genomes composed of 832 total proteins. In addition, to provide a theoretical basis for the method, we present a graphical interpretation of both the original frequency matrix and the SVD-derived matrix. These large matrices describe high-dimensional Euclidean spaces within which biomolecular sequences can be uniquely represented as vectors. In particular, the SVD-derived vector space describes each protein relative to a restricted set of newly defined, independent axes, each of which represents a novel form of conserved motif, termed a correlated peptide motif. A quantitative comparison of the relative orientations of protein vectors in this space provides accurate and straightforward estimates of sequence similarity, which can in turn be used to produce comprehensive gene trees. Alternatively, the vector representations of genes from individual species can be summed, allowing species trees to be produced.     

HIV-specific probabilistic models of protein evolution

Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1) genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1-the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic error. We argue that our model derivation procedure is immediately applicable to other organisms with extensive sequence data available, such as Hepatitis C and Influenza A viruses.     

Complete mitochondrial genome DNA sequence for two ophiuroids and a holothuroid: the utility of protein gene sequence and gene maps in the analyses of deep deuterostome phylogeny

The complete mitochondrial genome sequences have been determined for the holothuroid Cucumaria miniata and two ophiuroid species Ophiopholis aculeata and Ophiura lütkeni. In addition, the nucleotide sequence of the mitochondrial protein-coding genes for the asteroid Pisaster ochraceus has been completed. Maximum-likelihood and LogDet distance analyses of concatenated protein-coding sequences produced a series of trees that did not conclusively support generally accepted models of echinoderm phylogeny. The ophiuroid data consistently demonstrated accelerated nucleotide divergence rates and lack of stationarity. This confounds the phylogenetic analyses. Molecular investigations using individual protein-coding gene alignments demonstrated that the cytochrome b gene exhibits the least deviation in rate and stationarity and generated some trees consistent with proposed echinoderm phylogenies. Phylogenies based on echinoderm mitochondrial gene rearrangements also proved problematic because of extensive variation in gene order between and within classes. A comparison of the two distinctive ophiuroid mitochondrial gene orders supports the hypothesis that O. lütkeni has a more derived mitochondrial gene order versus O. aculeata. The variation in the echinoderm mitochondrial gene maps reinforces the limitations of the application of mitochondrial gene rearrangements as a global phylogenetic tool.     

DendroBLAST: Approximate Phylogenetic Trees in the Absence of Multiple Sequence Alignments

The rapidly growing availability of genome information has created considerable demand for both fast and accurate phylogenetic inference algorithms. We present a novel method called DendroBLAST for reconstructing phylogenetic dendrograms/trees from protein sequences using BLAST. This method differs from other methods by incorporating a simple model of sequence evolution to test the effect of introducing sequence changes on the reliability of the bipartitions in the inferred tree. Using realistic simulated sequence data we demonstrate that this method produces phylogenetic trees that are more accurate than other commonly-used distance based methods though not as accurate as maximum likelihood methods from good quality multiple sequence alignments. In addition to tests on simulated data, we use DendroBLAST to generate input trees for a supertree reconstruction of the phylogeny of the Archaea. This independent analysis produces an approximate phylogeny of the Archaea that has both high precision and recall when compared to previously published analysis of the same dataset using conventional methods. Taken together these results demonstrate that approximate phylogenetic trees can be produced in the absence of multiple sequence alignments, and we propose that these trees will provide a platform for improving and informing downstream bioinformatic analysis. A web implementation of the DendroBLAST method is freely available for use at http://www.dendroblast.com/.     

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.     

The Tree versus the Forest: The Fungal Tree of Life and the Topological Diversity within the Yeast Phylome

A recurrent topic in phylogenomics is the combination of various sequence alignments to reconstruct a tree that describes the evolutionary relationships within a group of species. However, such approach has been criticized for not being able to properly represent the topological diversity found among gene trees. To evaluate the representativeness of species trees based on concatenated alignments, we reconstruct several fungal species trees and compare them with the complete collection of phylogenies of genes encoded in the Saccharomyces cerevisiae genome. We found that, despite high levels of among-gene topological variation, the species trees do represent widely supported phylogenetic relationships. Most topological discrepancies between gene and species trees are concentrated in certain conflicting nodes. We propose to map such information on the species tree so that it accounts for the levels of congruence across the genome. We identified the lack of sufficient accuracy of current alignment and phylogenetic methods as an important source for the topological diversity encountered among gene trees. Finally, we discuss the implications of the high levels of topological variation for phylogeny-based orthology prediction strategies.     

Use of whole genome sequence data to infer baculovirus phylogeny

Several phylogenetic methods based on whole genome sequence data were evaluated using data from nine complete baculovirus genomes. The utility of three independent character sets was assessed. The first data set comprised the sequences of the 63 genes common to these viruses. The second set of characters was based on gene order, and phylogenies were inferred using both breakpoint distance analysis and a novel method developed here, termed neighbor pair analysis. The third set recorded gene content by scoring gene presence or absence in each genome. All three data sets yielded phylogenies supporting the separation of the Nucleopolyhedrovirus (NPV) and Granulovirus (GV) genera, the division of the NPVs into groups I and II, and species relationships within group I NPVs. Generation of phylogenies based on the combined sequences of all 63 shared genes proved to be the most effective approach to resolving the relationships among the group II NPVs and the GVs. The history of gene acquisitions and losses that have accompanied baculovirus diversification was visualized by mapping the gene content data onto the phylogenetic tree. This analysis highlighted the fluid nature of baculovirus genomes, with evidence of frequent genome rearrangements and multiple gene content changes during their evolution. Of more than 416 genes identified in the genomes analyzed, only 63 are present in all nine genomes, and 200 genes are found only in a single genome. Despite this fluidity, the whole genome-based methods we describe are sufficiently powerful to recover the underlying phylogeny of the viruses.     

A novel method of characterizing genetic sequences: genome space with biological distance and applications

Background

Most existing methods for phylogenetic analysis involve developing an evolutionary model and then using some type of computational algorithm to perform multiple sequence alignment. There are two problems with this approach: (1) different evolutionary models can lead to different results, and (2) the computation time required for multiple alignments makes it impossible to analyse the phylogeny of a whole genome. This motivates us to create a new approach to characterize genetic sequences.

Methodology

To each DNA sequence, we associate a natural vector based on the distributions of nucleotides. This produces a one-to-one correspondence between the DNA sequence and its natural vector. We define the distance between two DNA sequences to be the distance between their associated natural vectors. This creates a genome space with a biological distance which makes global comparison of genomes with same topology possible. We use our proposed method to analyze the genomes of the new influenza A (H1N1) virus, human rhinoviruses (HRV) and mammalian mitochondrial. The result shows that a triple-reassortant swine virus circulating in North America and the Eurasian swine virus belong to the lineage of the influenza A (H1N1) virus. For the HRV and mammalian mitochondrial genomes, the results coincide with biologists'' analyses.

Conclusions

Our approach provides a powerful new tool for analyzing and annotating genomes and their phylogenetic relationships. Whole or partial genomes can be handled more easily and more quickly than using multiple alignment methods. Once a genome space has been constructed, it can be stored in a database. There is no need to reconstruct the genome space for subsequent applications, whereas in multiple alignment methods, realignment is needed to add new sequences. Furthermore, one can make a global comparison of all genomes simultaneously, which no other existing method can achieve.     

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.     

Gene's Functional Arrangement as a Measure of thePhylogenetic Relationships of Microorganisms

With the development of genome sequencing more whole genomes of microorganisms were completed, many methods wereintroduced to reconstruct the phylogenetic tree of those microorganismswith the information extracted from the whole genomes through variousways of transforming or mapping the whole genome sequences into otherforms which can describe the evolutionary distance in a new way. We thinkit might be possible that there exists information buried in the wholegenome transferred along lineage, which remains stable and is moreessential than sequence conservation of individual genes or the arrangementof some genes of a selected set. We need to find one measurement that caninvolve as many phylogenetic features as possible that are beyond thegenome sequence itself. We converted each genome sequence of themicroorganisms into another linear sequence to represent the functionalstructure of the sequence, and we used a new information function tocalculate the discrepancy of sequences and to get one distance matrix of thegenomes, and built one phylogenetic tree with a neighbor joining method.The resulting tree shows that the major lineages are consistent with theresult based on their 16srRNA sequences. Our method discovered onephylogenetic feature derived from the genome sequences and the encodedgenes that can rebuild the phylogenetic tree correctly. The mapping of onegenome sequence to its new form representing the relative positions of thefunctional genes provides a new way to measure the phylogeneticrelationships, and with the more specific classification of gene functions theresult could be more sensitive.     

Insertions and deletions as phylogenetic signal in an alignment-free context

Most methods for phylogenetic tree reconstruction are based on sequence alignments; they infer phylogenies from substitutions that may have occurred at the aligned sequence positions. Gaps in alignments are usually not employed as phylogenetic signal. In this paper, we explore an alignment-free approach that uses insertions and deletions (indels) as an additional source of information for phylogeny inference. For a set of four or more input sequences, we generate so-called quartet blocks of four putative homologous segments each. For pairs of such quartet blocks involving the same four sequences, we compare the distances between the two blocks in these sequences, to obtain hints about indels that may have happened between the blocks since the respective four sequences have evolved from their last common ancestor. A prototype implementation that we call Gap-SpaM is presented to infer phylogenetic trees from these data, using a quartet-tree approach or, alternatively, under the maximum-parsimony paradigm. This approach should not be regarded as an alternative to established methods, but rather as a complementary source of phylogenetic information. Interestingly, however, our software is able to produce phylogenetic trees from putative indels alone that are comparable to trees obtained with existing alignment-free methods.     

Genome classification improvements based on k-mer intervals in sequences

Given the vast amount of genomic data, alignment-free sequence comparison methods are required due to their low computational complexity. k-mer based methods can improve comparison accuracy by extracting an effective feature of the genome sequences. The aim of this paper is to extract k-mer intervals of a sequence as a feature of a genome for high comparison accuracy. In the proposed method, we calculated the distance between genome sequences by comparing the distribution of k-mer intervals. Then, we identified the classification results using phylogenetic trees. We used viral, mitochondrial (MT), microbial and mammalian genome sequences to perform classification for various genome sets. We confirmed that the proposed method provides a better classification result than other k-mer based methods. Furthermore, the proposed method could efficiently be applied to long sequences such as human and mouse genomes.     

Anchor-Based Whole Genome Phylogeny (ABWGP): A Tool for Inferring Evolutionary Relationship among Closely Related Microorganims

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.