Correspondence of function and phylogeny of ABC proteins based on an automated analysis of 20 model protein data sets

Using our BLAST-based procedure RiPE (Retrieval-induced Phylogeny Environment), which automates the evolutionary analysis of a protein family, we assembled a set of 1138 ABC protein components [adenosine triphosphate (ATP)-binding cassette and transmembrane domain] from the protein data sets of 20 model organisms and subjected them to phylogenetic and functional analysis. For maximum speed, we based the alignment directly on a homology search with a profile of all known human ABC proteins and used neighbor-joining tree estimation. All but 11 sequences from Homo sapiens, Arabidopsis thaliana, Drosophila melanogaster, and Saccharomyces cerevisiae were placed into the correct subtree/subfamily, reproducing published classifications of the individual organisms. By following a simple "function transfer rule", our comparative phylogenetic analysis successfully predicted the known function of human ABC proteins in 19 of 22 cases. Three functional predictions did not correspond, and 10 were novel. Predictions based on BLAST alone were inferior in five cases and superior in two. Bacterial sequences were placed close to the root of most subtrees. This placement coincides with domain architecture, suggesting an early diversification of the ABC family before the kingdoms split apart. Our approach can, in principle, be used to annotate any protein family of any organism included in the study.     

Diatom phylogenetics inferred based on direct optimization of nuclear-encoded SSU rRNA sequences

Direct optimization (DO) of 126 nuclear‐encoded SSU rRNA diatom sequences was conducted. The optimal phylogeny indicated several unique relationships with respect to those recovered from a maximum likelihood (ML) analysis of an alignment based on maximizing primary and secondary structural similarity between 126 nuclear‐encoded SSU rRNA diatom sequences ( Medlin and Kaczmarska, 2004 ). Dividing diatoms into the subdivisions Coscinodiscophytina and Bacillariophytina was not supported by the DO phylogeny, due to the paraphyly of the former. The same pertains to Coscinodiscophyceae, Mediophyceae, Thalassiosira, Fragilaria and Amphora. The ordinal‐level classification of the diatoms proposed by Round et al. (1990 ) was for the most part found to be unsupported. The DO phylogeny represented a more rigorous hypothesis than the ML tree because DO maximized character congruence during the homology testing (i.e., alignment/tree search) process whereas the non‐phylogenetic similarity‐based alignment used in the ML analysis did not. The above statement is supported by “controlled” parsimony analyses of 35 sequences, which strongly suggested that dissimilarities in the DO and ML tree structure were due to the specific homology testing approach used. It could not be precluded that differences in taxon sampling and the use of a dissimilar optimality criteria contributed to discrepancies in the structure of the optimal ML and DO trees.     

Tree pattern matching in phylogenetic trees: automatic search for orthologs or paralogs in homologous gene sequence databases

MOTIVATION: Comparative sequence analysis is widely used to study genome function and evolution. This approach first requires the identification of homologous genes and then the interpretation of their homology relationships (orthology or paralogy). To provide help in this complex task, we developed three databases of homologous genes containing sequences, multiple alignments and phylogenetic trees: HOBACGEN, HOVERGEN and HOGENOM. In this paper, we present two new tools for automating the search for orthologs or paralogs in these databases. RESULTS: First, we have developed and implemented an algorithm to infer speciation and duplication events by comparison of gene and species trees (tree reconciliation). Second, we have developed a general method to search in our databases the gene families for which the tree topology matches a peculiar tree pattern. This algorithm of unordered tree pattern matching has been implemented in the FamFetch graphical interface. With the help of a graphical editor, the user can specify the topology of the tree pattern, and set constraints on its nodes and leaves. Then, this pattern is compared with all the phylogenetic trees of the database, to retrieve the families in which one or several occurrences of this pattern are found. By specifying ad hoc patterns, it is therefore possible to identify orthologs in our databases.     

A sequence sub-sampling algorithm increases the power to detect distant homologues

Searching databases for distant homologues using alignments instead of individual sequences increases the power of detection. However, most methods assume that protein evolution proceeds in a regular fashion, with the inferred tree of sequences providing a good estimation of the evolutionary process. We investigated the combined HMMER search results from random alignment subsets (with three sequences each) drawn from the parent alignment (Rand-shuffle algorithm), using the SCOP structural classification to determine true similarities. At false-positive rates of 5%, the Rand-shuffle algorithm improved HMMER's sensitivity, with a 37.5% greater sensitivity compared with HMMER alone, when easily identified similarities (identifiable by BLAST) were excluded from consideration. An extension of the Rand-shuffle algorithm (Ali-shuffle) weighted towards more informative sequence subsets. This approach improved the performance over HMMER alone and PSI-BLAST, particularly at higher false-positive rates. The improvements in performance of these sequence sub-sampling methods may reflect lower sensitivity to alignment error and irregular evolutionary patterns. The Ali-shuffle and Rand-shuffle sequence homology search programs are available by request from the authors.     

BMT: Bioinformatics mini toolbox for comprehensive DNA and protein analysis

BackgroundBioinformatics tools are of great significance and are used in different spheres of life sciences. There are wide variety of tools available to perform primary analysis of DNA and protein but most of them are available on different platforms and many remain undetected. Accessing these tools separately to perform individual task is uneconomical and inefficient.ObjectiveOur aim is to bring different bioinformatics models on a single platform to ameliorate scientific research. Hence, our objective is to make a tool for comprehensive DNA and protein analysis.MethodsTo develop a reliable, straight-forward and standalone desktop application we used state of the art python packages and libraries. Bioinformatics Mini Toolbox (BMT) is combination of seven tools including FastqTrimmer, Gene Prediction, DNA Analysis, Translation, Protein analysis and Pairwise and Multiple alignment.ResultsFastqTrimmer assists in quality assurance of NGS data. Gene prediction predicts the genes by homology from novel genome on the basis of reference sequence. Protein analysis and DNA analysis calculates physiochemical properties of nucleotide and protein sequences, respectively. Translation translates the DNA sequence into six open reading frames. Pairwise alignment performs pairwise global and local alignment of DNA and protein sequences on the basis or multiple matrices. Multiple alignment aligns multiple sequences and generates a phylogenetic tree.ConclusionWe developed a tool for comprehensive DNA and protein analysis. The link to download BMT is https://github.com/nasiriqbal012/BMT_SETUP.git     

The deterministic effects of alignment bias in phylogenetic inference

Alignment of nucleotide and/or amino acid sequences is a fundamental component of sequence‐based molecular phylogenetic studies. Here we examined how different alignment methods affect the phylogenetic trees that are inferred from the alignments. We used simulations to determine how alignment errors can lead to systematic biases that affect phylogenetic inference from those sequences. We compared four approaches to sequence alignment: progressive pairwise alignment, simultaneous multiple alignment of sequence fragments, local pairwise alignment and direct optimization. When taking into account branch support, implied alignments produced by direct optimization were found to show the most extreme behaviour (based on the alignment programs for which nearly equivalent alignment parameters could be set) in that they provided the strongest support for the correct tree in the simulations in which it was easy to resolve the correct tree and the strongest support for the incorrect tree in our long‐branch‐attraction simulations. When applied to alignment‐sensitive process partitions with different histories, direct optimization showed the strongest mutual influence between the process partitions when they were aligned and phylogenetically analysed together, which makes detecting recombination more difficult. Simultaneous alignment performed well relative to direct optimization and progressive pairwise alignment across all simulations. Rather than relying upon methods that integrate alignment and tree search into a single step without accounting for alignment uncertainty, as with implied alignments, we suggest that simultaneous alignment using the similarity criterion, within the context of information available on biological processes and function, be applied whenever possible for sequence‐based phylogenetic analyses.     

Geno3D: automatic comparative molecular modelling of protein

Geno3D (http://geno3d-pbil.ibcp.fr) is an automatic web server for protein molecular modelling. Starting with a query protein sequence, the server performs the homology modelling in six successive steps: (i) identify homologous proteins with known 3D structures by using PSI-BLAST; (ii) provide the user all potential templates through a very convenient user interface for target selection; (iii) perform the alignment of both query and subject sequences; (iv) extract geometrical restraints (dihedral angles and distances) for corresponding atoms between the query and the template; (v) perform the 3D construction of the protein by using a distance geometry approach and (vi) finally send the results by e-mail to the user.     

Treelength optimization for phylogeny estimation

The standard approach to phylogeny estimation uses two phases, in which the first phase produces an alignment on a set of homologous sequences, and the second phase estimates a tree on the multiple sequence alignment. POY, a method which seeks a tree/alignment pair minimizing the total treelength, is the most widely used alternative to this two-phase approach. The topological accuracy of trees computed under treelength optimization is, however, controversial. In particular, one study showed that treelength optimization using simple gap penalties produced poor trees and alignments, and suggested the possibility that if POY were used with an affine gap penalty, it might be able to be competitive with the best two-phase methods. In this paper we report on a study addressing this possibility. We present a new heuristic for treelength, called BeeTLe (Better Treelength), that is guaranteed to produce trees at least as short as POY. We then use this heuristic to analyze a large number of simulated and biological datasets, and compare the resultant trees and alignments to those produced using POY and also maximum likelihood (ML) and maximum parsimony (MP) trees computed on a number of alignments. In general, we find that trees produced by BeeTLe are shorter and more topologically accurate than POY trees, but that neither POY nor BeeTLe produces trees as topologically accurate as ML trees produced on standard alignments. These findings, taken as a whole, suggest that treelength optimization is not as good an approach to phylogenetic tree estimation as maximum likelihood based upon good alignment methods.     

Tree-based maximal likelihood substitution matrices and hidden Markov models

There has been considerable interest in the problem of making maximum likelihood (ML) evolutionary trees which allow insertions and deletions. This problem is partly one of formulation: how does one define a probabilistic model for such trees which treats insertion and deletion in a biologically plausible manner? A possible answer to this question is proposed here by extending the concept of a hidden Markov model (HMM) to evolutionary trees. The model, called a tree-HMM, allows what may be loosely regarded as learnable affine-type gap penalties for alignments. These penalties are expressed in HMMs as probabilities of transitions between states. In the tree-HMM, this idea is given an evolutionary embodiment by defining trees of transitions. Just as the probability of a tree composed of ungapped sequences is computed, by Felsenstein's method, using matrices representing the probabilities of substitutions of residues along the edges of the tree, so the probabilities in a tree-HMM are computed by substitution matrices for both residues and transitions. How to define these matrices by a ML procedure using an algorithm that learns from a database of protein sequences is shown here. Given these matrices, one can define a tree-HMM likelihood for a set of sequences, assuming a particular tree topology and an alignment of the sequences to the model. If one could efficiently find the alignment which maximizes (or comes close to maximizing) this likelihood, then one could search for the optimal tree topology for the sequences. An alignment algorithm is defined here which, given a particular tree topology, is guaranteed to increase the likelihood of the model. Unfortunately, it fails to find global optima for realistic sequence sets. Thus further research is needed to turn the tree-HMM into a practical phylogenetic tool.     

Analysis of Schistosoma mansoni genes using the expressed sequence tag approach

Expressed sequence tags (ESTs) are partial cDNA sequences read from both ends of random expressed gene fragments used for discovering new genes. DNA libraries from four different developmental stages of Schistosoma mansoni used in this study generated 141 ESTs representing about 2.5% of S. mansoni sequences in dbEST. Sequencing was done by the dideoxy chain termination method. The sequences were submitted to GenBank for homology searching in nonredundant databases using Basic Local Alignment Search Tool for DNA (BLASTN) alignment and for protein (BLASTX) alignment at the National Center for Biotechnology Information (NCBI). Among submitted ESTs, 29 were derived from lambdagt11 sporocyst library, 70 from lambdaZap adult worm library, 31 from lambdaZap cercarial library, and 11 from lambdaZap female B worm library. Homology search revealed that eight (5.6%) ESTs shared homology to previously identified S.mansoni genes in dbEST, 15 (10.6%) are homologous to known genes in other organisms, 116 (81.7%) showed no significant sequence homology in the databases, and the remaining sequences (2.1%) showed low homologies to rRNA or mitochondrial DNA sequences. Thus, among the 141 ESTs studied, 116 sequences are derived from noval, uncharactarized S. mansoni genes. Those 116 ESTs are important for identification of coding regions in the sequences, helping in mapping of schistosome genome, and identifying genes of immunological and pharmacological significance.     

Pandit: a database of protein and associated nucleotide domains with inferred trees

MOTIVATION: A large, high-quality database of homologous sequence alignments with good estimates of their corresponding phylogenetic trees will be a valuable resource to those studying phylogenetics. It will allow researchers to compare current and new models of sequence evolution across a large variety of sequences. The large quantity of data may provide inspiration for new models and methodology to study sequence evolution and may allow general statements about the relative effect of different molecular processes on evolution. RESULTS: The Pandit 7.6 database contains 4341 families of sequences derived from the seed alignments of the Pfam database of amino acid alignments of families of homologous protein domains (Bateman et al., 2002). Each family in Pandit includes an alignment of amino acid sequences that matches the corresponding Pfam family seed alignment, an alignment of DNA sequences that contain the coding sequence of the Pfam alignment when they can be recovered (overall, 82.9% of sequences taken from Pfam) and the alignment of amino acid sequences restricted to only those sequences for which a DNA sequence could be recovered. Each of the alignments has an estimate of the phylogenetic tree associated with it. The tree topologies were obtained using the neighbor joining method based on maximum likelihood estimates of the evolutionary distances, with branch lengths then calculated using a standard maximum likelihood approach.     

PhyloGena--a user-friendly system for automated phylogenetic annotation of unknown sequences

MOTIVATION: Phylogenomic approaches towards functional and evolutionary annotation of unknown sequences have been suggested to be superior to those based only on pairwise local alignments. User-friendly software tools making the advantages of phylogenetic annotation available for the ever widening range of bioinformatically uninitiated biologists involved in genome/EST annotation projects are, however, not available. We were particularly confronted with this issue in the annotation of sequences from different groups of complex algae originating from secondary endosymbioses, where the identification of the phylogenetic origin of genes is often more problematic than in taxa well represented in the databases (e.g. animals, plants or fungi). RESULTS: We present a flexible pipeline with a user-friendly, interactive graphical user interface running on desktop computers that automatically performs a basic local alignment search tool (BLAST) search of query sequences, selects a representative subset of them, then creates a multiple alignment from the selected sequences, and finally computes a phylogenetic tree. The pipeline, named PhyloGena, uses public domain software for all standard bioinformatics tasks (similarity search, multiple alignment, and phylogenetic reconstruction). As the major technological innovation, selection of a meaningful subset of BLAST hits was implemented using logic programming, mimicing the selection procedure (BLAST tables, multiple alignments and phylogenetic trees) are displayed graphically, allowing the user to interact with the pipeline and deduce the function and phylogenetic origin of the query. PhyloGena thus makes phylogenomic annotation available also for those biologists without access to large computing facilities and with little informatics background. Although phylogenetic annotation is particularly useful when working with composite genomes (e.g. from complex algae), PhyloGena can be helpful in expressed sequence tag and genome annotation also in other organisms. AVAILABILITY: PhyloGena (executables for LINUX and Windows 2000/XP as well as source code) is available by anonymous ftp from http://www.awi.de/en/phylogena.     

Characterization of the ABCA transporter subfamily: identification of prokaryotic and eukaryotic members,phylogeny and topology

An alignment of the mammalian ABCA transporters enabled the identification of sequence segments, specific to the ABCA subfamily, which were used as queries to search for eukaryotic and prokaryotic homologues. Thirty-seven eukaryotic half and full-length transporters were found, and a close relationship with prokaryotic subfamily 7 transporters was detected. Each half of the ABCA full-transporters is predicted to comprise a membrane-spanning domain (MSD) composed of six helices and a large extracellular loop, followed by a nucleotide-binding domain (NBD) and a conserved cytoplasmic 80-residue sequence, which might have a regulatory function. The topology predicted for the ABCA transporters was compared to the crystal structures of the MsbA and BtuCD bacterial transporters. The alignment of the MSD and NBD domains provided an estimate of the degree of residue conservation in the cytoplasmic, extracellular and transmembrane domains of the ABCA transporter subfamily. The phylogenic tree of eukaryotic ABCA transporters based upon the NBD sequences, consists of three major clades, corresponding to the half-transporter single NBDs and to the full-transporter NBDls and NBD2s. A phylogenic tree of prokaryotic transporters and the eukaryotic ABCA transporters confirmed the evolutionary relationship between prokaryotic subfamily 7 transporters and eukaryotic ABCA half and full-transporters.     

Size, frequency, and phylogenetic signal of multiple-residue indels in sequence alignment of introns

Indels in DNA sequences frequently affect more than a single nucleotide, creating problems for alignment, character coding and phylogenetic analysis. However, the size and frequency of multiple‐residue indels is not usually tested, and with popular alignment packages their reconstruction is indirectly acheived by reducing the affine (gap extension) cost. We explored the length distribution of indels in intron sequences of the gene Mp20 by modifying the gap opening and gap extension costs. Given a “known” tree for the study group, global homology levels were greatest under low gap cost, with gap extension costs of roughly 0.4‐fold the opening cost. Different approaches to gap coding and weighting suggested that taxonomic congruence was correlated with high frequencies of multiple‐position indels, with a maximum indel length of 2–5 bp and few indels above 15 bp, but also including a proportion of indels > 100 bp. Only a small minority of indels could be reconstructed as single‐position indels. Consequently, tree topologies improved when homologous multinucleotide indels were recoded as binary characters which are otherwise highly homoplastic and weighted characters in single‐position coding. In tree‐generating alignment procedures as implemented in POY, where gap penalty determines the character weight during tree search, the problem of assigning inappropriately high weight to multiple‐residue indels could partly be overcome by setting the extension costs to about 0.4‐fold lower than gap opening costs. We conclude that multiple consecutive gap positions are not independent characters and hence methods for parsimony reconstruction of long indels are required. Finally, we also observed a general lack of correlation between taxonomic and character congruence, demonstrating the difficulties of applying congruence criteria to decide among competing alignments. This highlights the value of recent model‐based alignment procedures which can implement the statistical distributions of indel size classes, and do not rely on potentially circular strategies for optimizing overall congruence. © The Willi Hennig Society 2006.     

The importance of genetic recombination for fidelity of chromosome pairing in meiosis

In budding yeast, absence of the Hop2 protein leads to extensive synaptonemal complex (SC) formation between nonhomologous chromosomes, suggesting a crucial role for Hop2 in the proper alignment of homologous chromosomes during meiotic prophase. Genetic analysis indicates that Hop2 acts in the same pathway as the Rad51 and Dmc1 proteins, two homologs of E. coli RecA. Thus, the hop2 mutant phenotype demonstrates the importance of the recombination machinery in promoting accurate chromosome pairing. We propose that the Dmc1/Rad51 recombinases require Hop2 to distinguish homologous from nonhomologous sequences during the homology search process. Thus, when Hop2 is absent, interactions between nonhomologous sequences become inappropriately stabilized and can initiate SC formation. Overexpression of RAD51 largely suppresses the meiotic defects of the dmc1 and hop2 mutants. We conclude that Rad51 is capable of carrying out a homology search independently, whereas Dmc1 requires additional factors such as Hop2.     

Annotation-free delineation of prokaryotic homology groups

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa.     

Phylogenetic relationships among Phytophthora species inferred from sequence analysis of mitochondrially encoded cytochrome oxidase I and II genes

The phylogenetic relationships of 51 isolates representing 27 species of Phytophthora were assessed by sequence alignment of 568 bp of the mitochondrially encoded cytochrome oxidase II gene. A total of 1299 bp of the cytochrome oxidase I gene also were examined for a subset of 13 species. The cox II gene trees constructed by a heuristic search, based on maximum parsimony for a bootstrap 50% majority-rule consensus tree, revealed 18 species grouping into seven clades and nine species unaffiliated with a specific clade. The phylogenetic relationships among species observed on cox II gene trees did not exhibit consistent similarities in groupings for morphology, pathogenicity, host range or temperature optima. The topology of cox I gene trees, constructed by a heuristic search based on maximum parsimony for a bootstrap 50% majority-rule consensus tree for 13 species of Phytophthora, revealed 10 species grouping into three clades and three species unaffiliated with a specific clade. The groupings in general agreed with what was observed in the cox II tree. Species relationships observed for the cox II gene tree were in agreement with those based on ITS regions, with several notable exceptions. Some of these differences were noted in species in which the same isolates were used for both ITS and cox II analysis, suggesting either a differential rate of evolutionary divergence for these two regions or incorrect assumptions about alignment of ITS sequences. Analysis of combined data sets of ITS and cox II sequences generated a tree that did not differ substantially from analysis of ITS data alone, however, the results of a partition homogeneity test suggest that combining data sets may not be valid.     

Automated ortholog inference from phylogenetic trees and calculation of orthology reliability

MOTIVATION: Orthologous proteins in different species are likely to have similar biochemical function and biological role. When annotating a newly sequenced genome by sequence homology, the most precise and reliable functional information can thus be derived from orthologs in other species. A standard method of finding orthologs is to compare the sequence tree with the species tree. However, since the topology of phylogenetic tree is not always reliable one might get incorrect assignments. RESULTS: Here we present a novel method that resolves this problem by analyzing a set of bootstrap trees instead of the optimal tree. The frequency of orthology assignments in the bootstrap trees can be interpreted as a support value for the possible orthology of the sequences. Our method is efficient enough to analyze data in the scale of whole genomes. It is implemented in Java and calculates orthology support levels for all pairwise combinations of homologous sequences of two species. The method was tested on simulated datasets and on real data of homologous proteins.     

SATCHMO: sequence alignment and tree construction using hidden Markov models

MOTIVATION:Aligning multiple proteins based on sequence information alone is challenging if sequence identity is low or there is a significant degree of structural divergence. We present a novel algorithm (SATCHMO) that is designed to address this challenge. SATCHMO simultaneously constructs a tree and a set of multiple sequence alignments, one for each internal node of the tree. The alignment at a given node contains all sequences within its sub-tree, and predicts which positions in those sequences are alignable and which are not. Aligned regions therefore typically get shorter on a path from a leaf to the root as sequences diverge in structure. Current methods either regard all positions as alignable (e.g. ClustalW), or align only those positions believed to be homologous across all sequences (e.g. profile HMM methods); by contrast SATCHMO makes different predictions of alignable regions in different subgroups. SATCHMO generates profile hidden Markov models at each node; these are used to determine branching order, to align sequences and to predict structurally alignable regions. RESULTS: In experiments on the BAliBASE benchmark alignment database, SATCHMO is shown to perform comparably to ClustalW and the UCSC SAM HMM software. Results using SATCHMO to identify protein domains are demonstrated on potassium channels, with implications for the mechanism by which tumor necrosis factor alpha affects potassium current. AVAILABILITY: The software is available for download from http://www.drive5.com/lobster/index.htm     

A new method of global search for functional DNA segments using a fractal representation of nucleotide texts]

New global method for computer prediction of functional sites in nucleotide sequences, based on the fractal representation, is presented. Fractal representation of set of sequences (FRS) provides simple way for generating recognitions matrix of functionally similar sequences and simple estimations of its efficiency for searching homologous regions in new sequences. Other advantages of the method are absence of the necessity of sequences alignment during generating based set and searching new homologous regions and small CPU time. Usage of the method illustrated for searching globin and histone genes, for ALU repeats in human genome and long terminal repeats in virus genome.