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PubMed2026

Theseus: fast and optimal affine-gap sequence-to-graph alignment.

MOTIVATION: Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long sequences to complex graphs. Practical solutions partially address this problem using heuristic strategies that ultimately trade off optimality for speed. RESULTS: This work presents Theseus, a novel, fast, and optimal affine-gap sequence-to-graph alignment algorithm. Theseus leverages similarities between genomic sequences to accelerate the alignment computation and reduces the overall memory requirements without compromising optimality. To that end, Theseus processes only a subset of the dynamic programming cells, using a sparse-data strategy that enables efficient sequence-to-graph alignment. Moreover, our algorithm supports optimal affine-gap alignment on arbitrary directed graphs, including those with cycles. We evaluate Theseus on two key problems: MSA and pangenome read mapping. For MSA, we compare it against SPOA, abPOA, and POASTA. Theseus is 1.6× to 17.6× faster than POASTA, and 7.3× faster, on average, than SPOA, both optimal aligners. Compared with abPOA, Theseus ensures optimality and scales to the largest problems. For pangenome read mapping, we benchmark Theseus against the alignment stage of the mapping tool vg map, along with the alignment kernels of SPOA, abPOA, and POASTA. Theseus outperforms the other methods, showing a 1.9× to 16.9× speedup on short reads. Moreover, Theseus is 1.5× to 36.3× faster than vg when aligning against synthetic cyclic graphs. AVAILABILITY AND IMPLEMENTATION: Theseus code and documentation are publicly available at https://github.com/albertjimenezbl/theseus-lib.

Algorithms↗
PubMed2000

Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis.

The use of some multiple-sequence alignments in phylogenetic analysis, particularly those that are not very well conserved, requires the elimination of poorly aligned positions and divergent regions, since they may not be homologous or may have been saturated by multiple substitutions. A computerized method that eliminates such positions and at the same time tries to minimize the loss of informative sites is presented here. The method is based on the selection of blocks of positions that fulfill a simple set of requirements with respect to the number of contiguous conserved positions, lack of gaps, and high conservation of flanking positions, making the final alignment more suitable for phylogenetic analysis. To illustrate the efficiency of this method, alignments of 10 mitochondrial proteins from several completely sequenced mitochondrial genomes belonging to diverse eukaryotes were used as examples. The percentages of removed positions were higher in the most divergent alignments. After removing divergent segments, the amino acid composition of the different sequences was more uniform, and pairwise distances became much smaller. Phylogenetic trees show that topologies can be different after removing conserved blocks, particularly when there are several poorly resolved nodes. Strong support was found for the grouping of animals and fungi but not for the position of more basal eukaryotes. The use of a computerized method such as the one presented here reduces to a certain extent the necessity of manually editing multiple alignments, makes the automation of phylogenetic analysis of large data sets feasible, and facilitates the reproduction of the final alignment by other researchers.

Amino Acid Sequence↗
PubMed2001

AL2CO: calculation of positional conservation in a protein sequence alignment.

MOTIVATION: Amino acid sequence alignments are widely used in the analysis of protein structure, function and evolutionary relationships. Proteins within a superfamily usually share the same fold and possess related functions. These structural and functional constraints are reflected in the alignment conservation patterns. Positions of functional and/or structural importance tend to be more conserved. Conserved positions are usually clustered in distinct motifs surrounded by sequence segments of low conservation. Poorly conserved regions might also arise from the imperfections in multiple alignment algorithms and thus indicate possible alignment errors. Quantification of conservation by attributing a conservation index to each aligned position makes motif detection more convenient. Mapping these conservation indices onto a protein spatial structure helps to visualize spatial conservation features of the molecule and to predict functionally and/or structurally important sites. Analysis of conservation indices could be a useful tool in detection of potentially misaligned regions and will aid in improvement of multiple alignments. RESULTS: We developed a program to calculate a conservation index at each position in a multiple sequence alignment using several methods. Namely, amino acid frequencies at each position are estimated and the conservation index is calculated from these frequencies. We utilize both unweighted frequencies and frequencies weighted using two different strategies. Three conceptually different approaches (entropy-based, variance-based and matrix score-based) are implemented in the algorithm to define the conservation index. Calculating conservation indices for 35522 positions in 284 alignments from SMART database we demonstrate that different methods result in highly correlated (correlation coefficient more than 0.85) conservation indices. Conservation indices show statistically significant correlation between sequentially adjacent positions i and i + j, where j < 13, and averaging of the indices over the window of three positions is optimal for motif detection. Positions with gaps display substantially lower conservation properties. We compare conservation properties of the SMART alignments or FSSP structural alignments to those of the ClustalW alignments. The results suggest that conservation indices should be a valuable tool of alignment quality assessment and might be used as an objective function for refinement of multiple alignments. AVAILABILITY: The C code of the AL2CO program and its pre-compiled versions for several platforms as well as the details of the analysis are freely available at ftp://iole.swmed.edu/pub/al2co/.

Algorithms↗
PubMed2002

Quality assessment of multiple alignment programs.

A renewed interest in the multiple sequence alignment problem has given rise to several new algorithms. In contrast to traditional progressive methods, computationally expensive score optimization strategies are now predominantly employed. We systematically tested four methods (Poa, Dialign, T-Coffee and ClustalW) for the speed and quality of their alignments. As test sequences we used structurally derived alignments from BAliBASE and synthetic alignments generated by Rose. The tests included alignments of variable numbers of domains embedded in random spacer sequences. Overall, Dialign was the most accurate in cases with low sequence identity, while T-Coffee won in cases with high sequence identity. The fast Poa algorithm was almost as accurate, while ClustalW could compete only in strictly global cases with high sequence similarity.

Evolution, Molecular↗
PubMed2005

A structure and evolution-guided Monte Carlo sequence selection strategy for multiple alignment-based analysis of proteins.

MOTIVATION: Various multiple sequence alignment-based methods have been proposed to detect functional surfaces in proteins, such as active sites or protein interfaces. The effect that the choice of sequences has on the conclusions of such analysis has seldom been discussed. In particular, no method has been discussed in terms of its ability to optimize the sequence selection for the reliable detection of functional surfaces. RESULTS: Here we propose, for the case of proteins with known structure, a heuristic Metropolis Monte Carlo strategy to select sequences from a large set of homologues, in order to improve detection of functional surfaces. The quantity guiding the optimization is the clustering of residues which are under increased evolutionary pressure, according to the sample of sequences under consideration. We show that we can either improve the overlap of our prediction with known functional surfaces in comparison with the sequence similarity criteria of selection or match the quality of prediction obtained through more elaborate non-structure based-methods of sequence selection. For the purpose of demonstration we use a set of 50 homodimerizing enzymes which were co-crystallized with their substrates and cofactors.

Algorithms↗
PubMed2004

Automatic prediction of protein domains from sequence information using a hybrid learning system.

MOTIVATION: We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using a neural network. The output is further smoothed and post-processed using a probabilistic model to predict the most likely transition positions between domains. RESULTS: The method was assessed using the domain definitions in SCOP and CATH for proteins of known structure and was compared with several other existing methods. Our method performs well both in terms of accuracy and sensitivity. It improves significantly over the best methods available, even some of the semi-manual ones, while being fully automatic. Our method can also be used to suggest and verify domain partitions based on structural data. A few examples of predicted domain definitions and alternative partitions, as suggested by our method, are also discussed. AVAILABILITY: An online domain-prediction server is available at http://biozon.org/tools/domains/

Algorithms↗
PubMed1992

Pattern-induced multi-sequence alignment (PIMA) algorithm employing secondary structure-dependent gap penalties for use in comparative protein modelling.

A multiple sequence alignment algorithm is described that uses a dynamic programming-based pattern construction method to align a set of homologous sequences based on their common pattern of conserved sequence elements. This pattern-induced multi-sequence alignment (PIMA) algorithm can employ secondary-structure dependent gap penalties for use in comparative modelling of new sequences when the three-dimensional structure of one or more members of the same family is known. We show that the use of secondary structure information can significantly improve the accuracy of aligning structure boundaries in a set of homologous sequences even when the structure of only one member of the family is known.

Algorithms↗
PubMed1993

Alignment-ambiguous nucleotide sites and the exclusion of systematic data.

Molecular systematists generally rely on computer algorithms to establish the alignment of DNA sequences. However, when alignment regions are characterized by multiple insertions and deletions, these gap-filled stretches of DNA are often excised before phylogenetic reconstruction. This exclusion of systematic data is generally determined by subjective criteria. We explore a replicable methodology in which the comparison of several multiple sequence alignments can be used to eliminate regions of unstable sequence alignment. Using crocodilian and insect mitochondrial (mt) ribosomal (r) DNA as examples, we caution against the removal of sequence data prior to phylogenetic reconstruction.

Algorithms↗
PubMed2006

FootPrinter3: phylogenetic footprinting in partially alignable sequences.

FootPrinter3 is a web server for predicting transcription factor binding sites by using phylogenetic footprinting. Until now, phylogenetic footprinting approaches have been based either on multiple alignment analysis (e.g. PhyloVista, PhastCons), or on motif-discovery algorithms (e.g. FootPrinter2). FootPrinter3 integrates these two approaches, making use of local multiple sequence alignment blocks when those are available and reliable, but also allowing finding motifs in unalignable regions. The result is a set of predictions that joins the advantages of alignment-based methods (good specificity) to those of motif-based methods (good sensitivity, even in the presence of highly diverged species). FootPrinter3 is thus a tool of choice to exploit the wealth of vertebrate genomes being sequenced, as it allows taking full advantage of the sequences of highly diverged species (e.g. chicken, zebrafish), as well as those of more closely related species (e.g. mammals). The FootPrinter3 web server is available at: http://www.mcb.mcgill.ca/~blanchem/FootPrinter3.

Animals↗
PubMed1991

A new method for building protein conformations from sequence alignments with homologues of known structure.

We describe a largely automatic procedure for building protein structures from sequence alignments with homologues of known structure. This procedure uses simple rules by which multiple sequence alignments can be translated into distance and chirality constraints, which are then used as input for distance geometry calculations. By this means one obtains an ensemble of conformations for the unknown structure that are compatible with the rules employed, and the differences among these conformations provide an indication of the reliability of the structure prediction. The overall approach is demonstrated here by applying it to several Kazal-type trypsin inhibitors, for which experimentally determined structures are available. On the basis of our experience with these test problems, we have further predicted the conformation of the human pancreatic secretory trypsin inhibitor, for which no experimentally determined structure is presently available.

Algorithms↗
PubMed2006

A new approach for alignment of multiple proteins.

We introduce a new graph-based multiple sequence alignment method for protein sequences. We name our method HSA (Horizontal Sequence Alignment) for it horizontally slides a window on the protein sequences simultaneously. Current progressive alignment tools build up final alignment by adding sequences one by one to existing alignment. Thus, they have the shortcoming of order-dependent alignment. In contrast, HSA considers all the proteins at once. It obtains final alignment by concatenating cliques of graph. In order to find a biologically relevant alignment, HSA takes secondary structure information as well as amino acid sequences into account. The experimental results show that HSA achieves higher accuracy compared to existing tools on BAliBASE benchmarks. The improvement is more significant for proteins with low similarity.

Algorithms↗
PubMedDate not supplied

A Bayesian model for detecting past recombination events in DNA multiple alignments.

Most phylogenetic tree estimation methods assume that there is a single set of hierarchical relationships among sequences in a data set for all sites along an alignment. Mosaic sequences produced by past recombination events will violate this assumption and may lead to misleading results from a phylogenetic analysis due to the imposition of a single tree along the entire alignment. Therefore, the detection of past recombination is an important first step in an analysis. A Bayesian model for the changes in topology caused by recombination events is described here. This model relaxes the assumption of one topology for all sites in an alignment and uses the theory of Hidden Markov models to facilitate calculations, the hidden states being the underlying topologies at each site in the data set. Changes in topology along the multiple sequence alignment are estimated by means of the maximum a posteriori (MAP) estimate. The performance of the MAP estimate is assessed by application of the model to data sets of four sequences, both simulated and real.

Bayes Theorem↗
PubMed2005

Predicted secondary structure for 28S and 18S rRNA from Ichneumonoidea (Insecta: Hymenoptera: Apocrita): impact on sequence alignment and phylogeny estimation.

We utilize the secondary structural properties of the 28S rRNA D2-D10 expansion segments to hypothesize a multiple sequence alignment for major lineages of the hymenopteran superfamily Ichneumonoidea (Braconidae, Ichneumonidae). The alignment consists of 290 sequences (originally analyzed in Belshaw and Quicke, Syst Biol 51:450-477, 2002) and provides the first global alignment template for this diverse group of insects. Predicted structures for these expansion segments as well as for over half of the 18S rRNA are given, with highly variable regions characterized and isolated within conserved structures. We demonstrate several pitfalls of optimization alignment and illustrate how these are potentially addressed with structure-based alignments. Our global alignment is presented online at (http://hymenoptera.tamu.edu/rna) with summary statistics, such as basepair frequency tables, along with novel tools for parsing structure-based alignments into input files for most commonly used phylogenetic software. These resources will be valuable for hymenopteran systematists, as well as researchers utilizing rRNA sequences for phylogeny estimation in any taxon. We explore the phylogenetic utility of our structure-based alignment by examining a subset of the data under a variety of optimality criteria using results from Belshaw and Quicke (2002) as a benchmark.

Animals↗
PubMed1995

ALIGNMENT SERVICE: creation and processing of alignments of sequences of unlimited length.

A package for the creation and processing of multiple sequence alignment is described. There is no limit on the lengths of the processed nucleotide or amino acid sequences, and the number of sequences in the alignment is also unlimited. The main groups of functions are: a semiautomatic alignment editor; a wide set of functions for technical processing of alignments; nucleotide alignment mapping and translation; and similarity search functions. A user-friendly interface and a set of generally used file actions provide a special operational subsystem for everyday tasks.

Amino Acid Sequence↗
PubMed1998

CINEMA--a novel colour INteractive editor for multiple alignments.

CINEMA is a new editor for manipulating and generating multiple sequence alignments. The program provides both an interface to existing databases of alignments on the Internet and a tool for constructing and modifying alignments locally. It is written in Java, so executable code will run on most major desktop platforms without modification. The implementation is highly flexible, so the applet can be easily customised with additional functions; and the object classes are reusable, promoting rapid development of program extensions. Formerly, such extended functionality might have been provided via browser plug-ins, which have to be downloaded and installed on every client before loading data. Now, for the first time, an applet is available that allows interactive client-side processing of an alignment, which can then be stored or processed automatically on the server. The program is embedded in a comprehensive help file and is accessible both as a stand-alone tool on UCL's Bioinformatics Server; http:/(/)www.biochem.ucl.ac.uk/bsm/dbbrowser+ ++/CINEMA2.02/, and as an integral part of the PRINTS protein fingerprint database. Exploitation of such novel technologies revolutionises the way users may interact with public databases in the future: bioinformatics centres need not simply provide data, but are now able to offer the means by which information is visualised and manipulated, without the requirement for users to install software.

Color Perception↗
PubMed2000

An assessment of the phylogenetic relationship among sugarcane and related taxa based on the nucleotide sequence of 5S rRNA intergenic spacers.

5S rRNA intergenic spacers were amplified from two elite sugarcane (Saccharum hybrids) cultivars and their related taxa by polymerase chain reaction (PCR) with 5S rDNA consensus primers. Resulting PCR products were uniform in length from each accession but exhibited some degree of length variation among the sugarcane accessions and related taxa. These PCR products did not always cross hybridize in Southern blot hybridization experiments. These PCR products were cloned into a commercial plasmid vector PCR 2.1 and sequenced. Direct sequencing of cloned PCR products revealed spacer length of 231-237 bp for S. officinarum, 233-237 for sugarcane cultivars, 228-238 bp for S. spontaneum, 239-252 bp for S. giganteum, 385-410 bp for Erianthus spp., 226-230 bp for Miscanthus sinensis Zebra, 206-207 bp for M. sinensis IMP 3057, 207-209 bp for Sorghum bicolor, and 247-249 bp for Zea mays. Nucleotide sequence polymorphism were found at both the segment and single nucleotide level. A consensus sequence for each taxon was obtained by Align X. Multiple sequences were aligned and phylogenetic trees constructed using Align X. CLUSTAL and DNAMAN programs. In general, accessions of the following taxa tended to group together to form distinct clusters: S. giganteum, Erianthus spp., M. sinensis, S. bicolor, and Z. mays. However, the two S. officinarum clones and two sugarcane cultivars did not form distinct clusters but interrelated within the S. spontaneum cluster. The disclosure of these 5S rRNA intergenic spacer sequences will facilitate marker-assisted breeding in sugarcane.

Base Sequence↗
PubMed2003

Protein family annotation in a multiple alignment viewer.

SUMMARY: The Pfaat protein family alignment annotation tool is a Java-based multiple sequence alignment editor and viewer designed for protein family analysis. The application merges display features such as dendrograms, secondary and tertiary protein structure with SRS retrieval, subgroup comparison, and extensive user-annotation capabilities. AVAILABILITY: The program and source code are freely available from the authors under the GNU General Public License at http://www.pfizerdtc.com

Amino Acid Sequence↗