A space-efficient algorithm for aligning large genomic sequences

SUMMARY: In the segment-by-segment approach to sequence alignment, pairwise and multiple alignments are generated by comparing gap-free segments of the sequences under study. This method is particularly efficient in detecting local homologies, and it has been used to identify functional regions in large genomic sequences. Herein, an algorithm is outlined that calculates optimal pairwise segment-by-segment alignments in essentially linear space. AVAILABILTIY: The program is available at the Bielefeld Bioinformatics Server (BiBiServ) at http://bibiserv.techfak. uni-bielefeld.de/dialign/     

Analysis on sliding helices and strands in protein structural comparisons: a case study with protein kinases

Protein structural alignments are generally considered as 'golden standard' for the alignment at the level of amino acid residues. In this study we have compared the quality of pairwise and multiple structural alignments of about 5900 homologous proteins from 718 families of known 3-D structures. We observe shifts in the alignment of regular secondary structural elements (helices and strands) between pairwise and multiple structural alignments. The differences between pairwise and multiple structural alignments within helical and beta-strand regions often correspond to 4 and 2 residue positions respectively. Such shifts correspond approximately to "one turn" of these regular secondary structures. We have performed manual analysis explicitly on the family of protein kinases. We note shifts of one or two turns in helix-helix alignments obtained using pairwise and multiple structural alignments. Investigations on the quality of the equivalent helix-helix, strand-strand pairs in terms of their residue side-chain accessibilities have been made. Our results indicate that the quality of the pairwise alignments is comparable to that of the multiple structural alignments and, in fact, is often better. We propose that pairwise alignment of protein structures should also be used in formulation of methods for structure prediction and evolutionary analysis.     

AuberGene--a sensitive genome alignment tool

MOTIVATION: The accumulation of genome sequences will only accelerate in the coming years. We aim to use this abundance of data to improve the quality of genomic alignments and devise a method which is capable of detecting regions evolving under weak or no evolutionary constraints. RESULTS: We describe a genome alignment program AuberGene, which explores the idea of transitivity of local alignments. Assessment of the program was done based on a 2 Mbp genomic region containing the CFTR gene of 13 species. In this region, we can identify 53% of human sequence sharing common ancestry with mouse, as compared with 44% found using the usual pairwise alignment. Between human and tetraodon 93 orthologous exons are found, as compared with 77 detected by the pairwise human-tetraodon comparison. AuberGene allows the user to (1) identify distant, previously undetected, conserved orthogonal regions such as ORFs or regulatory regions; (2) identify neutrally evolving regions in related species which are often overlooked by other alignment programs; (3) recognize false orthologous genomic regions. The increased sensitivity of the method is not obtained at the cost of reduced specificity. Our results suggest that, over the CFTR region, human shares 10% more sequence with mouse than previously thought ( approximately 50%, instead of 40% found with the pairwise alignment).     

Visualization of near-optimal sequence alignments

MOTIVATION: Mathematically optimal alignments do not always properly align active site residues or well-recognized structural elements. Most near-optimal sequence alignment algorithms display alternative alignment paths, rather than the conventional residue-by-residue pairwise alignment. Typically, these methods do not provide mechanisms for finding effectively the most biologically meaningful alignment in the potentially large set of options. RESULTS: We have developed Web-based software that displays near optimal or alternative alignments of two protein or DNA sequences as a continuous moving picture. A WWW interface to a C++ program generates near optimal alignments, which are sent to a Java Applet, which displays them in a series of alignment frames. The Applet aligns residues so that consistently aligned regions remain at a fixed position on the display, while variable regions move. The display can be stopped to examine alignment details.     

Analysis on sliding helices and strands in protein structural comparisons: A case study with protein kinases

Protein structural alignments are generally considered as ‘golden standard’ for the alignment at the level of amino acid residues. In this study we have compared the quality of pairwise and multiple structural alignments of about 5900 homologous proteins from 718 families of known 3-D structures. We observe shifts in the alignment of regular secondary structural elements (helices and strands) between pairwise and multiple structural alignments. The differences between pairwise and multiple structural alignments within helical and β-strand regions often correspond to 4 and 2 residue positions respectively. Such shifts correspond approximately to “one turn” of these regular secondary structures. We have performed manual analysis explicitly on the family of protein kinases. We note shifts of one or two turns in helix-helix alignments obtained using pairwise and multiple structural alignments. Investigations on the quality of the equivalent helix-helix, strand-strand pairs in terms of their residue side-chain accessibilities have been made. Our results indicate that the quality of the pairwise alignments is comparable to that of the multiple structural alignments and, in fact, is often better. We propose that pairwise alignment of protein structures should also be used in formulation of methods for structure prediction and evolutionary analysis.     

NcDNAlign: plausible multiple alignments of non-protein-coding genomic sequences

Genome-wide multiple sequence alignments (MSAs) are a necessary prerequisite for an increasingly diverse collection of comparative genomic approaches. Here we present a versatile method that generates high-quality MSAs for non-protein-coding sequences. The NcDNAlign pipeline combines pairwise BLAST alignments to create initial MSAs, which are then locally improved and trimmed. The program is optimized for speed and hence is particulary well-suited to pilot studies. We demonstrate the practical use of NcDNAlign in three case studies: the search for ncRNAs in gammaproteobacteria and the analysis of conserved noncoding DNA in nematodes and teleost fish, in the latter case focusing on the fate of duplicated ultra-conserved regions. Compared to the currently widely used genome-wide alignment program TBA, our program results in a 20- to 30-fold reduction of CPU time necessary to generate gammaproteobacterial alignments. A showcase application of bacterial ncRNA prediction based on alignments of both algorithms results in similar sensitivity, false discovery rates, and up to 100 putatively novel ncRNA structures. Similar findings hold for our application of NcDNAlign to the identification of ultra-conserved regions in nematodes and teleosts. Both approaches yield conserved sequences of unknown function, result in novel evolutionary insights into conservation patterns among these genomes, and manifest the benefits of an efficient and reliable genome-wide alignment package. The software is available under the GNU Public License at http://www.bioinf.uni-leipzig.de/Software/NcDNAlign/.     

Consistency of optimal sequence alignments

Pairwise optimal alignments between three or more sequences are not necessarily consistent as a whole, but consistent and inconsistent residues are usually distributed in clusters. An efficient method has been developed for locating consistent regions when each pairwise alignment is given in the form of a “skeletal representation” (Bull. math. Biol. 52, 359–373). This method is further extended so that the combination of pairwise alignments that gives the greatest consistency is found when possibly many alignments are equally optimal for each pairwise comparison. A method for acceleration of simultaneous multiple sequence alignment is proposed in which consistent regions serve as “anchor points” limiting application of direct multi-way alignment to the rest of “inconsistent” regions. Dedicated to Prof. Akiyoshi Wada on the occasion of his 60^th birthday.     

MAP2: multiple alignment of syntenic genomic sequences

We describe a multiple alignment program named MAP2 based on a generalized pairwise global alignment algorithm for handling long, different intergenic and intragenic regions in genomic sequences. The MAP2 program produces an ordered list of local multiple alignments of similar regions among sequences, where different regions between local alignments are indicated by reporting only similar regions. We propose two similarity measures for the evaluation of the performance of MAP2 and existing multiple alignment programs. Experimental results produced by MAP2 on four real sets of orthologous genomic sequences show that MAP2 rarely missed a block of transitively similar regions and that MAP2 never produced a block of regions that are not transitively similar. Experimental results by MAP2 on six simulated data sets show that MAP2 found the boundaries between similar and different regions precisely. This feature is useful for finding conserved functional elements in genomic sequences. The MAP2 program is freely available in source code form at http://bioinformatics.iastate.edu/aat/sas.html for academic use.     

MUSTANG: a multiple structural alignment algorithm

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.     

Large-scale comparison of protein sequence alignment algorithms with structure alignments

Sequence alignment programs such as BLAST and PSI-BLAST are used routinely in pairwise, profile-based, or intermediate-sequence-search (ISS) methods to detect remote homologies for the purposes of fold assignment and comparative modeling. Yet, the sequence alignment quality of these methods at low sequence identity is not known. We have used the CE structure alignment program (Shindyalov and Bourne, Prot Eng 1998;11:739) to derive sequence alignments for all superfamily and family-level related proteins in the SCOP domain database. CE aligns structures and their sequences based on distances within each protein, rather than on interprotein distances. We compared BLAST, PSI-BLAST, CLUSTALW, and ISS alignments with the CE structural alignments. We found that global alignments with CLUSTALW were very poor at low sequence identity (<25%), as judged by the CE alignments. We used PSI-BLAST to search the nonredundant sequence database (nr) with every sequence in SCOP using up to four iterations. The resulting matrix was used to search a database of SCOP sequences. PSI-BLAST is only slightly better than BLAST in alignment accuracy on a per-residue basis, but PSI-BLAST matrix alignments are much longer than BLAST's, and so align correctly a larger fraction of the total number of aligned residues in the structure alignments. Any two SCOP sequences in the same superfamily that shared a hit or hits in the nr PSI-BLAST searches were identified as linked by the shared intermediate sequence. We examined the quality of the longest SCOP-query/ SCOP-hit alignment via an intermediate sequence, and found that ISS produced longer alignments than PSI-BLAST searches alone, of nearly comparable per-residue quality. At 10-15% sequence identity, BLAST correctly aligns 28%, PSI-BLAST 40%, and ISS 46% of residues according to the structure alignments. We also compared CE structure alignments with FSSP structure alignments generated by the DALI program. In contrast to the sequence methods, CE and structure alignments from the FSSP database identically align 75% of residue pairs at the 10-15% level of sequence identity, indicating that there is substantial room for improvement in these sequence alignment methods. BLAST produced alignments for 8% of the 10,665 nonimmunoglobulin SCOP superfamily sequence pairs (nearly all <25% sequence identity), PSI-BLAST matched 17% and the double-PSI-BLAST ISS method aligned 38% with E-values <10.0. The results indicate that intermediate sequences may be useful not only in fold assignment but also in achieving more complete sequence alignments for comparative modeling.     

PSAR: measuring multiple sequence alignment reliability by probabilistic sampling

Multiple sequence alignment, which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. We propose a new probabilistic sampling-based alignment reliability (PSAR) score. Instead of relying on heuristic assumptions, such as the correlation between alignment quality and guide tree uncertainty in progressive alignment methods, we directly generate suboptimal alignments from an input multiple sequence alignment by a probabilistic sampling method, and compute the agreement of the input alignment with the suboptimal alignments as the alignment reliability score. We construct the suboptimal alignments by an approximate method that is based on pairwise comparisons between each single sequence and the sub-alignment of the input alignment where the chosen sequence is left out. By using simulation-based benchmarks, we find that our approach is superior to existing ones, supporting that the suboptimal alignments are highly informative source for assessing alignment reliability. We apply the PSAR method to the alignments in the UCSC Genome Browser to measure the reliability of alignments in different types of regions, such as coding exons and conserved non-coding regions, and use it to guide cross-species conservation study.     

A polynomial time solvable formulation of multiple sequence alignment.

Since traditional multiple alignment formulations are NP-hard, heuristics are commonly employed to find acceptable alignments with no guaranteed performance bound. This causes a substantial difficulty in understanding what the resulting alignment means and in assessing the quality of these alignments. We propose an alternative formulation of multiple alignment based on the idea of finding a multiple alignment of k sequences which preserves k - 1 pairwise alignments as specified by edges of a given tree. Although it is well known that such a preserving alignment always exists, it did not become a mainstream method for multiple alignment since it seems that a lot of information is lost from ignoring pairwise similarities outside the tree. In contrast, by using pairwise alignments that incorporate consistency information from other sequences, we show that it is possible to obtain very good accuracy with the preserving alignment formulation. We show that a reasonable objective function to use is to find the shortest preserving alignment, and, by a reduction to a graph-theoretic problem, that the problem of finding the shortest preserving multiple alignment can be solved in polynomial time. We demonstrate the success of this approach on three sets of benchmark multiple alignments by using consistency-based pairwise alignments from the first stage of two of the best performing progressive alignment algorithms TCoffee and ProbCons and replace the second heuristic progressive step of these algorithms by the exact preserving alignment step. We apply this strategy to TCoffee and show that our approach outperforms TCoffee on two of the three test sets. We apply the strategy to a variant of ProbCons with no iterative refinements and show that our approach achieves similar or better accuracy except on one test set. We also compare our performance to ProbCons with iterative refinements and show that our approach achieves similar or better accuracy on many subcategories even without further refinements. The most important advantage of the preserving alignment formulation is that we are certain that we can solve the problem in polynomial time without using a heuristic. A software program implementing this approach (PSAlign) is available at http://faculty.cs.tamu.edu/shsze/psalign.     

MSAT

This article describes the development of a new method for multiple sequence alignment based on fold-level protein structure alignments, which provides an improvement in accuracy compared with the most commonly used sequence-only-based techniques. This method integrates the widely used, progressive multiple sequence alignment approach ClustalW with the Topology of Protein Structure (TOPS) topology-based alignment algorithm. The TOPS approach produces a structural alignment for the input protein set by using a topology-based pattern discovery program, providing a set of matched sequence regions that can be used to guide a sequence alignment using ClustalW. The resulting alignments are more reliable than a sequence-only alignment, as determined by 20-fold cross-validation with a set of 106 protein examples from the CATH database, distributed in seven superfold families. The method is particularly effective for sets of proteins that have similar structures at the fold level but low sequence identity. The aim of this research is to contribute towards bridging the gap between protein sequence and structure analysis, in the hope that this can be used to assist the understanding of the relationship between sequence, structure and function. The tool is available at http://balabio.dcs.gla.ac.uk/msat/.     

MAVID multiple alignment server

MAVID is a multiple alignment program suitable for many large genomic regions. The MAVID web server allows biomedical researchers to quickly obtain multiple alignments for genomic sequences and to subsequently analyse the alignments for conserved regions. MAVID has been successfully used for the alignment of closely related species such as primates and also for the alignment of more distant organisms such as human and fugu. The server is fast, capable of aligning hundreds of kilobases in less than a minute. The multiple alignment is used to build a phylogenetic tree for the sequences, which is subsequently used as a basis for identifying conserved regions in the alignment. The server can be accessed at http://baboon.math.berkeley.edu/mavid/.     

Development and validation of a consistency based multiple structure alignment algorithm

SUMMARY: We introduce an algorithm that uses the information gained from simultaneous consideration of an entire group of related proteins to create multiple structure alignments (MSTAs). Consistency-based alignment (CBA) first harnesses the information contained within regions that are consistently aligned among a set of pairwise superpositions in order to realign pairs of proteins through both global and local refinement methods. It then constructs a multiple alignment that is maximally consistent with the improved pairwise alignments. We validate CBA's alignments by assessing their accuracy in regions where at least two of the aligned structures contain the same conserved sequence motif. RESULTS: CBA correctly aligns well over 90% of motif residues in superpositions of proteins belonging to the same family or superfamily, and it outperforms a number of previously reported MSTA algorithms.     

3DCoffee: combining protein sequences and structures within multiple sequence alignments

Most bioinformatics analyses require the assembly of a multiple sequence alignment. It has long been suspected that structural information can help to improve the quality of these alignments, yet the effect of combining sequences and structures has not been evaluated systematically. We developed 3DCoffee, a novel method for combining protein sequences and structures in order to generate high-quality multiple sequence alignments. 3DCoffee is based on TCoffee version 2.00, and uses a mixture of pairwise sequence alignments and pairwise structure comparison methods to generate multiple sequence alignments. We benchmarked 3DCoffee using a subset of HOMSTRAD, the collection of reference structural alignments. We found that combining TCoffee with the threading program Fugue makes it possible to improve the accuracy of our HOMSTRAD dataset by four percentage points when using one structure only per dataset. Using two structures yields an improvement of ten percentage points. The measures carried out on HOM39, a HOMSTRAD subset composed of distantly related sequences, show a linear correlation between multiple sequence alignment accuracy and the ratio of number of provided structure to total number of sequences. Our results suggest that in the case of distantly related sequences, a single structure may not be enough for computing an accurate multiple sequence alignment.     

CLUSTAL: a package for performing multiple sequence alignment on a microcomputer

An approach for performing multiple alignments of large numbers of amino acid or nucleotide sequences is described. The method is based on first deriving a phylogenetic tree from a matrix of all pairwise sequence similarity scores, obtained using a fast pairwise alignment algorithm. Then the multiple alignment is achieved from a series of pairwise alignments of clusters of sequences, following the order of branching in the tree. The method is sufficiently fast and economical with memory to be easily implemented on a microcomputer, and yet the results obtained are comparable to those from packages requiring mainframe computer facilities.     

CASA: a server for the critical assessment of protein sequence alignment accuracy

SUMMARY: A public server for evaluating the accuracy of protein sequence alignment methods is presented. CASA is an implementation of the alignment accuracy benchmark presented by Sauder et al. (Proteins, 40, 6-22, 2000). The benchmark currently contains 39321 pairwise protein structure alignments produced with the CE program from SCOP domain definitions. The server produces graphical and tabular comparisons of the accuracy of a user's input sequence alignments with other commonly used programs, such as BLAST, PSI-BLAST, Clustal W, and SAM-T99. AVAILABILITY: The server is located at http://capb.dbi.udel.edu/casa.     

Multiple sequence alignment with hierarchical clustering.

An algorithm is presented for the multiple alignment of sequences, either proteins or nucleic acids, that is both accurate and easy to use on microcomputers. The approach is based on the conventional dynamic-programming method of pairwise alignment. Initially, a hierarchical clustering of the sequences is performed using the matrix of the pairwise alignment scores. The closest sequences are aligned creating groups of aligned sequences. Then close groups are aligned until all sequences are aligned in one group. The pairwise alignments included in the multiple alignment form a new matrix that is used to produce a hierarchical clustering. If it is different from the first one, iteration of the process can be performed. The method is illustrated by an example: a global alignment of 39 sequences of cytochrome c.