BlastAlign: a program that uses blast to align problematic nucleotide sequences

BlastAlign uses NCBI blastn to build a multiple nucleotide alignment and is intended for use with sequences that have large indels or are otherwise difficult to align globally. The program builds a matrix representing regions of homology along the sequences, from which it selects the 'most representative' sequence and then extracts the blastn query-anchored multiple alignment for this sequence. The matrix is printed and allows subgroups to be identified visually and an option allows other sequences to be used as the 'most representative'. The program contains elements of both Perl and Python and will run on UNIX (including Mac OSX) and DOS. An additional Perl program BlastAlignP uses tblastn to align nucleotide sequences to a single amino acid sequence, thus allowing an open reading frame to be maintained in the resulting multiple alignment. AVAILABILITY: It is freely available at http://www.bio.ic.ac.uk/research/belshaw/BlastAlign.tar and at http://evolve.zoo.ox.ac.uk/software/blastalign.     

Artificial intelligence techniques for bioinformatics

This review provides an overview of the ways in which techniques from artificial intelligence (AI) can be usefully employed in bioinformatics, both for modelling biological data and for making new discoveries. The paper covers three techniques: symbolic machine learning approaches (nearest neighbour and identification tree techniques), artificial neural networks and genetic algorithms. Each technique is introduced and supported with examples taken from the bioinformatics literature. These examples include folding prediction, viral protease cleavage prediction, classification, multiple sequence alignment and microarray gene expression analysis.     

VIP Barcoding: composition vector‐based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time‐consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user‐friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two‐stage algorithm. First, an alignment‐free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment‐based K2P distance nearest‐neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment‐free methods and (ii) higher scalability than alignment‐based distance methods and character‐based methods. These results suggest that this platform is able to deal with both large‐scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/ .     

HoSeqI: automated homologous sequence identification in gene family databases

We present a web service allowing to automatically assign sequences to homologous gene families from a set of databases. After identification of the most similar gene family to the query sequence, this sequence is added to the whole alignment and the phylogenetic tree of the family is rebuilt. Thus, the phylogenetic position of the query sequence in its gene family can be easily identified. AVAILABILITY: http://pbil.univ-lyon1.fr/software/HoSeqI/.     

Glocal alignment: finding rearrangements during alignment

MOTIVATION: To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, where all locations of similarity between the two strings are returned. Global alignments are less prone to demonstrating false homology as each letter of one sequence is constrained to being aligned to only one letter of the other. Local alignments, on the other hand, can cope with rearrangements between non-syntenic, orthologous sequences by identifying similar regions in sequences; this, however, comes at the expense of a higher false positive rate due to the inability of local aligners to take into account overall conservation maps. RESULTS: In this paper we introduce the notion of glocal alignment, a combination of global and local methods, where one creates a map that transforms one sequence into the other while allowing for rearrangement events. We present Shuffle-LAGAN, a glocal alignment algorithm that is based on the CHAOS local alignment algorithm and the LAGAN global aligner, and is able to align long genomic sequences. To test Shuffle-LAGAN we split the mouse genome into BAC-sized pieces, and aligned these pieces to the human genome. We demonstrate that Shuffle-LAGAN compares favorably in terms of sensitivity and specificity with standard local and global aligners. From the alignments we conclude that about 9% of human/mouse homology may be attributed to small rearrangements, 63% of which are duplications.     

ViTO: tool for refinement of protein sequence-structure alignments

SUMMARY: ViTO is a graphical application, including an editor, of multiple sequence alignment and a three-dimensional (3D) structure viewer. It is possible to manipulate alignments containing hundreds of sequences and to display a dozen structures. ViTO can handle so-called 'multiparts' alignments to allow the visualization of complex structures (multi-chain proteins and/or small molecules and DNA) and the editing of the corresponding alignment. The 3D viewer and the alignment editor are connected together allowing rapid refinement of sequence-structure alignment by taking advantage of the immediate visualization of resulting insertions/deletions and strict conservations in their structural context. More generally, it allows the mapping of informations about the sequence conservation extracted from the alignment onto the 3D structures in a dynamic way. ViTO is also connected to two comparative modelling programs, SCWRL and MODELLER. These features make ViTO a powerful tool to characterize protein families and to optimize the alignments for comparative modelling. AVAILABILITY: http://bioserv.cbs.cnrs.fr/VITO/DOC/. SUPPLEMENTARY INFORMATION: http://bioserv.cbs.cnrs.fr/VITO/DOC/index.html.     

Grouping of amino acids and recognition of protein structurally conserved regions by reduced alphabets of amino acids

Sequence alignment is a common method for finding protein structurally conserved/similar regions. However, sequence alignment is often not accurate if sequence identities between to-be-aligned sequences are less than 30%. This is because that for these sequences, different residues may play similar structural roles and they are incorrectly aligned during the sequence alignment using substitution matrix consisting of 20 types of residues. Based on the similarity of physicochemical features, residues can be clustered into a few groups. Using such simplified alphabets, the complexity of protein sequences is reduced and at the same time the key information encoded in the sequences remains. As a result, the accuracy of sequence alignment might be improved if the residues are properly clustered. Here, by using a database of aligned protein structures (DAPS), a new clustering method based on the substitution scores is proposed for the grouping of residues, and substitution matrices of residues at different levels of simplification are constructed. The validity of the reduced alphabets is confirmed by relative entropy analysis. The reduced alphabets are applied to recognition of protein structurally conserved/similar regions by sequence alignment. The results indicate that the accuracy or efficiency of sequence alignment can be improved with the optimal reduced alphabet with N around 9.     

Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition

MOTIVATION: A key goal of genomics is to assign function to genes, especially for orphan sequences. RESULTS: We compared the clustered functional domains in the SBASE database to each protein sequence using BLASTP. This representation for a protein is a vector, where each of the non-zero entries in the vector indicates a significant match between the sequence of interest and the SBASE domain. The machine learning methods nearest neighbour algorithm (NNA) and support vector machines are used for predicting protein functional classes from this information. We find that the best results are found using the SBASE-A database and the NNA, namely 72% accuracy for 79% coverage. We tested an assigning function based on searching for InterPro sequence motifs and by taking the most significant BLAST match within the dataset. We applied the functional domain composition method to predict the functional class of 2018 currently unclassified yeast open reading frames. AVAILABILITY: A program for the prediction method, that uses NNA called Functional Class Prediction based on Functional Domains (FCPFD) is available and can be obtained by contacting Y.D.Cai at y.cai@umist.ac.uk     

Suboptimal sequence alignment in molecular biology. Alignment with error analysis

A molecular sequence alignment algorithm based on dynamic programming has been extended to allow the computation of all pairs of residues that can be part of optimal and suboptimal sequence alignments. The uncertainties inherent in sequence alignment can be displayed using a new form of dot plot. The method allows the qualitative assessment of whether or not two sequences are related, and can reveal what parts of the alignment are better determined than others. It also permits the computation of representative optimal and suboptimal alignments. The relation between alignment reliability and alignment parameters is discussed. Other applications are to cyclical permutations of sequences and the detection of self-similarity. An application to multiple sequence alignment is noted.     

Relationships among amino acid sequences of animal,microbial and plant peroxidases

Summary Relationships among 18 peroxidases amino acid sequences of animal, microbial and plant origin were examined using optimum alignment of all pairwise sequence combinations to generate a total distance matrix. The matrix was used to cluster the sequences with complete linkage (farthest neighbour) procedures. Specific distances were calculated from the total distances matrix. The patterns of specific distances for each sequence were compared to evaluate the relationships between sequences, check their significance and construct subgroups of related sequences. The results were compared with those from clustering and its resultant dendrogram; good agreement was achieved. The 18 sequences fell into two principal groups, plant peroxidases and animal/microbial peroxidases. Within the plant peroxidases four subgroups were detected; the animal/microbial peroxidases formed a fifth subgroup. Profiles were constructed for the subgroups from lists of matching amino acids generated by the alignment calculations. Superimposed lists were realigned to recognise conserved areas and elements. Individual subgroup profiles for the plant peroxidases were then combined into a single profile which in turn was combined with profiles from the animal/microbial peroxidases. The final profile suggested that numerous sequence features (motifs) were common to peroxidases of widely different function and origins.     

Spatial pattern,regeneration and growth rates of Brachystegia spiciformis and Julbernardia globiflora

Past work on tree-to-tree interactions in semi-arid savannas, through the use of nearest neighbour analysis, has shown both a regular dispersion pattern and a positive correlation between the size of a tree and the distance to its nearest neighbour. From these results, the importance of competition has been inferred. In the present study, tree-to-tree interactions in a mesic savanna woodland at Marondera, Zimbabwe, dominated by relatively small-sized individuals of Brachystegia spiciformis and Julbernardia globiflora, were examined. Results show that the regular dispersion pattern is uncommon; that there are few significant positive correlations between size of individual and distance to nearest neighbour; and that growth rate is not consistently correlated with size and distance of nearest neighbour. Results of a study of regeneration relative to canopy cover suggest a possible mechanism for these findings: unlike semi-arid savannas, young plants often grow in under-canopy environments so that early spacing of young trees does not occur. Significant positive correlations between the size of a tree and the distance to its nearest neighbour were found in a stand of larger, presumably older, trees, suggesting that such a relationship only develops in mesic miombo woodland through a thinning process as the trees mature. Familial clumping, which is common in the study area, may mask spatial patterns.Abbreviations RBAI Relative basal area increment     

Improved alignment of nucleosome DNA sequences using a mixture model

DNA sequences that are present in nucleosomes have a preferential approximately 10 bp periodicity of certain dinucleotide signals, but the overall sequence similarity of the nucleosomal DNA is weak, and traditional multiple sequence alignment tools fail to yield meaningful alignments. We develop a mixture model that characterizes the known dinucleotide periodicity probabilistically to improve the alignment of nucleosomal DNAs. We assume that a periodic dinucleotide signal of any type emits according to a probability distribution around a series of 'hot spots' that are equally spaced along nucleosomal DNA with 10 bp period, but with a 1 bp phase shift across the middle of the nucleosome. We model the three statistically most significant dinucleotide signals, AA/TT, GC and TA, simultaneously, while allowing phase shifts between the signals. The alignment is obtained by maximizing the likelihood of both Watson and Crick strands simultaneously. The resulting alignment of 177 chicken nucleosomal DNA sequences revealed that all 10 distinct dinucleotides are periodic, however, with only two distinct phases and varying intensity. By Fourier analysis, we show that our new alignment has enhanced periodicity and sequence identity compared with center alignment. The significance of the nucleosomal DNA sequence alignment is evaluated by comparing it with that obtained using the same model on non-nucleosomal sequences.     

Grouping of amino acids and recognition of protein structurally conserved regions by reduced alphabets of amino acids

Sequence alignment is a common method for finding protein structurally conserved/similar regions. However, sequence alignment is often not accurate if sequence identities between to-be-aligned sequences are less than 30%. This is because that for these sequences, different residues may play similar structural roles and they are incorrectly aligned during the sequence alignment using substitution matrix consisting of 20 types of residues. Based on the similarity of physicochemical features, residues can be clustered into a few groups. Using such simplified alphabets, the complexity of protein sequences is reduced and at the same time the key information encoded in the sequences remains. As a result, the accuracy of sequence alignment might be improved if the residues are properly clustered. Here, by using a database of aligned protein structures (DAPS), a new clustering method based on the substitution scores is proposed for the grouping of residues, and substitution matrices of residues at different levels of simplification are constructed. The validity of the reduced alphabets is confirmed by relative entropy analysis. The reduced alphabets are applied to recognition of protein structurally conserved/similar regions by sequence alignment. The results indicate that the accuracy or efficiency of sequence alignment can be improved with the optimal reduced alphabet with N around 9. Supported by the National Natural Science Foundation of China (Grant Nos. 90403120, 10474041 and 10021001) and the Nonlinear Project (973) of the NSM     

Multiple alignment by sequence annealing

MOTIVATION: We introduce a novel approach to multiple alignment that is based on an algorithm for rapidly checking whether single matches are consistent with a partial multiple alignment. This leads to a sequence annealing algorithm, which is an incremental method for building multiple sequence alignments one match at a time. Our approach improves significantly on the standard progressive alignment approach to multiple alignment. RESULTS: The sequence annealing algorithm performs well on benchmark test sets of protein sequences. It is not only sensitive, but also specific, drastically reducing the number of incorrectly aligned residues in comparison to other programs. The method allows for adjustment of the sensitivity/specificity tradeoff and can be used to reliably identify homologous regions among protein sequences. AVAILABILITY: An implementation of the sequence annealing algorithm is available at http://bio.math.berkeley.edu/amap/     

Nearest-neighbour interactions in species-rich shrublands: the roles of abundance, spatial patterns and resources

We explored pairwise nearest‐neighbour interactions in four species‐rich shrubland plant communities, asking the question: how often is an individual of species j the nearest‐neighbour of species i? In the observed data and null models, less than 35% of the maximum possible number of nearest‐neighbour species pairs was present, and at three of the four sites the number of observed nearest‐neighbour pairs were significantly less than those occurring in simulated null communities. Many of the missing pairs included woody shrubs whose absence might be interpreted as evidence of site‐specific competition between larger growth forms for soil resources or space. Less than 5% of the pairs of species that occurred did so at frequencies different from that expected under random mixing, and many of these pairs were conspecific. Of the heterospecific pairs whose frequency differed significantly from random mixing there was a weak bias towards pairs occurring at higher rather than lower frequencies than expected. There was no evidence for asymmetry (interaction of species j with species i but not the reverse) in the frequency of species pairs. Nearest‐neighbour relationships are species‐specific rather than between plant functional types. The four sites form a soil nutrient and water availability gradient, and, according to the stress gradient hypothesis, positive species interactions should be most prevalent at the most stressful sites. However, we found the opposite: the site with the highest availability of resources had both proportionally the most heterospecific pairs, and the most conspecific and heterospecific species pairs with frequencies departing significantly from that expected under random mixing.     

Generating consensus sequences from partial order multiple sequence alignment graphs

MOTIVATION: Consensus sequence generation is important in many kinds of sequence analysis ranging from sequence assembly to profile-based iterative search methods. However, how can a consensus be constructed when its inherent assumption-that the aligned sequences form a single linear consensus-is not true? RESULTS: Partial Order Alignment (POA) enables construction and analysis of multiple sequence alignments as directed acyclic graphs containing complex branching structure. Here we present a dynamic programming algorithm (heaviest_bundle) for generating multiple consensus sequences from such complex alignments. The number and relationships of these consensus sequences reveals the degree of structural complexity of the source alignment. This is a powerful and general approach for analyzing and visualizing complex alignment structures, and can be applied to any alignment. We illustrate its value for analyzing expressed sequence alignments to detect alternative splicing, reconstruct full length mRNA isoform sequences from EST fragments, and separate paralog mixtures that can cause incorrect SNP predictions. AVAILABILITY: The heaviest_bundle source code is available at http://www.bioinformatics.ucla.edu/poa     

Confirmation that Thiobacillus halophilus and Thiobacillus hydrothermalis are distinct species within the γ-subclass of the Proteobacteria

Thiobacillus halophilus and Thiobacillus hydrothermalis share 98.7% similarity in 16S rRNA sequence, possess similar gross DNA composition (64.2 and 67.4 mol% G+C values, respectively), and have similar physiological properties. While this might have indicated that they were strains of a single species, DNA-DNA hybridization between the type strains of the two species showed only 59% hybridization, indicating the organisms to be different at the species level. Thiobacillus neapolitanus is the phylogenetically nearest neighbour of T. halophilus and T. hydrothermalis (91.6–92.1% similarity in 16S rRNA sequence) and is the only other Thiobacillus in the γ-subclass of the Proteobacteria that can be regarded as exclusively related to these two species. The 16S rRNA gene sequences of these three species are so different from those of the other thiobacilli in the γ-subclass that they justify recognition as a distinct phyletic group. Their comparative properties are summarized. Received: 23 February 1998 / Accepted: 23 April 1998     

POAVIZ: a Partial order multiple sequence alignment visualizer

SUMMARY: POAVIZ creates a visualization of a multiple sequence alignment that makes clear the overall structure of how sequences match and diverge in the alignment. POAVIZ can construct visualizations from any multiple sequence alignment source (e.g. PIR and CLUSTAL formats), and is valuable for revealing complex branching structure (such as domains, large-scale insertions / deletions or recombinations), especially in partnership with the Partial Order Alignment (POA) multiple sequence alignment program. AVAILABILITY: The Partial Order multiple sequence Alignment Visualizer (POAVIZ) program is available at http://www.bioinformatics.ucla.edu/poa     

A flexible method to align large numbers of biological sequences

Summary A method for the alignment of two or more biological sequences is described. The method is a direct extension of the method of Taylor (1987) incorporating a consensus sequence approach and allows considerable freedom in the control of the clustering of the sequences. At one extreme this is equivalent to the earlier method (Taylor 1987), whereas at the other, the clustering approaches the binary method of Feng and Doolittle (1987). Such freedom allows the program to be adapted to particular problems, which has the important advantage of resulting in considerable savings in computer time, allowing very large problems to be tackled. Besides a detailed analysis of the alignment of the cytochrome c superfamily, the clustering and alignment of the PIR sequence data bank (3500 sequences approx.) is described.