Automated Sanger Analysis Pipeline (ASAP): A Tool for Rapidly Analyzing Sanger Sequencing Data with Minimum User Interference.

PubMed

Singh, Aditya; Bhatia, Prateek

2016-12-01

Sanger sequencing platforms, such as applied biosystems instruments, generate chromatogram files. Generally, for 1 region of a sequence, we use both forward and reverse primers to sequence that area, in that way, we have 2 sequences that need to be aligned and a consensus generated before mutation detection studies. This work is cumbersome and takes time, especially if the gene is large with many exons. Hence, we devised a rapid automated command system to filter, build, and align consensus sequences and also optionally extract exonic regions, translate them in all frames, and perform an amino acid alignment starting from raw sequence data within a very short time. In full capabilities of Automated Mutation Analysis Pipeline (ASAP), it is able to read "*.ab1" chromatogram files through command line interface, convert it to the FASTQ format, trim the low-quality regions, reverse-complement the reverse sequence, create a consensus sequence, extract the exonic regions using a reference exonic sequence, translate the sequence in all frames, and align the nucleic acid and amino acid sequences to reference nucleic acid and amino acid sequences, respectively. All files are created and can be used for further analysis. ASAP is available as Python 3.x executable at https://github.com/aditya-88/ASAP. The version described in this paper is 0.28.

AmpliVar: mutation detection in high-throughput sequence from amplicon-based libraries.

PubMed

Hsu, Arthur L; Kondrashova, Olga; Lunke, Sebastian; Love, Clare J; Meldrum, Cliff; Marquis-Nicholson, Renate; Corboy, Greg; Pham, Kym; Wakefield, Matthew; Waring, Paul M; Taylor, Graham R

2015-04-01

Conventional means of identifying variants in high-throughput sequencing align each read against a reference sequence, and then call variants at each position. Here, we demonstrate an orthogonal means of identifying sequence variation by grouping the reads as amplicons prior to any alignment. We used AmpliVar to make key-value hashes of sequence reads and group reads as individual amplicons using a table of flanking sequences. Low-abundance reads were removed according to a selectable threshold, and reads above this threshold were aligned as groups, rather than as individual reads, permitting the use of sensitive alignment tools. We show that this approach is more sensitive, more specific, and more computationally efficient than comparable methods for the analysis of amplicon-based high-throughput sequencing data. The method can be extended to enable alignment-free confirmation of variants seen in hybridization capture target-enrichment data. © 2015 WILEY PERIODICALS, INC.

High-throughput sequence alignment using Graphics Processing Units

PubMed Central

Schatz, Michael C; Trapnell, Cole; Delcher, Arthur L; Varshney, Amitabh

2007-01-01

Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs) in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA) from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU. PMID:18070356

Analysis of Ribosome Inactivating Protein (RIP): A Bioinformatics Approach

NASA Astrophysics Data System (ADS)

Jothi, G. Edward Gnana; Majilla, G. Sahaya Jose; Subhashini, D.; Deivasigamani, B.

2012-10-01

In spite of the medical advances in recent years, the world is in need of different sources to encounter certain health issues.Ribosome Inactivating Proteins (RIPs) were found to be one among them. In order to get easy access about RIPs, there is a need to analyse RIPs towards constructing a database on RIPs. Also, multiple sequence alignment was done towards screening for homologues of significant RIPs from rare sources against RIPs from easily available sources in terms of similarity. Protein sequences were retrieved from SWISS-PROT and are further analysed using pair wise and multiple sequence alignment.Analysis shows that, 151 RIPs have been characterized to date. Amongst them, there are 87 type I, 37 type II, 1 type III and 25 unknown RIPs. The sequence length information of various RIPs about the availability of full or partial sequence was also found. The multiple sequence alignment of 37 type I RIP using the online server Multalin, indicates the presence of 20 conserved residues. Pairwise alignment and multiple sequence alignment of certain selected RIPs in two groups namely Group I and Group II were carried out and the consensus level was found to be 98%, 98% and 90% respectively.

galaxie--CGI scripts for sequence identification through automated phylogenetic analysis.

PubMed

Nilsson, R Henrik; Larsson, Karl-Henrik; Ursing, Björn M

2004-06-12

The prevalent use of similarity searches like BLAST to identify sequences and species implicitly assumes the reference database to be of extensive sequence sampling. This is often not the case, restraining the correctness of the outcome as a basis for sequence identification. Phylogenetic inference outperforms similarity searches in retrieving correct phylogenies and consequently sequence identities, and a project was initiated to design a freely available script package for sequence identification through automated Web-based phylogenetic analysis. Three CGI scripts were designed to facilitate qualified sequence identification from a Web interface. Query sequences are aligned to pre-made alignments or to alignments made by ClustalW with entries retrieved from a BLAST search. The subsequent phylogenetic analysis is based on the PHYLIP package for inferring neighbor-joining and parsimony trees. The scripts are highly configurable. A service installation and a version for local use are found at http://andromeda.botany.gu.se/galaxiewelcome.html and http://galaxie.cgb.ki.se

MANGO: a new approach to multiple sequence alignment.

PubMed

Zhang, Zefeng; Lin, Hao; Li, Ming

2007-01-01

Multiple sequence alignment is a classical and challenging task for biological sequence analysis. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state of the art multiple sequence alignment programs suffer from the 'once a gap, always a gap' phenomenon. Is there a radically new way to do multiple sequence alignment? This paper introduces a novel and orthogonal multiple sequence alignment method, using multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds are provably significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks showing that MANGO compares favorably, in both accuracy and speed, against state-of-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, Prob-ConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0 and Kalign 2.0.

Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS.

PubMed

Warris, Sven; Yalcin, Feyruz; Jackson, Katherine J L; Nap, Jan Peter

2015-01-01

To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis. With the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation.

Fast alignment-free sequence comparison using spaced-word frequencies.

PubMed

Leimeister, Chris-Andre; Boden, Marcus; Horwege, Sebastian; Lindner, Sebastian; Morgenstern, Burkhard

2014-07-15

Alignment-free methods for sequence comparison are increasingly used for genome analysis and phylogeny reconstruction; they circumvent various difficulties of traditional alignment-based approaches. In particular, alignment-free methods are much faster than pairwise or multiple alignments. They are, however, less accurate than methods based on sequence alignment. Most alignment-free approaches work by comparing the word composition of sequences. A well-known problem with these methods is that neighbouring word matches are far from independent. To reduce the statistical dependency between adjacent word matches, we propose to use 'spaced words', defined by patterns of 'match' and 'don't care' positions, for alignment-free sequence comparison. We describe a fast implementation of this approach using recursive hashing and bit operations, and we show that further improvements can be achieved by using multiple patterns instead of single patterns. To evaluate our approach, we use spaced-word frequencies as a basis for fast phylogeny reconstruction. Using real-world and simulated sequence data, we demonstrate that our multiple-pattern approach produces better phylogenies than approaches relying on contiguous words. Our program is freely available at http://spaced.gobics.de/. © The Author 2014. Published by Oxford University Press.

K2 and K2*: efficient alignment-free sequence similarity measurement based on Kendall statistics.

PubMed

Lin, Jie; Adjeroh, Donald A; Jiang, Bing-Hua; Jiang, Yue

2018-05-15

Alignment-free sequence comparison methods can compute the pairwise similarity between a huge number of sequences much faster than sequence-alignment based methods. We propose a new non-parametric alignment-free sequence comparison method, called K2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K2 demonstrates competitive performance in generating the phylogenetic tree, in evaluating functionally related regulatory sequences, and in computing the edit distance (similarity/dissimilarity) between sequences. Furthermore, the K2 approach is much faster than the other methods. An improved method, K2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automatically, without first considering different values. Comparative analysis with the state-of-the-art alignment-free sequence similarity methods demonstrates the superiority of the proposed approaches, especially with increasing sequence length, or increasing dataset sizes. The K2 and K2* approaches are implemented in the R language as a package and is freely available for open access (http://community.wvu.edu/daadjeroh/projects/K2/K2_1.0.tar.gz). yueljiang@163.com. Supplementary data are available at Bioinformatics online.

MaxAlign: maximizing usable data in an alignment.

PubMed

Gouveia-Oliveira, Rodrigo; Sackett, Peter W; Pedersen, Anders G

2007-08-28

The presence of gaps in an alignment of nucleotide or protein sequences is often an inconvenience for bioinformatical studies. In phylogenetic and other analyses, for instance, gapped columns are often discarded entirely from the alignment. MaxAlign is a program that optimizes the alignment prior to such analyses. Specifically, it maximizes the number of nucleotide (or amino acid) symbols that are present in gap-free columns - the alignment area - by selecting the optimal subset of sequences to exclude from the alignment. MaxAlign can be used prior to phylogenetic and bioinformatical analyses as well as in other situations where this form of alignment improvement is useful. In this work we test MaxAlign's performance in these tasks and compare the accuracy of phylogenetic estimates including and excluding gapped columns from the analysis, with and without processing with MaxAlign. In this paper we also introduce a new simple measure of tree similarity, Normalized Symmetric Similarity (NSS) that we consider useful for comparing tree topologies. We demonstrate how MaxAlign is helpful in detecting misaligned or defective sequences without requiring manual inspection. We also show that it is not advisable to exclude gapped columns from phylogenetic analyses unless MaxAlign is used first. Finally, we find that the sequences removed by MaxAlign from an alignment tend to be those that would otherwise be associated with low phylogenetic accuracy, and that the presence of gaps in any given sequence does not seem to disturb the phylogenetic estimates of other sequences. The MaxAlign web-server is freely available online at http://www.cbs.dtu.dk/services/MaxAlign where supplementary information can also be found. The program is also freely available as a Perl stand-alone package.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

PubMed

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-08-01

RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis

PubMed Central

Steele, Joe; Bastola, Dhundy

2014-01-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base–base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel–Ziv techniques from data compression. PMID:23904502

EGenBio: A Data Management System for Evolutionary Genomics and Biodiversity

PubMed Central

Nahum, Laila A; Reynolds, Matthew T; Wang, Zhengyuan O; Faith, Jeremiah J; Jonna, Rahul; Jiang, Zhi J; Meyer, Thomas J; Pollock, David D

2006-01-01

Background Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed Evolutionary Genomics and Biodiversity (EGenBio; ) to begin to address this. Description EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs. Conclusion EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity. PMID:17118150

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. PMID:24861618

eShadow: A tool for comparing closely related sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ovcharenko, Ivan; Boffelli, Dario; Loots, Gabriela G.

2004-01-15

Primate sequence comparisons are difficult to interpret due to the high degree of sequence similarity shared between such closely related species. Recently, a novel method, phylogenetic shadowing, has been pioneered for predicting functional elements in the human genome through the analysis of multiple primate sequence alignments. We have expanded this theoretical approach to create a computational tool, eShadow, for the identification of elements under selective pressure in multiple sequence alignments of closely related genomes, such as in comparisons of human to primate or mouse to rat DNA. This tool integrates two different statistical methods and allows for the dynamic visualizationmore » of the resulting conservation profile. eShadow also includes a versatile optimization module capable of training the underlying Hidden Markov Model to differentially predict functional sequences. This module grants the tool high flexibility in the analysis of multiple sequence alignments and in comparing sequences with different divergence rates. Here, we describe the eShadow comparative tool and its potential uses for analyzing both multiple nucleotide and protein alignments to predict putative functional elements. The eShadow tool is publicly available at http://eshadow.dcode.org/« less

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

PubMed

Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2004-09-22

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

Differential evolution-simulated annealing for multiple sequence alignment

NASA Astrophysics Data System (ADS)

Addawe, R. C.; Addawe, J. M.; Sueño, M. R. K.; Magadia, J. C.

2017-10-01

Multiple sequence alignments (MSA) are used in the analysis of molecular evolution and sequence structure relationships. In this paper, a hybrid algorithm, Differential Evolution - Simulated Annealing (DESA) is applied in optimizing multiple sequence alignments (MSAs) based on structural information, non-gaps percentage and totally conserved columns. DESA is a robust algorithm characterized by self-organization, mutation, crossover, and SA-like selection scheme of the strategy parameters. Here, the MSA problem is treated as a multi-objective optimization problem of the hybrid evolutionary algorithm, DESA. Thus, we name the algorithm as DESA-MSA. Simulated sequences and alignments were generated to evaluate the accuracy and efficiency of DESA-MSA using different indel sizes, sequence lengths, deletion rates and insertion rates. The proposed hybrid algorithm obtained acceptable solutions particularly for the MSA problem evaluated based on the three objectives.

In silico Analysis of 2085 Clones from a Normalized Rat Vestibular Periphery 3′ cDNA Library

PubMed Central

Roche, Joseph P.; Cioffi, Joseph A.; Kwitek, Anne E.; Erbe, Christy B.; Popper, Paul

2005-01-01

The inserts from 2400 cDNA clones isolated from a normalized Rattus norvegicus vestibular periphery cDNA library were sequenced and characterized. The Wackym-Soares vestibular 3′ cDNA library was constructed from the saccular and utricular maculae, the ampullae of all three semicircular canals and Scarpa's ganglia containing the somata of the primary afferent neurons, microdissected from 104 male and female rats. The inserts from 2400 randomly selected clones were sequenced from the 5′ end. Each sequence was analyzed using the BLAST algorithm compared to the Genbank nonredundant, rat genome, mouse genome and human genome databases to search for high homology alignments. Of the initial 2400 clones, 315 (13%) were found to be of poor quality and did not yield useful information, and therefore were eliminated from the analysis. Of the remaining 2085 sequences, 918 (44%) were found to represent 758 unique genes having useful annotations that were identified in databases within the public domain or in the published literature; these sequences were designated as known characterized sequences. 1141 sequences (55%) aligned with 1011 unique sequences had no useful annotations and were designated as known but uncharacterized sequences. Of the remaining 26 sequences (1%), 24 aligned with rat genomic sequences, but none matched previously described rat expressed sequence tags or mRNAs. No significant alignment to the rat or human genomic sequences could be found for the remaining 2 sequences. Of the 2085 sequences analyzed, 86% were singletons. The known, characterized sequences were analyzed with the FatiGO online data-mining tool (http://fatigo.bioinfo.cnio.es/) to identify level 5 biological process gene ontology (GO) terms for each alignment and to group alignments with similar or identical GO terms. Numerous genes were identified that have not been previously shown to be expressed in the vestibular system. Further characterization of the novel cDNA sequences may lead to the identification of genes with vestibular-specific functions. Continued analysis of the rat vestibular periphery transcriptome should provide new insights into vestibular function and generate new hypotheses. Physiological studies are necessary to further elucidate the roles of the identified genes and novel sequences in vestibular function. PMID:16103642

HSA: a heuristic splice alignment tool.

PubMed

Bu, Jingde; Chi, Xuebin; Jin, Zhong

2013-01-01

RNA-Seq methodology is a revolutionary transcriptomics sequencing technology, which is the representative of Next generation Sequencing (NGS). With the high throughput sequencing of RNA-Seq, we can acquire much more information like differential expression and novel splice variants from deep sequence analysis and data mining. But the short read length brings a great challenge to alignment, especially when the reads span two or more exons. A two steps heuristic splice alignment tool is generated in this investigation. First, map raw reads to reference with unspliced aligner--BWA; second, split initial unmapped reads into three equal short reads (seeds), align each seed to the reference, filter hits, search possible split position of read and extend hits to a complete match. Compare with other splice alignment tools like SOAPsplice and Tophat2, HSA has a better performance in call rate and efficiency, but its results do not as accurate as the other software to some extent. HSA is an effective spliced aligner of RNA-Seq reads mapping, which is available at https://github.com/vlcc/HSA.

Phylo-VISTA: Interactive visualization of multiple DNA sequence alignments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shah, Nameeta; Couronne, Olivier; Pennacchio, Len A.

The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. Results: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a frameworkmore » based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. Availability: Phylo-VISTA is available at http://www-gsd.lbl. gov/phylovista. It requires an Internet browser with Java Plugin 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu« less

BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC

PubMed Central

Satija, Rahul; Novák, Ádám; Miklós, István; Lyngsø, Rune; Hein, Jotun

2009-01-01

Background We have previously combined statistical alignment and phylogenetic footprinting to detect conserved functional elements without assuming a fixed alignment. Considering a probability-weighted distribution of alignments removes sensitivity to alignment errors, properly accommodates regions of alignment uncertainty, and increases the accuracy of functional element prediction. Our method utilized standard dynamic programming hidden markov model algorithms to analyze up to four sequences. Results We present a novel approach, implemented in the software package BigFoot, for performing phylogenetic footprinting on greater numbers of sequences. We have developed a Markov chain Monte Carlo (MCMC) approach which samples both sequence alignments and locations of slowly evolving regions. We implement our method as an extension of the existing StatAlign software package and test it on well-annotated regions controlling the expression of the even-skipped gene in Drosophila and the α-globin gene in vertebrates. The results exhibit how adding additional sequences to the analysis has the potential to improve the accuracy of functional predictions, and demonstrate how BigFoot outperforms existing alignment-based phylogenetic footprinting techniques. Conclusion BigFoot extends a combined alignment and phylogenetic footprinting approach to analyze larger amounts of sequence data using MCMC. Our approach is robust to alignment error and uncertainty and can be applied to a variety of biological datasets. The source code and documentation are publicly available for download from PMID:19715598

BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC.

PubMed

Satija, Rahul; Novák, Adám; Miklós, István; Lyngsø, Rune; Hein, Jotun

2009-08-28

We have previously combined statistical alignment and phylogenetic footprinting to detect conserved functional elements without assuming a fixed alignment. Considering a probability-weighted distribution of alignments removes sensitivity to alignment errors, properly accommodates regions of alignment uncertainty, and increases the accuracy of functional element prediction. Our method utilized standard dynamic programming hidden markov model algorithms to analyze up to four sequences. We present a novel approach, implemented in the software package BigFoot, for performing phylogenetic footprinting on greater numbers of sequences. We have developed a Markov chain Monte Carlo (MCMC) approach which samples both sequence alignments and locations of slowly evolving regions. We implement our method as an extension of the existing StatAlign software package and test it on well-annotated regions controlling the expression of the even-skipped gene in Drosophila and the alpha-globin gene in vertebrates. The results exhibit how adding additional sequences to the analysis has the potential to improve the accuracy of functional predictions, and demonstrate how BigFoot outperforms existing alignment-based phylogenetic footprinting techniques. BigFoot extends a combined alignment and phylogenetic footprinting approach to analyze larger amounts of sequence data using MCMC. Our approach is robust to alignment error and uncertainty and can be applied to a variety of biological datasets. The source code and documentation are publicly available for download from http://www.stats.ox.ac.uk/~satija/BigFoot/

SeqLib: a C ++ API for rapid BAM manipulation, sequence alignment and sequence assembly

PubMed Central

Wala, Jeremiah; Beroukhim, Rameen

2017-01-01

Abstract We present SeqLib, a C ++ API and command line tool that provides a rapid and user-friendly interface to BAM/SAM/CRAM files, global sequence alignment operations and sequence assembly. Four C libraries perform core operations in SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment and Fermi for error correction and sequence assembly. Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence analysis APIs. We demonstrate an example of how minimal SeqLib code can extract, error-correct and assemble reads from a CRAM file and then align with BWA-MEM. SeqLib also provides additional capabilities, including chromosome-aware interval queries and read plotting. Command line tools are available for performing integrated error correction, micro-assemblies and alignment. Availability and Implementation: SeqLib is available on Linux and OSX for the C ++98 standard and later at github.com/walaj/SeqLib. SeqLib is released under the Apache2 license. Additional capabilities for BLAT alignment are available under the BLAT license. Contact: jwala@broadinstitue.org; rameen@broadinstitute.org PMID:28011768

SeqLib: a C ++ API for rapid BAM manipulation, sequence alignment and sequence assembly.

PubMed

Wala, Jeremiah; Beroukhim, Rameen

2017-03-01

We present SeqLib, a C ++ API and command line tool that provides a rapid and user-friendly interface to BAM/SAM/CRAM files, global sequence alignment operations and sequence assembly. Four C libraries perform core operations in SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment and Fermi for error correction and sequence assembly. Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence analysis APIs. We demonstrate an example of how minimal SeqLib code can extract, error-correct and assemble reads from a CRAM file and then align with BWA-MEM. SeqLib also provides additional capabilities, including chromosome-aware interval queries and read plotting. Command line tools are available for performing integrated error correction, micro-assemblies and alignment. SeqLib is available on Linux and OSX for the C ++98 standard and later at github.com/walaj/SeqLib. SeqLib is released under the Apache2 license. Additional capabilities for BLAT alignment are available under the BLAT license. jwala@broadinstitue.org ; rameen@broadinstitute.org. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A statistical physics perspective on alignment-independent protein sequence comparison.

PubMed

Chattopadhyay, Amit K; Nasiev, Diar; Flower, Darren R

2015-08-01

Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from 'first passage probability distribution' to summarize statistics of ensemble averaged amino acid propensity values. In this article, we introduce and elaborate this approach. © The Author 2015. Published by Oxford University Press.

SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

PubMed

Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

2012-07-15

In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies.

PubMed

Joseph, Agnel Praveen; Srinivasan, Narayanaswamy; de Brevern, Alexandre G

2012-09-01

Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a 1D sequence string. A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition. Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Long Read Alignment with Parallel MapReduce Cloud Platform

PubMed Central

Al-Absi, Ahmed Abdulhakim; Kang, Dae-Ki

2015-01-01

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms. PMID:26839887

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA.

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Long Read Alignment with Parallel MapReduce Cloud Platform.

PubMed

Al-Absi, Ahmed Abdulhakim; Kang, Dae-Ki

2015-01-01

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms.

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.

PubMed

Bonham-Carter, Oliver; Steele, Joe; Bastola, Dhundy

2014-11-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base-base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel-Ziv techniques from data compression. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

PubMed Central

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-01-01

Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465

Transcription Factor Map Alignment of Promoter Regions

PubMed Central

Blanco, Enrique; Messeguer, Xavier; Smith, Temple F; Guigó, Roderic

2006-01-01

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments. PMID:16733547

Rapid protein alignment in the cloud: HAMOND combines fast DIAMOND alignments with Hadoop parallelism.

PubMed

Yu, Jia; Blom, Jochen; Sczyrba, Alexander; Goesmann, Alexander

2017-09-10

The introduction of next generation sequencing has caused a steady increase in the amounts of data that have to be processed in modern life science. Sequence alignment plays a key role in the analysis of sequencing data e.g. within whole genome sequencing or metagenome projects. BLAST is a commonly used alignment tool that was the standard approach for more than two decades, but in the last years faster alternatives have been proposed including RapSearch, GHOSTX, and DIAMOND. Here we introduce HAMOND, an application that uses Apache Hadoop to parallelize DIAMOND computation in order to scale-out the calculation of alignments. HAMOND is fault tolerant and scalable by utilizing large cloud computing infrastructures like Amazon Web Services. HAMOND has been tested in comparative genomics analyses and showed promising results both in efficiency and accuracy. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

IVisTMSA: Interactive Visual Tools for Multiple Sequence Alignments.

PubMed

Pervez, Muhammad Tariq; Babar, Masroor Ellahi; Nadeem, Asif; Aslam, Naeem; Naveed, Nasir; Ahmad, Sarfraz; Muhammad, Shah; Qadri, Salman; Shahid, Muhammad; Hussain, Tanveer; Javed, Maryam

2015-01-01

IVisTMSA is a software package of seven graphical tools for multiple sequence alignments. MSApad is an editing and analysis tool. It can load 409% more data than Jalview, STRAP, CINEMA, and Base-by-Base. MSA comparator allows the user to visualize consistent and inconsistent regions of reference and test alignments of more than 21-MB size in less than 12 seconds. MSA comparator is 5,200% efficient and more than 40% efficient as compared to BALiBASE c program and FastSP, respectively. MSA reconstruction tool provides graphical user interfaces for four popular aligners and allows the user to load several sequence files at a time. FASTA generator converts seven formats of alignments of unlimited size into FASTA format in a few seconds. MSA ID calculator calculates identity matrix of more than 11,000 sequences with a sequence length of 2,696 base pairs in less than 100 seconds. Tree and Distance Matrix calculation tools generate phylogenetic tree and distance matrix, respectively, using neighbor joining% identity and BLOSUM 62 matrix.

HIA: a genome mapper using hybrid index-based sequence alignment.

PubMed

Choi, Jongpill; Park, Kiejung; Cho, Seong Beom; Chung, Myungguen

2015-01-01

A number of alignment tools have been developed to align sequencing reads to the human reference genome. The scale of information from next-generation sequencing (NGS) experiments, however, is increasing rapidly. Recent studies based on NGS technology have routinely produced exome or whole-genome sequences from several hundreds or thousands of samples. To accommodate the increasing need of analyzing very large NGS data sets, it is necessary to develop faster, more sensitive and accurate mapping tools. HIA uses two indices, a hash table index and a suffix array index. The hash table performs direct lookup of a q-gram, and the suffix array performs very fast lookup of variable-length strings by exploiting binary search. We observed that combining hash table and suffix array (hybrid index) is much faster than the suffix array method for finding a substring in the reference sequence. Here, we defined the matching region (MR) is a longest common substring between a reference and a read. And, we also defined the candidate alignment regions (CARs) as a list of MRs that is close to each other. The hybrid index is used to find candidate alignment regions (CARs) between a reference and a read. We found that aligning only the unmatched regions in the CAR is much faster than aligning the whole CAR. In benchmark analysis, HIA outperformed in mapping speed compared with the other aligners, without significant loss of mapping accuracy. Our experiments show that the hybrid of hash table and suffix array is useful in terms of speed for mapping NGS sequencing reads to the human reference genome sequence. In conclusion, our tool is appropriate for aligning massive data sets generated by NGS sequencing.

A basic analysis toolkit for biological sequences

PubMed Central

Giancarlo, Raffaele; Siragusa, Alessandro; Siragusa, Enrico; Utro, Filippo

2007-01-01

This paper presents a software library, nicknamed BATS, for some basic sequence analysis tasks. Namely, local alignments, via approximate string matching, and global alignments, via longest common subsequence and alignments with affine and concave gap cost functions. Moreover, it also supports filtering operations to select strings from a set and establish their statistical significance, via z-score computation. None of the algorithms is new, but although they are generally regarded as fundamental for sequence analysis, they have not been implemented in a single and consistent software package, as we do here. Therefore, our main contribution is to fill this gap between algorithmic theory and practice by providing an extensible and easy to use software library that includes algorithms for the mentioned string matching and alignment problems. The library consists of C/C++ library functions as well as Perl library functions. It can be interfaced with Bioperl and can also be used as a stand-alone system with a GUI. The software is available at under the GNU GPL. PMID:17877802

PASS2: an automated database of protein alignments organised as structural superfamilies.

PubMed

Bhaduri, Anirban; Pugalenthi, Ganesan; Sowdhamini, Ramanathan

2004-04-02

The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins. An automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database. The database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

BAYESIAN PROTEIN STRUCTURE ALIGNMENT.

PubMed

Rodriguez, Abel; Schmidler, Scott C

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over evolutionary timescales. A key challenge is the identification and evaluation of structural similarity between proteins; such analysis can aid in understanding the role of newly discovered proteins and help elucidate evolutionary relationships between organisms. Computational biologists have developed many clever algorithmic techniques for comparing protein structures, however, all are based on heuristic optimization criteria, making statistical interpretation somewhat difficult. Here we present a fully probabilistic framework for pairwise structural alignment of proteins. Our approach has several advantages, including the ability to capture alignment uncertainty and to estimate key "gap" parameters which critically affect the quality of the alignment. We show that several existing alignment methods arise as maximum a posteriori estimates under specific choices of prior distributions and error models. Our probabilistic framework is also easily extended to incorporate additional information, which we demonstrate by including primary sequence information to generate simultaneous sequence-structure alignments that can resolve ambiguities obtained using structure alone. This combined model also provides a natural approach for the difficult task of estimating evolutionary distance based on structural alignments. The model is illustrated by comparison with well-established methods on several challenging protein alignment examples.

Sequence Diversity Diagram for comparative analysis of multiple sequence alignments.

PubMed

Sakai, Ryo; Aerts, Jan

2014-01-01

The sequence logo is a graphical representation of a set of aligned sequences, commonly used to depict conservation of amino acid or nucleotide sequences. Although it effectively communicates the amount of information present at every position, this visual representation falls short when the domain task is to compare between two or more sets of aligned sequences. We present a new visual presentation called a Sequence Diversity Diagram and validate our design choices with a case study. Our software was developed using the open-source program called Processing. It loads multiple sequence alignment FASTA files and a configuration file, which can be modified as needed to change the visualization. The redesigned figure improves on the visual comparison of two or more sets, and it additionally encodes information on sequential position conservation. In our case study of the adenylate kinase lid domain, the Sequence Diversity Diagram reveals unexpected patterns and new insights, for example the identification of subgroups within the protein subfamily. Our future work will integrate this visual encoding into interactive visualization tools to support higher level data exploration tasks.

BlockLogo: visualization of peptide and sequence motif conservation

PubMed Central

Olsen, Lars Rønn; Kudahl, Ulrich Johan; Simon, Christian; Sun, Jing; Schönbach, Christian; Reinherz, Ellis L.; Zhang, Guang Lan; Brusic, Vladimir

2013-01-01

BlockLogo is a web-server application for visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, selection of motif positions, type of sequence, and output format definition. The output has BlockLogo along with the sequence logo, and a table of motif frequencies. We deployed BlockLogo as an online application and have demonstrated its utility through examples that show visualization of T-cell epitopes and B-cell epitopes (both continuous and discontinuous). Our additional example shows a visualization and analysis of structural motifs that determine specificity of peptide binding to HLA-DR molecules. The BlockLogo server also employs selected experimentally validated prediction algorithms to enable on-the-fly prediction of MHC binding affinity to 15 common HLA class I and class II alleles as well as visual analysis of discontinuous epitopes from multiple sequence alignments. It enables the visualization and analysis of structural and functional motifs that are usually described as regular expressions. It provides a compact view of discontinuous motifs composed of distant positions within biological sequences. BlockLogo is available at: http://research4.dfci.harvard.edu/cvc/blocklogo/ and http://methilab.bu.edu/blocklogo/ PMID:24001880

The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes.

PubMed

Treangen, Todd J; Ondov, Brian D; Koren, Sergey; Phillippy, Adam M

2014-01-01

Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from: http://github.com/marbl/harvest.

Customisation of the exome data analysis pipeline using a combinatorial approach.

PubMed

Pattnaik, Swetansu; Vaidyanathan, Srividya; Pooja, Durgad G; Deepak, Sa; Panda, Binay

2012-01-01

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.

Heuristics for multiobjective multiple sequence alignment.

PubMed

Abbasi, Maryam; Paquete, Luís; Pereira, Francisco B

2016-07-15

Aligning multiple sequences arises in many tasks in Bioinformatics. However, the alignments produced by the current software packages are highly dependent on the parameters setting, such as the relative importance of opening gaps with respect to the increase of similarity. Choosing only one parameter setting may provide an undesirable bias in further steps of the analysis and give too simplistic interpretations. In this work, we reformulate multiple sequence alignment from a multiobjective point of view. The goal is to generate several sequence alignments that represent a trade-off between maximizing the substitution score and minimizing the number of indels/gaps in the sum-of-pairs score function. This trade-off gives to the practitioner further information about the similarity of the sequences, from which she could analyse and choose the most plausible alignment. We introduce several heuristic approaches, based on local search procedures, that compute a set of sequence alignments, which are representative of the trade-off between the two objectives (substitution score and indels). Several algorithm design options are discussed and analysed, with particular emphasis on the influence of the starting alignment and neighborhood search definitions on the overall performance. A perturbation technique is proposed to improve the local search, which provides a wide range of high-quality alignments. The proposed approach is tested experimentally on a wide range of instances. We performed several experiments with sequences obtained from the benchmark database BAliBASE 3.0. To evaluate the quality of the results, we calculate the hypervolume indicator of the set of score vectors returned by the algorithms. The results obtained allow us to identify reasonably good choices of parameters for our approach. Further, we compared our method in terms of correctly aligned pairs ratio and columns correctly aligned ratio with respect to reference alignments. Experimental results show that our approaches can obtain better results than TCoffee and Clustal Omega in terms of the first ratio.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2010-01-01

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys. PMID:20530533

DNATagger, colors for codons.

PubMed

Scherer, N M; Basso, D M

2008-09-16

DNATagger is a web-based tool for coloring and editing DNA, RNA and protein sequences and alignments. It is dedicated to the visualization of protein coding sequences and also protein sequence alignments to facilitate the comprehension of evolutionary processes in sequence analysis. The distinctive feature of DNATagger is the use of codons as informative units for coloring DNA and RNA sequences. The codons are colored according to their corresponding amino acids. It is the first program that colors codons in DNA sequences without being affected by "out-of-frame" gaps of alignments. It can handle single gaps and gaps inside the triplets. The program also provides the possibility to edit the alignments and change color patterns and translation tables. DNATagger is a JavaScript application, following the W3C guidelines, designed to work on standards-compliant web browsers. It therefore requires no installation and is platform independent. The web-based DNATagger is available as free and open source software at http://www.inf.ufrgs.br/~dmbasso/dnatagger/.

Efficient alignment-free DNA barcode analytics.

PubMed

Kuksa, Pavel; Pavlovic, Vladimir

2009-11-10

In this work we consider barcode DNA analysis problems and address them using alternative, alignment-free methods and representations which model sequences as collections of short sequence fragments (features). The methods use fixed-length representations (spectrum) for barcode sequences to measure similarities or dissimilarities between sequences coming from the same or different species. The spectrum-based representation not only allows for accurate and computationally efficient species classification, but also opens possibility for accurate clustering analysis of putative species barcodes and identification of critical within-barcode loci distinguishing barcodes of different sample groups. New alignment-free methods provide highly accurate and fast DNA barcode-based identification and classification of species with substantial improvements in accuracy and speed over state-of-the-art barcode analysis methods. We evaluate our methods on problems of species classification and identification using barcodes, important and relevant analytical tasks in many practical applications (adverse species movement monitoring, sampling surveys for unknown or pathogenic species identification, biodiversity assessment, etc.) On several benchmark barcode datasets, including ACG, Astraptes, Hesperiidae, Fish larvae, and Birds of North America, proposed alignment-free methods considerably improve prediction accuracy compared to prior results. We also observe significant running time improvements over the state-of-the-art methods. Our results show that newly developed alignment-free methods for DNA barcoding can efficiently and with high accuracy identify specimens by examining only few barcode features, resulting in increased scalability and interpretability of current computational approaches to barcoding.

Clustalnet: the joining of Clustal and CORBA.

PubMed

Campagne, F

2000-07-01

Performing sequence alignment operations from a different program than the original sequence alignment code, and/or through a network connection, is often required. Interactive alignment editors and large-scale biological data analysis are common examples where such a flexibility is important. Interoperability between the alignment engine and the client should be obtained regardless of the architectures and programming languages of the server and client. Clustalnet, a Clustal alignment CORBA server is described, which was developed on the basis of Clustalw. This server brings the robustness of the algorithms and implementations of Clustal to a new level of reuse. A Clustalnet server object can be accessed from a program, transparently through the network. We present interfaces to perform the alignment operations and to control these operations via immutable contexts. The interfaces that select the contexts do not depend on the nature of the operation to be performed, making the design modular. The IDL interfaces presented here are not specific to Clustal and can be implemented on top of different sequence alignment algorithm implementations.

Evaluation of sequence alignments and oligonucleotide probes with respect to three-dimensional structure of ribosomal RNA using ARB software package

PubMed Central

Kumar, Yadhu; Westram, Ralf; Kipfer, Peter; Meier, Harald; Ludwig, Wolfgang

2006-01-01

Background Availability of high-resolution RNA crystal structures for the 30S and 50S ribosomal subunits and the subsequent validation of comparative secondary structure models have prompted the biologists to use three-dimensional structure of ribosomal RNA (rRNA) for evaluating sequence alignments of rRNA genes. Furthermore, the secondary and tertiary structural features of rRNA are highly useful and successfully employed in designing rRNA targeted oligonucleotide probes intended for in situ hybridization experiments. RNA3D, a program to combine sequence alignment information with three-dimensional structure of rRNA was developed. Integration into ARB software package, which is used extensively by the scientific community for phylogenetic analysis and molecular probe designing, has substantially extended the functionality of ARB software suite with 3D environment. Results Three-dimensional structure of rRNA is visualized in OpenGL 3D environment with the abilities to change the display and overlay information onto the molecule, dynamically. Phylogenetic information derived from the multiple sequence alignments can be overlaid onto the molecule structure in a real time. Superimposition of both statistical and non-statistical sequence associated information onto the rRNA 3D structure can be done using customizable color scheme, which is also applied to a textual sequence alignment for reference. Oligonucleotide probes designed by ARB probe design tools can be mapped onto the 3D structure along with the probe accessibility models for evaluation with respect to secondary and tertiary structural conformations of rRNA. Conclusion Visualization of three-dimensional structure of rRNA in an intuitive display provides the biologists with the greater possibilities to carry out structure based phylogenetic analysis. Coupled with secondary structure models of rRNA, RNA3D program aids in validating the sequence alignments of rRNA genes and evaluating probe target sites. Superimposition of the information derived from the multiple sequence alignment onto the molecule dynamically allows the researchers to observe any sequence inherited characteristics (phylogenetic information) in real-time environment. The extended ARB software package is made freely available for the scientific community via . PMID:16672074

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

PubMed

Xu, Weijia; Ozer, Stuart; Gutell, Robin R

2009-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA

PubMed Central

Xu, Weijia; Ozer, Stuart; Gutell, Robin R.

2010-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure. PMID:20502534

Evolutionary profiles from the QR factorization of multiple sequence alignments

PubMed Central

Sethi, Anurag; O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-01-01

We present an algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of the homologous group. The method, based on the multidimensional QR factorization of numerically encoded multiple sequence alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. We observe a general trend that these smaller, more evolutionarily balanced profiles have comparable and, in many cases, better performance in database searches than conventional profiles containing hundreds of sequences, constructed in an iterative and computationally intensive procedure. For more diverse families or superfamilies, with sequence identity <30%, structural alignments, based purely on the geometry of the protein structures, provide better alignments than pure sequence-based methods. Merging the structure and sequence information allows the construction of accurate profiles for distantly related groups. These structure-based profiles outperformed other sequence-based methods for finding distant homologs and were used to identify a putative class II cysteinyl-tRNA synthetase (CysRS) in several archaea that eluded previous annotation studies. Phylogenetic analysis showed the putative class II CysRSs to be a monophyletic group and homology modeling revealed a constellation of active site residues similar to that in the known class I CysRS. PMID:15741270

Accelerated probabilistic inference of RNA structure evolution

PubMed Central

Holmes, Ian

2005-01-01

Background Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary structure prediction, but the associated algorithms are intensive in both CPU and memory usage. The same problem is faced by other RNA alignment-and-folding algorithms based on Sankoff's 1985 algorithm. It is therefore desirable to constrain such algorithms, by pre-processing the sequences and using this first pass to limit the range of structures and/or alignments that can be considered. Results We demonstrate how flexible classes of constraint can be imposed, greatly reducing the computational costs while maintaining a high quality of structural homology prediction. Any score-attributed context-free grammar (e.g. energy-based scoring schemes, or conditionally normalized Pair SCFGs) is amenable to this treatment. It is now possible to combine independent structural and alignment constraints of unprecedented general flexibility in Pair SCFG alignment algorithms. We outline several applications to the bioinformatics of RNA sequence and structure, including Waterman-Eggert N-best alignments and progressive multiple alignment. We evaluate the performance of the algorithm on test examples from the RFAM database. Conclusion A program, Stemloc, that implements these algorithms for efficient RNA sequence alignment and structure prediction is available under the GNU General Public License. PMID:15790387

DendroBLAST: approximate phylogenetic trees in the absence of multiple sequence alignments.

PubMed

Kelly, Steven; Maini, Philip K

2013-01-01

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

RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

PubMed

Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

2017-01-21

RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA comparison tools, RNApdist and RNAdistance, showcased that RNA-TVcurve can efficiently capture subtle relationships among RNAs for mutation detection and non-coding RNA classification. All the relevant results were shown in an intuitive graphical manner, and can be freely downloaded from this server. RNA-TVcurve, along with test examples and detailed documents, are available at: http://ml.jlu.edu.cn/tvcurve/ .

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, G.; Korber, B.; Wain-Hobson, S.

This compendium, including accompanying floppy diskettes, is the result of an effort to compile and rapidly publish all relevant molecular data concerning the human immunodeficiency viruses (HIV) and related retroviruses. The scope of the compendium and database is best summarized by the five parts it comprises: (I) Nucleic Acid Alignments and Sequences; (II) Amino Acid Alignments; (III) Analysis; (IV) Related Sequences; (V) Database communications.

A novel approach to multiple sequence alignment using hadoop data grids.

PubMed

Sudha Sadasivam, G; Baktavatchalam, G

2010-01-01

Multiple alignment of protein sequences helps to determine evolutionary linkage and to predict molecular structures. The factors to be considered while aligning multiple sequences are speed and accuracy of alignment. Although dynamic programming algorithms produce accurate alignments, they are computation intensive. In this paper we propose a time efficient approach to sequence alignment that also produces quality alignment. The dynamic nature of the algorithm coupled with data and computational parallelism of hadoop data grids improves the accuracy and speed of sequence alignment. The principle of block splitting in hadoop coupled with its scalability facilitates alignment of very large sequences.

TaxI: a software tool for DNA barcoding using distance methods

PubMed Central

Steinke, Dirk; Vences, Miguel; Salzburger, Walter; Meyer, Axel

2005-01-01

DNA barcoding is a promising approach to the diagnosis of biological diversity in which DNA sequences serve as the primary key for information retrieval. Most existing software for evolutionary analysis of DNA sequences was designed for phylogenetic analyses and, hence, those algorithms do not offer appropriate solutions for the rapid, but precise analyses needed for DNA barcoding, and are also unable to process the often large comparative datasets. We developed a flexible software tool for DNA taxonomy, named TaxI. This program calculates sequence divergences between a query sequence (taxon to be barcoded) and each sequence of a dataset of reference sequences defined by the user. Because the analysis is based on separate pairwise alignments this software is also able to work with sequences characterized by multiple insertions and deletions that are difficult to align in large sequence sets (i.e. thousands of sequences) by multiple alignment algorithms because of computational restrictions. Here, we demonstrate the utility of this approach with two datasets of fish larvae and juveniles from Lake Constance and juvenile land snails under different models of sequence evolution. Sets of ribosomal 16S rRNA sequences, characterized by multiple indels, performed as good as or better than cox1 sequence sets in assigning sequences to species, demonstrating the suitability of rRNA genes for DNA barcoding. PMID:16214755

A method of alignment masking for refining the phylogenetic signal of multiple sequence alignments.

PubMed

Rajan, Vaibhav

2013-03-01

Inaccurate inference of positional homologies in multiple sequence alignments and systematic errors introduced by alignment heuristics obfuscate phylogenetic inference. Alignment masking, the elimination of phylogenetically uninformative or misleading sites from an alignment before phylogenetic analysis, is a common practice in phylogenetic analysis. Although masking is often done manually, automated methods are necessary to handle the much larger data sets being prepared today. In this study, we introduce the concept of subsplits and demonstrate their use in extracting phylogenetic signal from alignments. We design a clustering approach for alignment masking where each cluster contains similar columns-similarity being defined on the basis of compatible subsplits; our approach then identifies noisy clusters and eliminates them. Trees inferred from the columns in the retained clusters are found to be topologically closer to the reference trees. We test our method on numerous standard benchmarks (both synthetic and biological data sets) and compare its performance with other methods of alignment masking. We find that our method can eliminate sites more accurately than other methods, particularly on divergent data, and can improve the topologies of the inferred trees in likelihood-based analyses. Software available upon request from the author.

Efficient alignment-free DNA barcode analytics

PubMed Central

Kuksa, Pavel; Pavlovic, Vladimir

2009-01-01

Background In this work we consider barcode DNA analysis problems and address them using alternative, alignment-free methods and representations which model sequences as collections of short sequence fragments (features). The methods use fixed-length representations (spectrum) for barcode sequences to measure similarities or dissimilarities between sequences coming from the same or different species. The spectrum-based representation not only allows for accurate and computationally efficient species classification, but also opens possibility for accurate clustering analysis of putative species barcodes and identification of critical within-barcode loci distinguishing barcodes of different sample groups. Results New alignment-free methods provide highly accurate and fast DNA barcode-based identification and classification of species with substantial improvements in accuracy and speed over state-of-the-art barcode analysis methods. We evaluate our methods on problems of species classification and identification using barcodes, important and relevant analytical tasks in many practical applications (adverse species movement monitoring, sampling surveys for unknown or pathogenic species identification, biodiversity assessment, etc.) On several benchmark barcode datasets, including ACG, Astraptes, Hesperiidae, Fish larvae, and Birds of North America, proposed alignment-free methods considerably improve prediction accuracy compared to prior results. We also observe significant running time improvements over the state-of-the-art methods. Conclusion Our results show that newly developed alignment-free methods for DNA barcoding can efficiently and with high accuracy identify specimens by examining only few barcode features, resulting in increased scalability and interpretability of current computational approaches to barcoding. PMID:19900305

Phylogenetic relationships within the cyst-forming nematodes (Nematoda, Heteroderidae) based on analysis of sequences from the ITS regions of ribosomal DNA.

PubMed

Subbotin, S A; Vierstraete, A; De Ley, P; Rowe, J; Waeyenberge, L; Moens, M; Vanfleteren, J R

2001-10-01

The ITS1, ITS2, and 5.8S gene sequences of nuclear ribosomal DNA from 40 taxa of the family Heteroderidae (including the genera Afenestrata, Cactodera, Heterodera, Globodera, Punctodera, Meloidodera, Cryphodera, and Thecavermiculatus) were sequenced and analyzed. The ITS regions displayed high levels of sequence divergence within Heteroderinae and compared to outgroup taxa. Unlike recent findings in root knot nematodes, ITS sequence polymorphism does not appear to complicate phylogenetic analysis of cyst nematodes. Phylogenetic analyses with maximum-parsimony, minimum-evolution, and maximum-likelihood methods were performed with a range of computer alignments, including elision and culled alignments. All multiple alignments and phylogenetic methods yielded similar basic structure for phylogenetic relationships of Heteroderidae. The cyst-forming nematodes are represented by six main clades corresponding to morphological characters and host specialization, with certain clades assuming different positions depending on alignment procedure and/or method of phylogenetic inference. Hypotheses of monophyly of Punctoderinae and Heteroderinae are, respectively, strongly and moderately supported by the ITS data across most alignments. Close relationships were revealed between the Avenae and the Sacchari groups and between the Humuli group and the species H. salixophila within Heteroderinae. The Goettingiana group occupies a basal position within this subfamily. The validity of the genera Afenestrata and Bidera was tested and is discussed based on molecular data. We conclude that ITS sequence data are appropriate for studies of relationships within the different species groups and less so for recovery of more ancient speciations within Heteroderidae. Copyright 2001 Academic Press.

Interpreting the biological relevance of bioinformatic analyses with T-DNA sequence for protein allergenicity.

PubMed

Harper, B; McClain, S; Ganko, E W

2012-08-01

Global regulatory agencies require bioinformatic sequence analysis as part of their safety evaluation for transgenic crops. Analysis typically focuses on encoded proteins and adjacent endogenous flanking sequences. Recently, regulatory expectations have expanded to include all reading frames of the inserted DNA. The intent is to provide biologically relevant results that can be used in the overall assessment of safety. This paper evaluates the relevance of assessing the allergenic potential of all DNA reading frames found in common food genes using methods considered for the analysis of T-DNA sequences used in transgenic crops. FASTA and BLASTX algorithms were used to compare genes from maize, rice, soybean, cucumber, melon, watermelon, and tomato using international regulatory guidance. Results show that BLASTX for maize yielded 7254 alignments that exceeded allergen similarity thresholds and 210,772 alignments that matched eight or more consecutive amino acids with an allergen; other crops produced similar results. This analysis suggests that each nontransgenic crop has a much greater potential for allergenic risk than what has been observed clinically. We demonstrate that a meaningful safety assessment is unlikely to be provided by using methods with inherently high frequencies of false positive alignments when broadly applied to all reading frames of DNA sequence. Copyright © 2012 Elsevier Inc. All rights reserved.

Sequence analysis of Leukemia DNA

NASA Astrophysics Data System (ADS)

Nacong, Nasria; Lusiyanti, Desy; Irawan, Muhammad. Isa

2018-03-01

Cancer is a very deadly disease, one of which is leukemia disease or better known as blood cancer. The cancer cell can be detected by taking DNA in laboratory test. This study focused on local alignment of leukemia and non leukemia data resulting from NCBI in the form of DNA sequences by using Smith-Waterman algorithm. SmithWaterman algorithm was invented by TF Smith and MS Waterman in 1981. These algorithms try to find as much as possible similarity of a pair of sequences, by giving a negative value to the unequal base pair (mismatch), and positive values on the same base pair (match). So that will obtain the maximum positive value as the end of the alignment, and the minimum value as the initial alignment. This study will use sequences of leukemia and 3 sequences of non leukemia.

A new version of the RDP (Ribosomal Database Project)

NASA Technical Reports Server (NTRS)

Maidak, B. L.; Cole, J. R.; Parker, C. T. Jr; Garrity, G. M.; Larsen, N.; Li, B.; Lilburn, T. G.; McCaughey, M. J.; Olsen, G. J.; Overbeek, R.;

Sequence analysis by iterated maps, a review.

PubMed

Almeida, Jonas S

2014-05-01

Among alignment-free methods, Iterated Maps (IMs) are on a particular extreme: they are also scale free (order free). The use of IMs for sequence analysis is also distinct from other alignment-free methodologies in being rooted in statistical mechanics instead of computational linguistics. Both of these roots go back over two decades to the use of fractal geometry in the characterization of phase-space representations. The time series analysis origin of the field is betrayed by the title of the manuscript that started this alignment-free subdomain in 1990, 'Chaos Game Representation'. The clash between the analysis of sequences as continuous series and the better established use of Markovian approaches to discrete series was almost immediate, with a defining critique published in same journal 2 years later. The rest of that decade would go by before the scale-free nature of the IM space was uncovered. The ensuing decade saw this scalability generalized for non-genomic alphabets as well as an interest in its use for graphic representation of biological sequences. Finally, in the past couple of years, in step with the emergence of BigData and MapReduce as a new computational paradigm, there is a surprising third act in the IM story. Multiple reports have described gains in computational efficiency of multiple orders of magnitude over more conventional sequence analysis methodologies. The stage appears to be now set for a recasting of IMs with a central role in processing nextgen sequencing results.

Viral genome analysis and knowledge management.

PubMed

Kuiken, Carla; Yoon, Hyejin; Abfalterer, Werner; Gaschen, Brian; Lo, Chienchi; Korber, Bette

2013-01-01

One of the challenges of genetic data analysis is to combine information from sources that are distributed around the world and accessible through a wide array of different methods and interfaces. The HIV database and its footsteps, the hepatitis C virus (HCV) and hemorrhagic fever virus (HFV) databases, have made it their mission to make different data types easily available to their users. This involves a large amount of behind-the-scenes processing, including quality control and analysis of the sequences and their annotation. Gene and protein sequences are distilled from the sequences that are stored in GenBank; to this end, both submitter annotation and script-generated sequences are used. Alignments of both nucleotide and amino acid sequences are generated, manually curated, distilled into an alignment model, and regenerated in an iterative cycle that results in ever better new alignments. Annotation of epidemiological and clinical information is parsed, checked, and added to the database. User interfaces are updated, and new interfaces are added based upon user requests. Vital for its success, the database staff are heavy users of the system, which enables them to fix bugs and find opportunities for improvement. In this chapter we describe some of the infrastructure that keeps these heavily used analysis platforms alive and vital after nearly 25 years of use. The database/analysis platforms described in this chapter can be accessed at http://hiv.lanl.gov http://hcv.lanl.gov http://hfv.lanl.gov.

Wasabi: An Integrated Platform for Evolutionary Sequence Analysis and Data Visualization.

PubMed

Veidenberg, Andres; Medlar, Alan; Löytynoja, Ari

2016-04-01

Wasabi is an open source, web-based environment for evolutionary sequence analysis. Wasabi visualizes sequence data together with a phylogenetic tree within a modern, user-friendly interface: The interface hides extraneous options, supports context sensitive menus, drag-and-drop editing, and displays additional information, such as ancestral sequences, associated with specific tree nodes. The Wasabi environment supports reproducibility by automatically storing intermediate analysis steps and includes built-in functions to share data between users and publish analysis results. For computational analysis, Wasabi supports PRANK and PAGAN for phylogeny-aware alignment and alignment extension, and it can be easily extended with other tools. Along with drag-and-drop import of local files, Wasabi can access remote data through URL and import sequence data, GeneTrees and EPO alignments directly from Ensembl. To demonstrate a typical workflow using Wasabi, we reproduce key findings from recent comparative genomics studies, including a reanalysis of the EGLN1 gene from the tiger genome study: These case studies can be browsed within Wasabi at http://wasabiapp.org:8000?id=usecases. Wasabi runs inside a web browser and does not require any installation. One can start using it at http://wasabiapp.org. All source code is licensed under the AGPLv3. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Improving transmission efficiency of large sequence alignment/map (SAM) files.

PubMed

Sakib, Muhammad Nazmus; Tang, Jijun; Zheng, W Jim; Huang, Chin-Tser

2011-01-01

Research in bioinformatics primarily involves collection and analysis of a large volume of genomic data. Naturally, it demands efficient storage and transfer of this huge amount of data. In recent years, some research has been done to find efficient compression algorithms to reduce the size of various sequencing data. One way to improve the transmission time of large files is to apply a maximum lossless compression on them. In this paper, we present SAMZIP, a specialized encoding scheme, for sequence alignment data in SAM (Sequence Alignment/Map) format, which improves the compression ratio of existing compression tools available. In order to achieve this, we exploit the prior knowledge of the file format and specifications. Our experimental results show that our encoding scheme improves compression ratio, thereby reducing overall transmission time significantly.

ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output.

PubMed

Zaal, Dionne; Nota, Benjamin

2016-01-01

We present ADOMA, a command line tool that produces alternative outputs from ClustalW multiple alignments of nucleotide or protein sequences. ADOMA can simplify the output of alignments by showing only the different residues between sequences, which is often desirable when only small differences such as single nucleotide polymorphisms are present (e.g., between different alleles). Another feature of ADOMA is that it can enhance the ClustalW output by coloring the residues in the alignment. This tool is easily integrated into automated Linux pipelines for next-generation sequencing data analysis, and may be useful for researchers in a broad range of scientific disciplines including evolutionary biology and biomedical sciences. The source code is freely available at https://sourceforge. net/projects/adoma/. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments

PubMed Central

Di Tommaso, Paolo; Bussotti, Giovanni; Kemena, Carsten; Capriotti, Emidio; Chatzou, Maria; Prieto, Pablo; Notredame, Cedric

2014-01-01

This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available. The server can be accessed from http://tcoffee.crg.cat/apps/tcoffee/do:saracoffee. PMID:24972831

Using structure to explore the sequence alignment space of remote homologs.

PubMed

Kuziemko, Andrew; Honig, Barry; Petrey, Donald

2011-10-01

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is "optimal" in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are "suboptimal" in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for "modelability", we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended.

CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments.

PubMed

Zhou, Carol L Ecale

2015-01-01

In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure. This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins. CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.

Alignment of high-throughput sequencing data inside in-memory databases.

PubMed

Firnkorn, Daniel; Knaup-Gregori, Petra; Lorenzo Bermejo, Justo; Ganzinger, Matthias

2014-01-01

In times of high-throughput DNA sequencing techniques, performance-capable analysis of DNA sequences is of high importance. Computer supported DNA analysis is still an intensive time-consuming task. In this paper we explore the potential of a new In-Memory database technology by using SAP's High Performance Analytic Appliance (HANA). We focus on read alignment as one of the first steps in DNA sequence analysis. In particular, we examined the widely used Burrows-Wheeler Aligner (BWA) and implemented stored procedures in both, HANA and the free database system MySQL, to compare execution time and memory management. To ensure that the results are comparable, MySQL has been running in memory as well, utilizing its integrated memory engine for database table creation. We implemented stored procedures, containing exact and inexact searching of DNA reads within the reference genome GRCh37. Due to technical restrictions in SAP HANA concerning recursion, the inexact matching problem could not be implemented on this platform. Hence, performance analysis between HANA and MySQL was made by comparing the execution time of the exact search procedures. Here, HANA was approximately 27 times faster than MySQL which means, that there is a high potential within the new In-Memory concepts, leading to further developments of DNA analysis procedures in the future.

Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner.

PubMed

Lu, David V; Brown, Randall H; Arumugam, Manimozhiyan; Brent, Michael R

2009-07-01

The most accurate way to determine the intron-exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics. We present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created 'perfect' simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat. We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of >99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner. Pairagon source and executables are freely available at http://mblab.wustl.edu/software/pairagon/

Designing universal primers for the isolation of DNA sequences encoding Proanthocyanidins biosynthetic enzymes in Crataegus aronia

PubMed Central

2012-01-01

Background Hawthorn is the common name of all plant species in the genus Crataegus, which belongs to the Rosaceae family. Crataegus are considered useful medicinal plants because of their high content of proanthocyanidins (PAs) and other related compounds. To improve PAs production in Crataegus tissues, the sequences of genes encoding PAs biosynthetic enzymes are required. Findings Different bioinformatics tools, including BLAST, multiple sequence alignment and alignment PCR analysis were used to design primers suitable for the amplification of DNA fragments from 10 candidate genes encoding enzymes involved in PAs biosynthesis in C. aronia. DNA sequencing results proved the utility of the designed primers. The primers were used successfully to amplify DNA fragments of different PAs biosynthesis genes in different Rosaceae plants. Conclusion To the best of our knowledge, this is the first use of the alignment PCR approach to isolate DNA sequences encoding PAs biosynthetic enzymes in Rosaceae plants. PMID:22883984

Designing universal primers for the isolation of DNA sequences encoding Proanthocyanidins biosynthetic enzymes in Crataegus aronia.

PubMed

Zuiter, Afnan Saeid; Sawwan, Jammal; Al Abdallat, Ayed

2012-08-10

Hawthorn is the common name of all plant species in the genus Crataegus, which belongs to the Rosaceae family. Crataegus are considered useful medicinal plants because of their high content of proanthocyanidins (PAs) and other related compounds. To improve PAs production in Crataegus tissues, the sequences of genes encoding PAs biosynthetic enzymes are required. Different bioinformatics tools, including BLAST, multiple sequence alignment and alignment PCR analysis were used to design primers suitable for the amplification of DNA fragments from 10 candidate genes encoding enzymes involved in PAs biosynthesis in C. aronia. DNA sequencing results proved the utility of the designed primers. The primers were used successfully to amplify DNA fragments of different PAs biosynthesis genes in different Rosaceae plants. To the best of our knowledge, this is the first use of the alignment PCR approach to isolate DNA sequences encoding PAs biosynthetic enzymes in Rosaceae plants.

Application of discrete Fourier inter-coefficient difference for assessing genetic sequence similarity.

PubMed

King, Brian R; Aburdene, Maurice; Thompson, Alex; Warres, Zach

2014-01-01

Digital signal processing (DSP) techniques for biological sequence analysis continue to grow in popularity due to the inherent digital nature of these sequences. DSP methods have demonstrated early success for detection of coding regions in a gene. Recently, these methods are being used to establish DNA gene similarity. We present the inter-coefficient difference (ICD) transformation, a novel extension of the discrete Fourier transformation, which can be applied to any DNA sequence. The ICD method is a mathematical, alignment-free DNA comparison method that generates a genetic signature for any DNA sequence that is used to generate relative measures of similarity among DNA sequences. We demonstrate our method on a set of insulin genes obtained from an evolutionarily wide range of species, and on a set of avian influenza viral sequences, which represents a set of highly similar sequences. We compare phylogenetic trees generated using our technique against trees generated using traditional alignment techniques for similarity and demonstrate that the ICD method produces a highly accurate tree without requiring an alignment prior to establishing sequence similarity.

Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method

NASA Astrophysics Data System (ADS)

Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.

2017-09-01

Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

Fine-tuning structural RNA alignments in the twilight zone.

PubMed

Bremges, Andreas; Schirmer, Stefanie; Giegerich, Robert

2010-04-30

A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index.

Purification, developmental expression, and in silico characterization of α-amylase inhibitor from Echinochloa frumentacea.

PubMed

Panwar, Priyankar; Verma, A K; Dubey, Ashutosh

2018-05-01

Barnyard ( Echinochloa frumentacea ) and finger ( Eleusine coracana ) millet growing at northwestern Himalaya were explored for the α-amylase inhibitor (α-AI). The mature seeds of barnyard millet variety PRJ1 had maximum α-AI activity which increases in different developmental stage. α-AI was purified up to 22.25-fold from barnyard millet variety PRJ1. Semi-quantitative PCR of different developmental stages of barnyard millet seeds showed increased levels of the transcript from 7 to 28 days. Sequence analysis revealed that it contained 315 bp nucleotide which encodes 104 amino acid sequence with molecular weight 10.72 kDa. The predicted 3D structure of α-AI was 86.73% similar to a bifunctional inhibitor of ragi. In silico analysis of 71 α-AI protein sequences were carried out for biochemical features, homology search, multiple sequence alignment, phylogenetic tree construction, motif, and superfamily distribution of protein sequences. Analysis of multiple sequence alignment revealed the existence of conserved regions NPLP[S/G]CRWYVV[S/Q][Q/R]TCG[V/I] throughout sequences. Superfam analysis revealed that α-AI protein sequences were distributed among seven different superfamilies.

OPTIMA: sensitive and accurate whole-genome alignment of error-prone genomic maps by combinatorial indexing and technology-agnostic statistical analysis.

PubMed

Verzotto, Davide; M Teo, Audrey S; Hillmer, Axel M; Nagarajan, Niranjan

2016-01-01

Resolution of complex repeat structures and rearrangements in the assembly and analysis of large eukaryotic genomes is often aided by a combination of high-throughput sequencing and genome-mapping technologies (for example, optical restriction mapping). In particular, mapping technologies can generate sparse maps of large DNA fragments (150 kilo base pairs (kbp) to 2 Mbp) and thus provide a unique source of information for disambiguating complex rearrangements in cancer genomes. Despite their utility, combining high-throughput sequencing and mapping technologies has been challenging because of the lack of efficient and sensitive map-alignment algorithms for robustly aligning error-prone maps to sequences. We introduce a novel seed-and-extend glocal (short for global-local) alignment method, OPTIMA (and a sliding-window extension for overlap alignment, OPTIMA-Overlap), which is the first to create indexes for continuous-valued mapping data while accounting for mapping errors. We also present a novel statistical model, agnostic with respect to technology-dependent error rates, for conservatively evaluating the significance of alignments without relying on expensive permutation-based tests. We show that OPTIMA and OPTIMA-Overlap outperform other state-of-the-art approaches (1.6-2 times more sensitive) and are more efficient (170-200 %) and precise in their alignments (nearly 99 % precision). These advantages are independent of the quality of the data, suggesting that our indexing approach and statistical evaluation are robust, provide improved sensitivity and guarantee high precision.

Using ProMED-Mail and MedWorm blogs for cross-domain pattern analysis in epidemic intelligence.

PubMed

Stewart, Avaré; Denecke, Kerstin

2010-01-01

In this work we motivate the use of medical blog user generated content for gathering facts about disease reporting events to support biosurveillance investigation. Given the characteristics of blogs, the extraction of such events is made more difficult due to noise and data abundance. We address the problem of automatically inferring disease reporting event extraction patterns in this more noisy setting. The sublanguage used in outbreak reports is exploited to align with the sequences of disease reporting sentences in blogs. Based our Cross Domain Pattern Analysis Framework, experimental results show that Phase-Level sequences tend to produce more overlap across the domains than Word-Level sequences. The cross domain alignment process is effective at filtering noisy sequences from blogs and extracting good candidate sequence patterns from an abundance of text.

A generalized global alignment algorithm.

PubMed

Huang, Xiaoqiu; Chao, Kun-Mao

2003-01-22

Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions. We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity. The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.

COACH: profile-profile alignment of protein families using hidden Markov models.

PubMed

Edgar, Robert C; Sjölander, Kimmen

2004-05-22

Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile-profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence-sequence methods (such as BLAST) and profile-sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile-profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM. We compare the alignment accuracy of COACH with two recently published methods: Yona and Levitt's prof_sim and Sadreyev and Grishin's COMPASS. On two sets of reference alignments selected from the FSSP database, we find that COACH is able, on average, to produce alignments giving the best coverage or the fewest errors, depending on the chosen parameter settings. COACH is freely available from www.drive5.com/lobster

Community detection in sequence similarity networks based on attribute clustering

DOE PAGES

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

2017-07-24

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Community detection in sequence similarity networks based on attribute clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Evaluation of next generation mtGenome sequencing using the Ion Torrent Personal Genome Machine (PGM)☆

PubMed Central

Parson, Walther; Strobl, Christina; Huber, Gabriela; Zimmermann, Bettina; Gomes, Sibylle M.; Souto, Luis; Fendt, Liane; Delport, Rhena; Langit, Reina; Wootton, Sharon; Lagacé, Robert; Irwin, Jodi

2013-01-01

Insights into the human mitochondrial phylogeny have been primarily achieved by sequencing full mitochondrial genomes (mtGenomes). In forensic genetics (partial) mtGenome information can be used to assign haplotypes to their phylogenetic backgrounds, which may, in turn, have characteristic geographic distributions that would offer useful information in a forensic case. In addition and perhaps even more relevant in the forensic context, haplogroup-specific patterns of mutations form the basis for quality control of mtDNA sequences. The current method for establishing (partial) mtDNA haplotypes is Sanger-type sequencing (STS), which is laborious, time-consuming, and expensive. With the emergence of Next Generation Sequencing (NGS) technologies, the body of available mtDNA data can potentially be extended much more quickly and cost-efficiently. Customized chemistries, laboratory workflows and data analysis packages could support the community and increase the utility of mtDNA analysis in forensics. We have evaluated the performance of mtGenome sequencing using the Personal Genome Machine (PGM) and compared the resulting haplotypes directly with conventional Sanger-type sequencing. A total of 64 mtGenomes (>1 million bases) were established that yielded high concordance with the corresponding STS haplotypes (<0.02% differences). About two-thirds of the differences were observed in or around homopolymeric sequence stretches. In addition, the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of alignment software would be desirable to facilitate the application of NGS in mtDNA forensic genetics. PMID:23948325

MACSIMS : multiple alignment of complete sequences information management system

PubMed Central

Thompson, Julie D; Muller, Arnaud; Waterhouse, Andrew; Procter, Jim; Barton, Geoffrey J; Plewniak, Frédéric; Poch, Olivier

2006-01-01

Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at . PMID:16792820

DUK - A Fast and Efficient Kmer Based Sequence Matching Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Mingkun; Copeland, Alex; Han, James

2011-03-21

A new tool, DUK, is developed to perform matching task. Matching is to find whether a query sequence partially or totally matches given reference sequences or not. Matching is similar to alignment. Indeed many traditional analysis tasks like contaminant removal use alignment tools. But for matching, there is no need to know which bases of a query sequence matches which position of a reference sequence, it only need know whether there exists a match or not. This subtle difference can make matching task much faster than alignment. DUK is accurate, versatile, fast, and has efficient memory usage. It uses Kmermore » hashing method to index reference sequences and Poisson model to calculate p-value. DUK is carefully implemented in C++ in object oriented design. The resulted classes can also be used to develop other tools quickly. DUK have been widely used in JGI for a wide range of applications such as contaminant removal, organelle genome separation, and assembly refinement. Many real applications and simulated dataset demonstrate its power.« less

Reconstructing evolutionary trees in parallel for massive sequences.

PubMed

Zou, Quan; Wan, Shixiang; Zeng, Xiangxiang; Ma, Zhanshan Sam

2017-12-14

Building the evolutionary trees for massive unaligned DNA sequences is challenging and crucial. However, reconstructing evolutionary tree for ultra-large sequences is hard. Massive multiple sequence alignment is also challenging and time/space consuming. Hadoop and Spark are developed recently, which bring spring light for the classical computational biology problems. In this paper, we tried to solve the multiple sequence alignment and evolutionary reconstruction in parallel. HPTree, which is developed in this paper, can deal with big DNA sequence files quickly. It works well on the >1GB files, and gets better performance than other evolutionary reconstruction tools. Users could use HPTree for reonstructing evolutioanry trees on the computer clusters or cloud platform (eg. Amazon Cloud). HPTree could help on population evolution research and metagenomics analysis. In this paper, we employ the Hadoop and Spark platform and design an evolutionary tree reconstruction software tool for unaligned massive DNA sequences. Clustering and multiple sequence alignment are done in parallel. Neighbour-joining model was employed for the evolutionary tree building. We opened our software together with source codes via http://lab.malab.cn/soft/HPtree/ .

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

PubMed

Tso, Kai-Yuen; Lee, Sau Dan; Lo, Kwok-Wai; Yip, Kevin Y

2014-12-23

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data. We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing. Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

Fine-tuning structural RNA alignments in the twilight zone

PubMed Central

2010-01-01

Background A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably. Results Based on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices. Conclusions Employing the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index. PMID:20433706

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Local alignment of two-base encoded DNA sequence

PubMed Central

Homer, Nils; Merriman, Barry; Nelson, Stanley F

2009-01-01

Background DNA sequence comparison is based on optimal local alignment of two sequences using a similarity score. However, some new DNA sequencing technologies do not directly measure the base sequence, but rather an encoded form, such as the two-base encoding considered here. In order to compare such data to a reference sequence, the data must be decoded into sequence. The decoding is deterministic, but the possibility of measurement errors requires searching among all possible error modes and resulting alignments to achieve an optimal balance of fewer errors versus greater sequence similarity. Results We present an extension of the standard dynamic programming method for local alignment, which simultaneously decodes the data and performs the alignment, maximizing a similarity score based on a weighted combination of errors and edits, and allowing an affine gap penalty. We also present simulations that demonstrate the performance characteristics of our two base encoded alignment method and contrast those with standard DNA sequence alignment under the same conditions. Conclusion The new local alignment algorithm for two-base encoded data has substantial power to properly detect and correct measurement errors while identifying underlying sequence variants, and facilitating genome re-sequencing efforts based on this form of sequence data. PMID:19508732

Simultaneous phylogeny reconstruction and multiple sequence alignment

PubMed Central

Yue, Feng; Shi, Jian; Tang, Jijun

2009-01-01

Background A phylogeny is the evolutionary history of a group of organisms. To date, sequence data is still the most used data type for phylogenetic reconstruction. Before any sequences can be used for phylogeny reconstruction, they must be aligned, and the quality of the multiple sequence alignment has been shown to affect the quality of the inferred phylogeny. At the same time, all the current multiple sequence alignment programs use a guide tree to produce the alignment and experiments showed that good guide trees can significantly improve the multiple alignment quality. Results We devise a new algorithm to simultaneously align multiple sequences and search for the phylogenetic tree that leads to the best alignment. We also implemented the algorithm as a C program package, which can handle both DNA and protein data and can take simple cost model as well as complex substitution matrices, such as PAM250 or BLOSUM62. The performance of the new method are compared with those from other popular multiple sequence alignment tools, including the widely used programs such as ClustalW and T-Coffee. Experimental results suggest that this method has good performance in terms of both phylogeny accuracy and alignment quality. Conclusion We present an algorithm to align multiple sequences and reconstruct the phylogenies that minimize the alignment score, which is based on an efficient algorithm to solve the median problems for three sequences. Our extensive experiments suggest that this method is very promising and can produce high quality phylogenies and alignments. PMID:19208110

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Quantiprot - a Python package for quantitative analysis of protein sequences.

PubMed

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

PubMed

Neuwald, Andrew F

2009-08-01

The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.

Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

PubMed

Oliveira, Francisco P M; Tavares, João Manuel R S

2013-03-01

This article presents an enhanced methodology to align plantar pressure image sequences simultaneously in time and space. The temporal alignment of the sequences is accomplished using B-splines in the time modeling, and the spatial alignment can be attained using several geometric transformation models. The methodology was tested on a dataset of 156 real plantar pressure image sequences (3 sequences for each foot of the 26 subjects) that was acquired using a common commercial plate during barefoot walking. In the alignment of image sequences that were synthetically deformed both in time and space, an outstanding accuracy was achieved with the cubic B-splines. This accuracy was significantly better (p < 0.001) than the one obtained using the best solution proposed in our previous work. When applied to align real image sequences with unknown transformation involved, the alignment based on cubic B-splines also achieved superior results than our previous methodology (p < 0.001). The consequences of the temporal alignment on the dynamic center of pressure (COP) displacement was also assessed by computing the intraclass correlation coefficients (ICC) before and after the temporal alignment of the three image sequence trials of each foot of the associated subject at six time instants. The results showed that, generally, the ICCs related to the medio-lateral COP displacement were greater when the sequences were temporally aligned than the ICCs of the original sequences. Based on the experimental findings, one can conclude that the cubic B-splines are a remarkable solution for the temporal alignment of plantar pressure image sequences. These findings also show that the temporal alignment can increase the consistency of the COP displacement on related acquired plantar pressure image sequences.

aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity.

PubMed

Kuraku, Shigehiro; Zmasek, Christian M; Nishimura, Osamu; Katoh, Kazutaka

2013-07-01

We report a new web server, aLeaves (http://aleaves.cdb.riken.jp/), for homologue collection from diverse animal genomes. In molecular comparative studies involving multiple species, orthology identification is the basis on which most subsequent biological analyses rely. It can be achieved most accurately by explicit phylogenetic inference. More and more species are subjected to large-scale sequencing, but the resultant resources are scattered in independent project-based, and multi-species, but separate, web sites. This complicates data access and is becoming a serious barrier to the comprehensiveness of molecular phylogenetic analysis. aLeaves, launched to overcome this difficulty, collects sequences similar to an input query sequence from various data sources. The collected sequences can be passed on to the MAFFT sequence alignment server (http://mafft.cbrc.jp/alignment/server/), which has been significantly improved in interactivity. This update enables to switch between (i) sequence selection using the Archaeopteryx tree viewer, (ii) multiple sequence alignment and (iii) tree inference. This can be performed as a loop until one reaches a sensible data set, which minimizes redundancy for better visibility and handling in phylogenetic inference while covering relevant taxa. The work flow achieved by the seamless link between aLeaves and MAFFT provides a convenient online platform to address various questions in zoology and evolutionary biology.

aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity

PubMed Central

Kuraku, Shigehiro; Zmasek, Christian M.; Nishimura, Osamu; Katoh, Kazutaka

2013-01-01

We report a new web server, aLeaves (http://aleaves.cdb.riken.jp/), for homologue collection from diverse animal genomes. In molecular comparative studies involving multiple species, orthology identification is the basis on which most subsequent biological analyses rely. It can be achieved most accurately by explicit phylogenetic inference. More and more species are subjected to large-scale sequencing, but the resultant resources are scattered in independent project-based, and multi-species, but separate, web sites. This complicates data access and is becoming a serious barrier to the comprehensiveness of molecular phylogenetic analysis. aLeaves, launched to overcome this difficulty, collects sequences similar to an input query sequence from various data sources. The collected sequences can be passed on to the MAFFT sequence alignment server (http://mafft.cbrc.jp/alignment/server/), which has been significantly improved in interactivity. This update enables to switch between (i) sequence selection using the Archaeopteryx tree viewer, (ii) multiple sequence alignment and (iii) tree inference. This can be performed as a loop until one reaches a sensible data set, which minimizes redundancy for better visibility and handling in phylogenetic inference while covering relevant taxa. The work flow achieved by the seamless link between aLeaves and MAFFT provides a convenient online platform to address various questions in zoology and evolutionary biology. PMID:23677614

FASMA: a service to format and analyze sequences in multiple alignments.

PubMed

Costantini, Susan; Colonna, Giovanni; Facchiano, Angelo M

2007-12-01

Multiple sequence alignments are successfully applied in many studies for under- standing the structural and functional relations among single nucleic acids and protein sequences as well as whole families. Because of the rapid growth of sequence databases, multiple sequence alignments can often be very large and difficult to visualize and analyze. We offer a new service aimed to visualize and analyze the multiple alignments obtained with different external algorithms, with new features useful for the comparison of the aligned sequences as well as for the creation of a final image of the alignment. The service is named FASMA and is available at http://bioinformatica.isa.cnr.it/FASMA/.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

PubMed Central

Leonard, Guy; Stevens, Jamie R.; Richards, Thomas A.

2009-01-01

The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends. PMID:19812722

CMSA: a heterogeneous CPU/GPU computing system for multiple similar RNA/DNA sequence alignment.

PubMed

Chen, Xi; Wang, Chen; Tang, Shanjiang; Yu, Ce; Zou, Quan

2017-06-24

The multiple sequence alignment (MSA) is a classic and powerful technique for sequence analysis in bioinformatics. With the rapid growth of biological datasets, MSA parallelization becomes necessary to keep its running time in an acceptable level. Although there are a lot of work on MSA problems, their approaches are either insufficient or contain some implicit assumptions that limit the generality of usage. First, the information of users' sequences, including the sizes of datasets and the lengths of sequences, can be of arbitrary values and are generally unknown before submitted, which are unfortunately ignored by previous work. Second, the center star strategy is suited for aligning similar sequences. But its first stage, center sequence selection, is highly time-consuming and requires further optimization. Moreover, given the heterogeneous CPU/GPU platform, prior studies consider the MSA parallelization on GPU devices only, making the CPUs idle during the computation. Co-run computation, however, can maximize the utilization of the computing resources by enabling the workload computation on both CPU and GPU simultaneously. This paper presents CMSA, a robust and efficient MSA system for large-scale datasets on the heterogeneous CPU/GPU platform. It performs and optimizes multiple sequence alignment automatically for users' submitted sequences without any assumptions. CMSA adopts the co-run computation model so that both CPU and GPU devices are fully utilized. Moreover, CMSA proposes an improved center star strategy that reduces the time complexity of its center sequence selection process from O(mn 2 ) to O(mn). The experimental results show that CMSA achieves an up to 11× speedup and outperforms the state-of-the-art software. CMSA focuses on the multiple similar RNA/DNA sequence alignment and proposes a novel bitmap based algorithm to improve the center star strategy. We can conclude that harvesting the high performance of modern GPU is a promising approach to accelerate multiple sequence alignment. Besides, adopting the co-run computation model can maximize the entire system utilization significantly. The source code is available at https://github.com/wangvsa/CMSA .

Markov model plus k-word distributions: a synergy that produces novel statistical measures for sequence comparison.

PubMed

Dai, Qi; Yang, Yanchun; Wang, Tianming

2008-10-15

Many proposed statistical measures can efficiently compare biological sequences to further infer their structures, functions and evolutionary information. They are related in spirit because all the ideas for sequence comparison try to use the information on the k-word distributions, Markov model or both. Motivated by adding k-word distributions to Markov model directly, we investigated two novel statistical measures for sequence comparison, called wre.k.r and S2.k.r. The proposed measures were tested by similarity search, evaluation on functionally related regulatory sequences and phylogenetic analysis. This offers the systematic and quantitative experimental assessment of our measures. Moreover, we compared our achievements with these based on alignment or alignment-free. We grouped our experiments into two sets. The first one, performed via ROC (receiver operating curve) analysis, aims at assessing the intrinsic ability of our statistical measures to search for similar sequences from a database and discriminate functionally related regulatory sequences from unrelated sequences. The second one aims at assessing how well our statistical measure is used for phylogenetic analysis. The experimental assessment demonstrates that our similarity measures intending to incorporate k-word distributions into Markov model are more efficient.

rVISTA 2.0: Evolutionary Analysis of Transcription Factor Binding Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loots, G G; Ovcharenko, I

2004-01-28

Identifying and characterizing the patterns of DNA cis-regulatory modules represents a challenge that has the potential to reveal the regulatory language the genome uses to dictate transcriptional dynamics. Several studies have demonstrated that regulatory modules are under positive selection and therefore are often conserved between related species. Using this evolutionary principle we have created a comparative tool, rVISTA, for analyzing the regulatory potential of noncoding sequences. The rVISTA tool combines transcription factor binding site (TFBS) predictions, sequence comparisons and cluster analysis to identify noncoding DNA regions that are highly conserved and present in a specific configuration within an alignment. Heremore » we present the newly developed version 2.0 of the rVISTA tool that can process alignments generated by both zPicture and PipMaker alignment programs or use pre-computed pairwise alignments of seven vertebrate genomes available from the ECR Browser. The rVISTA web server is closely interconnected with the TRANSFAC database, allowing users to either search for matrices present in the TRANSFAC library collection or search for user-defined consensus sequences. rVISTA tool is publicly available at http://rvista.dcode.org/.« less

Applications and Extensions of pClust to Big Microbial Proteomic Data

ERIC Educational Resources Information Center

Lockwood, Svetlana

2016-01-01

The goal of biological sciences is to understand the biomolecular mechanics of living organisms. Proteins serve as the foundation for organisms functional analysis and sequence analysis has shown to be invaluable in answering questions about individual organisms. The first step in any sequence analysis is alignment and it is common that even…

The number of reduced alignments between two DNA sequences

PubMed Central

2014-01-01

Background In this study we consider DNA sequences as mathematical strings. Total and reduced alignments between two DNA sequences have been considered in the literature to measure their similarity. Results for explicit representations of some alignments have been already obtained. Results We present exact, explicit and computable formulas for the number of different possible alignments between two DNA sequences and a new formula for a class of reduced alignments. Conclusions A unified approach for a wide class of alignments between two DNA sequences has been provided. The formula is computable and, if complemented by software development, will provide a deeper insight into the theory of sequence alignment and give rise to new comparison methods. AMS Subject Classification Primary 92B05, 33C20, secondary 39A14, 65Q30 PMID:24684679

Probabilistic topic modeling for the analysis and classification of genomic sequences

PubMed Central

2015-01-01

Background Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques. Methods The presented method is based on Probabilistic Topic Modeling, a statistical technique originally proposed for text documents. Probabilistic topic models are able to find in a document corpus the topics (recurrent themes) characterizing classes of documents. This technique, applied on DNA sequences representing the documents, exploits the frequency of fixed-length k-mers and builds a generative model for a training group of sequences. This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. Results and conclusions We performed classification of over 7000 16S DNA barcode sequences taken from Ribosomal Database Project (RDP) repository, training probabilistic topic models. The proposed method is compared to the RDP tool and Support Vector Machine (SVM) classification algorithm in a extensive set of trials using both complete sequences and short sequence snippets (from 400 bp to 25 bp). Our method reaches very similar results to RDP classifier and SVM for complete sequences. The most interesting results are obtained when short sequence snippets are considered. In these conditions the proposed method outperforms RDP and SVM with ultra short sequences and it exhibits a smooth decrease of performance, at every taxonomic level, when the sequence length is decreased. PMID:25916734

QUASAR--scoring and ranking of sequence-structure alignments.

PubMed

Birzele, Fabian; Gewehr, Jan E; Zimmer, Ralf

2005-12-15

Sequence-structure alignments are a common means for protein structure prediction in the fields of fold recognition and homology modeling, and there is a broad variety of programs that provide such alignments based on sequence similarity, secondary structure or contact potentials. Nevertheless, finding the best sequence-structure alignment in a pool of alignments remains a difficult problem. QUASAR (quality of sequence-structure alignments ranking) provides a unifying framework for scoring sequence-structure alignments that aids finding well-performing combinations of well-known and custom-made scoring schemes. Those scoring functions can be benchmarked against widely accepted quality scores like MaxSub, TMScore, Touch and APDB, thus enabling users to test their own alignment scores against 'standard-of-truth' structure-based scores. Furthermore, individual score combinations can be optimized with respect to benchmark sets based on known structural relationships using QUASAR's in-built optimization routines.

The twilight zone of cis element alignments.

PubMed

Sebastian, Alvaro; Contreras-Moreira, Bruno

2013-02-01

Sequence alignment of proteins and nucleic acids is a routine task in bioinformatics. Although the comparison of complete peptides, genes or genomes can be undertaken with a great variety of tools, the alignment of short DNA sequences and motifs entails pitfalls that have not been fully addressed yet. Here we confront the structural superposition of transcription factors with the sequence alignment of their recognized cis elements. Our goals are (i) to test TFcompare (http://floresta.eead.csic.es/tfcompare), a structural alignment method for protein-DNA complexes; (ii) to benchmark the pairwise alignment of regulatory elements; (iii) to define the confidence limits and the twilight zone of such alignments and (iv) to evaluate the relevance of these thresholds with elements obtained experimentally. We find that the structure of cis elements and protein-DNA interfaces is significantly more conserved than their sequence and measures how this correlates with alignment errors when only sequence information is considered. Our results confirm that DNA motifs in the form of matrices produce better alignments than individual sequences. Finally, we report that empirical and theoretically derived twilight thresholds are useful for estimating the natural plasticity of regulatory sequences, and hence for filtering out unreliable alignments.

The twilight zone of cis element alignments

PubMed Central

Sebastian, Alvaro; Contreras-Moreira, Bruno

2013-01-01

Sequence alignment of proteins and nucleic acids is a routine task in bioinformatics. Although the comparison of complete peptides, genes or genomes can be undertaken with a great variety of tools, the alignment of short DNA sequences and motifs entails pitfalls that have not been fully addressed yet. Here we confront the structural superposition of transcription factors with the sequence alignment of their recognized cis elements. Our goals are (i) to test TFcompare (http://floresta.eead.csic.es/tfcompare), a structural alignment method for protein–DNA complexes; (ii) to benchmark the pairwise alignment of regulatory elements; (iii) to define the confidence limits and the twilight zone of such alignments and (iv) to evaluate the relevance of these thresholds with elements obtained experimentally. We find that the structure of cis elements and protein–DNA interfaces is significantly more conserved than their sequence and measures how this correlates with alignment errors when only sequence information is considered. Our results confirm that DNA motifs in the form of matrices produce better alignments than individual sequences. Finally, we report that empirical and theoretically derived twilight thresholds are useful for estimating the natural plasticity of regulatory sequences, and hence for filtering out unreliable alignments. PMID:23268451

DNAAlignEditor: DNA alignment editor tool

PubMed Central

Sanchez-Villeda, Hector; Schroeder, Steven; Flint-Garcia, Sherry; Guill, Katherine E; Yamasaki, Masanori; McMullen, Michael D

2008-01-01

Background With advances in DNA re-sequencing methods and Next-Generation parallel sequencing approaches, there has been a large increase in genomic efforts to define and analyze the sequence variability present among individuals within a species. For very polymorphic species such as maize, this has lead to a need for intuitive, user-friendly software that aids the biologist, often with naïve programming capability, in tracking, editing, displaying, and exporting multiple individual sequence alignments. To fill this need we have developed a novel DNA alignment editor. Results We have generated a nucleotide sequence alignment editor (DNAAlignEditor) that provides an intuitive, user-friendly interface for manual editing of multiple sequence alignments with functions for input, editing, and output of sequence alignments. The color-coding of nucleotide identity and the display of associated quality score aids in the manual alignment editing process. DNAAlignEditor works as a client/server tool having two main components: a relational database that collects the processed alignments and a user interface connected to database through universal data access connectivity drivers. DNAAlignEditor can be used either as a stand-alone application or as a network application with multiple users concurrently connected. Conclusion We anticipate that this software will be of general interest to biologists and population genetics in editing DNA sequence alignments and analyzing natural sequence variation regardless of species, and will be particularly useful for manual alignment editing of sequences in species with high levels of polymorphism. PMID:18366684

CRITICA: coding region identification tool invoking comparative analysis

NASA Technical Reports Server (NTRS)

Badger, J. H.; Olsen, G. J.; Woese, C. R. (Principal Investigator)

1999-01-01

Gene recognition is essential to understanding existing and future DNA sequence data. CRITICA (Coding Region Identification Tool Invoking Comparative Analysis) is a suite of programs for identifying likely protein-coding sequences in DNA by combining comparative analysis of DNA sequences with more common noncomparative methods. In the comparative component of the analysis, regions of DNA are aligned with related sequences from the DNA databases; if the translation of the aligned sequences has greater amino acid identity than expected for the observed percentage nucleotide identity, this is interpreted as evidence for coding. CRITICA also incorporates noncomparative information derived from the relative frequencies of hexanucleotides in coding frames versus other contexts (i.e., dicodon bias). The dicodon usage information is derived by iterative analysis of the data, such that CRITICA is not dependent on the existence or accuracy of coding sequence annotations in the databases. This independence makes the method particularly well suited for the analysis of novel genomes. CRITICA was tested by analyzing the available Salmonella typhimurium DNA sequences. Its predictions were compared with the DNA sequence annotations and with the predictions of GenMark. CRITICA proved to be more accurate than GenMark, and moreover, many of its predictions that would seem to be errors instead reflect problems in the sequence databases. The source code of CRITICA is freely available by anonymous FTP (rdp.life.uiuc.edu in/pub/critica) and on the World Wide Web (http:/(/)rdpwww.life.uiuc.edu).

KinView: A visual comparative sequence analysis tool for integrated kinome research

PubMed Central

McSkimming, Daniel Ian; Dastgheib, Shima; Baffi, Timothy R.; Byrne, Dominic P.; Ferries, Samantha; Scott, Steven Thomas; Newton, Alexandra C.; Eyers, Claire E.; Kochut, Krzysztof J.; Eyers, Patrick A.

2017-01-01

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats. PMID:27731453

Score distributions of gapped multiple sequence alignments down to the low-probability tail

NASA Astrophysics Data System (ADS)

Fieth, Pascal; Hartmann, Alexander K.

2016-08-01

Assessing the significance of alignment scores of optimally aligned DNA or amino acid sequences can be achieved via the knowledge of the score distribution of random sequences. But this requires obtaining the distribution in the biologically relevant high-scoring region, where the probabilities are exponentially small. For gapless local alignments of infinitely long sequences this distribution is known analytically to follow a Gumbel distribution. Distributions for gapped local alignments and global alignments of finite lengths can only be obtained numerically. To obtain result for the small-probability region, specific statistical mechanics-based rare-event algorithms can be applied. In previous studies, this was achieved for pairwise alignments. They showed that, contrary to results from previous simple sampling studies, strong deviations from the Gumbel distribution occur in case of finite sequence lengths. Here we extend the studies to multiple sequence alignments with gaps, which are much more relevant for practical applications in molecular biology. We study the distributions of scores over a large range of the support, reaching probabilities as small as 10-160, for global and local (sum-of-pair scores) multiple alignments. We find that even after suitable rescaling, eliminating the sequence-length dependence, the distributions for multiple alignment differ from the pairwise alignment case. Furthermore, we also show that the previously discussed Gaussian correction to the Gumbel distribution needs to be refined, also for the case of pairwise alignments.

SWPhylo - A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees.

PubMed

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA.

SWPhylo – A Novel Tool for Phylogenomic Inferences by Comparison of Oligonucleotide Patterns and Integration of Genome-Based and Gene-Based Phylogenetic Trees

PubMed Central

Yu, Xiaoyu; Reva, Oleg N

2018-01-01

Modern phylogenetic studies may benefit from the analysis of complete genome sequences of various microorganisms. Evolutionary inferences based on genome-scale analysis are believed to be more accurate than the gene-based alternative. However, the computational complexity of current phylogenomic procedures, inappropriateness of standard phylogenetic tools to process genome-wide data, and lack of reliable substitution models which correlates with alignment-free phylogenomic approaches deter microbiologists from using these opportunities. For example, the super-matrix and super-tree approaches of phylogenomics use multiple integrated genomic loci or individual gene-based trees to infer an overall consensus tree. However, these approaches potentially multiply errors of gene annotation and sequence alignment not mentioning the computational complexity and laboriousness of the methods. In this article, we demonstrate that the annotation- and alignment-free comparison of genome-wide tetranucleotide frequencies, termed oligonucleotide usage patterns (OUPs), allowed a fast and reliable inference of phylogenetic trees. These were congruent to the corresponding whole genome super-matrix trees in terms of tree topology when compared with other known approaches including 16S ribosomal RNA and GyrA protein sequence comparison, complete genome-based MAUVE, and CVTree methods. A Web-based program to perform the alignment-free OUP-based phylogenomic inferences was implemented at http://swphylo.bi.up.ac.za/. Applicability of the tool was tested on different taxa from subspecies to intergeneric levels. Distinguishing between closely related taxonomic units may be enforced by providing the program with alignments of marker protein sequences, eg, GyrA. PMID:29511354

Multiple DNA and protein sequence alignment on a workstation and a supercomputer.

PubMed

Tajima, K

1988-11-01

This paper describes a multiple alignment method using a workstation and supercomputer. The method is based on the alignment of a set of aligned sequences with the new sequence, and uses a recursive procedure of such alignment. The alignment is executed in a reasonable computation time on diverse levels from a workstation to a supercomputer, from the viewpoint of alignment results and computational speed by parallel processing. The application of the algorithm is illustrated by several examples of multiple alignment of 12 amino acid and DNA sequences of HIV (human immunodeficiency virus) env genes. Colour graphic programs on a workstation and parallel processing on a supercomputer are discussed.

Solving the problem of Trans-Genomic Query with alignment tables.

PubMed

Parker, Douglass Stott; Hsiao, Ruey-Lung; Xing, Yi; Resch, Alissa M; Lee, Christopher J

2008-01-01

The trans-genomic query (TGQ) problem--enabling the free query of biological information, even across genomes--is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

Sequence Alignment to Predict Across Species Susceptibility ...

EPA Pesticide Factsheets

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target, so it is amenable to variable degrees of protein characterization, depending on available information about the chemical/protein interaction and the molecular target itself. To allow for flexibility in the analysis, a layered strategy was adopted for the tool. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of candidate orthologs), the second level evaluates sequence similarity within selected domains (e.g., ligand-binding domain, DNA binding domain), and the third level of analysis compares individual amino acid residue positions identified as being of importance for protein conformation and/or ligand binding upon chemical perturbation. Each level of the SeqAPASS analysis provides increasing evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further ev

Hal: an automated pipeline for phylogenetic analyses of genomic data.

PubMed

Robbertse, Barbara; Yoder, Ryan J; Boyd, Alex; Reeves, John; Spatafora, Joseph W

2011-02-07

The rapid increase in genomic and genome-scale data is resulting in unprecedented levels of discrete sequence data available for phylogenetic analyses. Major analytical impasses exist, however, prior to analyzing these data with existing phylogenetic software. Obstacles include the management of large data sets without standardized naming conventions, identification and filtering of orthologous clusters of proteins or genes, and the assembly of alignments of orthologous sequence data into individual and concatenated super alignments. Here we report the production of an automated pipeline, Hal that produces multiple alignments and trees from genomic data. These alignments can be produced by a choice of four alignment programs and analyzed by a variety of phylogenetic programs. In short, the Hal pipeline connects the programs BLASTP, MCL, user specified alignment programs, GBlocks, ProtTest and user specified phylogenetic programs to produce species trees. The script is available at sourceforge (http://sourceforge.net/projects/bio-hal/). The results from an example analysis of Kingdom Fungi are briefly discussed.

Analysing the performance of personal computers based on Intel microprocessors for sequence aligning bioinformatics applications.

PubMed

Nair, Pradeep S; John, Eugene B

2007-01-01

Aligning specific sequences against a very large number of other sequences is a central aspect of bioinformatics. With the widespread availability of personal computers in biology laboratories, sequence alignment is now often performed locally. This makes it necessary to analyse the performance of personal computers for sequence aligning bioinformatics benchmarks. In this paper, we analyse the performance of a personal computer for the popular BLAST and FASTA sequence alignment suites. Results indicate that these benchmarks have a large number of recurring operations and use memory operations extensively. It seems that the performance can be improved with a bigger L1-cache.

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

PubMed

Schmollinger, Martin; Nieselt, Kay; Kaufmann, Michael; Morgenstern, Burkhard

2004-09-09

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

An Accurate Scalable Template-based Alignment Algorithm

PubMed Central

Gardner, David P.; Xu, Weijia; Miranker, Daniel P.; Ozer, Stuart; Cannone, Jamie J.; Gutell, Robin R.

2013-01-01

The rapid determination of nucleic acid sequences is increasing the number of sequences that are available. Inherent in a template or seed alignment is the culmination of structural and functional constraints that are selecting those mutations that are viable during the evolution of the RNA. While we might not understand these structural and functional, template-based alignment programs utilize the patterns of sequence conservation to encapsulate the characteristics of viable RNA sequences that are aligned properly. We have developed a program that utilizes the different dimensions of information in rCAD, a large RNA informatics resource, to establish a profile for each position in an alignment. The most significant include sequence identity and column composition in different phylogenetic taxa. We have compared our methods with a maximum of eight alternative alignment methods on different sets of 16S and 23S rRNA sequences with sequence percent identities ranging from 50% to 100%. The results showed that CRWAlign outperformed the other alignment methods in both speed and accuracy. A web-based alignment server is available at http://www.rna.ccbb.utexas.edu/SAE/2F/CRWAlign. PMID:24772376

Simple chained guide trees give high-quality protein multiple sequence alignments

PubMed Central

Boyce, Kieran; Sievers, Fabian; Higgins, Desmond G.

2014-01-01

Guide trees are used to decide the order of sequence alignment in the progressive multiple sequence alignment heuristic. These guide trees are often the limiting factor in making large alignments, and considerable effort has been expended over the years in making these quickly or accurately. In this article we show that, at least for protein families with large numbers of sequences that can be benchmarked with known structures, simple chained guide trees give the most accurate alignments. These also happen to be the fastest and simplest guide trees to construct, computationally. Such guide trees have a striking effect on the accuracy of alignments produced by some of the most widely used alignment packages. There is a marked increase in accuracy and a marked decrease in computational time, once the number of sequences goes much above a few hundred. This is true, even if the order of sequences in the guide tree is random. PMID:25002495

Influenza Virus Database (IVDB): an integrated information resource and analysis platform for influenza virus research.

PubMed

Chang, Suhua; Zhang, Jiajie; Liao, Xiaoyun; Zhu, Xinxing; Wang, Dahai; Zhu, Jiang; Feng, Tao; Zhu, Baoli; Gao, George F; Wang, Jian; Yang, Huanming; Yu, Jun; Wang, Jing

2007-01-01

Frequent outbreaks of highly pathogenic avian influenza and the increasing data available for comparative analysis require a central database specialized in influenza viruses (IVs). We have established the Influenza Virus Database (IVDB) to integrate information and create an analysis platform for genetic, genomic, and phylogenetic studies of the virus. IVDB hosts complete genome sequences of influenza A virus generated by Beijing Institute of Genomics (BIG) and curates all other published IV sequences after expert annotation. Our Q-Filter system classifies and ranks all nucleotide sequences into seven categories according to sequence content and integrity. IVDB provides a series of tools and viewers for comparative analysis of the viral genomes, genes, genetic polymorphisms and phylogenetic relationships. A search system has been developed for users to retrieve a combination of different data types by setting search options. To facilitate analysis of global viral transmission and evolution, the IV Sequence Distribution Tool (IVDT) has been developed to display the worldwide geographic distribution of chosen viral genotypes and to couple genomic data with epidemiological data. The BLAST, multiple sequence alignment and phylogenetic analysis tools were integrated for online data analysis. Furthermore, IVDB offers instant access to pre-computed alignments and polymorphisms of IV genes and proteins, and presents the results as SNP distribution plots and minor allele distributions. IVDB is publicly available at http://influenza.genomics.org.cn.

High-speed multiple sequence alignment on a reconfigurable platform.

PubMed

Oliver, Tim; Schmidt, Bertil; Maskell, Douglas; Nathan, Darran; Clemens, Ralf

2006-01-01

Progressive alignment is a widely used approach to compute multiple sequence alignments (MSAs). However, aligning several hundred sequences by popular progressive alignment tools requires hours on sequential computers. Due to the rapid growth of sequence databases biologists have to compute MSAs in a far shorter time. In this paper we present a new approach to MSA on reconfigurable hardware platforms to gain high performance at low cost. We have constructed a linear systolic array to perform pairwise sequence distance computations using dynamic programming. This results in an implementation with significant runtime savings on a standard FPGA.

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A

PubMed Central

Ndhlovu, Andrew; Durand, Pierre M.; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. Database URL: http://www.bioinf.wits.ac.za/software/fire/evodb PMID:26140928

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A.

PubMed

Ndhlovu, Andrew; Durand, Pierre M; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. © The Author(s) 2015. Published by Oxford University Press.

Parametric and non-parametric masking of randomness in sequence alignments can be improved and leads to better resolved trees.

PubMed

Kück, Patrick; Meusemann, Karen; Dambach, Johannes; Thormann, Birthe; von Reumont, Björn M; Wägele, Johann W; Misof, Bernhard

2010-03-31

Methods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective. ALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict. Alignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

PubMed

Delong, Allison K; Wu, Mingham; Bennett, Diane; Parkin, Neil; Wu, Zhijin; Hogan, Joseph W; Kantor, Rami

2012-08-01

Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802 PR and 44,432 RT sequences) from the published literature ( http://hivdb.Stanford.edu ). Nucleic acid sequences are read into SQUAT, identified, aligned, and translated. Nucleic acid sequences are flagged if with >five 1-2-base insertions; >one 3-base insertion; >one deletion; >six PR or >18 RT ambiguous bases; >three consecutive PR or >four RT nucleic acid mutations; >zero stop codons; >three PR or >six RT ambiguous amino acids; >three consecutive PR or >four RT amino acid mutations; >zero unique amino acids; or <0.5% or >15% genetic distance from another submitted sequence. Thresholds are user modifiable. SQUAT output includes a summary report with detailed comments for troubleshooting of flagged sequences, histograms of pairwise genetic distances, neighbor joining phylogenetic trees, and aligned nucleic and amino acid sequences. SQUAT is a stand-alone, free, web-independent tool to ensure use of high-quality HIV PR/RT sequences in interpretation and reporting of drug resistance, while increasing awareness and expertise and facilitating troubleshooting of potentially problematic sequences.

Linking GPS and travel diary data using sequence alignment in a study of children's independent mobility

PubMed Central

2011-01-01

Background Global positioning systems (GPS) are increasingly being used in health research to determine the location of study participants. Combining GPS data with data collected via travel/activity diaries allows researchers to assess where people travel in conjunction with data about trip purpose and accompaniment. However, linking GPS and diary data is problematic and to date the only method has been to match the two datasets manually, which is time consuming and unlikely to be practical for larger data sets. This paper assesses the feasibility of a new sequence alignment method of linking GPS and travel diary data in comparison with the manual matching method. Methods GPS and travel diary data obtained from a study of children's independent mobility were linked using sequence alignment algorithms to test the proof of concept. Travel diaries were assessed for quality by counting the number of errors and inconsistencies in each participant's set of diaries. The success of the sequence alignment method was compared for higher versus lower quality travel diaries, and for accompanied versus unaccompanied trips. Time taken and percentage of trips matched were compared for the sequence alignment method and the manual method. Results The sequence alignment method matched 61.9% of all trips. Higher quality travel diaries were associated with higher match rates in both the sequence alignment and manual matching methods. The sequence alignment method performed almost as well as the manual method and was an order of magnitude faster. However, the sequence alignment method was less successful at fully matching trips and at matching unaccompanied trips. Conclusions Sequence alignment is a promising method of linking GPS and travel diary data in large population datasets, especially if limitations in the trip detection algorithm are addressed. PMID:22142322

A Novel Partial Sequence Alignment Tool for Finding Large Deletions

PubMed Central

Aruk, Taner; Ustek, Duran; Kursun, Olcay

2012-01-01

Finding large deletions in genome sequences has become increasingly more useful in bioinformatics, such as in clinical research and diagnosis. Although there are a number of publically available next generation sequencing mapping and sequence alignment programs, these software packages do not correctly align fragments containing deletions larger than one kb. We present a fast alignment software package, BinaryPartialAlign, that can be used by wet lab scientists to find long structural variations in their experiments. For BinaryPartialAlign, we make use of the Smith-Waterman (SW) algorithm with a binary-search-based approach for alignment with large gaps that we called partial alignment. BinaryPartialAlign implementation is compared with other straight-forward applications of SW. Simulation results on mtDNA fragments demonstrate the effectiveness (runtime and accuracy) of the proposed method. PMID:22566777

Fast single-pass alignment and variant calling using sequencing data

USDA-ARS?s Scientific Manuscript database

Sequencing research requires efficient computation. Few programs use already known information about DNA variants when aligning sequence data to the reference map. New program findmap.f90 reads the previous variant list before aligning sequence, calling variant alleles, and summing the allele counts...

SeqAPASS (Sequence Alignment to Predict Across Species Susceptibility) software and documentation

EPA Science Inventory

SeqAPASS is a software application facilitates rapid and streamlined, yet transparent, comparisons of the similarity of toxicologically-significant molecular targets across species. The present application facilitates analysis of primary amino acid sequence similarity (including ...

Query-seeded iterative sequence similarity searching improves selectivity 5–20-fold

PubMed Central

Li, Weizhong; Lopez, Rodrigo

2017-01-01

Abstract Iterative similarity search programs, like psiblast, jackhmmer, and psisearch, are much more sensitive than pairwise similarity search methods like blast and ssearch because they build a position specific scoring model (a PSSM or HMM) that captures the pattern of sequence conservation characteristic to a protein family. But models are subject to contamination; once an unrelated sequence has been added to the model, homologs of the unrelated sequence will also produce high scores, and the model can diverge from the original protein family. Examination of alignment errors during psiblast PSSM contamination suggested a simple strategy for dramatically reducing PSSM contamination. psiblast PSSMs are built from the query-based multiple sequence alignment (MSA) implied by the pairwise alignments between the query model (PSSM, HMM) and the subject sequences in the library. When the original query sequence residues are inserted into gapped positions in the aligned subject sequence, the resulting PSSM rarely produces alignment over-extensions or alignments to unrelated sequences. This simple step, which tends to anchor the PSSM to the original query sequence and slightly increase target percent identity, can reduce the frequency of false-positive alignments more than 20-fold compared with psiblast and jackhmmer, with little loss in search sensitivity. PMID:27923999

Biclustering as a method for RNA local multiple sequence alignment.

PubMed

Wang, Shu; Gutell, Robin R; Miranker, Daniel P

2007-12-15

Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment; precisely the kind of dual situation biclustering is intended to address. We define a representation of the MSA problem enabling the application of biclustering algorithms. We develop a computer program for local MSA, BlockMSA, that combines biclustering with divide-and-conquer. BlockMSA simultaneously finds groups of similar sequences and locally aligns subsequences within them. Further alignment is accomplished by dividing both the set of sequences and their contents. The net result is both a multiple sequence alignment and a hierarchical clustering of the sequences. BlockMSA was tested on the subsets of the BRAliBase 2.1 benchmark suite that display high variability and on an extension to that suite to larger problem sizes. Also, alignments were evaluated of two large datasets of current biological interest, T box sequences and Group IC1 Introns. The results were compared with alignments computed by ClustalW, MAFFT, MUCLE and PROBCONS alignment programs using Sum of Pairs (SPS) and Consensus Count. Results for the benchmark suite are sensitive to problem size. On problems of 15 or greater sequences, BlockMSA is consistently the best. On none of the problems in the test suite are there appreciable differences in scores among BlockMSA, MAFFT and PROBCONS. On the T box sequences, BlockMSA does the most faithful job of reproducing known annotations. MAFFT and PROBCONS do not. On the Intron sequences, BlockMSA, MAFFT and MUSCLE are comparable at identifying conserved regions. BlockMSA is implemented in Java. Source code and supplementary datasets are available at http://aug.csres.utexas.edu/msa/

SFESA: a web server for pairwise alignment refinement by secondary structure shifts.

PubMed

Tong, Jing; Pei, Jimin; Grishin, Nick V

2015-09-03

Protein sequence alignment is essential for a variety of tasks such as homology modeling and active site prediction. Alignment errors remain the main cause of low-quality structure models. A bioinformatics tool to refine alignments is needed to make protein alignments more accurate. We developed the SFESA web server to refine pairwise protein sequence alignments. Compared to the previous version of SFESA, which required a set of 3D coordinates for a protein, the new server will search a sequence database for the closest homolog with an available 3D structure to be used as a template. For each alignment block defined by secondary structure elements in the template, SFESA evaluates alignment variants generated by local shifts and selects the best-scoring alignment variant. A scoring function that combines the sequence score of profile-profile comparison and the structure score of template-derived contact energy is used for evaluation of alignments. PROMALS pairwise alignments refined by SFESA are more accurate than those produced by current advanced alignment methods such as HHpred and CNFpred. In addition, SFESA also improves alignments generated by other software. SFESA is a web-based tool for alignment refinement, designed for researchers to compute, refine, and evaluate pairwise alignments with a combined sequence and structure scoring of alignment blocks. To our knowledge, the SFESA web server is the only tool that refines alignments by evaluating local shifts of secondary structure elements. The SFESA web server is available at http://prodata.swmed.edu/sfesa.

Embedding strategies for effective use of information from multiple sequence alignments.

PubMed Central

Henikoff, S.; Henikoff, J. G.

1997-01-01

We describe a new strategy for utilizing multiple sequence alignment information to detect distant relationships in searches of sequence databases. A single sequence representing a protein family is enriched by replacing conserved regions with position-specific scoring matrices (PSSMs) or consensus residues derived from multiple alignments of family members. In comprehensive tests of these and other family representations, PSSM-embedded queries produced the best results overall when used with a special version of the Smith-Waterman searching algorithm. Moreover, embedding consensus residues instead of PSSMs improved performance with readily available single sequence query searching programs, such as BLAST and FASTA. Embedding PSSMs or consensus residues into a representative sequence improves searching performance by extracting multiple alignment information from motif regions while retaining single sequence information where alignment is uncertain. PMID:9070452

TCW: Transcriptome Computational Workbench

PubMed Central

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R.

2013-01-01

Background The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. Methodology The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. Conclusion It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw. PMID:23874959

TCW: transcriptome computational workbench.

PubMed

Soderlund, Carol; Nelson, William; Willer, Mark; Gang, David R

2013-01-01

The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw.

PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences.

PubMed

Mirarab, Siavash; Nguyen, Nam; Guo, Sheng; Wang, Li-San; Kim, Junhyong; Warnow, Tandy

2015-05-01

We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate--slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory.

Pairwise Sequence Alignment Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeff Daily, PNNL

2015-05-20

Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, amore » novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.« less

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies.

PubMed

Zeng, Lu; Kortschak, R Daniel; Raison, Joy M; Bertozzi, Terry; Adelson, David L

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package.

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies

PubMed Central

Zeng, Lu; Kortschak, R. Daniel; Raison, Joy M.

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package. PMID:29538441

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments.

PubMed

Daily, Jeff

2016-02-10

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. A faster intra-sequence local pairwise alignment implementation is described and benchmarked, including new global and semi-global variants. Using a 375 residue query sequence a speed of 136 billion cell updates per second (GCUPS) was achieved on a dual Intel Xeon E5-2670 24-core processor system, the highest reported for an implementation based on Farrar's 'striped' approach. Rognes's SWIPE optimal database search application is still generally the fastest available at 1.2 to at best 2.4 times faster than Parasail for sequences shorter than 500 amino acids. However, Parasail was faster for longer sequences. For global alignments, Parasail's prefix scan implementation is generally the fastest, faster even than Farrar's 'striped' approach, however the opal library is faster for single-threaded applications. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. Applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.

The LANL hemorrhagic fever virus database, a new platform for analyzing biothreat viruses.

PubMed

Kuiken, Carla; Thurmond, Jim; Dimitrijevic, Mira; Yoon, Hyejin

2012-01-01

Hemorrhagic fever viruses (HFVs) are a diverse set of over 80 viral species, found in 10 different genera comprising five different families: arena-, bunya-, flavi-, filo- and togaviridae. All these viruses are highly variable and evolve rapidly, making them elusive targets for the immune system and for vaccine and drug design. About 55,000 HFV sequences exist in the public domain today. A central website that provides annotated sequences and analysis tools will be helpful to HFV researchers worldwide. The HFV sequence database collects and stores sequence data and provides a user-friendly search interface and a large number of sequence analysis tools, following the model of the highly regarded and widely used Los Alamos HIV database [Kuiken, C., B. Korber, and R.W. Shafer, HIV sequence databases. AIDS Rev, 2003. 5: p. 52-61]. The database uses an algorithm that aligns each sequence to a species-wide reference sequence. The NCBI RefSeq database [Sayers et al. (2011) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 39, D38-D51.] is used for this; if a reference sequence is not available, a Blast search finds the best candidate. Using this method, sequences in each genus can be retrieved pre-aligned. The HFV website can be accessed via http://hfv.lanl.gov.

PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences

PubMed Central

Mirarab, Siavash; Nguyen, Nam; Guo, Sheng; Wang, Li-San; Kim, Junhyong

2015-01-01

Abstract We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATé). We also show that trees estimated on PASTA alignments are highly accurate—slightly better than SATé trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATé, highly parallelizable, and requires relatively little memory. PMID:25549288

A Novel Center Star Multiple Sequence Alignment Algorithm Based on Affine Gap Penalty and K-Band

NASA Astrophysics Data System (ADS)

Zou, Quan; Shan, Xiao; Jiang, Yi

Multiple sequence alignment is one of the most important topics in computational biology, but it cannot deal with the large data so far. As the development of copy-number variant(CNV) and Single Nucleotide Polymorphisms(SNP) research, many researchers want to align numbers of similar sequences for detecting CNV and SNP. In this paper, we propose a novel multiple sequence alignment algorithm based on affine gap penalty and k-band. It can align more quickly and accurately, that will be helpful for mining CNV and SNP. Experiments prove the performance of our algorithm.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase.

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Evaluating the efficacy of a structure-derived amino acid substitution matrix in detecting protein homologs by BLAST and PSI-BLAST.

PubMed

Goonesekere, Nalin Cw

2009-01-01

The large numbers of protein sequences generated by whole genome sequencing projects require rapid and accurate methods of annotation. The detection of homology through computational sequence analysis is a powerful tool in determining the complex evolutionary and functional relationships that exist between proteins. Homology search algorithms employ amino acid substitution matrices to detect similarity between proteins sequences. The substitution matrices in common use today are constructed using sequences aligned without reference to protein structure. Here we present amino acid substitution matrices constructed from the alignment of a large number of protein domain structures from the structural classification of proteins (SCOP) database. We show that when incorporated into the homology search algorithms BLAST and PSI-blast, the structure-based substitution matrices enhance the efficacy of detecting remote homologs.

Evidence for Widespread Reticulate Evolution within Human Duplicons

PubMed Central

Jackson, Michael S. ; Oliver, Karen ; Loveland, Jane ; Humphray, Sean ; Dunham, Ian ; Rocchi, Mariano ; Viggiano, Luigi ; Park, Jonathan P. ; Hurles, Matthew E. ; Santibanez-Koref, Mauro 

2005-01-01

Approximately 5% of the human genome consists of segmental duplications that can cause genomic mutations and may play a role in gene innovation. Reticulate evolutionary processes, such as unequal crossing-over and gene conversion, are known to occur within specific duplicon families, but the broader contribution of these processes to the evolution of human duplications remains poorly characterized. Here, we use phylogenetic profiling to analyze multiple alignments of 24 human duplicon families that span >8 Mb of DNA. Our results indicate that none of them are evolving independently, with all alignments showing sharp discontinuities in phylogenetic signal consistent with reticulation. To analyze these results in more detail, we have developed a quartet method that estimates the relative contribution of nucleotide substitution and reticulate processes to sequence evolution. Our data indicate that most of the duplications show a highly significant excess of sites consistent with reticulate evolution, compared with the number expected by nucleotide substitution alone, with 15 of 30 alignments showing a >20-fold excess over that expected. Using permutation tests, we also show that at least 5% of the total sequence shares 100% sequence identity because of reticulation, a figure that includes 74 independent tracts of perfect identity >2 kb in length. Furthermore, analysis of a subset of alignments indicates that the density of reticulation events is as high as 1 every 4 kb. These results indicate that phylogenetic relationships within recently duplicated human DNA can be rapidly disrupted by reticulate evolution. This finding has important implications for efforts to finish the human genome sequence, complicates comparative sequence analysis of duplicon families, and could profoundly influence the tempo of gene-family evolution. PMID:16252241

REPPER—repeats and their periodicities in fibrous proteins

PubMed Central

Gruber, Markus; Söding, Johannes; Lupas, Andrei N.

2005-01-01

REPPER (REPeats and their PERiodicities) is an integrated server that detects and analyzes regions with short gapless repeats in protein sequences or alignments. It finds periodicities by Fourier Transform (FTwin) and internal similarity analysis (REPwin). FTwin assigns numerical values to amino acids that reflect certain properties, for instance hydrophobicity, and gives information on corresponding periodicities. REPwin uses self-alignments and displays repeats that reveal significant internal similarities. Both programs use a sliding window to ensure that different periodic regions within the same protein are detected independently. FTwin and REPwin are complemented by secondary structure prediction (PSIPRED) and coiled coil prediction (COILS), making the server a versatile analysis tool for sequences of fibrous proteins. REPPER is available at . PMID:15980460

Introducing difference recurrence relations for faster semi-global alignment of long sequences.

PubMed

Suzuki, Hajime; Kasahara, Masahiro

2018-02-19

The read length of single-molecule DNA sequencers is reaching 1 Mb. Popular alignment software tools widely used for analyzing such long reads often take advantage of single-instruction multiple-data (SIMD) operations to accelerate calculation of dynamic programming (DP) matrices in the Smith-Waterman-Gotoh (SWG) algorithm with a fixed alignment start position at the origin. Nonetheless, 16-bit or 32-bit integers are necessary for storing the values in a DP matrix when sequences to be aligned are long; this situation hampers the use of the full SIMD width of modern processors. We proposed a faster semi-global alignment algorithm, "difference recurrence relations," that runs more rapidly than the state-of-the-art algorithm by a factor of 2.1. Instead of calculating and storing all the values in a DP matrix directly, our algorithm computes and stores mainly the differences between the values of adjacent cells in the matrix. Although the SWG algorithm and our algorithm can output exactly the same result, our algorithm mainly involves 8-bit integer operations, enabling us to exploit the full width of SIMD operations (e.g., 32) on modern processors. We also developed a library, libgaba, so that developers can easily integrate our algorithm into alignment programs. Our novel algorithm and optimized library implementation will facilitate accelerating nucleotide long-read analysis algorithms that use pairwise alignment stages. The library is implemented in the C programming language and available at https://github.com/ocxtal/libgaba .

MSAViewer: interactive JavaScript visualization of multiple sequence alignments.

PubMed

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E; Rost, Burkhard; Goldberg, Tatyana

2016-11-15

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is 'web ready': written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online. msa@bio.sh. © The Author 2016. Published by Oxford University Press.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments

PubMed Central

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E.; Rost, Burkhard; Goldberg, Tatyana

2016-01-01

Summary: The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. Availability and Implementation: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: msa@bio.sh PMID:27412096

Using reconfigurable hardware to accelerate multiple sequence alignment with ClustalW.

PubMed

Oliver, Tim; Schmidt, Bertil; Nathan, Darran; Clemens, Ralf; Maskell, Douglas

2005-08-15

Aligning hundreds of sequences using progressive alignment tools such as ClustalW requires several hours on state-of-the-art workstations. We present a new approach to compute multiple sequence alignments in far shorter time using reconfigurable hardware. This results in an implementation of ClustalW with significant runtime savings on a standard off-the-shelf FPGA.

JCoDA: a tool for detecting evolutionary selection.

PubMed

Steinway, Steven N; Dannenfelser, Ruth; Laucius, Christopher D; Hayes, James E; Nayak, Sudhir

2010-05-27

The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences. JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway. JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda.

JCoDA: a tool for detecting evolutionary selection

PubMed Central

2010-01-01

Background The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences. Results JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway. Conclusions JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda. PMID:20507581

Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores.

PubMed

Bastien, Olivier; Maréchal, Eric

2008-08-07

Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2) following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory) is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure). Homologous sequences were considered as systems 1) having a high redundancy of information reflected by the magnitude of their alignment scores, 2) which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a constant rate, corresponding to the information hazard rate, and that pairwise sequence alignment scores should follow a Gumbel distribution, which parameters could find some theoretical rationale. In particular, one parameter corresponds to the information hazard rate. Extreme value distribution of alignment scores, assessed from high scoring segments pairs following the Karlin-Altschul model, can also be deduced from the Reliability Theory applied to molecular sequences. It reflects the redundancy of information between homologous sequences, under functional conservative pressure. This model also provides a link between concepts of biological sequence analysis and of systems biology.

Alignment methods: strategies, challenges, benchmarking, and comparative overview.

PubMed

Löytynoja, Ari

2012-01-01

Comparative evolutionary analyses of molecular sequences are solely based on the identities and differences detected between homologous characters. Errors in this homology statement, that is errors in the alignment of the sequences, are likely to lead to errors in the downstream analyses. Sequence alignment and phylogenetic inference are tightly connected and many popular alignment programs use the phylogeny to divide the alignment problem into smaller tasks. They then neglect the phylogenetic tree, however, and produce alignments that are not evolutionarily meaningful. The use of phylogeny-aware methods reduces the error but the resulting alignments, with evolutionarily correct representation of homology, can challenge the existing practices and methods for viewing and visualising the sequences. The inter-dependency of alignment and phylogeny can be resolved by joint estimation of the two; methods based on statistical models allow for inferring the alignment parameters from the data and correctly take into account the uncertainty of the solution but remain computationally challenging. Widely used alignment methods are based on heuristic algorithms and unlikely to find globally optimal solutions. The whole concept of one correct alignment for the sequences is questionable, however, as there typically exist vast numbers of alternative, roughly equally good alignments that should also be considered. This uncertainty is hidden by many popular alignment programs and is rarely correctly taken into account in the downstream analyses. The quest for finding and improving the alignment solution is complicated by the lack of suitable measures of alignment goodness. The difficulty of comparing alternative solutions also affects benchmarks of alignment methods and the results strongly depend on the measure used. As the effects of alignment error cannot be predicted, comparing the alignments' performance in downstream analyses is recommended.

Designing a Bioengine for Detection and Analysis of Base String on an Affected Sequence in High-Concentration Regions

PubMed Central

Mandal, Bijoy Kumar; Kim, Tai-hoon

2013-01-01

We design an Algorithm for bioengine. As a program are enable optimal alignments searching between two sequences, the host sequence (normal plant) as well as query sequence (virus). Searching for homologues has become a routine operation of biological sequences in 4 × 4 combination with different subsequence (word size). This program takes the advantage of the high degree of homology between such sequences to construct an alignment of the matching regions. There is a main aim which is to detect the overlapping reading frames. This program also enables to find out the highly infected colones selection highest matching region with minimum gap or mismatch zones and unique virus colones matches. This is a small, portable, interactive, front-end program intended to be used to find out the regions of matching between host sequence and query subsequences. All the operations are carried out in fraction of seconds, depending on the required task and on the sequence length. PMID:24000321

A survey and evaluations of histogram-based statistics in alignment-free sequence comparison.

PubMed

Luczak, Brian B; James, Benjamin T; Girgis, Hani Z

2017-12-06

Since the dawn of the bioinformatics field, sequence alignment scores have been the main method for comparing sequences. However, alignment algorithms are quadratic, requiring long execution time. As alternatives, scientists have developed tens of alignment-free statistics for measuring the similarity between two sequences. We surveyed tens of alignment-free k-mer statistics. Additionally, we evaluated 33 statistics and multiplicative combinations between the statistics and/or their squares. These statistics are calculated on two k-mer histograms representing two sequences. Our evaluations using global alignment scores revealed that the majority of the statistics are sensitive and capable of finding similar sequences to a query sequence. Therefore, any of these statistics can filter out dissimilar sequences quickly. Further, we observed that multiplicative combinations of the statistics are highly correlated with the identity score. Furthermore, combinations involving sequence length difference or Earth Mover's distance, which takes the length difference into account, are always among the highest correlated paired statistics with identity scores. Similarly, paired statistics including length difference or Earth Mover's distance are among the best performers in finding the K-closest sequences. Interestingly, similar performance can be obtained using histograms of shorter words, resulting in reducing the memory requirement and increasing the speed remarkably. Moreover, we found that simple single statistics are sufficient for processing next-generation sequencing reads and for applications relying on local alignment. Finally, we measured the time requirement of each statistic. The survey and the evaluations will help scientists with identifying efficient alternatives to the costly alignment algorithm, saving thousands of computational hours. The source code of the benchmarking tool is available as Supplementary Materials. © The Author 2017. Published by Oxford University Press.

Survey of local and global biological network alignment: the need to reconcile the two sides of the same coin.

PubMed

Guzzi, Pietro Hiram; Milenkovic, Tijana

2018-05-01

Analogous to genomic sequence alignment that allows for across-species transfer of biological knowledge between conserved sequence regions, biological network alignment can be used to guide the knowledge transfer between conserved regions of molecular networks of different species. Hence, biological network alignment can be used to redefine the traditional notion of a sequence-based homology to a new notion of network-based homology. Analogous to genomic sequence alignment, there exist local and global biological network alignments. Here, we survey prominent and recent computational approaches of each network alignment type and discuss their (dis)advantages. Then, as it was recently shown that the two approach types are complementary, in the sense that they capture different slices of cellular functioning, we discuss the need to reconcile the two network alignment types and present a recent first step in this direction. We conclude with some open research problems on this topic and comment on the usefulness of network alignment in other domains besides computational biology.

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

The Saccharomyces Genome Database Variant Viewer

PubMed Central

Sheppard, Travis K.; Hitz, Benjamin C.; Engel, Stacia R.; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C.; Dalusag, Kyla S.; Demeter, Janos; Hellerstedt, Sage T.; Karra, Kalpana; Nash, Robert S.; Paskov, Kelley M.; Skrzypek, Marek S.; Weng, Shuai; Wong, Edith D.; Cherry, J. Michael

2016-01-01

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. PMID:26578556

BuddySuite: Command-Line Toolkits for Manipulating Sequences, Alignments, and Phylogenetic Trees.

PubMed

Bond, Stephen R; Keat, Karl E; Barreira, Sofia N; Baxevanis, Andreas D

2017-06-01

The ability to manipulate sequence, alignment, and phylogenetic tree files has become an increasingly important skill in the life sciences, whether to generate summary information or to prepare data for further downstream analysis. The command line can be an extremely powerful environment for interacting with these resources, but only if the user has the appropriate general-purpose tools on hand. BuddySuite is a collection of four independent yet interrelated command-line toolkits that facilitate each step in the workflow of sequence discovery, curation, alignment, and phylogenetic reconstruction. Most common sequence, alignment, and tree file formats are automatically detected and parsed, and over 100 tools have been implemented for manipulating these data. The project has been engineered to easily accommodate the addition of new tools, is written in the popular programming language Python, and is hosted on the Python Package Index and GitHub to maximize accessibility. Documentation for each BuddySuite tool, including usage examples, is available at http://tiny.cc/buddysuite_wiki. All software is open source and freely available through http://research.nhgri.nih.gov/software/BuddySuite. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering

PubMed Central

Sul, Woo Jun; Cole, James R.; Jesus, Ederson da C.; Wang, Qiong; Farris, Ryan J.; Fish, Jordan A.; Tiedje, James M.

2011-01-01

High-throughput sequencing of 16S rRNA genes has increased our understanding of microbial community structure, but now even higher-throughput methods to the Illumina scale allow the creation of much larger datasets with more samples and orders-of-magnitude more sequences that swamp current analytic methods. We developed a method capable of handling these larger datasets on the basis of assignment of sequences into an existing taxonomy using a supervised learning approach (taxonomy-supervised analysis). We compared this method with a commonly used clustering approach based on sequence similarity (taxonomy-unsupervised analysis). We sampled 211 different bacterial communities from various habitats and obtained ∼1.3 million 16S rRNA sequences spanning the V4 hypervariable region by pyrosequencing. Both methodologies gave similar ecological conclusions in that β-diversity measures calculated by using these two types of matrices were significantly correlated to each other, as were the ordination configurations and hierarchical clustering dendrograms. In addition, our taxonomy-supervised analyses were also highly correlated with phylogenetic methods, such as UniFrac. The taxonomy-supervised analysis has the advantages that it is not limited by the exhaustive computation required for the alignment and clustering necessary for the taxonomy-unsupervised analysis, is more tolerant of sequencing errors, and allows comparisons when sequences are from different regions of the 16S rRNA gene. With the tremendous expansion in 16S rRNA data acquisition underway, the taxonomy-supervised approach offers the potential to provide more rapid and extensive community comparisons across habitats and samples. PMID:21873204

Node fingerprinting: an efficient heuristic for aligning biological networks.

PubMed

Radu, Alex; Charleston, Michael

2014-10-01

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

A Lossy Compression Technique Enabling Duplication-Aware Sequence Alignment

PubMed Central

Freschi, Valerio; Bogliolo, Alessandro

2012-01-01

In spite of the recognized importance of tandem duplications in genome evolution, commonly adopted sequence comparison algorithms do not take into account complex mutation events involving more than one residue at the time, since they are not compliant with the underlying assumption of statistical independence of adjacent residues. As a consequence, the presence of tandem repeats in sequences under comparison may impair the biological significance of the resulting alignment. Although solutions have been proposed, repeat-aware sequence alignment is still considered to be an open problem and new efficient and effective methods have been advocated. The present paper describes an alternative lossy compression scheme for genomic sequences which iteratively collapses repeats of increasing length. The resulting approximate representations do not contain tandem duplications, while retaining enough information for making their comparison even more significant than the edit distance between the original sequences. This allows us to exploit traditional alignment algorithms directly on the compressed sequences. Results confirm the validity of the proposed approach for the problem of duplication-aware sequence alignment. PMID:22518086

Viewing multiple sequence alignments with the JavaScript Sequence Alignment Viewer (JSAV)

PubMed Central

Martin, Andrew C. R.

2014-01-01

The JavaScript Sequence Alignment Viewer (JSAV) is designed as a simple-to-use JavaScript component for displaying sequence alignments on web pages. The display of sequences is highly configurable with options to allow alternative coloring schemes, sorting of sequences and ’dotifying’ repeated amino acids. An option is also available to submit selected sequences to another web site, or to other JavaScript code. JSAV is implemented purely in JavaScript making use of the JQuery and JQuery-UI libraries. It does not use any HTML5-specific options to help with browser compatibility. The code is documented using JSDOC and is available from http://www.bioinf.org.uk/software/jsav/. PMID:25653836

Viewing multiple sequence alignments with the JavaScript Sequence Alignment Viewer (JSAV).

PubMed

Martin, Andrew C R

2014-01-01

The JavaScript Sequence Alignment Viewer (JSAV) is designed as a simple-to-use JavaScript component for displaying sequence alignments on web pages. The display of sequences is highly configurable with options to allow alternative coloring schemes, sorting of sequences and 'dotifying' repeated amino acids. An option is also available to submit selected sequences to another web site, or to other JavaScript code. JSAV is implemented purely in JavaScript making use of the JQuery and JQuery-UI libraries. It does not use any HTML5-specific options to help with browser compatibility. The code is documented using JSDOC and is available from http://www.bioinf.org.uk/software/jsav/.

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. As a result, a faster intra-sequence pairwise alignment implementation is described and benchmarked. Using a 375 residue query sequence a speed of 136 billion cell updates permore » second (GCUPS) was achieved on a dual Intel Xeon E5-2670 12-core processor system, the highest reported for an implementation based on Farrar’s ’striped’ approach. When using only a single thread, parasail was 1.7 times faster than Rognes’s SWIPE. For many score matrices, parasail is faster than BLAST. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. In conclusion, applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.« less

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments

DOE PAGES

Daily, Jeffrey A.

2016-02-10

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. As a result, a faster intra-sequence pairwise alignment implementation is described and benchmarked. Using a 375 residue query sequence a speed of 136 billion cell updates permore » second (GCUPS) was achieved on a dual Intel Xeon E5-2670 12-core processor system, the highest reported for an implementation based on Farrar’s ’striped’ approach. When using only a single thread, parasail was 1.7 times faster than Rognes’s SWIPE. For many score matrices, parasail is faster than BLAST. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. In conclusion, applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.« less

BarraCUDA - a fast short read sequence aligner using graphics processing units

PubMed Central

2012-01-01

Background With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. Findings Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. Conclusions BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available from http://seqbarracuda.sf.net PMID:22244497

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification.

PubMed

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-05-01

Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. ivan.borozan@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification

PubMed Central

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-01-01

Motivation: Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Results: Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. Availability and implementation: All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. Contact: ivan.borozan@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573913

Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Version 3.0 User Guide

EPA Science Inventory

User Guide to describe the complete functionality of the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Version 3.0 online tool. The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility tool (SeqAPASS; https://seqa...

Dcode.org anthology of comparative genomic tools.

PubMed

Loots, Gabriela G; Ovcharenko, Ivan

2005-07-01

Comparative genomics provides the means to demarcate functional regions in anonymous DNA sequences. The successful application of this method to identifying novel genes is currently shifting to deciphering the non-coding encryption of gene regulation across genomes. To facilitate the practical application of comparative sequence analysis to genetics and genomics, we have developed several analytical and visualization tools for the analysis of arbitrary sequences and whole genomes. These tools include two alignment tools, zPicture and Mulan; a phylogenetic shadowing tool, eShadow for identifying lineage- and species-specific functional elements; two evolutionary conserved transcription factor analysis tools, rVista and multiTF; a tool for extracting cis-regulatory modules governing the expression of co-regulated genes, Creme 2.0; and a dynamic portal to multiple vertebrate and invertebrate genome alignments, the ECR Browser. Here, we briefly describe each one of these tools and provide specific examples on their practical applications. All the tools are publicly available at the http://www.dcode.org/ website.

The effects of different representations on static structure analysis of computer malware signatures.

PubMed

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka.

The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures

PubMed Central

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka. PMID:23983644

GibbsCluster: unsupervised clustering and alignment of peptide sequences.

PubMed

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-07-03

Receptor interactions with short linear peptide fragments (ligands) are at the base of many biological signaling processes. Conserved and information-rich amino acid patterns, commonly called sequence motifs, shape and regulate these interactions. Because of the properties of a receptor-ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Using a color-coded ambigraphic nucleic acid notation to visualize conserved palindromic motifs within and across genomes

PubMed Central

2014-01-01

Background Ambiscript is a graphically-designed nucleic acid notation that uses symbol symmetries to support sequence complementation, highlight biologically-relevant palindromes, and facilitate the analysis of consensus sequences. Although the original Ambiscript notation was designed to easily represent consensus sequences for multiple sequence alignments, the notation’s black-on-white ambiguity characters are unable to reflect the statistical distribution of nucleotides found at each position. We now propose a color-augmented ambigraphic notation to encode the frequency of positional polymorphisms in these consensus sequences. Results We have implemented this color-coding approach by creating an Adobe Flash® application ( http://www.ambiscript.org) that shades and colors modified Ambiscript characters according to the prevalence of the encoded nucleotide at each position in the alignment. The resulting graphic helps viewers perceive biologically-relevant patterns in multiple sequence alignments by uniquely combining color, shading, and character symmetries to highlight palindromes and inverted repeats in conserved DNA motifs. Conclusion Juxtaposing an intuitive color scheme over the deliberate character symmetries of an ambigraphic nucleic acid notation yields a highly-functional nucleic acid notation that maximizes information content and successfully embodies key principles of graphic excellence put forth by the statistician and graphic design theorist, Edward Tufte. PMID:24447494

Evolutionary distances in the twilight zone--a rational kernel approach.

PubMed

Schwarz, Roland F; Fletcher, William; Förster, Frank; Merget, Benjamin; Wolf, Matthias; Schultz, Jörg; Markowetz, Florian

2010-12-31

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.

Spatio-temporal alignment of pedobarographic image sequences.

PubMed

Oliveira, Francisco P M; Sousa, Andreia; Santos, Rubim; Tavares, João Manuel R S

2011-07-01

This article presents a methodology to align plantar pressure image sequences simultaneously in time and space. The spatial position and orientation of a foot in a sequence are changed to match the foot represented in a second sequence. Simultaneously with the spatial alignment, the temporal scale of the first sequence is transformed with the aim of synchronizing the two input footsteps. Consequently, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is automatically attained, making the study easier and more straightforward. In terms of spatial alignment, the methodology can use one of four possible geometric transformation models: rigid, similarity, affine, or projective. In the temporal alignment, a polynomial transformation up to the 4th degree can be adopted in order to model linear and curved time behaviors. Suitable geometric and temporal transformations are found by minimizing the mean squared error (MSE) between the input sequences. The methodology was tested on a set of real image sequences acquired from a common pedobarographic device. When used in experimental cases generated by applying geometric and temporal control transformations, the methodology revealed high accuracy. In addition, the intra-subject alignment tests from real plantar pressure image sequences showed that the curved temporal models produced better MSE results (P < 0.001) than the linear temporal model. This article represents an important step forward in the alignment of pedobarographic image data, since previous methods can only be applied on static images.

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs.

PubMed

Blazewicz, Jacek; Frohmberg, Wojciech; Kierzynka, Michal; Pesch, Erwin; Wojciechowski, Pawel

2011-05-20

Pairwise sequence alignment methods are widely used in biological research. The increasing number of sequences is perceived as one of the upcoming challenges for sequence alignment methods in the nearest future. To overcome this challenge several GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of a GPU platform but in most cases address the problem of sequence database scanning and computing only the alignment score whereas the alignment itself is omitted. Thus, the need arose to implement the global and semiglobal Needleman-Wunsch, and Smith-Waterman algorithms with a backtracking procedure which is needed to construct the alignment. In this paper we present the solution that performs the alignment of every given sequence pair, which is a required step for progressive multiple sequence alignment methods, as well as for DNA recognition at the DNA assembly stage. Performed tests show that the implementation, with performance up to 6.3 GCUPS on a single GPU for affine gap penalties, is very efficient in comparison to other CPU and GPU-based solutions. Moreover, multiple GPUs support with load balancing makes the application very scalable. The article shows that the backtracking procedure of the sequence alignment algorithms may be designed to fit in with the GPU architecture. Therefore, our algorithm, apart from scores, is able to compute pairwise alignments. This opens a wide range of new possibilities, allowing other methods from the area of molecular biology to take advantage of the new computational architecture. Performed tests show that the efficiency of the implementation is excellent. Moreover, the speed of our GPU-based algorithms can be almost linearly increased when using more than one graphics card.

ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences.

PubMed

Bonizzoni, Paola; Rizzi, Raffaella; Pesole, Graziano

2005-10-05

Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems--hence the need to develop novel strategies. We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at http://aspic.algo.disco.unimib.it/aspic-devel/.

The LANL hemorrhagic fever virus database, a new platform for analyzing biothreat viruses

PubMed Central

Kuiken, Carla; Thurmond, Jim; Dimitrijevic, Mira; Yoon, Hyejin

2012-01-01

Hemorrhagic fever viruses (HFVs) are a diverse set of over 80 viral species, found in 10 different genera comprising five different families: arena-, bunya-, flavi-, filo- and togaviridae. All these viruses are highly variable and evolve rapidly, making them elusive targets for the immune system and for vaccine and drug design. About 55 000 HFV sequences exist in the public domain today. A central website that provides annotated sequences and analysis tools will be helpful to HFV researchers worldwide. The HFV sequence database collects and stores sequence data and provides a user-friendly search interface and a large number of sequence analysis tools, following the model of the highly regarded and widely used Los Alamos HIV database [Kuiken, C., B. Korber, and R.W. Shafer, HIV sequence databases. AIDS Rev, 2003. 5: p. 52–61]. The database uses an algorithm that aligns each sequence to a species-wide reference sequence. The NCBI RefSeq database [Sayers et al. (2011) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 39, D38–D51.] is used for this; if a reference sequence is not available, a Blast search finds the best candidate. Using this method, sequences in each genus can be retrieved pre-aligned. The HFV website can be accessed via http://hfv.lanl.gov. PMID:22064861

Interactional convergence in conversational storytelling: when reported speech is a cue of alignment and/or affiliation.

PubMed

Guardiola, Mathilde; Bertrand, Roxane

2013-01-01

This paper investigates how and when interactional convergence is established by participants in conversation. We analyze sequences of storytelling using an original method that combines Conversation Analysis and a corpus-based approach. In storytelling, the participant in the position of "listener" is expected to produce either generic or specific responses adapted to the storyteller's narrative. The listener's behavior produced within the current activity is a cue of his/her interactional alignment. We show here that the listener can produce a specific type of (aligned) response, which we term a reported speech utterance in echo. The participant who is not telling the story is nonetheless able to animate the characters, while reversing the usual asymmetric roles of storyteller and listener. The use of this device is a way for the listener to display his/her stance toward the events told by the storyteller. If the listener's stance is congruent with that of the storyteller, this reveals a high degree of affiliation between the participants. We present seventeen excerpts from a collection of 94 instances of Echo Reported Speech (ERS) which we examined using the concepts of alignment and affiliation in order to show how different kinds of convergent sequences are constructed. We demonstrate that this phenomenon is mainly used by the listener to align and affiliate with the storyteller by means of reformulative, enumerative, or overbidding ERS. We also show that in affiliative sequences, reported speech can be used by the listener in a humorous way in order to temporarily disalign. This disalignment constitutes a potential starting point for an oblique sequence, which, if accepted and continued by the storyteller, gives rise to a highly convergent sequence.

Interactional convergence in conversational storytelling: when reported speech is a cue of alignment and/or affiliation

PubMed Central

Guardiola, Mathilde; Bertrand, Roxane

2013-01-01

This paper investigates how and when interactional convergence is established by participants in conversation. We analyze sequences of storytelling using an original method that combines Conversation Analysis and a corpus-based approach. In storytelling, the participant in the position of “listener” is expected to produce either generic or specific responses adapted to the storyteller's narrative. The listener's behavior produced within the current activity is a cue of his/her interactional alignment. We show here that the listener can produce a specific type of (aligned) response, which we term a reported speech utterance in echo. The participant who is not telling the story is nonetheless able to animate the characters, while reversing the usual asymmetric roles of storyteller and listener. The use of this device is a way for the listener to display his/her stance toward the events told by the storyteller. If the listener's stance is congruent with that of the storyteller, this reveals a high degree of affiliation between the participants. We present seventeen excerpts from a collection of 94 instances of Echo Reported Speech (ERS) which we examined using the concepts of alignment and affiliation in order to show how different kinds of convergent sequences are constructed. We demonstrate that this phenomenon is mainly used by the listener to align and affiliate with the storyteller by means of reformulative, enumerative, or overbidding ERS. We also show that in affiliative sequences, reported speech can be used by the listener in a humorous way in order to temporarily disalign. This disalignment constitutes a potential starting point for an oblique sequence, which, if accepted and continued by the storyteller, gives rise to a highly convergent sequence. PMID:24115939

Molecular systematics of terraranas (Anura: Brachycephaloidea) with an assessment of the effects of alignment and optimality criteria.

PubMed

Padial, José M; Grant, Taran; Frost, Darrel R

2014-06-26

Brachycephaloidea is a monophyletic group of frogs with more than 1000 species distributed throughout the New World tropics, subtropics, and Andean regions. Recently, the group has been the target of multiple molecular phylogenetic analyses, resulting in extensive changes in its taxonomy. Here, we test previous hypotheses of phylogenetic relationships for the group by combining available molecular evidence (sequences of 22 genes representing 431 ingroup and 25 outgroup terminals) and performing a tree-alignment analysis under the parsimony optimality criterion using the program POY. To elucidate the effects of alignment and optimality criterion on phylogenetic inferences, we also used the program MAFFT to obtain a similarity-alignment for analysis under both parsimony and maximum likelihood using the programs TNT and GARLI, respectively. Although all three analytical approaches agreed on numerous points, there was also extensive disagreement. Tree-alignment under parsimony supported the monophyly of the ingroup and the sister group relationship of the monophyletic marsupial frogs (Hemiphractidae), while maximum likelihood and parsimony analyses of the MAFFT similarity-alignment did not. All three methods differed with respect to the position of Ceuthomantis smaragdinus (Ceuthomantidae), with tree-alignment using parsimony recovering this species as the sister of Pristimantis + Yunganastes. All analyses rejected the monophyly of Strabomantidae and Strabomantinae as originally defined, and the tree-alignment analysis under parsimony further rejected the recently redefined Craugastoridae and Pristimantinae. Despite the greater emphasis in the systematics literature placed on the choice of optimality criterion for evaluating trees than on the choice of method for aligning DNA sequences, we found that the topological differences attributable to the alignment method were as great as those caused by the optimality criterion. Further, the optimal tree-alignment indicates that insertions and deletions occurred in twice as many aligned positions as implied by the optimal similarity-alignment, confirming previous findings that sequence turnover through insertion and deletion events plays a greater role in molecular evolution than indicated by similarity-alignments. Our results also provide a clear empirical demonstration of the different effects of wildcard taxa produced by missing data in parsimony and maximum likelihood analyses. Specifically, maximum likelihood analyses consistently (81% bootstrap frequency) provided spurious resolution despite a lack of evidence, whereas parsimony correctly depicted the ambiguity due to missing data by collapsing unsupported nodes. We provide a new taxonomy for the group that retains previously recognized Linnaean taxa except for Ceuthomantidae, Strabomantidae, and Strabomantinae. A phenotypically diagnosable superfamily is recognized formally as Brachycephaloidea, with the informal, unranked name terrarana retained as the standard common name for these frogs. We recognize three families within Brachycephaloidea that are currently diagnosable solely on molecular grounds (Brachycephalidae, Craugastoridae, and Eleutherodactylidae), as well as five subfamilies (Craugastorinae, Eleutherodactylinae, Holoadeninae, Phyzelaphryninae, and Pristimantinae) corresponding in large part to previous families and subfamilies. Our analyses upheld the monophyly of all tested genera, but we found numerous subgeneric taxa to be non-monophyletic and modified the taxonomy accordingly.

Coval: Improving Alignment Quality and Variant Calling Accuracy for Next-Generation Sequencing Data

PubMed Central

Kosugi, Shunichi; Natsume, Satoshi; Yoshida, Kentaro; MacLean, Daniel; Cano, Liliana; Kamoun, Sophien; Terauchi, Ryohei

2013-01-01

Accurate identification of DNA polymorphisms using next-generation sequencing technology is challenging because of a high rate of sequencing error and incorrect mapping of reads to reference genomes. Currently available short read aligners and DNA variant callers suffer from these problems. We developed the Coval software to improve the quality of short read alignments. Coval is designed to minimize the incidence of spurious alignment of short reads, by filtering mismatched reads that remained in alignments after local realignment and error correction of mismatched reads. The error correction is executed based on the base quality and allele frequency at the non-reference positions for an individual or pooled sample. We demonstrated the utility of Coval by applying it to simulated genomes and experimentally obtained short-read data of rice, nematode, and mouse. Moreover, we found an unexpectedly large number of incorrectly mapped reads in ‘targeted’ alignments, where the whole genome sequencing reads had been aligned to a local genomic segment, and showed that Coval effectively eliminated such spurious alignments. We conclude that Coval significantly improves the quality of short-read sequence alignments, thereby increasing the calling accuracy of currently available tools for SNP and indel identification. Coval is available at http://sourceforge.net/projects/coval105/. PMID:24116042

Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos

PubMed Central

Freyhult, Eva; Moulton, Vincent; Ardell, David H.

2006-01-01

Sequence logos are stacked bar graphs that generalize the notion of consensus sequence. They employ entropy statistics very effectively to display variation in a structural alignment of sequences of a common function, while emphasizing its over-represented features. Yet sequence logos cannot display features that distinguish functional subclasses within a structurally related superfamily nor do they display under-represented features. We introduce two extensions to address these needs: function logos and inverse logos. Function logos display subfunctions that are over-represented among sequences carrying a specific feature. Inverse logos generalize both sequence logos and function logos by displaying under-represented, rather than over-represented, features or functions in structural alignments. To make inverse logos, a compositional inverse is applied to the feature or function frequency distributions before logo construction, where a compositional inverse is a mathematical transform that makes common features or functions rare and vice versa. We applied these methods to a database of structurally aligned bacterial tDNAs to create highly condensed, birds-eye views of potentially all so-called identity determinants and antideterminants that confer specific amino acid charging or initiator function on tRNAs in bacteria. We recovered both known and a few potentially novel identity elements. Function logos and inverse logos are useful tools for exploratory bioinformatic analysis of structure–function relationships in sequence families and superfamilies. PMID:16473848

rasbhari: Optimizing Spaced Seeds for Database Searching, Read Mapping and Alignment-Free Sequence Comparison.

PubMed

Hahn, Lars; Leimeister, Chris-André; Ounit, Rachid; Lonardi, Stefano; Morgenstern, Burkhard

2016-10-01

Many algorithms for sequence analysis rely on word matching or word statistics. Often, these approaches can be improved if binary patterns representing match and don't-care positions are used as a filter, such that only those positions of words are considered that correspond to the match positions of the patterns. The performance of these approaches, however, depends on the underlying patterns. Herein, we show that the overlap complexity of a pattern set that was introduced by Ilie and Ilie is closely related to the variance of the number of matches between two evolutionarily related sequences with respect to this pattern set. We propose a modified hill-climbing algorithm to optimize pattern sets for database searching, read mapping and alignment-free sequence comparison of nucleic-acid sequences; our implementation of this algorithm is called rasbhari. Depending on the application at hand, rasbhari can either minimize the overlap complexity of pattern sets, maximize their sensitivity in database searching or minimize the variance of the number of pattern-based matches in alignment-free sequence comparison. We show that, for database searching, rasbhari generates pattern sets with slightly higher sensitivity than existing approaches. In our Spaced Words approach to alignment-free sequence comparison, pattern sets calculated with rasbhari led to more accurate estimates of phylogenetic distances than the randomly generated pattern sets that we previously used. Finally, we used rasbhari to generate patterns for short read classification with CLARK-S. Here too, the sensitivity of the results could be improved, compared to the default patterns of the program. We integrated rasbhari into Spaced Words; the source code of rasbhari is freely available at http://rasbhari.gobics.de/.

What's in your next-generation sequence data? An exploration of unmapped DNA and RNA sequence reads from the bovine reference individual

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Next-generation sequencing projects commonly commence by aligning reads to a reference genome assembly. While improvements in alignment algorithms and computational hardware have greatly enhanced the efficiency and accuracy of alignments, a significant percentage of reads often remain u...

W-curve alignments for HIV-1 genomic comparisons.

PubMed

Cork, Douglas J; Lembark, Steven; Tovanabutra, Sodsai; Robb, Merlin L; Kim, Jerome H

2010-06-01

The W-curve was originally developed as a graphical visualization technique for viewing DNA and RNA sequences. Its ability to render features of DNA also makes it suitable for computational studies. Its main advantage in this area is utilizing a single-pass algorithm for comparing the sequences. Avoiding recursion during sequence alignments offers advantages for speed and in-process resources. The graphical technique also allows for multiple models of comparison to be used depending on the nucleotide patterns embedded in similar whole genomic sequences. The W-curve approach allows us to compare large numbers of samples quickly. We are currently tuning the algorithm to accommodate quirks specific to HIV-1 genomic sequences so that it can be used to aid in diagnostic and vaccine efforts. Tracking the molecular evolution of the virus has been greatly hampered by gap associated problems predominantly embedded within the envelope gene of the virus. Gaps and hypermutation of the virus slow conventional string based alignments of the whole genome. This paper describes the W-curve algorithm itself, and how we have adapted it for comparison of similar HIV-1 genomes. A treebuilding method is developed with the W-curve that utilizes a novel Cylindrical Coordinate distance method and gap analysis method. HIV-1 C2-V5 env sequence regions from a Mother/Infant cohort study are used in the comparison. The output distance matrix and neighbor results produced by the W-curve are functionally equivalent to those from Clustal for C2-V5 sequences in the mother/infant pairs infected with CRF01_AE. Significant potential exists for utilizing this method in place of conventional string based alignment of HIV-1 genomes, such as Clustal X. With W-curve heuristic alignment, it may be possible to obtain clinically useful results in a short time-short enough to affect clinical choices for acute treatment. A description of the W-curve generation process, including a comparison technique of aligning extremes of the curves to effectively phase-shift them past the HIV-1 gap problem, is presented. Besides yielding similar neighbor-joining phenogram topologies, most Mother and Infant C2-V5 sequences in the cohort pairs geometrically map closest to each other, indicating that W-curve heuristics overcame any gap problem.

DNA Multiple Sequence Alignment Guided by Protein Domains: The MSA-PAD 2.0 Method.

PubMed

Balech, Bachir; Monaco, Alfonso; Perniola, Michele; Santamaria, Monica; Donvito, Giacinto; Vicario, Saverio; Maggi, Giorgio; Pesole, Graziano

2018-01-01

Multiple sequence alignment (MSA) is a fundamental component in many DNA sequence analyses including metagenomics studies and phylogeny inference. When guided by protein profiles, DNA multiple alignments assume a higher precision and robustness. Here we present details of the use of the upgraded version of MSA-PAD (2.0), which is a DNA multiple sequence alignment framework able to align DNA sequences coding for single/multiple protein domains guided by PFAM or user-defined annotations. MSA-PAD has two alignment strategies, called "Gene" and "Genome," accounting for coding domains order and genomic rearrangements, respectively. Novel options were added to the present version, where the MSA can be guided by protein profiles provided by the user. This allows MSA-PAD 2.0 to run faster and to add custom protein profiles sometimes not present in PFAM database according to the user's interest. MSA-PAD 2.0 is currently freely available as a Web application at https://recasgateway.cloud.ba.infn.it/ .

Incorporation of unique molecular identifiers in TruSeq adapters improves the accuracy of quantitative sequencing.

PubMed

Hong, Jungeui; Gresham, David

2017-11-01

Quantitative analysis of next-generation sequencing (NGS) data requires discriminating duplicate reads generated by PCR from identical molecules that are of unique origin. Typically, PCR duplicates are identified as sequence reads that align to the same genomic coordinates using reference-based alignment. However, identical molecules can be independently generated during library preparation. Misidentification of these molecules as PCR duplicates can introduce unforeseen biases during analyses. Here, we developed a cost-effective sequencing adapter design by modifying Illumina TruSeq adapters to incorporate a unique molecular identifier (UMI) while maintaining the capacity to undertake multiplexed, single-index sequencing. Incorporation of UMIs into TruSeq adapters (TrUMIseq adapters) enables identification of bona fide PCR duplicates as identically mapped reads with identical UMIs. Using TrUMIseq adapters, we show that accurate removal of PCR duplicates results in improved accuracy of both allele frequency (AF) estimation in heterogeneous populations using DNA sequencing and gene expression quantification using RNA-Seq.

Power law tails in phylogenetic systems.

PubMed

Qin, Chongli; Colwell, Lucy J

2018-01-23

Covariance analysis of protein sequence alignments uses coevolving pairs of sequence positions to predict features of protein structure and function. However, current methods ignore the phylogenetic relationships between sequences, potentially corrupting the identification of covarying positions. Here, we use random matrix theory to demonstrate the existence of a power law tail that distinguishes the spectrum of covariance caused by phylogeny from that caused by structural interactions. The power law is essentially independent of the phylogenetic tree topology, depending on just two parameters-the sequence length and the average branch length. We demonstrate that these power law tails are ubiquitous in the large protein sequence alignments used to predict contacts in 3D structure, as predicted by our theory. This suggests that to decouple phylogenetic effects from the interactions between sequence distal sites that control biological function, it is necessary to remove or down-weight the eigenvectors of the covariance matrix with largest eigenvalues. We confirm that truncating these eigenvectors improves contact prediction.

enoLOGOS: a versatile web tool for energy normalized sequence logos

PubMed Central

Workman, Christopher T.; Yin, Yutong; Corcoran, David L.; Ideker, Trey; Stormo, Gary D.; Benos, Panayiotis V.

2005-01-01

enoLOGOS is a web-based tool that generates sequence logos from various input sources. Sequence logos have become a popular way to graphically represent DNA and amino acid sequence patterns from a set of aligned sequences. Each position of the alignment is represented by a column of stacked symbols with its total height reflecting the information content in this position. Currently, the available web servers are able to create logo images from a set of aligned sequences, but none of them generates weighted sequence logos directly from energy measurements or other sources. With the advent of high-throughput technologies for estimating the contact energy of different DNA sequences, tools that can create logos directly from binding affinity data are useful to researchers. enoLOGOS generates sequence logos from a variety of input data, including energy measurements, probability matrices, alignment matrices, count matrices and aligned sequences. Furthermore, enoLOGOS can represent the mutual information of different positions of the consensus sequence, a unique feature of this tool. Another web interface for our software, C2H2-enoLOGOS, generates logos for the DNA-binding preferences of the C2H2 zinc-finger transcription factor family members. enoLOGOS and C2H2-enoLOGOS are accessible over the web at . PMID:15980495

Slider--maximum use of probability information for alignment of short sequence reads and SNP detection.

PubMed

Malhis, Nawar; Butterfield, Yaron S N; Ester, Martin; Jones, Steven J M

2009-01-01

A plethora of alignment tools have been created that are designed to best fit different types of alignment conditions. While some of these are made for aligning Illumina Sequence Analyzer reads, none of these are fully utilizing its probability (prb) output. In this article, we will introduce a new alignment approach (Slider) that reduces the alignment problem space by utilizing each read base's probabilities given in the prb files. Compared with other aligners, Slider has higher alignment accuracy and efficiency. In addition, given that Slider matches bases with probabilities other than the most probable, it significantly reduces the percentage of base mismatches. The result is that its SNP predictions are more accurate than other SNP prediction approaches used today that start from the most probable sequence, including those using base quality.

Structure-Based Sequence Alignment of the Transmembrane Domains of All Human GPCRs: Phylogenetic, Structural and Functional Implications

PubMed Central

Cvicek, Vaclav; Goddard, William A.; Abrol, Ravinder

2016-01-01

The understanding of G-protein coupled receptors (GPCRs) is undergoing a revolution due to increased information about their signaling and the experimental determination of structures for more than 25 receptors. The availability of at least one receptor structure for each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide analysis to identify signatures involving the role of conserved residues, conserved contacts, and downstream signaling in the context of receptor structures. In this study, we align the transmembrane (TM) domains of all experimental GPCR structures to maximize the conserved inter-helical contacts. The resulting superfamily-wide GpcR Sequence-Structure (GRoSS) alignment of the TM domains for all human GPCR sequences is sufficient to generate a phylogenetic tree that correctly distinguishes all different GPCR classes, suggesting that the class-level differences in the GPCR superfamily are encoded at least partly in the TM domains. The inter-helical contacts conserved across all GPCR classes describe the evolutionarily conserved GPCR structural fold. The corresponding structural alignment of the inactive and active conformations, available for a few GPCRs, identifies activation hot-spot residues in the TM domains that get rewired upon activation. Many GPCR mutations, known to alter receptor signaling and cause disease, are located at these conserved contact and activation hot-spot residue positions. The GRoSS alignment places the chemosensory receptor subfamilies for bitter taste (TAS2R) and pheromones (Vomeronasal, VN1R) in the rhodopsin family, known to contain the chemosensory olfactory receptor subfamily. The GRoSS alignment also enables the quantification of the structural variability in the TM regions of experimental structures, useful for homology modeling and structure prediction of receptors. Furthermore, this alignment identifies structurally and functionally important residues in all human GPCRs. These residues can be used to make testable hypotheses about the structural basis of receptor function and about the molecular basis of disease-associated single nucleotide polymorphisms. PMID:27028541

MultiSeq: unifying sequence and structure data for evolutionary analysis

PubMed Central

Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida

2006-01-01

Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055

Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.

PubMed

Loh, Yong-Hwee Eddie; Shen, Li

2016-01-01

The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.

2015-05-01

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of alreadymore » annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.« less

AntiClustal: Multiple Sequence Alignment by antipole clustering and linear approximate 1-median computation.

PubMed

Di Pietro, C; Di Pietro, V; Emmanuele, G; Ferro, A; Maugeri, T; Modica, E; Pigola, G; Pulvirenti, A; Purrello, M; Ragusa, M; Scalia, M; Shasha, D; Travali, S; Zimmitti, V

2003-01-01

In this paper we present a new Multiple Sequence Alignment (MSA) algorithm called AntiClusAl. The method makes use of the commonly use idea of aligning homologous sequences belonging to classes generated by some clustering algorithm, and then continue the alignment process ina bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of the progressive alignment with the 1-median (center) of the cluster. The 1-median of set S of sequences is the element of S which minimizes the average distance from any other sequence in S. Its exact computation requires quadratic time. The basic idea of our proposed algorithm is to make use of a simple and natural algorithmic technique based on randomized tournaments which has been successfully applied to large size search problems in general metric spaces. In particular a clustering algorithm called Antipole tree and an approximate linear 1-median computation are used. Our algorithm compared with Clustal W, a widely used tool to MSA, shows a better running time results with fully comparable alignment quality. A successful biological application showing high aminoacid conservation during evolution of Xenopus laevis SOD2 is also cited.

HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.

PubMed

Hashemifar, Somaye; Xu, Jinbo

2014-09-01

High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Alignment of RNA molecules: Binding energy and statistical properties of random sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valba, O. V., E-mail: valbaolga@gmail.com; Nechaev, S. K., E-mail: sergei.nechaev@gmail.com; Tamm, M. V., E-mail: thumm.m@gmail.com

2012-02-15

A new statistical approach to the problem of pairwise alignment of RNA sequences is proposed. The problem is analyzed for a pair of interacting polymers forming an RNA-like hierarchical cloverleaf structures. An alignment is characterized by the numbers of matches, mismatches, and gaps. A weight function is assigned to each alignment; this function is interpreted as a free energy taking into account both direct monomer-monomer interactions and a combinatorial contribution due to formation of various cloverleaf secondary structures. The binding free energy is determined for a pair of RNA molecules. Statistical properties are discussed, including fluctuations of the binding energymore » between a pair of RNA molecules and loop length distribution in a complex. Based on an analysis of the free energy per nucleotide pair complexes of random RNAs as a function of the number of nucleotide types c, a hypothesis is put forward about the exclusivity of the alphabet c = 4 used by nature.« less

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures.

PubMed

Goldenberg, Ofir; Erez, Elana; Nimrod, Guy; Ben-Tal, Nir

2009-01-01

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il/

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures

PubMed Central

Goldenberg, Ofir; Erez, Elana; Nimrod, Guy; Ben-Tal, Nir

2009-01-01

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il/ PMID:18971256

Choice of Reference Sequence and Assembler for Alignment of Listeria monocytogenes Short-Read Sequence Data Greatly Influences Rates of Error in SNP Analyses

PubMed Central

Pightling, Arthur W.; Petronella, Nicholas; Pagotto, Franco

2014-01-01

The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (i.e., true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real Listeria monocytogenes strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (i.e., quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results. PMID:25144537

A Fast Alignment-Free Approach for De Novo Detection of Protein Conserved Regions

PubMed Central

Abnousi, Armen; Broschat, Shira L.; Kalyanaraman, Ananth

2016-01-01

Background Identifying conserved regions in protein sequences is a fundamental operation, occurring in numerous sequence-driven analysis pipelines. It is used as a way to decode domain-rich regions within proteins, to compute protein clusters, to annotate sequence function, and to compute evolutionary relationships among protein sequences. A number of approaches exist for identifying and characterizing protein families based on their domains, and because domains represent conserved portions of a protein sequence, the primary computation involved in protein family characterization is identification of such conserved regions. However, identifying conserved regions from large collections (millions) of protein sequences presents significant challenges. Methods In this paper we present a new, alignment-free method for detecting conserved regions in protein sequences called NADDA (No-Alignment Domain Detection Algorithm). Our method exploits the abundance of exact matching short subsequences (k-mers) to quickly detect conserved regions, and the power of machine learning is used to improve the prediction accuracy of detection. We present a parallel implementation of NADDA using the MapReduce framework and show that our method is highly scalable. Results We have compared NADDA with Pfam and InterPro databases. For known domains annotated by Pfam, accuracy is 83%, sensitivity 96%, and specificity 44%. For sequences with new domains not present in the training set an average accuracy of 63% is achieved when compared to Pfam. A boost in results in comparison with InterPro demonstrates the ability of NADDA to capture conserved regions beyond those present in Pfam. We have also compared NADDA with ADDA and MKDOM2, assuming Pfam as ground-truth. On average NADDA shows comparable accuracy, more balanced sensitivity and specificity, and being alignment-free, is significantly faster. Excluding the one-time cost of training, runtimes on a single processor were 49s, 10,566s, and 456s for NADDA, ADDA, and MKDOM2, respectively, for a data set comprised of approximately 2500 sequences. PMID:27552220

Isolation and identification of multidrug-resistant Staphylococcus haemolyticus from a laboratory-breeding mouse.

PubMed

Huang, Fengying; Meng, Qiuping; Tan, Guanghong; Huang, Yonghao; Wang, Hua; Mei, Wenli; Dai, Haofu

2011-06-01

To analysis and identify a bacterium strain isolated from laboratory breeding mouse far away from a hospital. Phenotype of the isolate was investigated by conventional microbiological methods, including Gram-staining, colony morphology, tests for haemolysis, catalase, coagulase, and antimicrobial susceptibility test. The mecA and 16S rRNA genes were amplified by the polymerase chain reaction (PCR) and sequenced. The base sequence of the PCR product was compared with known 16S rRNA gene sequences in the GenBank database by phylogenetic analysis and multiple sequence alignment. The isolate in this study was a gram positive, coagulase negative, and catalase positive coccus. The isolate was resistant to oxacillin, methicillin, penicillin, ampicillin, cefazolin, ciprofloxacin erythromycin, et al. PCR results indicated that the isolate was mecA gene positive and its 16S rRNA was 1 465 bp. Phylogenetic analysis of the resultant 16S rRNA indicated the isolate belonged to genus Saphylococcus, and multiple sequence alignment showed that the isolate was Saphylococcus haemolyticus with only one base difference from the corresponding 16S rRNA deposited in the GenBank. 16S rRNA gene sequencing is a suitable technique for non-specialist researchers. Laboratory animals are possible sources of lethal pathogens, and researchers must adapt protective measures when they manipulate animals. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Disentangling methodological and biological sources of gene tree discordance on Oryza (Poaceae) chromosome 3.

PubMed

Zwickl, Derrick J; Stein, Joshua C; Wing, Rod A; Ware, Doreen; Sanderson, Michael J

2014-09-01

We describe new methods for characterizing gene tree discordance in phylogenomic data sets, which screen for deviations from neutral expectations, summarize variation in statistical support among gene trees, and allow comparison of the patterns of discordance induced by various analysis choices. Using an exceptionally complete set of genome sequences for the short arm of chromosome 3 in Oryza (rice) species, we applied these methods to identify the causes and consequences of differing patterns of discordance in the sets of gene trees inferred using a panel of 20 distinct analysis pipelines. We found that discordance patterns were strongly affected by aspects of data selection, alignment, and alignment masking. Unusual patterns of discordance evident when using certain pipelines were reduced or eliminated by using alternative pipelines, suggesting that they were the product of methodological biases rather than evolutionary processes. In some cases, once such biases were eliminated, evolutionary processes such as introgression could be implicated. Additionally, patterns of gene tree discordance had significant downstream impacts on species tree inference. For example, inference from supermatrices was positively misleading when pipelines that led to biased gene trees were used. Several results may generalize to other data sets: we found that gene tree and species tree inference gave more reasonable results when intron sequence was included during sequence alignment and tree inference, the alignment software PRANK was used, and detectable "block-shift" alignment artifacts were removed. We discuss our findings in the context of well-established relationships in Oryza and continuing controversies regarding the domestication history of O. sativa. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

PubMed Central

2011-01-01

Background Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. Methods We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. Results Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. Conclusions Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer. PMID:21261984

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

Dipeptide Sequence Determination: Analyzing Phenylthiohydantoin Amino Acids by HPLC

NASA Astrophysics Data System (ADS)

Barton, Janice S.; Tang, Chung-Fei; Reed, Steven S.

2000-02-01

Amino acid composition and sequence determination, important techniques for characterizing peptides and proteins, are essential for predicting conformation and studying sequence alignment. This experiment presents improved, fundamental methods of sequence analysis for an upper-division biochemistry laboratory. Working in pairs, students use the Edman reagent to prepare phenylthiohydantoin derivatives of amino acids for determination of the sequence of an unknown dipeptide. With a single HPLC technique, students identify both the N-terminal amino acid and the composition of the dipeptide. This method yields good precision of retention times and allows use of a broad range of amino acids as components of the dipeptide. Students learn fundamental principles and techniques of sequence analysis and HPLC.

Phylogenetic inference under varying proportions of indel-induced alignment gaps

PubMed Central

Dwivedi, Bhakti; Gadagkar, Sudhindra R

2009-01-01

Background The effect of alignment gaps on phylogenetic accuracy has been the subject of numerous studies. In this study, we investigated the relationship between the total number of gapped sites and phylogenetic accuracy, when the gaps were introduced (by means of computer simulation) to reflect indel (insertion/deletion) events during the evolution of DNA sequences. The resulting (true) alignments were subjected to commonly used gap treatment and phylogenetic inference methods. Results (1) In general, there was a strong – almost deterministic – relationship between the amount of gap in the data and the level of phylogenetic accuracy when the alignments were very "gappy", (2) gaps resulting from deletions (as opposed to insertions) contributed more to the inaccuracy of phylogenetic inference, (3) the probabilistic methods (Bayesian, PhyML & "MLε, " a method implemented in DNAML in PHYLIP) performed better at most levels of gap percentage when compared to parsimony (MP) and distance (NJ) methods, with Bayesian analysis being clearly the best, (4) methods that treat gapped sites as missing data yielded less accurate trees when compared to those that attribute phylogenetic signal to the gapped sites (by coding them as binary character data – presence/absence, or as in the MLε method), and (5) in general, the accuracy of phylogenetic inference depended upon the amount of available data when the gaps resulted from mainly deletion events, and the amount of missing data when insertion events were equally likely to have caused the alignment gaps. Conclusion When gaps in an alignment are a consequence of indel events in the evolution of the sequences, the accuracy of phylogenetic analysis is likely to improve if: (1) alignment gaps are categorized as arising from insertion events or deletion events and then treated separately in the analysis, (2) the evolutionary signal provided by indels is harnessed in the phylogenetic analysis, and (3) methods that utilize the phylogenetic signal in indels are developed for distance methods too. When the true homology is known and the amount of gaps is 20 percent of the alignment length or less, the methods used in this study are likely to yield trees with 90–100 percent accuracy. PMID:19698168

Construction of Red Fox Chromosomal Fragments from the Short-Read Genome Assembly.

PubMed

Rando, Halie M; Farré, Marta; Robson, Michael P; Won, Naomi B; Johnson, Jennifer L; Buch, Ronak; Bastounes, Estelle R; Xiang, Xueyan; Feng, Shaohong; Liu, Shiping; Xiong, Zijun; Kim, Jaebum; Zhang, Guojie; Trut, Lyudmila N; Larkin, Denis M; Kukekova, Anna V

2018-06-20

The genome of a red fox ( Vulpes vulpes ) was recently sequenced and assembled using next-generation sequencing (NGS). The assembly is of high quality, with 94X coverage and a scaffold N50 of 11.8 Mbp, but is split into 676,878 scaffolds, some of which are likely to contain assembly errors. Fragmentation and misassembly hinder accurate gene prediction and downstream analysis such as the identification of loci under selection. Therefore, assembly of the genome into chromosome-scale fragments was an important step towards developing this genomic model. Scaffolds from the assembly were aligned to the dog reference genome and compared to the alignment of an outgroup genome (cat) against the dog to identify syntenic sequences among species. The program Reference-Assisted Chromosome Assembly (RACA) then integrated the comparative alignment with the mapping of the raw sequencing reads generated during assembly against the fox scaffolds. The 128 sequence fragments RACA assembled were compared to the fox meiotic linkage map to guide the construction of 40 chromosomal fragments. This computational approach to assembly was facilitated by prior research in comparative mammalian genomics, and the continued improvement of the red fox genome can in turn offer insight into canid and carnivore chromosome evolution. This assembly is also necessary for advancing genetic research in foxes and other canids.

Human retroviruses and AIDS 1996. A compilation and analysis of nucleic acid and amino acid sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, G.; Foley, B.; Korber, B.

1997-04-01

This compendium and the accompanying floppy diskettes are the result of an effort to compile and rapidly publish all relevant molecular data concerning the human immunodeficiency viruses (HIV) and related retroviruses. The scope of the compendium and database is best summarized by the five parts that it comprises: (1) Nuclear Acid Alignments and Sequences; (2) Amino Acid Alignments; (3) Analysis; (4) Related Sequences; and (5) Database Communications. Information within all the parts is updated throughout the year on the Web site, http://hiv-web.lanl.gov. While this publication could take the form of a review or sequence monograph, it is not so conceived.more » Instead, the literature from which the database is derived has simply been summarized and some elementary computational analyses have been performed upon the data. Interpretation and commentary have been avoided insofar as possible so that the reader can form his or her own judgments concerning the complex information. In addition to the general descriptions of the parts of the compendium, the user should read the individual introductions for each part.« less

Generic accelerated sequence alignment in SeqAn using vectorization and multi-threading.

PubMed

Rahn, René; Budach, Stefan; Costanza, Pascal; Ehrhardt, Marcel; Hancox, Jonny; Reinert, Knut

2018-05-03

Pairwise sequence alignment is undoubtedly a central tool in many bioinformatics analyses. In this paper, we present a generically accelerated module for pairwise sequence alignments applicable for a broad range of applications. In our module, we unified the standard dynamic programming kernel used for pairwise sequence alignments and extended it with a generalized inter-sequence vectorization layout, such that many alignments can be computed simultaneously by exploiting SIMD (Single Instruction Multiple Data) instructions of modern processors. We then extended the module by adding two layers of thread-level parallelization, where we a) distribute many independent alignments on multiple threads and b) inherently parallelize a single alignment computation using a work stealing approach producing a dynamic wavefront progressing along the minor diagonal. We evaluated our alignment vectorization and parallelization on different processors, including the newest Intel® Xeon® (Skylake) and Intel® Xeon Phi™ (KNL) processors, and use cases. The instruction set AVX512-BW (Byte and Word), available on Skylake processors, can genuinely improve the performance of vectorized alignments. We could run single alignments 1600 times faster on the Xeon Phi™ and 1400 times faster on the Xeon® than executing them with our previous sequential alignment module. The module is programmed in C++ using the SeqAn (Reinert et al., 2017) library and distributed with version 2.4. under the BSD license. We support SSE4, AVX2, AVX512 instructions and included UME::SIMD, a SIMD-instruction wrapper library, to extend our module for further instruction sets. We thoroughly test all alignment components with all major C++ compilers on various platforms. rene.rahn@fu-berlin.de.

The Saccharomyces Genome Database Variant Viewer.

PubMed

Sheppard, Travis K; Hitz, Benjamin C; Engel, Stacia R; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C; Dalusag, Kyla S; Demeter, Janos; Hellerstedt, Sage T; Karra, Kalpana; Nash, Robert S; Paskov, Kelley M; Skrzypek, Marek S; Weng, Shuai; Wong, Edith D; Cherry, J Michael

2016-01-04

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The current status and portability of our sequence handling software.

PubMed Central

Staden, R

1986-01-01

I describe the current status of our sequence analysis software. The package contains a comprehensive suite of programs for managing large shotgun sequencing projects, a program containing 61 functions for analysing single sequences and a program for comparing pairs of sequences for similarity. The programs that have been described before have been improved by the addition of new functions and by being made very much easier to use. The major interactive programs have 125 pages of online help available from within them. Several new programs are described including screen editing of aligned gel readings for shotgun sequencing projects; a method to highlight errors in aligned gel readings, new methods for searching for putative signals in sequences. We use the programs on a VAX computer but the whole package has been rewritten to make it easy to transport it to other machines. I believe the programs will now run on any machine with a FORTRAN77 compiler and sufficient memory. We are currently putting the programs onto an IBM PC XT/AT and another micro running under UNIX. PMID:3511446

New powerful statistics for alignment-free sequence comparison under a pattern transfer model.

PubMed

Liu, Xuemei; Wan, Lin; Li, Jing; Reinert, Gesine; Waterman, Michael S; Sun, Fengzhu

2011-09-07

Alignment-free sequence comparison is widely used for comparing gene regulatory regions and for identifying horizontally transferred genes. Recent studies on the power of a widely used alignment-free comparison statistic D2 and its variants D*2 and D(s)2 showed that their power approximates a limit smaller than 1 as the sequence length tends to infinity under a pattern transfer model. We develop new alignment-free statistics based on D2, D*2 and D(s)2 by comparing local sequence pairs and then summing over all the local sequence pairs of certain length. We show that the new statistics are much more powerful than the corresponding statistics and the power tends to 1 as the sequence length tends to infinity under the pattern transfer model. Copyright © 2011 Elsevier Ltd. All rights reserved.

New Powerful Statistics for Alignment-free Sequence Comparison Under a Pattern Transfer Model

PubMed Central

Liu, Xuemei; Wan, Lin; Li, Jing; Reinert, Gesine; Waterman, Michael S.; Sun, Fengzhu

2011-01-01

Alignment-free sequence comparison is widely used for comparing gene regulatory regions and for identifying horizontally transferred genes. Recent studies on the power of a widely used alignment-free comparison statistic D2 and its variants D2∗ and D2s showed that their power approximates a limit smaller than 1 as the sequence length tends to infinity under a pattern transfer model. We develop new alignment-free statistics based on D2, D2∗ and D2s by comparing local sequence pairs and then summing over all the local sequence pairs of certain length. We show that the new statistics are much more powerful than the corresponding statistics and the power tends to 1 as the sequence length tends to infinity under the pattern transfer model. PMID:21723298

GuiTope: an application for mapping random-sequence peptides to protein sequences.

PubMed

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

ARYANA: Aligning Reads by Yet Another Approach

PubMed Central

2014-01-01

Motivation Although there are many different algorithms and software tools for aligning sequencing reads, fast gapped sequence search is far from solved. Strong interest in fast alignment is best reflected in the $106 prize for the Innocentive competition on aligning a collection of reads to a given database of reference genomes. In addition, de novo assembly of next-generation sequencing long reads requires fast overlap-layout-concensus algorithms which depend on fast and accurate alignment. Contribution We introduce ARYANA, a fast gapped read aligner, developed on the base of BWA indexing infrastructure with a completely new alignment engine that makes it significantly faster than three other aligners: Bowtie2, BWA and SeqAlto, with comparable generality and accuracy. Instead of the time-consuming backtracking procedures for handling mismatches, ARYANA comes with the seed-and-extend algorithmic framework and a significantly improved efficiency by integrating novel algorithmic techniques including dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming. As the read length increases ARYANA's superiority in terms of speed and alignment rate becomes more evident. This is in perfect harmony with the read length trend as the sequencing technologies evolve. The algorithmic platform of ARYANA makes it easy to develop mission-specific aligners for other applications using ARYANA engine. Availability ARYANA with complete source code can be obtained from http://github.com/aryana-aligner PMID:25252881

ARYANA: Aligning Reads by Yet Another Approach.

PubMed

Gholami, Milad; Arbabi, Aryan; Sharifi-Zarchi, Ali; Chitsaz, Hamidreza; Sadeghi, Mehdi

2014-01-01

Although there are many different algorithms and software tools for aligning sequencing reads, fast gapped sequence search is far from solved. Strong interest in fast alignment is best reflected in the $10(6) prize for the Innocentive competition on aligning a collection of reads to a given database of reference genomes. In addition, de novo assembly of next-generation sequencing long reads requires fast overlap-layout-concensus algorithms which depend on fast and accurate alignment. We introduce ARYANA, a fast gapped read aligner, developed on the base of BWA indexing infrastructure with a completely new alignment engine that makes it significantly faster than three other aligners: Bowtie2, BWA and SeqAlto, with comparable generality and accuracy. Instead of the time-consuming backtracking procedures for handling mismatches, ARYANA comes with the seed-and-extend algorithmic framework and a significantly improved efficiency by integrating novel algorithmic techniques including dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming. As the read length increases ARYANA's superiority in terms of speed and alignment rate becomes more evident. This is in perfect harmony with the read length trend as the sequencing technologies evolve. The algorithmic platform of ARYANA makes it easy to develop mission-specific aligners for other applications using ARYANA engine. ARYANA with complete source code can be obtained from http://github.com/aryana-aligner.

Iterative pass optimization of sequence data

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Multi-Harmony: detecting functional specificity from sequence alignment

PubMed Central

Brandt, Bernd W.; Feenstra, K. Anton; Heringa, Jaap

2010-01-01

Many protein families contain sub-families with functional specialization, such as binding different ligands or being involved in different protein–protein interactions. A small number of amino acids generally determine functional specificity. The identification of these residues can aid the understanding of protein function and help finding targets for experimental analysis. Here, we present multi-Harmony, an interactive web sever for detecting sub-type-specific sites in proteins starting from a multiple sequence alignment. Combining our Sequence Harmony (SH) and multi-Relief (mR) methods in one web server allows simultaneous analysis and comparison of specificity residues; furthermore, both methods have been significantly improved and extended. SH has been extended to cope with more than two sub-groups. mR has been changed from a sampling implementation to a deterministic one, making it more consistent and user friendly. For both methods Z-scores are reported. The multi-Harmony web server produces a dynamic output page, which includes interactive connections to the Jalview and Jmol applets, thereby allowing interactive analysis of the results. Multi-Harmony is available at http://www.ibi.vu.nl/ programs/shmrwww. PMID:20525785

SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees.

PubMed

Liu, Kevin; Warnow, Tandy J; Holder, Mark T; Nelesen, Serita M; Yu, Jiaye; Stamatakis, Alexandros P; Linder, C Randal

2012-01-01

Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of those sequences that maximize likelihood under the Jukes-Cantor model is uninformative in the worst possible sense. For all inputs, all trees optimize the likelihood score. Second, we show that a greedy heuristic that uses GTR+Gamma ML to optimize the alignment and the tree can produce very poor alignments and trees. Therefore, the excellent performance of SATé-II and SATé-I is not because ML is used as an optimization criterion for choosing the best tree/alignment pair but rather due to the particular divide-and-conquer realignment techniques employed.

An analysis of the New York State Earth Science Curriculum with respect to standards, classroom practices, and the Regents Examination

NASA Astrophysics Data System (ADS)

Contino, Julie Anna

In a standards-based system, it is important for all components of the system to align in order to achieve the intended goals. In New York State, standards are provided to the teachers who then create individual curricula that will lead to student success on the state assessment. This mixed methods study presents an analysis of the alignment between the National Science Education Standards (NSES), New York State Physical Setting/Earth Science Core Curriculum (Core Curriculum), and New York State Earth Science Regents Examination (Regents)---the sources teachers use for creating Earth Science curricula in New York State. The NSES were found to have a 49% overlap with the Core Curriculum and a 27% overlap with the Regents. The Core Curriculum and Regents, represented by matrices consisting of performance indicators and cognitive demands, were compared using the Porter alignment index. The alignment was 0.35, categorized as slightly aligned, due to the different emphases on cognitive levels (the Core Curriculum focused on Understand and Apply while the Regents focused on Apply followed by Understand and Remember). Additionally, a purposeful sample of experienced and innovative teachers were surveyed and interviewed to gain insight on how NYS Earth Science teachers organize their scope and sequences, align their lessons with the Core Curriculum, establish internal lesson coherence, and prepare their students for the Regents Exam. Teachers' scope and sequences were well-aligned with the Core Curriculum and Regents but misalignment was found between their lessons and the Core Curriculum as well as between the stated objectives for their students and evaluation of those objectives. Based on the findings, it is suggested that the NSES be revised and the Core Curriculum updated to include quantifiable emphasis on the major understandings such as percentage of time, as well as an emphasis on alignment principles. Teacher professional development focused on alignment issues relative to the state standards and enhancing internal lesson coherence should also be provided. The insights gained from this analysis of the NYS system may be helpful to other states as they move toward standards-based systems.

Delineating slowly and rapidly evolving fractions of the Drosophila genome.

PubMed

Keith, Jonathan M; Adams, Peter; Stephen, Stuart; Mattick, John S

2008-05-01

Evolutionary conservation is an important indicator of function and a major component of bioinformatic methods to identify non-protein-coding genes. We present a new Bayesian method for segmenting pairwise alignments of eukaryotic genomes while simultaneously classifying segments into slowly and rapidly evolving fractions. We also describe an information criterion similar to the Akaike Information Criterion (AIC) for determining the number of classes. Working with pairwise alignments enables detection of differences in conservation patterns among closely related species. We analyzed three whole-genome and three partial-genome pairwise alignments among eight Drosophila species. Three distinct classes of conservation level were detected. Sequences comprising the most slowly evolving component were consistent across a range of species pairs, and constituted approximately 62-66% of the D. melanogaster genome. Almost all (>90%) of the aligned protein-coding sequence is in this fraction, suggesting much of it (comprising the majority of the Drosophila genome, including approximately 56% of non-protein-coding sequences) is functional. The size and content of the most rapidly evolving component was species dependent, and varied from 1.6% to 4.8%. This fraction is also enriched for protein-coding sequence (while containing significant amounts of non-protein-coding sequence), suggesting it is under positive selection. We also classified segments according to conservation and GC content simultaneously. This analysis identified numerous sub-classes of those identified on the basis of conservation alone, but was nevertheless consistent with that classification. Software, data, and results available at www.maths.qut.edu.au/-keithj/. Genomic segments comprising the conservation classes available in BED format.

Obtaining a more resolute teleost growth hormone phylogeny by the introduction of gaps in sequence alignment.

PubMed

Rubin, D A; Dores, R M

1995-06-01

In order to obtain a more resolute phylogeny of teleosts based on growth hormone (GH) sequences, phylogenetic analyses were performed in which deletions (gaps), which appear to be order specific, were upheld to maintain GH's structural information. Sequences were analyzed at 194 amino acid positions. In addition, the two closest genealogically related groups to the teleosts, Amia calva and Acipenser guldenstadti, were used as outgroups. Modified sequence alignments were also analyzed to determine clade stability. Analyses indicated, in the most parsimonious cladogram, that molecular and morphological relationships for the orders of fishes are congruent. With GH molecular sequence data it was possible to resolve all clades at the familial level. Analyses of the primary sequence data indicate that: (a) the halecomorphean and chondrostean GH sequences are the appropriate outgroups for generating the most parsimonious cladogram for teleosts; (b) proper alignment of teleost GH sequence by the inclusion of gaps is necessary for resolution of the Percomorpha; and (c) removal of sequence information by deleting improperly aligned sequence decreases the phylogenetic signal obtained.

BEAUTY: an enhanced BLAST-based search tool that integrates multiple biological information resources into sequence similarity search results.

PubMed

Worley, K C; Wiese, B A; Smith, R F

1995-09-01

BEAUTY (BLAST enhanced alignment utility) is an enhanced version of the NCBI's BLAST data base search tool that facilitates identification of the functions of matched sequences. We have created new data bases of conserved regions and functional domains for protein sequences in NCBI's Entrez data base, and BEAUTY allows this information to be incorporated directly into BLAST search results. A Conserved Regions Data Base, containing the locations of conserved regions within Entrez protein sequences, was constructed by (1) clustering the entire data base into families, (2) aligning each family using our PIMA multiple sequence alignment program, and (3) scanning the multiple alignments to locate the conserved regions within each aligned sequence. A separate Annotated Domains Data Base was constructed by extracting the locations of all annotated domains and sites from sequences represented in the Entrez, PROSITE, BLOCKS, and PRINTS data bases. BEAUTY performs a BLAST search of those Entrez sequences with conserved regions and/or annotated domains. BEAUTY then uses the information from the Conserved Regions and Annotated Domains data bases to generate, for each matched sequence, a schematic display that allows one to directly compare the relative locations of (1) the conserved regions, (2) annotated domains and sites, and (3) the locally aligned regions matched in the BLAST search. In addition, BEAUTY search results include World-Wide Web hypertext links to a number of external data bases that provide a variety of additional types of information on the function of matched sequences. This convenient integration of protein families, conserved regions, annotated domains, alignment displays, and World-Wide Web resources greatly enhances the biological informativeness of sequence similarity searches. BEAUTY searches can be performed remotely on our system using the "BCM Search Launcher" World-Wide Web pages (URL is < http:/ /gc.bcm.tmc.edu:8088/ search-launcher/launcher.html > ).

Finding similar nucleotide sequences using network BLAST searches.

PubMed

Ladunga, Istvan

2009-06-01

The Basic Local Alignment Search Tool (BLAST) is a keystone of bioinformatics due to its performance and user-friendliness. Beginner and intermediate users will learn how to design and submit blastn and Megablast searches on the Web pages at the National Center for Biotechnology Information. We map nucleic acid sequences to genomes, find identical or similar mRNA, expressed sequence tag, and noncoding RNA sequences, and run Megablast searches, which are much faster than blastn. Understanding results is assisted by taxonomy reports, genomic views, and multiple alignments. We interpret expected frequency thresholds, biological significance, and statistical significance. Weak hits provide no evidence, but hints for further analyses. We find genes that may code for homologous proteins by translated BLAST. We reduce false positives by filtering out low-complexity regions. Parsed BLAST results can be integrated into analysis pipelines. Links in the output connect to Entrez, PUBMED, structural, sequence, interaction, and expression databases. This facilitates integration with a wide spectrum of biological knowledge.

Implied alignment: a synapomorphy-based multiple-sequence alignment method and its use in cladogram search

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

A method to align sequence data based on parsimonious synapomorphy schemes generated by direct optimization (DO; earlier termed optimization alignment) is proposed. DO directly diagnoses sequence data on cladograms without an intervening multiple-alignment step, thereby creating topology-specific, dynamic homology statements. Hence, no multiple-alignment is required to generate cladograms. Unlike general and globally optimal multiple-alignment procedures, the method described here, implied alignment (IA), takes these dynamic homologies and traces them back through a single cladogram, linking the unaligned sequence positions in the terminal taxa via DO transformation series. These "lines of correspondence" link ancestor-descendent states and, when displayed as linearly arrayed columns without hypothetical ancestors, are largely indistinguishable from standard multiple alignment. Since this method is based on synapomorphy, the treatment of certain classes of insertion-deletion (indel) events may be different from that of other alignment procedures. As with all alignment methods, results are dependent on parameter assumptions such as indel cost and transversion:transition ratios. Such an IA could be used as a basis for phylogenetic search, but this would be questionable since the homologies derived from the implied alignment depend on its natal cladogram and any variance, between DO and IA + Search, due to heuristic approach. The utility of this procedure in heuristic cladogram searches using DO and the improvement of heuristic cladogram cost calculations are discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences

PubMed Central

2010-01-01

Background Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses. Results AlignMiner is a Web-based application for detection of conserved and divergent regions in alignments of conserved sequences, focusing particularly on divergence. It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results. AlignMiner uses different scoring methods for assessing conserved/divergent regions, Entropy being the method that provides the highest number of regions with the greatest length, and Weighted being the most restrictive. Conserved/divergent regions can be generated either with respect to the consensus sequence or to one master sequence. The resulting data are presented in a graphical interface developed in AJAX, which provides remarkable user interaction capabilities. Users do not need to wait until execution is complete and can.even inspect their results on a different computer. Data can be downloaded onto a user disk, in standard formats. In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies. Primer design is assisted by a module that deploys several oligonucleotide parameters for designing primers "on the fly". Conclusions AlignMiner can be used to reliably detect divergent regions via several scoring methods that provide different levels of selectivity. Its predictions have been verified by experimental means. Hence, it is expected that its usage will save researchers' time and ensure an objective selection of the best-possible divergent region when closely related sequences are analysed. AlignMiner is freely available at http://www.scbi.uma.es/alignminer. PMID:20525162

Processing and population genetic analysis of multigenic datasets with ProSeq3 software.

PubMed

Filatov, Dmitry A

2009-12-01

The current tendency in molecular population genetics is to use increasing numbers of genes in the analysis. Here I describe a program for handling and population genetic analysis of DNA polymorphism data collected from multiple genes. The program includes a sequence/alignment editor and an internal relational database that simplify the preparation and manipulation of multigenic DNA polymorphism datasets. The most commonly used DNA polymorphism analyses are implemented in ProSeq3, facilitating population genetic analysis of large multigenic datasets. Extensive input/output options make ProSeq3 a convenient hub for sequence data processing and analysis. The program is available free of charge from http://dps.plants.ox.ac.uk/sequencing/proseq.htm.

Spreadsheet-based program for alignment of overlapping DNA sequences.

PubMed

Anbazhagan, R; Gabrielson, E

1999-06-01

Molecular biology laboratories frequently face the challenge of aligning small overlapping DNA sequences derived from a long DNA segment. Here, we present a short program that can be used to adapt Excel spreadsheets as a tool for aligning DNA sequences, regardless of their orientation. The program runs on any Windows or Macintosh operating system computer with Excel 97 or Excel 98. The program is available for use as an Excel file, which can be downloaded from the BioTechniques Web site. Upon execution, the program opens a specially designed customized workbook and is capable of identifying overlapping regions between two sequence fragments and displaying the sequence alignment. It also performs a number of specialized functions such as recognition of restriction enzyme cutting sites and CpG island mapping without costly specialized software.

EAPhy: A Flexible Tool for High-throughput Quality Filtering of Exon-alignments and Data Processing for Phylogenetic Methods.

PubMed

Blom, Mozes P K

2015-08-05

Recently developed molecular methods enable geneticists to target and sequence thousands of orthologous loci and infer evolutionary relationships across the tree of life. Large numbers of genetic markers benefit species tree inference but visual inspection of alignment quality, as traditionally conducted, is challenging with thousands of loci. Furthermore, due to the impracticality of repeated visual inspection with alternative filtering criteria, the potential consequences of using datasets with different degrees of missing data remain nominally explored in most empirical phylogenomic studies. In this short communication, I describe a flexible high-throughput pipeline designed to assess alignment quality and filter exonic sequence data for subsequent inference. The stringency criteria for alignment quality and missing data can be adapted based on the expected level of sequence divergence. Each alignment is automatically evaluated based on the stringency criteria specified, significantly reducing the number of alignments that require visual inspection. By developing a rapid method for alignment filtering and quality assessment, the consistency of phylogenetic estimation based on exonic sequence alignments can be further explored across distinct inference methods, while accounting for different degrees of missing data.

Exact calculation of distributions on integers, with application to sequence alignment.

PubMed

Newberg, Lee A; Lawrence, Charles E

2009-01-01

Computational biology is replete with high-dimensional discrete prediction and inference problems. Dynamic programming recursions can be applied to several of the most important of these, including sequence alignment, RNA secondary-structure prediction, phylogenetic inference, and motif finding. In these problems, attention is frequently focused on some scalar quantity of interest, a score, such as an alignment score or the free energy of an RNA secondary structure. In many cases, score is naturally defined on integers, such as a count of the number of pairing differences between two sequence alignments, or else an integer score has been adopted for computational reasons, such as in the test of significance of motif scores. The probability distribution of the score under an appropriate probabilistic model is of interest, such as in tests of significance of motif scores, or in calculation of Bayesian confidence limits around an alignment. Here we present three algorithms for calculating the exact distribution of a score of this type; then, in the context of pairwise local sequence alignments, we apply the approach so as to find the alignment score distribution and Bayesian confidence limits.

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

PubMed

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Homologues of insulinase, a new superfamily of metalloendopeptidases.

PubMed Central

Rawlings, N D; Barrett, A J

1991-01-01

On the basis of a statistical analysis of an alignment of the amino acid sequences, a new superfamily of metalloendopeptidases is proposed, consisting of human insulinase, Escherichia coli protease III and mitochondrial processing endopeptidases from Saccharomyces and Neurospora. These enzymes do not contain the 'HEXXH' consensus sequence found in all previously recognized zinc metalloendopeptidases. PMID:2025223

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

PubMed

DeLuca, David S; Levin, Joshua Z; Sivachenko, Andrey; Fennell, Timothy; Nazaire, Marc-Danie; Williams, Chris; Reich, Michael; Winckler, Wendy; Getz, Gad

2012-06-01

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

Multiple alignment-free sequence comparison

PubMed Central

Ren, Jie; Song, Kai; Sun, Fengzhu; Deng, Minghua; Reinert, Gesine

2013-01-01

Motivation: Recently, a range of new statistics have become available for the alignment-free comparison of two sequences based on k-tuple word content. Here, we extend these statistics to the simultaneous comparison of more than two sequences. Our suite of statistics contains, first, and , extensions of statistics for pairwise comparison of the joint k-tuple content of all the sequences, and second, , and , averages of sums of pairwise comparison statistics. The two tasks we consider are, first, to identify sequences that are similar to a set of target sequences, and, second, to measure the similarity within a set of sequences. Results: Our investigation uses both simulated data as well as cis-regulatory module data where the task is to identify cis-regulatory modules with similar transcription factor binding sites. We find that although for real data, all of our statistics show a similar performance, on simulated data the Shepp-type statistics are in some instances outperformed by star-type statistics. The multiple alignment-free statistics are more sensitive to contamination in the data than the pairwise average statistics. Availability: Our implementation of the five statistics is available as R package named ‘multiAlignFree’ at be http://www-rcf.usc.edu/∼fsun/Programs/multiAlignFree/multiAlignFreemain.html. Contact: reinert@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23990418

Heuristic reusable dynamic programming: efficient updates of local sequence alignment.

PubMed

Hong, Changjin; Tewfik, Ahmed H

2009-01-01

Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm.

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server.

PubMed

Abriata, Luciano A; Bovigny, Christophe; Dal Peraro, Matteo

2016-06-17

Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting detailed analyses to positions of extremely high or low variability or dubbed important beforehand based on existing knowledge about active sites, interaction surfaces, (de)stabilizing mutations, etc. Our new webserver PsychoProt (freely available without registration at http://psychoprot.epfl.ch or at http://lucianoabriata.altervista.org/psychoprot/index.html ) helps to detect, quantify, and sequence/structure map the biophysical and biochemical traits that shape amino acid preferences throughout a protein as determined by deep-sequencing of saturated mutational libraries or from large alignments of naturally occurring variants. We exemplify how PsychoProt helps to (i) unveil protein structure-function relationships from experiments and from alignments that are consistent with structures according to coevolution analysis, (ii) recall global information about structural and functional features and identify hitherto unknown constraints to variation in alignments, and (iii) point at different sources of variation among related experimental datasets or between experimental and alignment-based data. Remarkably, metabolic costs of the amino acids pose strong constraints to variability at protein surfaces in nature but not in the laboratory. This and other differences call for caution when extrapolating results from in vitro experiments to natural scenarios in, for example, studies of protein evolution. We show through examples how PsychoProt can be a useful tool for the broad communities of structural biology and molecular evolution, particularly for studies about protein modeling, evolution and design.

Genome-wide identification of conserved intronic non-coding sequences using a Bayesian segmentation approach.

PubMed

Algama, Manjula; Tasker, Edward; Williams, Caitlin; Parslow, Adam C; Bryson-Richardson, Robert J; Keith, Jonathan M

2017-03-27

Computational identification of non-coding RNAs (ncRNAs) is a challenging problem. We describe a genome-wide analysis using Bayesian segmentation to identify intronic elements highly conserved between three evolutionarily distant vertebrate species: human, mouse and zebrafish. We investigate the extent to which these elements include ncRNAs (or conserved domains of ncRNAs) and regulatory sequences. We identified 655 deeply conserved intronic sequences in a genome-wide analysis. We also performed a pathway-focussed analysis on genes involved in muscle development, detecting 27 intronic elements, of which 22 were not detected in the genome-wide analysis. At least 87% of the genome-wide and 70% of the pathway-focussed elements have existing annotations indicative of conserved RNA secondary structure. The expression of 26 of the pathway-focused elements was examined using RT-PCR, providing confirmation that they include expressed ncRNAs. Consistent with previous studies, these elements are significantly over-represented in the introns of transcription factors. This study demonstrates a novel, highly effective, Bayesian approach to identifying conserved non-coding sequences. Our results complement previous findings that these sequences are enriched in transcription factors. However, in contrast to previous studies which suggest the majority of conserved sequences are regulatory factor binding sites, the majority of conserved sequences identified using our approach contain evidence of conserved RNA secondary structures, and our laboratory results suggest most are expressed. Functional roles at DNA and RNA levels are not mutually exclusive, and many of our elements possess evidence of both. Moreover, ncRNAs play roles in transcriptional and post-transcriptional regulation, and this may contribute to the over-representation of these elements in introns of transcription factors. We attribute the higher sensitivity of the pathway-focussed analysis compared to the genome-wide analysis to improved alignment quality, suggesting that enhanced genomic alignments may reveal many more conserved intronic sequences.

MicRhoDE: a curated database for the analysis of microbial rhodopsin diversity and evolution

PubMed Central

Boeuf, Dominique; Audic, Stéphane; Brillet-Guéguen, Loraine; Caron, Christophe; Jeanthon, Christian

2015-01-01

Microbial rhodopsins are a diverse group of photoactive transmembrane proteins found in all three domains of life and in viruses. Today, microbial rhodopsin research is a flourishing research field in which new understandings of rhodopsin diversity, function and evolution are contributing to broader microbiological and molecular knowledge. Here, we describe MicRhoDE, a comprehensive, high-quality and freely accessible database that facilitates analysis of the diversity and evolution of microbial rhodopsins. Rhodopsin sequences isolated from a vast array of marine and terrestrial environments were manually collected and curated. To each rhodopsin sequence are associated related metadata, including predicted spectral tuning of the protein, putative activity and function, taxonomy for sequences that can be linked to a 16S rRNA gene, sampling date and location, and supporting literature. The database currently covers 7857 aligned sequences from more than 450 environmental samples or organisms. Based on a robust phylogenetic analysis, we introduce an operational classification system with multiple phylogenetic levels ranging from superclusters to species-level operational taxonomic units. An integrated pipeline for online sequence alignment and phylogenetic tree construction is also provided. With a user-friendly interface and integrated online bioinformatics tools, this unique resource should be highly valuable for upcoming studies of the biogeography, diversity, distribution and evolution of microbial rhodopsins. Database URL: http://micrhode.sb-roscoff.fr. PMID:26286928

MicRhoDE: a curated database for the analysis of microbial rhodopsin diversity and evolution.

PubMed

Boeuf, Dominique; Audic, Stéphane; Brillet-Guéguen, Loraine; Caron, Christophe; Jeanthon, Christian

2015-01-01

Microbial rhodopsins are a diverse group of photoactive transmembrane proteins found in all three domains of life and in viruses. Today, microbial rhodopsin research is a flourishing research field in which new understandings of rhodopsin diversity, function and evolution are contributing to broader microbiological and molecular knowledge. Here, we describe MicRhoDE, a comprehensive, high-quality and freely accessible database that facilitates analysis of the diversity and evolution of microbial rhodopsins. Rhodopsin sequences isolated from a vast array of marine and terrestrial environments were manually collected and curated. To each rhodopsin sequence are associated related metadata, including predicted spectral tuning of the protein, putative activity and function, taxonomy for sequences that can be linked to a 16S rRNA gene, sampling date and location, and supporting literature. The database currently covers 7857 aligned sequences from more than 450 environmental samples or organisms. Based on a robust phylogenetic analysis, we introduce an operational classification system with multiple phylogenetic levels ranging from superclusters to species-level operational taxonomic units. An integrated pipeline for online sequence alignment and phylogenetic tree construction is also provided. With a user-friendly interface and integrated online bioinformatics tools, this unique resource should be highly valuable for upcoming studies of the biogeography, diversity, distribution and evolution of microbial rhodopsins. Database URL: http://micrhode.sb-roscoff.fr. © The Author(s) 2015. Published by Oxford University Press.

Systematic evaluation of the impact of ChIP-seq read designs on genome coverage, peak identification, and allele-specific binding detection.

PubMed

Zhang, Qi; Zeng, Xin; Younkin, Sam; Kawli, Trupti; Snyder, Michael P; Keleş, Sündüz

2016-02-24

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments revolutionized genome-wide profiling of transcription factors and histone modifications. Although maturing sequencing technologies allow these experiments to be carried out with short (36-50 bps), long (75-100 bps), single-end, or paired-end reads, the impact of these read parameters on the downstream data analysis are not well understood. In this paper, we evaluate the effects of different read parameters on genome sequence alignment, coverage of different classes of genomic features, peak identification, and allele-specific binding detection. We generated 101 bps paired-end ChIP-seq data for many transcription factors from human GM12878 and MCF7 cell lines. Systematic evaluations using in silico variations of these data as well as fully simulated data, revealed complex interplay between the sequencing parameters and analysis tools, and indicated clear advantages of paired-end designs in several aspects such as alignment accuracy, peak resolution, and most notably, allele-specific binding detection. Our work elucidates the effect of design on the downstream analysis and provides insights to investigators in deciding sequencing parameters in ChIP-seq experiments. We present the first systematic evaluation of the impact of ChIP-seq designs on allele-specific binding detection and highlights the power of pair-end designs in such studies.

Assignment of protein sequences to existing domain and family classification systems: Pfam and the PDB.

PubMed

Xu, Qifang; Dunbrack, Roland L

2012-11-01

Automating the assignment of existing domain and protein family classifications to new sets of sequences is an important task. Current methods often miss assignments because remote relationships fail to achieve statistical significance. Some assignments are not as long as the actual domain definitions because local alignment methods often cut alignments short. Long insertions in query sequences often erroneously result in two copies of the domain assigned to the query. Divergent repeat sequences in proteins are often missed. We have developed a multilevel procedure to produce nearly complete assignments of protein families of an existing classification system to a large set of sequences. We apply this to the task of assigning Pfam domains to sequences and structures in the Protein Data Bank (PDB). We found that HHsearch alignments frequently scored more remotely related Pfams in Pfam clans higher than closely related Pfams, thus, leading to erroneous assignment at the Pfam family level. A greedy algorithm allowing for partial overlaps was, thus, applied first to sequence/HMM alignments, then HMM-HMM alignments and then structure alignments, taking care to join partial alignments split by large insertions into single-domain assignments. Additional assignment of repeat Pfams with weaker E-values was allowed after stronger assignments of the repeat HMM. Our database of assignments, presented in a database called PDBfam, contains Pfams for 99.4% of chains >50 residues. The Pfam assignment data in PDBfam are available at http://dunbrack2.fccc.edu/ProtCid/PDBfam, which can be searched by PDB codes and Pfam identifiers. They will be updated regularly.

DEMO: Sequence Alignment to Predict Across Species Susceptibility

EPA Science Inventory

The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility tool (SeqAPASS; https://seqapass.epa.gov/seqapass/) was developed to comparatively evaluate protein sequence and structural similarity across species as a means to extrapolate toxic...

Whole Genome Sequencing of Greater Amberjack (Seriola dumerili) for SNP Identification on Aligned Scaffolds and Genome Structural Variation Analysis Using Parallel Resequencing

PubMed Central

Aokic, Jun-ya; Kawase, Junya; Hamada, Kazuhisa; Fujimoto, Hiroshi; Yamamoto, Ikki; Usuki, Hironori

2018-01-01

Greater amberjack (Seriola dumerili) is distributed in tropical and temperate waters worldwide and is an important aquaculture fish. We carried out de novo sequencing of the greater amberjack genome to construct a reference genome sequence to identify single nucleotide polymorphisms (SNPs) for breeding amberjack by marker-assisted or gene-assisted selection as well as to identify functional genes for biological traits. We obtained 200 times coverage and constructed a high-quality genome assembly using next generation sequencing technology. The assembled sequences were aligned onto a yellowtail (Seriola quinqueradiata) radiation hybrid (RH) physical map by sequence homology. A total of 215 of the longest amberjack sequences, with a total length of 622.8 Mbp (92% of the total length of the genome scaffolds), were lined up on the yellowtail RH map. We resequenced the whole genomes of 20 greater amberjacks and mapped the resulting sequences onto the reference genome sequence. About 186,000 nonredundant SNPs were successfully ordered on the reference genome. Further, we found differences in the genome structural variations between two greater amberjack populations using BreakDancer. We also analyzed the greater amberjack transcriptome and mapped the annotated sequences onto the reference genome sequence. PMID:29785397

VISA--Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing.

PubMed

Hocum, Jonah D; Battrell, Logan R; Maynard, Ryan; Adair, Jennifer E; Beard, Brian C; Rawlings, David J; Kiem, Hans-Peter; Miller, Daniel G; Trobridge, Grant D

2015-07-07

Analyzing the integration profile of retroviral vectors is a vital step in determining their potential genotoxic effects and developing safer vectors for therapeutic use. Identifying retroviral vector integration sites is also important for retroviral mutagenesis screens. We developed VISA, a vector integration site analysis server, to analyze next-generation sequencing data for retroviral vector integration sites. Sequence reads that contain a provirus are mapped to the human genome, sequence reads that cannot be localized to a unique location in the genome are filtered out, and then unique retroviral vector integration sites are determined based on the alignment scores of the remaining sequence reads. VISA offers a simple web interface to upload sequence files and results are returned in a concise tabular format to allow rapid analysis of retroviral vector integration sites.

Identifying functionally informative evolutionary sequence profiles.

PubMed

Gil, Nelson; Fiser, Andras

2018-04-15

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.

Mycofier: a new machine learning-based classifier for fungal ITS sequences.

PubMed

Delgado-Serrano, Luisa; Restrepo, Silvia; Bustos, Jose Ricardo; Zambrano, Maria Mercedes; Anzola, Juan Manuel

2016-08-11

The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .

A direct method for computing extreme value (Gumbel) parameters for gapped biological sequence alignments.

PubMed

Quinn, Terrance; Sinkala, Zachariah

2014-01-01

We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.

Robust temporal alignment of multimodal cardiac sequences

NASA Astrophysics Data System (ADS)

Perissinotto, Andrea; Queirós, Sandro; Morais, Pedro; Baptista, Maria J.; Monaghan, Mark; Rodrigues, Nuno F.; D'hooge, Jan; Vilaça, João. L.; Barbosa, Daniel

2015-03-01

Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized cross-correlation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates different temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1.6 +/- 1.9% and 4.0 +/- 4.2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.

MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer

PubMed Central

Gauthier, Nicholas Paul; Reznik, Ed; Gao, Jianjiong; Sumer, Selcuk Onur; Schultz, Nikolaus; Sander, Chris; Miller, Martin L.

2016-01-01

The MutationAligner web resource, available at http://www.mutationaligner.org, enables discovery and exploration of somatic mutation hotspots identified in protein domains in currently (mid-2015) more than 5000 cancer patient samples across 22 different tumor types. Using multiple sequence alignments of protein domains in the human genome, we extend the principle of recurrence analysis by aggregating mutations in homologous positions across sets of paralogous genes. Protein domain analysis enhances the statistical power to detect cancer-relevant mutations and links mutations to the specific biological functions encoded in domains. We illustrate how the MutationAligner database and interactive web tool can be used to explore, visualize and analyze mutation hotspots in protein domains across genes and tumor types. We believe that MutationAligner will be an important resource for the cancer research community by providing detailed clues for the functional importance of particular mutations, as well as for the design of functional genomics experiments and for decision support in precision medicine. MutationAligner is slated to be periodically updated to incorporate additional analyses and new data from cancer genomics projects. PMID:26590264

Sequence analysis of the L protein of the Ebola 2014 outbreak: Insight into conserved regions and mutations.

PubMed

Ayub, Gohar; Waheed, Yasir

2016-06-01

The 2014 Ebola outbreak was one of the largest that have occurred; it started in Guinea and spread to Nigeria, Liberia and Sierra Leone. Phylogenetic analysis of the current virus species indicated that this outbreak is the result of a divergent lineage of the Zaire ebolavirus. The L protein of Ebola virus (EBOV) is the catalytic subunit of the RNA‑dependent RNA polymerase complex, which, with VP35, is key for the replication and transcription of viral RNA. Earlier sequence analysis demonstrated that the L protein of all non‑segmented negative‑sense (NNS) RNA viruses consists of six domains containing conserved functional motifs. The aim of the present study was to analyze the presence of these motifs in 2014 EBOV isolates, highlight their function and how they may contribute to the overall pathogenicity of the isolates. For this purpose, 81 2014 EBOV L protein sequences were aligned with 475 other NNS RNA viruses, including Paramyxoviridae and Rhabdoviridae viruses. Phylogenetic analysis of all EBOV outbreak L protein sequences was also performed. Analysis of the amino acid substitutions in the 2014 EBOV outbreak was conducted using sequence analysis. The alignment demonstrated the presence of previously conserved motifs in the 2014 EBOV isolates and novel residues. Notably, all the mutations identified in the 2014 EBOV isolates were tolerant, they were pathogenic with certain examples occurring within previously determined functional conserved motifs, possibly altering viral pathogenicity, replication and virulence. The phylogenetic analysis demonstrated that all sequences with the exception of the 2014 EBOV sequences were clustered together. The 2014 EBOV outbreak has acquired a great number of mutations, which may explain the reasons behind this unprecedented outbreak. Certain residues critical to the function of the polymerase remain conserved and may be targets for the development of antiviral therapeutic agents.

Spreadsheet macros for coloring sequence alignments.

PubMed

Haygood, M G

1993-12-01

This article describes a set of Microsoft Excel macros designed to color amino acid and nucleotide sequence alignments for review and preparation of visual aids. The colored alignments can then be modified to emphasize features of interest. Procedures for importing and coloring sequences are described. The macro file adds a new menu to the menu bar containing sequence-related commands to enable users unfamiliar with Excel to use the macros more readily. The macros were designed for use with Macintosh computers but will also run with the DOS version of Excel.

Validation of Splicing Events in Transcriptome Sequencing Data

PubMed Central

Kaisers, Wolfgang; Ptok, Johannes; Schwender, Holger; Schaal, Heiner

2017-01-01

Genomic alignments of sequenced cellular messenger RNA contain gapped alignments which are interpreted as consequence of intron removal. The resulting gap-sites, genomic locations of alignment gaps, are landmarks representing potential splice-sites. As alignment algorithms report gap-sites with a considerable false discovery rate, validations are required. We describe two quality scores, gap quality score (gqs) and weighted gap information score (wgis), developed for validation of putative splicing events: While gqs solely relies on alignment data wgis additionally considers information from the genomic sequence. FASTQ files obtained from 54 human dermal fibroblast samples were aligned against the human genome (GRCh38) using TopHat and STAR aligner. Statistical properties of gap-sites validated by gqs and wgis were evaluated by their sequence similarity to known exon-intron borders. Within the 54 samples, TopHat identifies 1,000,380 and STAR reports 6,487,577 gap-sites. Due to the lack of strand information, however, the percentage of identified GT-AG gap-sites is rather low. While gap-sites from TopHat contain ≈89% GT-AG, gap-sites from STAR only contain ≈42% GT-AG dinucleotide pairs in merged data from 54 fibroblast samples. Validation with gqs yields 156,251 gap-sites from TopHat alignments and 166,294 from STAR alignments. Validation with wgis yields 770,327 gap-sites from TopHat alignments and 1,065,596 from STAR alignments. Both alignment algorithms, TopHat and STAR, report gap-sites with considerable false discovery rate, which can drastically be reduced by validation with gqs and wgis. PMID:28545234

MUSCLE: multiple sequence alignment with high accuracy and high throughput.

PubMed

Edgar, Robert C

2004-01-01

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zemla, A; Lang, D; Kostova, T

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitatemore » the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position.« less

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

A Mathematical Optimization Problem in Bioinformatics

ERIC Educational Resources Information Center

Heyer, Laurie J.

2008-01-01

This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…

The MIGenAS integrated bioinformatics toolkit for web-based sequence analysis

PubMed Central

Rampp, Markus; Soddemann, Thomas; Lederer, Hermann

2006-01-01

We describe a versatile and extensible integrated bioinformatics toolkit for the analysis of biological sequences over the Internet. The web portal offers convenient interactive access to a growing pool of chainable bioinformatics software tools and databases that are centrally installed and maintained by the RZG. Currently, supported tasks comprise sequence similarity searches in public or user-supplied databases, computation and validation of multiple sequence alignments, phylogenetic analysis and protein–structure prediction. Individual tools can be seamlessly chained into pipelines allowing the user to conveniently process complex workflows without the necessity to take care of any format conversions or tedious parsing of intermediate results. The toolkit is part of the Max-Planck Integrated Gene Analysis System (MIGenAS) of the Max Planck Society available at (click ‘Start Toolkit’). PMID:16844980

SEAN: SNP prediction and display program utilizing EST sequence clusters.

PubMed

Huntley, Derek; Baldo, Angela; Johri, Saurabh; Sergot, Marek

2006-02-15

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data

USGS Publications Warehouse

Miller, Mark P.; Knaus, Brian J.; Mullins, Thomas D.; Haig, Susan M.

2013-01-01

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (SSRs; for example, microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains three analysis modules along with a fourth control module that can be used to automate analyses of large volumes of data. The modules are used to (1) identify the subset of paired-end sequences that pass quality standards, (2) align paired-end reads into a single composite DNA sequence, and (3) identify sequences that possess microsatellites conforming to user specified parameters. Each of the three separate analysis modules also can be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc). All modules are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, Windows). The program suite relies on a compiled Python extension module to perform paired-end alignments. Instructions for compiling the extension from source code are provided in the documentation. Users who do not have Python installed on their computers or who do not have the ability to compile software also may choose to download packaged executable files. These files include all Python scripts, a copy of the compiled extension module, and a minimal installation of Python in a single binary executable. See program documentation for more information.

Mango: multiple alignment with N gapped oligos.

PubMed

Zhang, Zefeng; Lin, Hao; Li, Ming

2008-06-01

Multiple sequence alignment is a classical and challenging task. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state-of-the-art works suffer from the "once a gap, always a gap" phenomenon. Is there a radically new way to do multiple sequence alignment? In this paper, we introduce a novel and orthogonal multiple sequence alignment method, using both multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole and tries to build the alignment vertically, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds have proved significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks, showing that MANGO compares favorably, in both accuracy and speed, against state-of-the-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, ProbConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0, and Kalign 2.0. We have further demonstrated the scalability of MANGO on very large datasets of repeat elements. MANGO can be downloaded at http://www.bioinfo.org.cn/mango/ and is free for academic usage.

Method and apparatus for biological sequence comparison

DOEpatents

Marr, T.G.; Chang, W.I.

1997-12-23

A method and apparatus are disclosed for comparing biological sequences from a known source of sequences, with a subject (query) sequence. The apparatus takes as input a set of target similarity levels (such as evolutionary distances in units of PAM), and finds all fragments of known sequences that are similar to the subject sequence at each target similarity level, and are long enough to be statistically significant. The invention device filters out fragments from the known sequences that are too short, or have a lower average similarity to the subject sequence than is required by each target similarity level. The subject sequence is then compared only to the remaining known sequences to find the best matches. The filtering member divides the subject sequence into overlapping blocks, each block being sufficiently large to contain a minimum-length alignment from a known sequence. For each block, the filter member compares the block with every possible short fragment in the known sequences and determines a best match for each comparison. The determined set of short fragment best matches for the block provide an upper threshold on alignment values. Regions of a certain length from the known sequences that have a mean alignment value upper threshold greater than a target unit score are concatenated to form a union. The current block is compared to the union and provides an indication of best local alignment with the subject sequence. 5 figs.

Method and apparatus for biological sequence comparison

DOEpatents

Marr, Thomas G.; Chang, William I-Wei

1997-01-01

A method and apparatus for comparing biological sequences from a known source of sequences, with a subject (query) sequence. The apparatus takes as input a set of target similarity levels (such as evolutionary distances in units of PAM), and finds all fragments of known sequences that are similar to the subject sequence at each target similarity level, and are long enough to be statistically significant. The invention device filters out fragments from the known sequences that are too short, or have a lower average similarity to the subject sequence than is required by each target similarity level. The subject sequence is then compared only to the remaining known sequences to find the best matches. The filtering member divides the subject sequence into overlapping blocks, each block being sufficiently large to contain a minimum-length alignment from a known sequence. For each block, the filter member compares the block with every possible short fragment in the known sequences and determines a best match for each comparison. The determined set of short fragment best matches for the block provide an upper threshold on alignment values. Regions of a certain length from the known sequences that have a mean alignment value upper threshold greater than a target unit score are concatenated to form a union. The current block is compared to the union and provides an indication of best local alignment with the subject sequence.

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

SW#db: GPU-Accelerated Exact Sequence Similarity Database Search.

PubMed

Korpar, Matija; Šošić, Martin; Blažeka, Dino; Šikić, Mile

2015-01-01

In recent years we have witnessed a growth in sequencing yield, the number of samples sequenced, and as a result-the growth of publicly maintained sequence databases. The increase of data present all around has put high requirements on protein similarity search algorithms with two ever-opposite goals: how to keep the running times acceptable while maintaining a high-enough level of sensitivity. The most time consuming step of similarity search are the local alignments between query and database sequences. This step is usually performed using exact local alignment algorithms such as Smith-Waterman. Due to its quadratic time complexity, alignments of a query to the whole database are usually too slow. Therefore, the majority of the protein similarity search methods prior to doing the exact local alignment apply heuristics to reduce the number of possible candidate sequences in the database. However, there is still a need for the alignment of a query sequence to a reduced database. In this paper we present the SW#db tool and a library for fast exact similarity search. Although its running times, as a standalone tool, are comparable to the running times of BLAST, it is primarily intended to be used for exact local alignment phase in which the database of sequences has already been reduced. It uses both GPU and CPU parallelization and was 4-5 times faster than SSEARCH, 6-25 times faster than CUDASW++ and more than 20 times faster than SSW at the time of writing, using multiple queries on Swiss-prot and Uniref90 databases.

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

PubMed

Fan, Long; Hui, Jerome H L; Yu, Zu Guo; Chu, Ka Hou

2014-07-01

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/. © 2014 John Wiley & Sons Ltd.

Short-read, high-throughput sequencing technology for STR genotyping

PubMed Central

Bornman, Daniel M.; Hester, Mark E.; Schuetter, Jared M.; Kasoji, Manjula D.; Minard-Smith, Angela; Barden, Curt A.; Nelson, Scott C.; Godbold, Gene D.; Baker, Christine H.; Yang, Boyu; Walther, Jacquelyn E.; Tornes, Ivan E.; Yan, Pearlly S.; Rodriguez, Benjamin; Bundschuh, Ralf; Dickens, Michael L.; Young, Brian A.; Faith, Seth A.

2013-01-01

DNA-based methods for human identification principally rely upon genotyping of short tandem repeat (STR) loci. Electrophoretic-based techniques for variable-length classification of STRs are universally utilized, but are limited in that they have relatively low throughput and do not yield nucleotide sequence information. High-throughput sequencing technology may provide a more powerful instrument for human identification, but is not currently validated for forensic casework. Here, we present a systematic method to perform high-throughput genotyping analysis of the Combined DNA Index System (CODIS) STR loci using short-read (150 bp) massively parallel sequencing technology. Open source reference alignment tools were optimized to evaluate PCR-amplified STR loci using a custom designed STR genome reference. Evaluation of this approach demonstrated that the 13 CODIS STR loci and amelogenin (AMEL) locus could be accurately called from individual and mixture samples. Sensitivity analysis showed that as few as 18,500 reads, aligned to an in silico referenced genome, were required to genotype an individual (>99% confidence) for the CODIS loci. The power of this technology was further demonstrated by identification of variant alleles containing single nucleotide polymorphisms (SNPs) and the development of quantitative measurements (reads) for resolving mixed samples. PMID:25621315

Improve homology search sensitivity of PacBio data by correcting frameshifts.

PubMed

Du, Nan; Sun, Yanni

2016-09-01

Single-molecule, real-time sequencing (SMRT) developed by Pacific BioSciences produces longer reads than secondary generation sequencing technologies such as Illumina. The long read length enables PacBio sequencing to close gaps in genome assembly, reveal structural variations, and identify gene isoforms with higher accuracy in transcriptomic sequencing. However, PacBio data has high sequencing error rate and most of the errors are insertion or deletion errors. During alignment-based homology search, insertion or deletion errors in genes will cause frameshifts and may only lead to marginal alignment scores and short alignments. As a result, it is hard to distinguish true alignments from random alignments and the ambiguity will incur errors in structural and functional annotation. Existing frameshift correction tools are designed for data with much lower error rate and are not optimized for PacBio data. As an increasing number of groups are using SMRT, there is an urgent need for dedicated homology search tools for PacBio data. In this work, we introduce Frame-Pro, a profile homology search tool for PacBio reads. Our tool corrects sequencing errors and also outputs the profile alignments of the corrected sequences against characterized protein families. We applied our tool to both simulated and real PacBio data. The results showed that our method enables more sensitive homology search, especially for PacBio data sets of low sequencing coverage. In addition, we can correct more errors when comparing with a popular error correction tool that does not rely on hybrid sequencing. The source code is freely available at https://sourceforge.net/projects/frame-pro/ yannisun@msu.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

HIV Sequence Compendium 2010

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuiken, Carla; Foley, Brian; Leitner, Thomas

This compendium is an annual printed summary of the data contained in the HIV sequence database. In these compendia we try to present a judicious selection of the data in such a way that it is of maximum utility to HIV researchers. Each of the alignments attempts to display the genetic variability within the different species, groups and subtypes of the virus. This compendium contains sequences published before January 1, 2010. Hence, though it is called the 2010 Compendium, its contents correspond to the 2009 curated alignments on our website. The number of sequences in the HIV database is stillmore » increasing exponentially. In total, at the time of printing, there were 339,306 sequences in the HIV Sequence Database, an increase of 45% since last year. The number of near complete genomes (>7000 nucleotides) increased to 2576 by end of 2009, reflecting a smaller increase than in previous years. However, as in previous years, the compendium alignments contain only a small fraction of these. Included in the alignments are a small number of sequences representing each of the subtypes and the more prevalent circulating recombinant forms (CRFs) such as 01 and 02, as well as a few outgroup sequences (group O and N and SIV-CPZ). Of the rarer CRFs we included one representative each. A more complete version of all alignments is available on our website, http://www.hiv.lanl.gov/content/sequence/NEWALIGN/align.html. Reprints are available from our website in the form of both HTML and PDF files. As always, we are open to complaints and suggestions for improvement. Inquiries and comments regarding the compendium should be addressed to seq-info@lanl.gov.« less

Optimization of sequence alignment for simple sequence repeat regions.

PubMed

Jighly, Abdulqader; Hamwieh, Aladdin; Ogbonnaya, Francis C

2011-07-20

Microsatellites, or simple sequence repeats (SSRs), are tandemly repeated DNA sequences, including tandem copies of specific sequences no longer than six bases, that are distributed in the genome. SSR has been used as a molecular marker because it is easy to detect and is used in a range of applications, including genetic diversity, genome mapping, and marker assisted selection. It is also very mutable because of slipping in the DNA polymerase during DNA replication. This unique mutation increases the insertion/deletion (INDELs) mutation frequency to a high ratio - more than other types of molecular markers such as single nucleotide polymorphism (SNPs).SNPs are more frequent than INDELs. Therefore, all designed algorithms for sequence alignment fit the vast majority of the genomic sequence without considering microsatellite regions, as unique sequences that require special consideration. The old algorithm is limited in its application because there are many overlaps between different repeat units which result in false evolutionary relationships. To overcome the limitation of the aligning algorithm when dealing with SSR loci, a new algorithm was developed using PERL script with a Tk graphical interface. This program is based on aligning sequences after determining the repeated units first, and the last SSR nucleotides positions. This results in a shifting process according to the inserted repeated unit type.When studying the phylogenic relations before and after applying the new algorithm, many differences in the trees were obtained by increasing the SSR length and complexity. However, less distance between different linage had been observed after applying the new algorithm. The new algorithm produces better estimates for aligning SSR loci because it reflects more reliable evolutionary relations between different linages. It reduces overlapping during SSR alignment, which results in a more realistic phylogenic relationship.

Assignment of protein sequences to existing domain and family classification systems: Pfam and the PDB

PubMed Central

Dunbrack, Roland L.

2012-01-01

Motivation: Automating the assignment of existing domain and protein family classifications to new sets of sequences is an important task. Current methods often miss assignments because remote relationships fail to achieve statistical significance. Some assignments are not as long as the actual domain definitions because local alignment methods often cut alignments short. Long insertions in query sequences often erroneously result in two copies of the domain assigned to the query. Divergent repeat sequences in proteins are often missed. Results: We have developed a multilevel procedure to produce nearly complete assignments of protein families of an existing classification system to a large set of sequences. We apply this to the task of assigning Pfam domains to sequences and structures in the Protein Data Bank (PDB). We found that HHsearch alignments frequently scored more remotely related Pfams in Pfam clans higher than closely related Pfams, thus, leading to erroneous assignment at the Pfam family level. A greedy algorithm allowing for partial overlaps was, thus, applied first to sequence/HMM alignments, then HMM–HMM alignments and then structure alignments, taking care to join partial alignments split by large insertions into single-domain assignments. Additional assignment of repeat Pfams with weaker E-values was allowed after stronger assignments of the repeat HMM. Our database of assignments, presented in a database called PDBfam, contains Pfams for 99.4% of chains >50 residues. Availability: The Pfam assignment data in PDBfam are available at http://dunbrack2.fccc.edu/ProtCid/PDBfam, which can be searched by PDB codes and Pfam identifiers. They will be updated regularly. Contact: Roland.Dunbracks@fccc.edu PMID:22942020

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment.

PubMed

Warris, Sven; Timal, N Roshan N; Kempenaar, Marcel; Poortinga, Arne M; van de Geest, Henri; Varbanescu, Ana L; Nap, Jan-Peter

2018-01-01

Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python. The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS. pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

CLAST: CUDA implemented large-scale alignment search tool.

PubMed

Yano, Masahiro; Mori, Hiroshi; Akiyama, Yutaka; Yamada, Takuji; Kurokawa, Ken

2014-12-11

Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets. We developed a tool, which we named CLAST (CUDA implemented large-scale alignment search tool), that enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. CLAST has four main advantages over existing alignment tools. First, CLAST was capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy. Third, CLAST does not need a preprocessed sequence database like Burrows-Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases. Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node. CLAST achieved very high speed (similar to the Burrows-Wheeler Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, and FR-HIT) without the need for extensive database preprocessing or a specialized computing platform. Our results demonstrate that CLAST has the potential to be one of the most powerful and realistic approaches to analyze the massive amount of sequence data from next-generation sequencing technologies.

Comparative modeling without implicit sequence alignments.

PubMed

Kolinski, Andrzej; Gront, Dominik

2007-10-01

The number of known protein sequences is about thousand times larger than the number of experimentally solved 3D structures. For more than half of the protein sequences a close or distant structural analog could be identified. The key starting point in a classical comparative modeling is to generate the best possible sequence alignment with a template or templates. With decreasing sequence similarity, the number of errors in the alignments increases and these errors are the main causes of the decreasing accuracy of the molecular models generated. Here we propose a new approach to comparative modeling, which does not require the implicit alignment - the model building phase explores geometric, evolutionary and physical properties of a template (or templates). The proposed method requires prior identification of a template, although the initial sequence alignment is ignored. The model is built using a very efficient reduced representation search engine CABS to find the best possible superposition of the query protein onto the template represented as a 3D multi-featured scaffold. The criteria used include: sequence similarity, predicted secondary structure consistency, local geometric features and hydrophobicity profile. For more difficult cases, the new method qualitatively outperforms existing schemes of comparative modeling. The algorithm unifies de novo modeling, 3D threading and sequence-based methods. The main idea is general and could be easily combined with other efficient modeling tools as Rosetta, UNRES and others.

HIV Sequence Compendium 2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foley, Brian Thomas; Leitner, Thomas Kenneth; Apetrei, Cristian

This compendium is an annual printed summary of the data contained in the HIV sequence database. We try to present a judicious selection of the data in such a way that it is of maximum utility to HIV researchers. Each of the alignments attempts to display the genetic variability within the different species, groups and subtypes of the virus. This compendium contains sequences published before January 1, 2015. Hence, though it is published in 2015 and called the 2015 Compendium, its contents correspond to the 2014 curated alignments on our website. The number of sequences in the HIV database ismore » still increasing. In total, at the end of 2014, there were 624,121 sequences in the HIV Sequence Database, an increase of 7% since the previous year. This is the first year that the number of new sequences added to the database has decreased compared to the previous year. The number of near complete genomes (>7000 nucleotides) increased to 5834 by end of 2014. However, as in previous years, the compendium alignments contain only a fraction of these. A more complete version of all alignments is available on our website, http://www.hiv.lanl.gov/ content/sequence/NEWALIGN/align.html As always, we are open to complaints and suggestions for improvement. Inquiries and comments regarding the compendium should be addressed to seq-info@lanl.gov.« less

Rapid Threat Organism Recognition Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Kelly P.; Solberg, Owen D.; Schoeniger, Joseph S.

2013-05-07

The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on qualitymore » and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.« less

Library preparation and data analysis packages for rapid genome sequencing.

PubMed

Pomraning, Kyle R; Smith, Kristina M; Bredeweg, Erin L; Connolly, Lanelle R; Phatale, Pallavi A; Freitag, Michael

2012-01-01

High-throughput sequencing (HTS) has quickly become a valuable tool for comparative genetics and genomics and is now regularly carried out in laboratories that are not connected to large sequencing centers. Here we describe an updated version of our protocol for constructing single- and paired-end Illumina sequencing libraries, beginning with purified genomic DNA. The present protocol can also be used for "multiplexing," i.e. the analysis of several samples in a single flowcell lane by generating "barcoded" or "indexed" Illumina sequencing libraries in a way that is independent from Illumina-supported methods. To analyze sequencing results, we suggest several independent approaches but end users should be aware that this is a quickly evolving field and that currently many alignment (or "mapping") and counting algorithms are being developed and tested.

PARTS: Probabilistic Alignment for RNA joinT Secondary structure prediction

PubMed Central

Harmanci, Arif Ozgun; Sharma, Gaurav; Mathews, David H.

2008-01-01

A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accomplished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed constraints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP) common secondary structures, sequence alignment and joint posterior probabilities of base pairing are obtained from the model via a dynamic programming algorithm called PARTS. The advantage of the more general structural alignment of PARTS is seen in secondary structure predictions for the RNase P family. For this family, the PARTS MAP predictions of secondary structures and alignment perform significantly better than prior methods that utilize a more restrictive structural alignment model. For the tRNA and 5S rRNA families, the richer structural alignment model of PARTS does not offer a benefit and the method therefore performs comparably with existing alternatives. For all RNA families studied, the posterior probability estimates obtained from PARTS offer an improvement over posterior probability estimates from a single sequence prediction. When considering the base pairings predicted over a threshold value of confidence, the combination of sensitivity and positive predictive value is superior for PARTS than for the single sequence prediction. PARTS source code is available for download under the GNU public license at http://rna.urmc.rochester.edu. PMID:18304945

Is multiple-sequence alignment required for accurate inference of phylogeny?

PubMed

Höhl, Michael; Ragan, Mark A

2007-04-01

The process of inferring phylogenetic trees from molecular sequences almost always starts with a multiple alignment of these sequences but can also be based on methods that do not involve multiple sequence alignment. Very little is known about the accuracy with which such alignment-free methods recover the correct phylogeny or about the potential for increasing their accuracy. We conducted a large-scale comparison of ten alignment-free methods, among them one new approach that does not calculate distances and a faster variant of our pattern-based approach; all distance-based alignment-free methods are freely available from http://www.bioinformatics.org.au (as Python package decaf+py). We show that most methods exhibit a higher overall reconstruction accuracy in the presence of high among-site rate variation. Under all conditions that we considered, variants of the pattern-based approach were significantly better than the other alignment-free methods. The new pattern-based variant achieved a speed-up of an order of magnitude in the distance calculation step, accompanied by a small loss of tree reconstruction accuracy. A method of Bayesian inference from k-mers did not improve on classical alignment-free (and distance-based) methods but may still offer other advantages due to its Bayesian nature. We found the optimal word length k of word-based methods to be stable across various data sets, and we provide parameter ranges for two different alphabets. The influence of these alphabets was analyzed to reveal a trade-off in reconstruction accuracy between long and short branches. We have mapped the phylogenetic accuracy for many alignment-free methods, among them several recently introduced ones, and increased our understanding of their behavior in response to biologically important parameters. In all experiments, the pattern-based approach emerged as superior, at the expense of higher resource consumption. Nonetheless, no alignment-free method that we examined recovers the correct phylogeny as accurately as does an approach based on maximum-likelihood distance estimates of multiply aligned sequences.

Modular and configurable optimal sequence alignment software: Cola.

PubMed

Zamani, Neda; Sundström, Görel; Höppner, Marc P; Grabherr, Manfred G

2014-01-01

The fundamental challenge in optimally aligning homologous sequences is to define a scoring scheme that best reflects the underlying biological processes. Maximising the overall number of matches in the alignment does not always reflect the patterns by which nucleotides mutate. Efficiently implemented algorithms that can be parameterised to accommodate more complex non-linear scoring schemes are thus desirable. We present Cola, alignment software that implements different optimal alignment algorithms, also allowing for scoring contiguous matches of nucleotides in a nonlinear manner. The latter places more emphasis on short, highly conserved motifs, and less on the surrounding nucleotides, which can be more diverged. To illustrate the differences, we report results from aligning 14,100 sequences from 3' untranslated regions of human genes to 25 of their mammalian counterparts, where we found that a nonlinear scoring scheme is more consistent than a linear scheme in detecting short, conserved motifs. Cola is freely available under LPGL from https://github.com/nedaz/cola.

Two Simple and Efficient Algorithms to Compute the SP-Score Objective Function of a Multiple Sequence Alignment.

PubMed

Ranwez, Vincent

2016-01-01

Multiple sequence alignment (MSA) is a crucial step in many molecular analyses and many MSA tools have been developed. Most of them use a greedy approach to construct a first alignment that is then refined by optimizing the sum of pair score (SP-score). The SP-score estimation is thus a bottleneck for most MSA tools since it is repeatedly required and is time consuming. Given an alignment of n sequences and L sites, I introduce here optimized solutions reaching O(nL) time complexity for affine gap cost, instead of O(n2L), which are easy to implement.

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Subset of Kappa and Lambda Germline Sequences Result in Light Chains with a Higher Molecular Mass Phenotype.

PubMed

Barnidge, David R; Lundström, Susanna L; Zhang, Bo; Dasari, Surendra; Murray, David L; Zubarev, Roman A

2015-12-04

In our previous work, we showed that electrospray ionization of intact polyclonal kappa and lambda light chains isolated from normal serum generates two distinct, Gaussian-shaped, molecular mass distributions representing the light-chain repertoire. During the analysis of a large (>100) patient sample set, we noticed a low-intensity molecular mass distribution with a mean of approximately 24 250 Da, roughly 800 Da higher than the mean of the typical kappa molecular-mass distribution mean of 23 450 Da. We also observed distinct clones in this region that did not appear to contain any typical post-translational modifications that would account for such a large mass shift. To determine the origin of the high molecular mass clones, we performed de novo bottom-up mass spectrometry on a purified IgM monoclonal light chain that had a calculated molecular mass of 24 275.03 Da. The entire sequence of the monoclonal light chain was determined using multienzyme digestion and de novo sequence-alignment software and was found to belong to the germline allele IGKV2-30. The alignment of kappa germline sequences revealed ten IGKV2 and one IGKV4 sequences that contained additional amino acids in their CDR1 region, creating the high-molecular-mass phenotype. We also performed an alignment of lambda germline sequences, which showed additional amino acids in the CDR2 region, and the FR3 region of functional germline sequences that result in a high-molecular-mass phenotype. The work presented here illustrates the ability of mass spectrometry to provide information on the diversity of light-chain molecular mass phenotypes in circulation, which reflects the germline sequences selected by the immunoglobulin-secreting B-cell population.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets.

PubMed

Shrimankar, D D; Sathe, S R

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today's supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets

PubMed Central

Shrimankar, D. D.; Sathe, S. R.

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today’s supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures. PMID:27932868

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Fast and accurate phylogeny reconstruction using filtered spaced-word matches

PubMed Central

Sohrabi-Jahromi, Salma; Morgenstern, Burkhard

2017-01-01

Abstract Motivation: Word-based or ‘alignment-free’ algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods. Results: We propose Filtered Spaced Word Matches (FSWM), a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don’t-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don’t-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don’t-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes. Availability and Implementation: The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/ Contact: chris.leimeister@stud.uni-goettingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28073754

Fast and accurate phylogeny reconstruction using filtered spaced-word matches.

PubMed

Leimeister, Chris-André; Sohrabi-Jahromi, Salma; Morgenstern, Burkhard

2017-04-01

Word-based or 'alignment-free' algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods. We propose Filtered Spaced Word Matches (FSWM) , a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don't-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don't-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don't-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes. The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/. chris.leimeister@stud.uni-goettingen.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

SVM-dependent pairwise HMM: an application to protein pairwise alignments.

PubMed

Orlando, Gabriele; Raimondi, Daniele; Khan, Taushif; Lenaerts, Tom; Vranken, Wim F

2017-12-15

Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondary structure, have been used to improve the alignment performances. This is especially relevant for proteins with highly divergent sequences. However, recent works suggest that different features may have different importance in diverse protein classes and it would be an advantage to have more customizable approaches, capable to deal with different alignment definitions. Here we present Rigapollo, a highly flexible pairwise alignment method based on a pairwise HMM-SVM that can use any type of information to build alignments. Rigapollo lets the user decide the optimal features to align their protein class of interest. It outperforms current state of the art methods on two well-known benchmark datasets when aligning highly divergent sequences. A Python implementation of the algorithm is available at http://ibsquare.be/rigapollo. wim.vranken@vub.be. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Statistical alignment: computational properties, homology testing and goodness-of-fit.

PubMed

Hein, J; Wiuf, C; Knudsen, B; Møller, M B; Wibling, G

2000-09-08

The model of insertions and deletions in biological sequences, first formulated by Thorne, Kishino, and Felsenstein in 1991 (the TKF91 model), provides a basis for performing alignment within a statistical framework. Here we investigate this model.Firstly, we show how to accelerate the statistical alignment algorithms several orders of magnitude. The main innovations are to confine likelihood calculations to a band close to the similarity based alignment, to get good initial guesses of the evolutionary parameters and to apply an efficient numerical optimisation algorithm for finding the maximum likelihood estimate. In addition, the recursions originally presented by Thorne, Kishino and Felsenstein can be simplified. Two proteins, about 1500 amino acids long, can be analysed with this method in less than five seconds on a fast desktop computer, which makes this method practical for actual data analysis.Secondly, we propose a new homology test based on this model, where homology means that an ancestor to a sequence pair can be found finitely far back in time. This test has statistical advantages relative to the traditional shuffle test for proteins.Finally, we describe a goodness-of-fit test, that allows testing the proposed insertion-deletion (indel) process inherent to this model and find that real sequences (here globins) probably experience indels longer than one, contrary to what is assumed by the model. Copyright 2000 Academic Press.

Biosynthesis of extracellular and intracellular gold nanoparticles by Aspergillus fumigatus and A. flavus.

PubMed

Gupta, Saurabh; Bector, Shruti

2013-05-01

Green chemistry is a boon for the development of safe, stable and ecofriendly nanostructures using biological tools. The present study was carried out to explore the potential of selected fungal strains for biosynthesis of intra- and extracellular gold nanostructures. Out of the seven cultures, two fungal strains (SBS-3 and SBS-7) were selected on the basis of development of dark pink colour in cell free supernatant and fungal beads, respectively indicative of extra- and intracellular gold nanoparticles production. Both biomass associated and cell free gold nanoparticles were characterized using X-ray diffractogram (XRD) analysis and transmission electron microscopy (TEM). XRD analysis confirmed crystalline, face-centered cubic lattice of metallic gold nanoparticles along with average crystallite size. A marginal difference in average crystallite size of extracellular (17.76 nm) and intracellular (26 and 22 nm) Au-nanostructures was observed using Scherrer equation. In TEM, a variety of shapes (triangles, spherical, hexagonal) were observed in both extra- and intracellular nanoparticles. 18S rRNA gene sequence analysis by multiple sequence alignment (BLAST) indicated 99 % homology of SBS-3 to Aspergillus fumigatus with 99 % alignment coverage and 98 % homology of SBS-7 to Aspergillus flavus with 98 % alignment coverage respectively. Native-PAGE and activity staining further confirmed enzyme linked synthesis of gold nanoparticles.

VCFtoTree: a user-friendly tool to construct locus-specific alignments and phylogenies from thousands of anthropologically relevant genome sequences.

PubMed

Xu, Duo; Jaber, Yousef; Pavlidis, Pavlos; Gokcumen, Omer

2017-09-26

Constructing alignments and phylogenies for a given locus from large genome sequencing studies with relevant outgroups allow novel evolutionary and anthropological insights. However, no user-friendly tool has been developed to integrate thousands of recently available and anthropologically relevant genome sequences to construct complete sequence alignments and phylogenies. Here, we provide VCFtoTree, a user friendly tool with a graphical user interface that directly accesses online databases to download, parse and analyze genome variation data for regions of interest. Our pipeline combines popular sequence datasets and tree building algorithms with custom data parsing to generate accurate alignments and phylogenies using all the individuals from the 1000 Genomes Project, Neanderthal and Denisovan genomes, as well as reference genomes of Chimpanzee and Rhesus Macaque. It can also be applied to other phased human genomes, as well as genomes from other species. The output of our pipeline includes an alignment in FASTA format and a tree file in newick format. VCFtoTree fulfills the increasing demand for constructing alignments and phylogenies for a given loci from thousands of available genomes. Our software provides a user friendly interface for a wider audience without prerequisite knowledge in programming. VCFtoTree can be accessed from https://github.com/duoduoo/VCFtoTree_3.0.0 .

Sequence alignment visualization in HTML5 without Java.

PubMed

Gille, Christoph; Birgit, Weyand; Gille, Andreas

2014-01-01

Java has been extensively used for the visualization of biological data in the web. However, the Java runtime environment is an additional layer of software with an own set of technical problems and security risks. HTML in its new version 5 provides features that for some tasks may render Java unnecessary. Alignment-To-HTML is the first HTML-based interactive visualization for annotated multiple sequence alignments. The server side script interpreter can perform all tasks like (i) sequence retrieval, (ii) alignment computation, (iii) rendering, (iv) identification of a homologous structural models and (v) communication with BioDAS-servers. The rendered alignment can be included in web pages and is displayed in all browsers on all platforms including touch screen tablets. The functionality of the user interface is similar to legacy Java applets and includes color schemes, highlighting of conserved and variable alignment positions, row reordering by drag and drop, interlinked 3D visualization and sequence groups. Novel features are (i) support for multiple overlapping residue annotations, such as chemical modifications, single nucleotide polymorphisms and mutations, (ii) mechanisms to quickly hide residue annotations, (iii) export to MS-Word and (iv) sequence icons. Alignment-To-HTML, the first interactive alignment visualization that runs in web browsers without additional software, confirms that to some extend HTML5 is already sufficient to display complex biological data. The low speed at which programs are executed in browsers is still the main obstacle. Nevertheless, we envision an increased use of HTML and JavaScript for interactive biological software. Under GPL at: http://www.bioinformatics.org/strap/toHTML/.

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

Java bioinformatics analysis web services for multiple sequence alignment--JABAWS:MSA.

PubMed

Troshin, Peter V; Procter, James B; Barton, Geoffrey J

2011-07-15

JABAWS is a web services framework that simplifies the deployment of web services for bioinformatics. JABAWS:MSA provides services for five multiple sequence alignment (MSA) methods (Probcons, T-coffee, Muscle, Mafft and ClustalW), and is the system employed by the Jalview multiple sequence analysis workbench since version 2.6. A fully functional, easy to set up server is provided as a Virtual Appliance (VA), which can be run on most operating systems that support a virtualization environment such as VMware or Oracle VirtualBox. JABAWS is also distributed as a Web Application aRchive (WAR) and can be configured to run on a single computer and/or a cluster managed by Grid Engine, LSF or other queuing systems that support DRMAA. JABAWS:MSA provides clients full access to each application's parameters, allows administrators to specify named parameter preset combinations and execution limits for each application through simple configuration files. The JABAWS command-line client allows integration of JABAWS services into conventional scripts. JABAWS is made freely available under the Apache 2 license and can be obtained from: http://www.compbio.dundee.ac.uk/jabaws.

STELLAR: fast and exact local alignments

PubMed Central

2011-01-01

Background Large-scale comparison of genomic sequences requires reliable tools for the search of local alignments. Practical local aligners are in general fast, but heuristic, and hence sometimes miss significant matches. Results We present here the local pairwise aligner STELLAR that has full sensitivity for ε-alignments, i.e. guarantees to report all local alignments of a given minimal length and maximal error rate. The aligner is composed of two steps, filtering and verification. We apply the SWIFT algorithm for lossless filtering, and have developed a new verification strategy that we prove to be exact. Our results on simulated and real genomic data confirm and quantify the conjecture that heuristic tools like BLAST or BLAT miss a large percentage of significant local alignments. Conclusions STELLAR is very practical and fast on very long sequences which makes it a suitable new tool for finding local alignments between genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows, and Mac OS X at http://www.seqan.de/projects/stellar. The source code is freely distributed with the SeqAn C++ library version 1.3 and later at http://www.seqan.de. PMID:22151882

Functional annotation by sequence-weighted structure alignments: statistical analysis and case studies from the Protein 3000 structural genomics project in Japan.

PubMed

Standley, Daron M; Toh, Hiroyuki; Nakamura, Haruki

2008-09-01

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized. 2008 Wiley-Liss, Inc.

Ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses.

PubMed

Fouquier, Jennifer; Rideout, Jai Ram; Bolyen, Evan; Chase, John; Shiffer, Arron; McDonald, Daniel; Knight, Rob; Caporaso, J Gregory; Kelley, Scott T

2016-02-24

Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child. We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes. The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees. ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .

Analysis Tool Web Services from the EMBL-EBI.

PubMed

McWilliam, Hamish; Li, Weizhong; Uludag, Mahmut; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Cowley, Andrew Peter; Lopez, Rodrigo

2013-07-01

Since 2004 the European Bioinformatics Institute (EMBL-EBI) has provided access to a wide range of databases and analysis tools via Web Services interfaces. This comprises services to search across the databases available from the EMBL-EBI and to explore the network of cross-references present in the data (e.g. EB-eye), services to retrieve entry data in various data formats and to access the data in specific fields (e.g. dbfetch), and analysis tool services, for example, sequence similarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSCLE), pairwise sequence alignment and protein functional analysis (e.g. InterProScan and Phobius). The REST/SOAP Web Services (http://www.ebi.ac.uk/Tools/webservices/) interfaces to these databases and tools allow their integration into other tools, applications, web sites, pipeline processes and analytical workflows. To get users started using the Web Services, sample clients are provided covering a range of programming languages and popular Web Service tool kits, and a brief guide to Web Services technologies, including a set of tutorials, is available for those wishing to learn more and develop their own clients. Users of the Web Services are informed of improvements and updates via a range of methods.

Analysis Tool Web Services from the EMBL-EBI

PubMed Central

McWilliam, Hamish; Li, Weizhong; Uludag, Mahmut; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Cowley, Andrew Peter; Lopez, Rodrigo

2013-01-01

Since 2004 the European Bioinformatics Institute (EMBL-EBI) has provided access to a wide range of databases and analysis tools via Web Services interfaces. This comprises services to search across the databases available from the EMBL-EBI and to explore the network of cross-references present in the data (e.g. EB-eye), services to retrieve entry data in various data formats and to access the data in specific fields (e.g. dbfetch), and analysis tool services, for example, sequence similarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSCLE), pairwise sequence alignment and protein functional analysis (e.g. InterProScan and Phobius). The REST/SOAP Web Services (http://www.ebi.ac.uk/Tools/webservices/) interfaces to these databases and tools allow their integration into other tools, applications, web sites, pipeline processes and analytical workflows. To get users started using the Web Services, sample clients are provided covering a range of programming languages and popular Web Service tool kits, and a brief guide to Web Services technologies, including a set of tutorials, is available for those wishing to learn more and develop their own clients. Users of the Web Services are informed of improvements and updates via a range of methods. PMID:23671338

Revisiting the phylogeny of Zoanthidea (Cnidaria: Anthozoa): Staggered alignment of hypervariable sequences improves species tree inference.

PubMed

Swain, Timothy D

2018-01-01

The recent rapid proliferation of novel taxon identification in the Zoanthidea has been accompanied by a parallel propagation of gene trees as a tool of species discovery, but not a corresponding increase in our understanding of phylogeny. This disparity is caused by the trade-off between the capabilities of automated DNA sequence alignment and data content of genes applied to phylogenetic inference in this group. Conserved genes or segments are easily aligned across the order, but produce poorly resolved trees; hypervariable genes or segments contain the evolutionary signal necessary for resolution and robust support, but sequence alignment is daunting. Staggered alignments are a form of phylogeny-informed sequence alignment composed of a mosaic of local and universal regions that allow phylogenetic inference to be applied to all nucleotides from both hypervariable and conserved gene segments. Comparisons between species tree phylogenies inferred from all data (staggered alignment) and hypervariable-excluded data (standard alignment) demonstrate improved confidence and greater topological agreement with other sources of data for the complete-data tree. This novel phylogeny is the most comprehensive to date (in terms of taxa and data) and can serve as an expandable tool for evolutionary hypothesis testing in the Zoanthidea. Spanish language abstract available in Text S1. Translation by L. O. Swain, DePaul University, Chicago, Illinois, 60604, USA. Copyright © 2017 Elsevier Inc. All rights reserved.

Epidemiological survey of idiopathic scoliosis and sequence alignment analysis of multiple candidate genes.

PubMed

Yang, Tao; Jia, Quanzhang; Guo, Hong; Xu, Jianzhong; Bai, Yun; Yang, Kai; Luo, Fei; Zhang, Zehua; Hou, Tianyong

2012-06-01

To investigate the effects of genetic factors on idiopathic scoliosis (IS) and genetic modes through genetic epidemiological survey on IS in Chongqing City, China, and to determine whether SH3GL1, GADD45B, and FGF22 in the chromosome 19p13.3 are the pathogenic genes of IS through genetic sequence analysis. 214 nuclear families were investigated to analyse the age incidence, familial aggregation, and heritability. SH3GL1, GADD45B, and FGF22 were chosen as candidate genes for mutation screening in 56 IS patients of 214 families. The sequence alignment analysis was performed to determine mutations and predict the protein structure. The average age of onset of 10.8 years suggests that IS is a early onset disease. Incidences of IS in first-, second-, third-degree relatives and the overall incidence in families (5.68%) were also significantly higher than that of the general population (1.04%). The U test indicated a significant difference, suggesting that IS has a familial aggregation. The heritability of first-degree relatives (77.68 ±10.39%), second-degree relatives (69.89 ±3.14%), and third-degree relatives (62.14 ±11.92%) illustrated that genetic factors play an important role in IS pathogenesis. The incidence of first-degree relatives (10.01%), second-degree relatives (2.55%) and third-degree relatives (1.76%) illustrated that IS is not in simple accord with monogenic Mendel's law but manifests as traits of multifactorial hereditary diseases. Sequence alignment of exons of SH3GL1, GADD45B, and FGF22 showed 17 base mutations, of which 16 mutations do not induce open reading frame (ORF) shift or amino acid changes whereas one mutation (C→T)occurred in SH3GL1 results in formation of the termination codon, which induces variation of protein reading frame. Prediction analysis of protein sequence showed that the SH3GL1 mutant encoded a truncated protein, thus affecting the protein structure. IS is a multifactorial genetic disease and SH3GL1 may be one of the pathogenic genes for IS.

Special Focus

PubMed Central

Nawrocki, Eric P.; Burge, Sarah W.

2013-01-01

The development of RNA bioinformatic tools began more than 30 y ago with the description of the Nussinov and Zuker dynamic programming algorithms for single sequence RNA secondary structure prediction. Since then, many tools have been developed for various RNA sequence analysis problems such as homology search, multiple sequence alignment, de novo RNA discovery, read-mapping, and many more. In this issue, we have collected a sampling of reviews and original research that demonstrate some of the many ways bioinformatics is integrated with current RNA biology research. PMID:23948768

SNPServer: a real-time SNP discovery tool.

PubMed

Savage, David; Batley, Jacqueline; Erwin, Tim; Logan, Erica; Love, Christopher G; Lim, Geraldine A C; Mongin, Emmanuel; Barker, Gary; Spangenberg, German C; Edwards, David

2005-07-01

SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at http://hornbill.cspp.latrobe.edu.au/snpdiscovery.html.

GASP: Gapped Ancestral Sequence Prediction for proteins

PubMed Central

Edwards, Richard J; Shields, Denis C

2004-01-01

Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. PMID:15350199

K-mer Content, Correlation, and Position Analysis of Genome DNA Sequences for the Identification of Function and Evolutionary Features

PubMed Central

Sievers, Aaron; Bosiek, Katharina; Bisch, Marc; Dreessen, Chris; Riedel, Jascha; Froß, Patrick; Hausmann, Michael; Hildenbrand, Georg

2017-01-01

In genome analysis, k-mer-based comparison methods have become standard tools. However, even though they are able to deliver reliable results, other algorithms seem to work better in some cases. To improve k-mer-based DNA sequence analysis and comparison, we successfully checked whether adding positional resolution is beneficial for finding and/or comparing interesting organizational structures. A simple but efficient algorithm for extracting and saving local k-mer spectra (frequency distribution of k-mers) was developed and used. The results were analyzed by including positional information based on visualizations as genomic maps and by applying basic vector correlation methods. This analysis was concentrated on small word lengths (1 ≤ k ≤ 4) on relatively small viral genomes of Papillomaviridae and Herpesviridae, while also checking its usability for larger sequences, namely human chromosome 2 and the homologous chromosomes (2A, 2B) of a chimpanzee. Using this alignment-free analysis, several regions with specific characteristics in Papillomaviridae and Herpesviridae formerly identified by independent, mostly alignment-based methods, were confirmed. Correlations between the k-mer content and several genes in these genomes have been found, showing similarities between classified and unclassified viruses, which may be potentially useful for further taxonomic research. Furthermore, unknown k-mer correlations in the genomes of Human Herpesviruses (HHVs), which are probably of major biological function, are found and described. Using the chromosomes of a chimpanzee and human that are currently known, identities between the species on every analyzed chromosome were reproduced. This demonstrates the feasibility of our approach for large data sets of complex genomes. Based on these results, we suggest k-mer analysis with positional resolution as a method for closing a gap between the effectiveness of alignment-based methods (like NCBI BLAST) and the high pace of standard k-mer analysis. PMID:28422050

Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.

PubMed

Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias

2011-01-01

The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

CpG PatternFinder: a Windows-based utility program for easy and rapid identification of the CpG methylation status of DNA.

PubMed

Xu, Yi-Hua; Manoharan, Herbert T; Pitot, Henry C

2007-09-01

The bisulfite genomic sequencing technique is one of the most widely used techniques to study sequence-specific DNA methylation because of its unambiguous ability to reveal DNA methylation status to the order of a single nucleotide. One characteristic feature of the bisulfite genomic sequencing technique is that a number of sample sequence files will be produced from a single DNA sample. The PCR products of bisulfite-treated DNA samples cannot be sequenced directly because they are heterogeneous in nature; therefore they should be cloned into suitable plasmids and then sequenced. This procedure generates an enormous number of sample DNA sequence files as well as adding extra bases belonging to the plasmids to the sequence, which will cause problems in the final sequence comparison. Finding the methylation status for each CpG in each sample sequence is not an easy job. As a result CpG PatternFinder was developed for this purpose. The main functions of the CpG PatternFinder are: (i) to analyze the reference sequence to obtain CpG and non-CpG-C residue position information. (ii) To tailor sample sequence files (delete insertions and mark deletions from the sample sequence files) based on a configuration of ClustalW multiple alignment. (iii) To align sample sequence files with a reference file to obtain bisulfite conversion efficiency and CpG methylation status. And, (iv) to produce graphics, highlighted aligned sequence text and a summary report which can be easily exported to Microsoft Office suite. CpG PatternFinder is designed to operate cooperatively with BioEdit, a freeware on the internet. It can handle up to 100 files of sample DNA sequences simultaneously, and the total CpG pattern analysis process can be finished in minutes. CpG PatternFinder is an ideal software tool for DNA methylation studies to determine the differential methylation pattern in a large number of individuals in a population. Previously we developed the CpG Analyzer program; CpG PatternFinder is our further effort to create software tools for DNA methylation studies.

An intuitive graphical webserver for multiple-choice protein sequence search.

PubMed

Banky, Daniel; Szalkai, Balazs; Grolmusz, Vince

2014-04-10

Every day tens of thousands of sequence searches and sequence alignment queries are submitted to webservers. The capitalized word "BLAST" becomes a verb, describing the act of performing sequence search and alignment. However, if one needs to search for sequences that contain, for example, two hydrophobic and three polar residues at five given positions, the query formation on the most frequently used webservers will be difficult. Some servers support the formation of queries with regular expressions, but most of the users are unfamiliar with their syntax. Here we present an intuitive, easily applicable webserver, the Protein Sequence Analysis server, that allows the formation of multiple choice queries by simply drawing the residues to their positions; if more than one residue are drawn to the same position, then they will be nicely stacked on the user interface, indicating the multiple choice at the given position. This computer-game-like interface is natural and intuitive, and the coloring of the residues makes possible to form queries requiring not just certain amino acids in the given positions, but also small nonpolar, negatively charged, hydrophobic, positively charged, or polar ones. The webserver is available at http://psa.pitgroup.org. Copyright © 2014 Elsevier B.V. All rights reserved.

Reference-guided assembly of four diverse Arabidopsis thaliana genomes

PubMed Central

Schneeberger, Korbinian; Ossowski, Stephan; Ott, Felix; Klein, Juliane D.; Wang, Xi; Lanz, Christa; Smith, Lisa M.; Cao, Jun; Fitz, Joffrey; Warthmann, Norman; Henz, Stefan R.; Huson, Daniel H.; Weigel, Detlef

2011-01-01

We present whole-genome assemblies of four divergent Arabidopsis thaliana strains that complement the 125-Mb reference genome sequence released a decade ago. Using a newly developed reference-guided approach, we assembled large contigs from 9 to 42 Gb of Illumina short-read data from the Landsberg erecta (Ler-1), C24, Bur-0, and Kro-0 strains, which have been sequenced as part of the 1,001 Genomes Project for this species. Using alignments against the reference sequence, we first reduced the complexity of the de novo assembly and later integrated reads without similarity to the reference sequence. As an example, half of the noncentromeric C24 genome was covered by scaffolds that are longer than 260 kb, with a maximum of 2.2 Mb. Moreover, over 96% of the reference genome was covered by the reference-guided assembly, compared with only 87% with a complete de novo assembly. Comparisons with 2 Mb of dideoxy sequence reveal that the per-base error rate of the reference-guided assemblies was below 1 in 10,000. Our assemblies provide a detailed, genomewide picture of large-scale differences between A. thaliana individuals, most of which are difficult to access with alignment-consensus methods only. We demonstrate their practical relevance in studying the expression differences of polymorphic genes and show how the analysis of sRNA sequencing data can lead to erroneous conclusions if aligned against the reference genome alone. Genome assemblies, raw reads, and further information are accessible through http://1001genomes.org/projects/assemblies.html. PMID:21646520

MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer.

PubMed

Gauthier, Nicholas Paul; Reznik, Ed; Gao, Jianjiong; Sumer, Selcuk Onur; Schultz, Nikolaus; Sander, Chris; Miller, Martin L

2016-01-04

The MutationAligner web resource, available at http://www.mutationaligner.org, enables discovery and exploration of somatic mutation hotspots identified in protein domains in currently (mid-2015) more than 5000 cancer patient samples across 22 different tumor types. Using multiple sequence alignments of protein domains in the human genome, we extend the principle of recurrence analysis by aggregating mutations in homologous positions across sets of paralogous genes. Protein domain analysis enhances the statistical power to detect cancer-relevant mutations and links mutations to the specific biological functions encoded in domains. We illustrate how the MutationAligner database and interactive web tool can be used to explore, visualize and analyze mutation hotspots in protein domains across genes and tumor types. We believe that MutationAligner will be an important resource for the cancer research community by providing detailed clues for the functional importance of particular mutations, as well as for the design of functional genomics experiments and for decision support in precision medicine. MutationAligner is slated to be periodically updated to incorporate additional analyses and new data from cancer genomics projects. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Small subunit ribosomal RNA genes of tabanids and hippoboscids (Diptera: Brachycera): evolutionary relationships and comparison with other Diptera.

PubMed

Carreno, R A; Barta, J R

1998-11-01

The small subunit ribosomal RNA (SSU rRNA) genes of hippoboscid (Ornithoica vicina Walker) and tabanid (Chrysops niger Macquart) Diptera were sequenced to determine their phylogenetic position within the order and to determine whether or not extensive hypervariable regions in this gene are widespread in the Diptera. A parsimony analysis of an alignment containing 8 dipteran sequences produced a single most parsimonious tree that placed O. vicina as sister group to Drosophila melanogaster Meigen. The tabanid Chrysops niger was sister group to the asilomorphan taxa, and the sister group to the Brachycera was a Tipula sp. although this relationship was not supported by bootstrap analysis. The hippoboscid and tabanid sequences contain extensive hypervariable regions in the V2, V4, V6, and V7 regions as do other Diptera. When these regions of the alignment were excluded from the phylogenetic analysis, a single most parsimonious tree was found. This tree had an identical overall topology to the tree obtained from the total data set. The hypervariable regions in parts of the dipteran SSU rRNA genes were more extensive in the nematocerous dipteran sequences used in this study than in the other dipteran representatives; these hypervariable regions may be of more utility in inferring relationship among species and subspecies than at the suprageneric level.

JVM: Java Visual Mapping tool for next generation sequencing read.

PubMed

Yang, Ye; Liu, Juan

2015-01-01

We developed a program JVM (Java Visual Mapping) for mapping next generation sequencing read to reference sequence. The program is implemented in Java and is designed to deal with millions of short read generated by sequence alignment using the Illumina sequencing technology. It employs seed index strategy and octal encoding operations for sequence alignments. JVM is useful for DNA-Seq, RNA-Seq when dealing with single-end resequencing. JVM is a desktop application, which supports reads capacity from 1 MB to 10 GB.

RNA-Seq analysis and transcriptome assembly for blackberry (Rubus sp. Var. Lochness) fruit.

PubMed

Garcia-Seco, Daniel; Zhang, Yang; Gutierrez-Mañero, Francisco J; Martin, Cathie; Ramos-Solano, Beatriz

2015-01-22

There is an increasing interest in berries, especially blackberries in the diet, because of recent reports of their health benefits due to their high content of flavonoids. A broad range of genomic tools are available for other Rosaceae species but these tools are still lacking in the Rubus genus, thus limiting gene discovery and the breeding of improved varieties. De novo RNA-seq of ripe blackberries grown under field conditions was performed using Illumina Hiseq 2000. Almost 9 billion nucleotide bases were sequenced in total. Following assembly, 42,062 consensus sequences were detected. For functional annotation, 33,040 (NR), 32,762 (NT), 21,932 (Swiss-Prot), 20,134 (KEGG), 13,676 (COG), 24,168 (GO) consensus sequences were annotated using different databases; in total 34,552 annotated sequences were identified. For protein prediction analysis, the number of coding DNA sequences (CDS) that mapped to the protein database was 32,540. Non redundant (NR), annotation showed that 25,418 genes (73.5%) has the highest similarity with Fragaria vesca subspecies vesca. Reanalysis was undertaken by aligning the reads with this reference genome for a deeper analysis of the transcriptome. We demonstrated that de novo assembly, using Trinity and later annotation with Blast using different databases, were complementary to alignment to the reference sequence using SOAPaligner/SOAP2. The Fragaria reference genome belongs to a species in the same family as blackberry (Rosaceae) but to a different genus. Since blackberries are tetraploids, the possibility of artefactual gene chimeras resulting from mis-assembly was tested with one of the genes sequenced by RNAseq, Chalcone Synthase (CHS). cDNAs encoding this protein were cloned and sequenced. Primers designed to the assembled sequences accurately distinguished different contigs, at least for chalcone synthase genes. We prepared and analysed transcriptome data from ripe blackberries, for which prior genomic information was limited. This new sequence information will improve the knowledge of this important and healthy fruit, providing an invaluable new tool for biological research.

Representation of DNA sequences with virtual potentials and their processing by (SEQREP) Kohonen self-organizing maps.

PubMed

Aires-de-Sousa, João; Aires-de-Sousa, Luisa

2003-01-01

We propose representing individual positions in DNA sequences by virtual potentials generated by other bases of the same sequence. This is a compact representation of the neighbourhood of a base. The distribution of the virtual potentials over the whole sequence can be used as a representation of the entire sequence (SEQREP code). It is a flexible code, with a length independent of the sequence size, does not require previous alignment, and is convenient for processing by neural networks or statistical techniques. To evaluate its biological significance, the SEQREP code was used for training Kohonen self-organizing maps (SOMs) in two applications: (a) detection of Alu sequences, and (b) classification of sequences encoding for HIV-1 envelope glycoprotein (env) into subtypes A-G. It was demonstrated that SOMs clustered sequences belonging to different classes into distinct regions. For independent test sets, very high rates of correct predictions were obtained (97% in the first application, 91% in the second). Possible areas of application of SEQREP codes include functional genomics, phylogenetic analysis, detection of repetitions, database retrieval, and automatic alignment. Software for representing sequences by SEQREP code, and for training Kohonen SOMs is made freely available from http://www.dq.fct.unl.pt/qoa/jas/seqrep. Supplementary material is available at http://www.dq.fct.unl.pt/qoa/jas/seqrep/bioinf2002

ExoLocator--an online view into genetic makeup of vertebrate proteins.

PubMed

Khoo, Aik Aun; Ogrizek-Tomas, Mario; Bulovic, Ana; Korpar, Matija; Gürler, Ece; Slijepcevic, Ivan; Šikic, Mile; Mihalek, Ivana

2014-01-01

ExoLocator (http://exolocator.eopsf.org) collects in a single place information needed for comparative analysis of protein-coding exons from vertebrate species. The main source of data--the genomic sequences, and the existing exon and homology annotation--is the ENSEMBL database of completed vertebrate genomes. To these, ExoLocator adds the search for ostensibly missing exons in orthologous protein pairs across species, using an extensive computational pipeline to narrow down the search region for the candidate exons and find a suitable template in the other species, as well as state-of-the-art implementations of pairwise alignment algorithms. The resulting complements of exons are organized in a way currently unique to ExoLocator: multiple sequence alignments, both on the nucleotide and on the peptide levels, clearly indicating the exon boundaries. The alignments can be inspected in the web-embedded viewer, downloaded or used on the spot to produce an estimate of conservation within orthologous sets, or functional divergence across paralogues.

Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment

PubMed Central

2011-01-01

Background Many Bioinformatics studies begin with a multiple sequence alignment as the foundation for their research. This is because multiple sequence alignment can be a useful technique for studying molecular evolution and analyzing sequence structure relationships. Results In this paper, we have proposed a Vertical Decomposition with Genetic Algorithm (VDGA) for Multiple Sequence Alignment (MSA). In VDGA, we divide the sequences vertically into two or more subsequences, and then solve them individually using a guide tree approach. Finally, we combine all the subsequences to generate a new multiple sequence alignment. This technique is applied on the solutions of the initial generation and of each child generation within VDGA. We have used two mechanisms to generate an initial population in this research: the first mechanism is to generate guide trees with randomly selected sequences and the second is shuffling the sequences inside such trees. Two different genetic operators have been implemented with VDGA. To test the performance of our algorithm, we have compared it with existing well-known methods, namely PRRP, CLUSTALX, DIALIGN, HMMT, SB_PIMA, ML_PIMA, MULTALIGN, and PILEUP8, and also other methods, based on Genetic Algorithms (GA), such as SAGA, MSA-GA and RBT-GA, by solving a number of benchmark datasets from BAliBase 2.0. Conclusions The experimental results showed that the VDGA with three vertical divisions was the most successful variant for most of the test cases in comparison to other divisions considered with VDGA. The experimental results also confirmed that VDGA outperformed the other methods considered in this research. PMID:21867510

Illuminator, a desktop program for mutation detection using short-read clonal sequencing.

PubMed

Carr, Ian M; Morgan, Joanne E; Diggle, Christine P; Sheridan, Eamonn; Markham, Alexander F; Logan, Clare V; Inglehearn, Chris F; Taylor, Graham R; Bonthron, David T

2011-10-01

Current methods for sequencing clonal populations of DNA molecules yield several gigabases of data per day, typically comprising reads of < 100 nt. Such datasets permit widespread genome resequencing and transcriptome analysis or other quantitative tasks. However, this huge capacity can also be harnessed for the resequencing of smaller (gene-sized) target regions, through the simultaneous parallel analysis of multiple subjects, using sample "tagging" or "indexing". These methods promise to have a huge impact on diagnostic mutation analysis and candidate gene testing. Here we describe a software package developed for such studies, offering the ability to resolve pooled samples carrying barcode tags and to align reads to a reference sequence using a mutation-tolerant process. The program, Illuminator, can identify rare sequence variants, including insertions and deletions, and permits interactive data analysis on standard desktop computers. It facilitates the effective analysis of targeted clonal sequencer data without dedicated computational infrastructure or specialized training. Copyright © 2011 Elsevier Inc. All rights reserved.

Sequence Similarity Presenter: a tool for the graphic display of similarities of long sequences for use in presentations.

PubMed

Fröhlich, K U

1994-04-01

A new method for the presentation of alignments of long sequences is described. The degree of identity for the aligned sequences is averaged for sections of a fixed number of residues. The resulting values are converted to shades of gray, with white corresponding to lack of identity and black corresponding to perfect identity. A sequence alignment is represented as a bar filled with varying shades of gray. The display is compact and allows for a fast and intuitive recognition of the distribution of regions with a high similarity. It is well suited for the presentation of alignments of long sequences, e.g. of protein superfamilies, in plenary lectures. The method is implemented as a HyperCard stack for Apple Macintosh computers. Several options for the modification of the output are available (e.g. background reduction, size of the summation window, consideration of amino acid similarity, inclusion of graphic markers to indicate specific domains). The output is a PostScript file which can be printed, imported as EPS or processed further with Adobe Illustrator.

SATCHMO-JS: a webserver for simultaneous protein multiple sequence alignment and phylogenetic tree construction.

PubMed

Hagopian, Raffi; Davidson, John R; Datta, Ruchira S; Samad, Bushra; Jarvis, Glen R; Sjölander, Kimmen

2010-07-01

We present the jump-start simultaneous alignment and tree construction using hidden Markov models (SATCHMO-JS) web server for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic trees. The server takes as input a set of sequences in FASTA format, and outputs a phylogenetic tree and MSA; these can be viewed online or downloaded from the website. SATCHMO-JS is an extension of the SATCHMO algorithm, and employs a divide-and-conquer strategy to jump-start SATCHMO at a higher point in the phylogenetic tree, reducing the computational complexity of the progressive all-versus-all HMM-HMM scoring and alignment. Results on a benchmark dataset of 983 structurally aligned pairs from the PREFAB benchmark dataset show that SATCHMO-JS provides a statistically significant improvement in alignment accuracy over MUSCLE, Multiple Alignment using Fast Fourier Transform (MAFFT), ClustalW and the original SATCHMO algorithm. The SATCHMO-JS webserver is available at http://phylogenomics.berkeley.edu/satchmo-js. The datasets used in these experiments are available for download at http://phylogenomics.berkeley.edu/satchmo-js/supplementary/.

Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data.

PubMed

Li, Peipei; Piao, Yongjun; Shon, Ho Sun; Ryu, Keun Ho

2015-10-28

Recently, rapid improvements in technology and decrease in sequencing costs have made RNA-Seq a widely used technique to quantify gene expression levels. Various normalization approaches have been proposed, owing to the importance of normalization in the analysis of RNA-Seq data. A comparison of recently proposed normalization methods is required to generate suitable guidelines for the selection of the most appropriate approach for future experiments. In this paper, we compared eight non-abundance (RC, UQ, Med, TMM, DESeq, Q, RPKM, and ERPKM) and two abundance estimation normalization methods (RSEM and Sailfish). The experiments were based on real Illumina high-throughput RNA-Seq of 35- and 76-nucleotide sequences produced in the MAQC project and simulation reads. Reads were mapped with human genome obtained from UCSC Genome Browser Database. For precise evaluation, we investigated Spearman correlation between the normalization results from RNA-Seq and MAQC qRT-PCR values for 996 genes. Based on this work, we showed that out of the eight non-abundance estimation normalization methods, RC, UQ, Med, TMM, DESeq, and Q gave similar normalization results for all data sets. For RNA-Seq of a 35-nucleotide sequence, RPKM showed the highest correlation results, but for RNA-Seq of a 76-nucleotide sequence, least correlation was observed than the other methods. ERPKM did not improve results than RPKM. Between two abundance estimation normalization methods, for RNA-Seq of a 35-nucleotide sequence, higher correlation was obtained with Sailfish than that with RSEM, which was better than without using abundance estimation methods. However, for RNA-Seq of a 76-nucleotide sequence, the results achieved by RSEM were similar to without applying abundance estimation methods, and were much better than with Sailfish. Furthermore, we found that adding a poly-A tail increased alignment numbers, but did not improve normalization results. Spearman correlation analysis revealed that RC, UQ, Med, TMM, DESeq, and Q did not noticeably improve gene expression normalization, regardless of read length. Other normalization methods were more efficient when alignment accuracy was low; Sailfish with RPKM gave the best normalization results. When alignment accuracy was high, RC was sufficient for gene expression calculation. And we suggest ignoring poly-A tail during differential gene expression analysis.

Evaluation of microRNA alignment techniques

PubMed Central

Kaspi, Antony; El-Osta, Assam

2016-01-01

Genomic alignment of small RNA (smRNA) sequences such as microRNAs poses considerable challenges due to their short length (∼21 nucleotides [nt]) as well as the large size and complexity of plant and animal genomes. While several tools have been developed for high-throughput mapping of longer mRNA-seq reads (>30 nt), there are few that are specifically designed for mapping of smRNA reads including microRNAs. The accuracy of these mappers has not been systematically determined in the case of smRNA-seq. In addition, it is unknown whether these aligners accurately map smRNA reads containing sequence errors and polymorphisms. By using simulated read sets, we determine the alignment sensitivity and accuracy of 16 short-read mappers and quantify their robustness to mismatches, indels, and nontemplated nucleotide additions. These were explored in the context of a plant genome (Oryza sativa, ∼500 Mbp) and a mammalian genome (Homo sapiens, ∼3.1 Gbp). Analysis of simulated and real smRNA-seq data demonstrates that mapper selection impacts differential expression results and interpretation. These results will inform on best practice for smRNA mapping and enable more accurate smRNA detection and quantification of expression and RNA editing. PMID:27284164

Approximate matching of regular expressions.

PubMed

Myers, E W; Miller, W

1989-01-01

Given a sequence A and regular expression R, the approximate regular expression matching problem is to find a sequence matching R whose optimal alignment with A is the highest scoring of all such sequences. This paper develops an algorithm to solve the problem in time O(MN), where M and N are the lengths of A and R. Thus, the time requirement is asymptotically no worse than for the simpler problem of aligning two fixed sequences. Our method is superior to an earlier algorithm by Wagner and Seiferas in several ways. First, it treats real-valued costs, in addition to integer costs, with no loss of asymptotic efficiency. Second, it requires only O(N) space to deliver just the score of the best alignment. Finally, its structure permits implementation techniques that make it extremely fast in practice. We extend the method to accommodate gap penalties, as required for typical applications in molecular biology, and further refine it to search for sub-strings of A that strongly align with a sequence in R, as required for typical data base searches. We also show how to deliver an optimal alignment between A and R in only O(N + log M) space using O(MN log M) time. Finally, an O(MN(M + N) + N2log N) time algorithm is presented for alignment scoring schemes where the cost of a gap is an arbitrary increasing function of its length.

Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic

PubMed Central

Derkach, Andriy; Chiang, Theodore; Gong, Jiafen; Addis, Laura; Dobbins, Sara; Tomlinson, Ian; Houlston, Richard; Pal, Deb K.; Strug, Lisa J.

2014-01-01

Motivation: Sufficiently powered case–control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. Results: We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the ‘gold standard’ analysis with the true underlying genotypes for both common and rare variants. Availability and implementation: An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. Contact: lisa.strug@utoronto.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24733292

Sequence comparison alignment-free approach based on suffix tree and L-words frequency.

PubMed

Soares, Inês; Goios, Ana; Amorim, António

2012-01-01

The vast majority of methods available for sequence comparison rely on a first sequence alignment step, which requires a number of assumptions on evolutionary history and is sometimes very difficult or impossible to perform due to the abundance of gaps (insertions/deletions). In such cases, an alternative alignment-free method would prove valuable. Our method starts by a computation of a generalized suffix tree of all sequences, which is completed in linear time. Using this tree, the frequency of all possible words with a preset length L-L-words--in each sequence is rapidly calculated. Based on the L-words frequency profile of each sequence, a pairwise standard Euclidean distance is then computed producing a symmetric genetic distance matrix, which can be used to generate a neighbor joining dendrogram or a multidimensional scaling graph. We present an improvement to word counting alignment-free approaches for sequence comparison, by determining a single optimal word length and combining suffix tree structures to the word counting tasks. Our approach is, thus, a fast and simple application that proved to be efficient and powerful when applied to mitochondrial genomes. The algorithm was implemented in Python language and is freely available on the web.

Minimap2: pairwise alignment for nucleotide sequences.

PubMed

Li, Heng

2018-05-10

Recent advances in sequencing technologies promise ultra-long reads of ∼100 kilo bases (kb) in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 mega bases (Mb) in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms. Minimap2 is a general-purpose alignment program to map DNA or long mRNA sequences against a large reference database. It works with accurate short reads of ≥ 100bp in length, ≥1kb genomic reads at error rate ∼15%, full-length noisy Direct RNA or cDNA reads, and assembly contigs or closely related full chromosomes of hundreds of megabases in length. Minimap2 does split-read alignment, employs concave gap cost for long insertions and deletions (INDELs) and introduces new heuristics to reduce spurious alignments. It is 3-4 times as fast as mainstream short-read mappers at comparable accuracy, and is ≥30 times faster than long-read genomic or cDNA mappers at higher accuracy, surpassing most aligners specialized in one type of alignment. https://github.com/lh3/minimap2. hengli@broadinstitute.org.

Evaluating approaches to find exon chains based on long reads.

PubMed

Kuosmanen, Anna; Norri, Tuukka; Mäkinen, Veli

2018-05-01

Transcript prediction can be modeled as a graph problem where exons are modeled as nodes and reads spanning two or more exons are modeled as exon chains. Pacific Biosciences third-generation sequencing technology produces significantly longer reads than earlier second-generation sequencing technologies, which gives valuable information about longer exon chains in a graph. However, with the high error rates of third-generation sequencing, aligning long reads correctly around the splice sites is a challenging task. Incorrect alignments lead to spurious nodes and arcs in the graph, which in turn lead to incorrect transcript predictions. We survey several approaches to find the exon chains corresponding to long reads in a splicing graph, and experimentally study the performance of these methods using simulated data to allow for sensitivity/precision analysis. Our experiments show that short reads from second-generation sequencing can be used to significantly improve exon chain correctness either by error-correcting the long reads before splicing graph creation, or by using them to create a splicing graph on which the long-read alignments are then projected. We also study the memory and time consumption of various modules, and show that accurate exon chains lead to significantly increased transcript prediction accuracy. The simulated data and in-house scripts used for this article are available at http://www.cs.helsinki.fi/group/gsa/exon-chains/exon-chains-bib.tar.bz2.

Genome alignment with graph data structures: a comparison

PubMed Central

2014-01-01

Background Recent advances in rapid, low-cost sequencing have opened up the opportunity to study complete genome sequences. The computational approach of multiple genome alignment allows investigation of evolutionarily related genomes in an integrated fashion, providing a basis for downstream analyses such as rearrangement studies and phylogenetic inference. Graphs have proven to be a powerful tool for coping with the complexity of genome-scale sequence alignments. The potential of graphs to intuitively represent all aspects of genome alignments led to the development of graph-based approaches for genome alignment. These approaches construct a graph from a set of local alignments, and derive a genome alignment through identification and removal of graph substructures that indicate errors in the alignment. Results We compare the structures of commonly used graphs in terms of their abilities to represent alignment information. We describe how the graphs can be transformed into each other, and identify and classify graph substructures common to one or more graphs. Based on previous approaches, we compile a list of modifications that remove these substructures. Conclusion We show that crucial pieces of alignment information, associated with inversions and duplications, are not visible in the structure of all graphs. If we neglect vertex or edge labels, the graphs differ in their information content. Still, many ideas are shared among all graph-based approaches. Based on these findings, we outline a conceptual framework for graph-based genome alignment that can assist in the development of future genome alignment tools. PMID:24712884

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

PubMed

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Phylogeny Reconstruction with Alignment-Free Method That Corrects for Horizontal Gene Transfer.

PubMed

Bromberg, Raquel; Grishin, Nick V; Otwinowski, Zbyszek

2016-06-01

Advances in sequencing have generated a large number of complete genomes. Traditionally, phylogenetic analysis relies on alignments of orthologs, but defining orthologs and separating them from paralogs is a complex task that may not always be suited to the large datasets of the future. An alternative to traditional, alignment-based approaches are whole-genome, alignment-free methods. These methods are scalable and require minimal manual intervention. We developed SlopeTree, a new alignment-free method that estimates evolutionary distances by measuring the decay of exact substring matches as a function of match length. SlopeTree corrects for horizontal gene transfer, for composition variation and low complexity sequences, and for branch-length nonlinearity caused by multiple mutations at the same site. We tested SlopeTree on 495 bacteria, 73 archaea, and 72 strains of Escherichia coli and Shigella. We compared our trees to the NCBI taxonomy, to trees based on concatenated alignments, and to trees produced by other alignment-free methods. The results were consistent with current knowledge about prokaryotic evolution. We assessed differences in tree topology over different methods and settings and found that the majority of bacteria and archaea have a core set of proteins that evolves by descent. In trees built from complete genomes rather than sets of core genes, we observed some grouping by phenotype rather than phylogeny, for instance with a cluster of sulfur-reducing thermophilic bacteria coming together irrespective of their phyla. The source-code for SlopeTree is available at: http://prodata.swmed.edu/download/pub/slopetree_v1/slopetree.tar.gz.

Clustering of reads with alignment-free measures and quality values.

PubMed

Comin, Matteo; Leoni, Andrea; Schimd, Michele

2015-01-01

The data volume generated by Next-Generation Sequencing (NGS) technologies is growing at a pace that is now challenging the storage and data processing capacities of modern computer systems. In this context an important aspect is the reduction of data complexity by collapsing redundant reads in a single cluster to improve the run time, memory requirements, and quality of post-processing steps like assembly and error correction. Several alignment-free measures, based on k-mers counts, have been used to cluster reads. Quality scores produced by NGS platforms are fundamental for various analysis of NGS data like reads mapping and error detection. Moreover future-generation sequencing platforms will produce long reads but with a large number of erroneous bases (up to 15 %). In this scenario it will be fundamental to exploit quality value information within the alignment-free framework. To the best of our knowledge this is the first study that incorporates quality value information and k-mers counts, in the context of alignment-free measures, for the comparison of reads data. Based on this principles, in this paper we present a family of alignment-free measures called D (q) -type. A set of experiments on simulated and real reads data confirms that the new measures are superior to other classical alignment-free statistics, especially when erroneous reads are considered. Also results on de novo assembly and metagenomic reads classification show that the introduction of quality values improves over standard alignment-free measures. These statistics are implemented in a software called QCluster (http://www.dei.unipd.it/~ciompin/main/qcluster.html).

Phylogeny Reconstruction with Alignment-Free Method That Corrects for Horizontal Gene Transfer

PubMed Central

Grishin, Nick V.; Otwinowski, Zbyszek

2016-01-01

Advances in sequencing have generated a large number of complete genomes. Traditionally, phylogenetic analysis relies on alignments of orthologs, but defining orthologs and separating them from paralogs is a complex task that may not always be suited to the large datasets of the future. An alternative to traditional, alignment-based approaches are whole-genome, alignment-free methods. These methods are scalable and require minimal manual intervention. We developed SlopeTree, a new alignment-free method that estimates evolutionary distances by measuring the decay of exact substring matches as a function of match length. SlopeTree corrects for horizontal gene transfer, for composition variation and low complexity sequences, and for branch-length nonlinearity caused by multiple mutations at the same site. We tested SlopeTree on 495 bacteria, 73 archaea, and 72 strains of Escherichia coli and Shigella. We compared our trees to the NCBI taxonomy, to trees based on concatenated alignments, and to trees produced by other alignment-free methods. The results were consistent with current knowledge about prokaryotic evolution. We assessed differences in tree topology over different methods and settings and found that the majority of bacteria and archaea have a core set of proteins that evolves by descent. In trees built from complete genomes rather than sets of core genes, we observed some grouping by phenotype rather than phylogeny, for instance with a cluster of sulfur-reducing thermophilic bacteria coming together irrespective of their phyla. The source-code for SlopeTree is available at: http://prodata.swmed.edu/download/pub/slopetree_v1/slopetree.tar.gz. PMID:27336403

SP-Designer: a user-friendly program for designing species-specific primer pairs from DNA sequence alignments.

PubMed

Villard, Pierre; Malausa, Thibaut

2013-07-01

SP-Designer is an open-source program providing a user-friendly tool for the design of specific PCR primer pairs from a DNA sequence alignment containing sequences from various taxa. SP-Designer selects PCR primer pairs for the amplification of DNA from a target species on the basis of several criteria: (i) primer specificity, as assessed by interspecific sequence polymorphism in the annealing regions, (ii) the biochemical characteristics of the primers and (iii) the intended PCR conditions. SP-Designer generates tables, detailing the primer pair and PCR characteristics, and a FASTA file locating the primer sequences in the original sequence alignment. SP-Designer is Windows-compatible and freely available from http://www2.sophia.inra.fr/urih/sophia_mart/sp_designer/info_sp_designer.php. © 2013 John Wiley & Sons Ltd.

Aligner optimization increases accuracy and decreases compute times in multi-species sequence data.

PubMed

Robinson, Kelly M; Hawkins, Aziah S; Santana-Cruz, Ivette; Adkins, Ricky S; Shetty, Amol C; Nagaraj, Sushma; Sadzewicz, Lisa; Tallon, Luke J; Rasko, David A; Fraser, Claire M; Mahurkar, Anup; Silva, Joana C; Dunning Hotopp, Julie C

2017-09-01

As sequencing technologies have evolved, the tools to analyze these sequences have made similar advances. However, for multi-species samples, we observed important and adverse differences in alignment specificity and computation time for bwa- mem (Burrows-Wheeler aligner-maximum exact matches) relative to bwa-aln. Therefore, we sought to optimize bwa-mem for alignment of data from multi-species samples in order to reduce alignment time and increase the specificity of alignments. In the multi-species cases examined, there was one majority member (i.e. Plasmodium falciparum or Brugia malayi ) and one minority member (i.e. human or the Wolbachia endosymbiont w Bm) of the sequence data. Increasing bwa-mem seed length from the default value reduced the number of read pairs from the majority sequence member that incorrectly aligned to the reference genome of the minority sequence member. Combining both source genomes into a single reference genome increased the specificity of mapping, while also reducing the central processing unit (CPU) time. In Plasmodium , at a seed length of 18 nt, 24.1 % of reads mapped to the human genome using 1.7±0.1 CPU hours, while 83.6 % of reads mapped to the Plasmodium genome using 0.2±0.0 CPU hours (total: 107.7 % reads mapping; in 1.9±0.1 CPU hours). In contrast, 97.1 % of the reads mapped to a combined Plasmodium- human reference in only 0.7±0.0 CPU hours. Overall, the results suggest that combining all references into a single reference database and using a 23 nt seed length reduces the computational time, while maximizing specificity. Similar results were found for simulated sequence reads from a mock metagenomic data set. We found similar improvements to computation time in a publicly available human-only data set.

G-Anchor: a novel approach for whole-genome comparative mapping utilizing evolutionary conserved DNA sequences.

PubMed

Lenis, Vasileios Panagiotis E; Swain, Martin; Larkin, Denis M

2018-05-01

Cross-species whole-genome sequence alignment is a critical first step for genome comparative analyses, ranging from the detection of sequence variants to studies of chromosome evolution. Animal genomes are large and complex, and whole-genome alignment is a computationally intense process, requiring expensive high-performance computing systems due to the need to explore extensive local alignments. With hundreds of sequenced animal genomes available from multiple projects, there is an increasing demand for genome comparative analyses. Here, we introduce G-Anchor, a new, fast, and efficient pipeline that uses a strictly limited but highly effective set of local sequence alignments to anchor (or map) an animal genome to another species' reference genome. G-Anchor makes novel use of a databank of highly conserved DNA sequence elements. We demonstrate how these elements may be aligned to a pair of genomes, creating anchors. These anchors enable the rapid mapping of scaffolds from a de novo assembled genome to chromosome assemblies of a reference species. Our results demonstrate that G-Anchor can successfully anchor a vertebrate genome onto a phylogenetically related reference species genome using a desktop or laptop computer within a few hours and with comparable accuracy to that achieved by a highly accurate whole-genome alignment tool such as LASTZ. G-Anchor thus makes whole-genome comparisons accessible to researchers with limited computational resources. G-Anchor is a ready-to-use tool for anchoring a pair of vertebrate genomes. It may be used with large genomes that contain a significant fraction of evolutionally conserved DNA sequences and that are not highly repetitive, polypoid, or excessively fragmented. G-Anchor is not a substitute for whole-genome aligning software but can be used for fast and accurate initial genome comparisons. G-Anchor is freely available and a ready-to-use tool for the pairwise comparison of two genomes.

The Function of Neuroendocrine Cells in Prostate Cancer

DTIC Science & Technology

2013-04-01

integration site. We then performed deep sequencing and aligned reads to the genome. Our analysis revealed that both histological phenotypes are derived from...lentiviral integration site analysis . (B) Laser capture microdissection was performed on individual glands containing both squamous and...lentiviral integration site analysis . LTR: long terminal repeat (viral DNA), PCR: polymerase chain reaction. (D) Venn diagrams depict shared lentiviral

Application of Quaternion in improving the quality of global sequence alignment scores for an ambiguous sequence target in Streptococcus pneumoniae DNA

NASA Astrophysics Data System (ADS)

Lestari, D.; Bustamam, A.; Novianti, T.; Ardaneswari, G.

2017-07-01

DNA sequence can be defined as a succession of letters, representing the order of nucleotides within DNA, using a permutation of four DNA base codes including adenine (A), guanine (G), cytosine (C), and thymine (T). The precise code of the sequences is determined using DNA sequencing methods and technologies, which have been developed since the 1970s and currently become highly developed, advanced and highly throughput sequencing technologies. So far, DNA sequencing has greatly accelerated biological and medical research and discovery. However, in some cases DNA sequencing could produce any ambiguous and not clear enough sequencing results that make them quite difficult to be determined whether these codes are A, T, G, or C. To solve these problems, in this study we can introduce other representation of DNA codes namely Quaternion Q = (PA, PT, PG, PC), where PA, PT, PG, PC are the probability of A, T, G, C bases that could appear in Q and PA + PT + PG + PC = 1. Furthermore, using Quaternion representations we are able to construct the improved scoring matrix for global sequence alignment processes, by applying a dot product method. Moreover, this scoring matrix produces better and higher quality of the match and mismatch score between two DNA base codes. In implementation, we applied the Needleman-Wunsch global sequence alignment algorithm using Octave, to analyze our target sequence which contains some ambiguous sequence data. The subject sequences are the DNA sequences of Streptococcus pneumoniae families obtained from the Genebank, meanwhile the target DNA sequence are received from our collaborator database. As the results we found the Quaternion representations improve the quality of the sequence alignment score and we can conclude that DNA sequence target has maximum similarity with Streptococcus pneumoniae.

Alignment-Annotator web server: rendering and annotating sequence alignments.

PubMed

Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

2014-07-01

Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Alignment-Annotator web server: rendering and annotating sequence alignments

PubMed Central

Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

2014-01-01

Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. Availability: http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. PMID:24813445

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

PubMed

Jones, David T; Kandathil, Shaun M

2018-04-26

In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-residue contacts, such as solvent accessibility, predicted secondary structure, and scores from other contact prediction methods. It is unclear how much of this information is needed to achieve state-of-the-art results. Here, we show that using deep neural network models, simple alignment statistics contain sufficient information to achieve state-of-the-art precision. Our prediction method, DeepCov, uses fully convolutional neural networks operating on amino-acid pair frequency or covariance data derived directly from sequence alignments, without using global statistical methods such as sparse inverse covariance or pseudolikelihood estimation. Comparisons against CCMpred and MetaPSICOV2 show that using pairwise covariance data calculated from raw alignments as input allows us to match or exceed the performance of both of these methods. Almost all of the achieved precision is obtained when considering relatively local windows (around 15 residues) around any member of a given residue pairing; larger window sizes have comparable performance. Assessment on a set of shallow sequence alignments (fewer than 160 effective sequences) indicates that the new method is substantially more precise than CCMpred and MetaPSICOV2 in this regime, suggesting that improved precision is attainable on smaller sequence families. Overall, the performance of DeepCov is competitive with the state of the art, and our results demonstrate that global models, which employ features from all parts of the input alignment when predicting individual contacts, are not strictly needed in order to attain precise contact predictions. DeepCov is freely available at https://github.com/psipred/DeepCov. d.t.jones@ucl.ac.uk.

Sequence harmony: detecting functional specificity from alignments

PubMed Central

Feenstra, K. Anton; Pirovano, Walter; Krab, Klaas; Heringa, Jaap

2007-01-01

Multiple sequence alignments are often used for the identification of key specificity-determining residues within protein families. We present a web server implementation of the Sequence Harmony (SH) method previously introduced. SH accurately detects subfamily specific positions from a multiple alignment by scoring compositional differences between subfamilies, without imposing conservation. The SH web server allows a quick selection of subtype specific sites from a multiple alignment given a subfamily grouping. In addition, it allows the predicted sites to be directly mapped onto a protein structure and displayed. We demonstrate the use of the SH server using the family of plant mitochondrial alternative oxidases (AOX). In addition, we illustrate the usefulness of combining sequence and structural information by showing that the predicted sites are clustered into a few distinct regions in an AOX homology model. The SH web server can be accessed at www.ibi.vu.nl/programs/seqharmwww. PMID:17584793

Transcriptome Sequencing Revealed Significant Alteration of Cortical Promoter Usage and Splicing in Schizophrenia

PubMed Central

Wu, Jing Qin; Wang, Xi; Beveridge, Natalie J.; Tooney, Paul A.; Scott, Rodney J.; Carr, Vaughan J.; Cairns, Murray J.

2012-01-01

Background While hybridization based analysis of the cortical transcriptome has provided important insight into the neuropathology of schizophrenia, it represents a restricted view of disease-associated gene activity based on predetermined probes. By contrast, sequencing technology can provide un-biased analysis of transcription at nucleotide resolution. Here we use this approach to investigate schizophrenia-associated cortical gene expression. Methodology/Principal Findings The data was generated from 76 bp reads of RNA-Seq, aligned to the reference genome and assembled into transcripts for quantification of exons, splice variants and alternative promoters in postmortem superior temporal gyrus (STG/BA22) from 9 male subjects with schizophrenia and 9 matched non-psychiatric controls. Differentially expressed genes were then subjected to further sequence and functional group analysis. The output, amounting to more than 38 Gb of sequence, revealed significant alteration of gene expression including many previously shown to be associated with schizophrenia. Gene ontology enrichment analysis followed by functional map construction identified three functional clusters highly relevant to schizophrenia including neurotransmission related functions, synaptic vesicle trafficking, and neural development. Significantly, more than 2000 genes displayed schizophrenia-associated alternative promoter usage and more than 1000 genes showed differential splicing (FDR<0.05). Both types of transcriptional isoforms were exemplified by reads aligned to the neurodevelopmentally significant doublecortin-like kinase 1 (DCLK1) gene. Conclusions This study provided the first deep and un-biased analysis of schizophrenia-associated transcriptional diversity within the STG, and revealed variants with important implications for the complex pathophysiology of schizophrenia. PMID:22558445

PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.

PubMed

Thomas, Paul D; Kejariwal, Anish; Campbell, Michael J; Mi, Huaiyu; Diemer, Karen; Guo, Nan; Ladunga, Istvan; Ulitsky-Lazareva, Betty; Muruganujan, Anushya; Rabkin, Steven; Vandergriff, Jody A; Doremieux, Olivier

2003-01-01

The PANTHER database was designed for high-throughput analysis of protein sequences. One of the key features is a simplified ontology of protein function, which allows browsing of the database by biological functions. Biologist curators have associated the ontology terms with groups of protein sequences rather than individual sequences. Statistical models (Hidden Markov Models, or HMMs) are built from each of these groups. The advantage of this approach is that new sequences can be automatically classified as they become available. To ensure accurate functional classification, HMMs are constructed not only for families, but also for functionally distinct subfamilies. Multiple sequence alignments and phylogenetic trees, including curator-assigned information, are available for each family. The current version of the PANTHER database includes training sequences from all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classify gene products across the entire genomes of human, and Drosophila melanogaster. The ontology terms and protein families and subfamilies, as well as Drosophila gene c;assifications, can be browsed and searched for free. Due to outstanding contractual obligations, access to human gene classifications and to protein family trees and multiple sequence alignments will temporarily require a nominal registration fee. PANTHER is publicly available on the web at http://panther.celera.com.

Estimation of a Killer Whale (Orcinus orca) Population’s Diet Using Sequencing Analysis of DNA from Feces

PubMed Central

Ford, Michael J.; Hempelmann, Jennifer; Hanson, M. Bradley; Ayres, Katherine L.; Baird, Robin W.; Emmons, Candice K.; Lundin, Jessica I.; Schorr, Gregory S.; Wasser, Samuel K.; Park, Linda K.

2016-01-01

Estimating diet composition is important for understanding interactions between predators and prey and thus illuminating ecosystem function. The diet of many species, however, is difficult to observe directly. Genetic analysis of fecal material collected in the field is therefore a useful tool for gaining insight into wild animal diets. In this study, we used high-throughput DNA sequencing to quantitatively estimate the diet composition of an endangered population of wild killer whales (Orcinus orca) in their summer range in the Salish Sea. We combined 175 fecal samples collected between May and September from five years between 2006 and 2011 into 13 sample groups. Two known DNA composition control groups were also created. Each group was sequenced at a ~330bp segment of the 16s gene in the mitochondrial genome using an Illumina MiSeq sequencing system. After several quality controls steps, 4,987,107 individual sequences were aligned to a custom sequence database containing 19 potential fish prey species and the most likely species of each fecal-derived sequence was determined. Based on these alignments, salmonids made up >98.6% of the total sequences and thus of the inferred diet. Of the six salmonid species, Chinook salmon made up 79.5% of the sequences, followed by coho salmon (15%). Over all years, a clear pattern emerged with Chinook salmon dominating the estimated diet early in the summer, and coho salmon contributing an average of >40% of the diet in late summer. Sockeye salmon appeared to be occasionally important, at >18% in some sample groups. Non-salmonids were rarely observed. Our results are consistent with earlier results based on surface prey remains, and confirm the importance of Chinook salmon in this population’s summer diet. PMID:26735849

Estimation of a Killer Whale (Orcinus orca) Population's Diet Using Sequencing Analysis of DNA from Feces.

PubMed

Ford, Michael J; Hempelmann, Jennifer; Hanson, M Bradley; Ayres, Katherine L; Baird, Robin W; Emmons, Candice K; Lundin, Jessica I; Schorr, Gregory S; Wasser, Samuel K; Park, Linda K

2016-01-01

Estimating diet composition is important for understanding interactions between predators and prey and thus illuminating ecosystem function. The diet of many species, however, is difficult to observe directly. Genetic analysis of fecal material collected in the field is therefore a useful tool for gaining insight into wild animal diets. In this study, we used high-throughput DNA sequencing to quantitatively estimate the diet composition of an endangered population of wild killer whales (Orcinus orca) in their summer range in the Salish Sea. We combined 175 fecal samples collected between May and September from five years between 2006 and 2011 into 13 sample groups. Two known DNA composition control groups were also created. Each group was sequenced at a ~330bp segment of the 16s gene in the mitochondrial genome using an Illumina MiSeq sequencing system. After several quality controls steps, 4,987,107 individual sequences were aligned to a custom sequence database containing 19 potential fish prey species and the most likely species of each fecal-derived sequence was determined. Based on these alignments, salmonids made up >98.6% of the total sequences and thus of the inferred diet. Of the six salmonid species, Chinook salmon made up 79.5% of the sequences, followed by coho salmon (15%). Over all years, a clear pattern emerged with Chinook salmon dominating the estimated diet early in the summer, and coho salmon contributing an average of >40% of the diet in late summer. Sockeye salmon appeared to be occasionally important, at >18% in some sample groups. Non-salmonids were rarely observed. Our results are consistent with earlier results based on surface prey remains, and confirm the importance of Chinook salmon in this population's summer diet.

Iterative Correction of Reference Nucleotides (iCORN) using second generation sequencing technology.

PubMed

Otto, Thomas D; Sanders, Mandy; Berriman, Matthew; Newbold, Chris

2010-07-15

The accuracy of reference genomes is important for downstream analysis but a low error rate requires expensive manual interrogation of the sequence. Here, we describe a novel algorithm (Iterative Correction of Reference Nucleotides) that iteratively aligns deep coverage of short sequencing reads to correct errors in reference genome sequences and evaluate their accuracy. Using Plasmodium falciparum (81% A + T content) as an extreme example, we show that the algorithm is highly accurate and corrects over 2000 errors in the reference sequence. We give examples of its application to numerous other eukaryotic and prokaryotic genomes and suggest additional applications. The software is available at http://icorn.sourceforge.net

A simple grid implementation with Berkeley Open Infrastructure for Network Computing using BLAST as a model

PubMed Central

Pinthong, Watthanai; Muangruen, Panya

2016-01-01

Development of high-throughput technologies, such as Next-generation sequencing, allows thousands of experiments to be performed simultaneously while reducing resource requirement. Consequently, a massive amount of experiment data is now rapidly generated. Nevertheless, the data are not readily usable or meaningful until they are further analysed and interpreted. Due to the size of the data, a high performance computer (HPC) is required for the analysis and interpretation. However, the HPC is expensive and difficult to access. Other means were developed to allow researchers to acquire the power of HPC without a need to purchase and maintain one such as cloud computing services and grid computing system. In this study, we implemented grid computing in a computer training center environment using Berkeley Open Infrastructure for Network Computing (BOINC) as a job distributor and data manager combining all desktop computers to virtualize the HPC. Fifty desktop computers were used for setting up a grid system during the off-hours. In order to test the performance of the grid system, we adapted the Basic Local Alignment Search Tools (BLAST) to the BOINC system. Sequencing results from Illumina platform were aligned to the human genome database by BLAST on the grid system. The result and processing time were compared to those from a single desktop computer and HPC. The estimated durations of BLAST analysis for 4 million sequence reads on a desktop PC, HPC and the grid system were 568, 24 and 5 days, respectively. Thus, the grid implementation of BLAST by BOINC is an efficient alternative to the HPC for sequence alignment. The grid implementation by BOINC also helped tap unused computing resources during the off-hours and could be easily modified for other available bioinformatics software. PMID:27547555

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

PubMed Central

2010-01-01

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size. PMID:20565983

In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

EPA Science Inventory

The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

MISTICA: Minimum Spanning Tree-based Coarse Image Alignment for Microscopy Image Sequences

PubMed Central

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T.

2016-01-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to re-order the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries. PMID:26415193

MISTICA: Minimum Spanning Tree-Based Coarse Image Alignment for Microscopy Image Sequences.

PubMed

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T

2016-11-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to reorder the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by the way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries.

QuickProbs 2: Towards rapid construction of high-quality alignments of large protein families

PubMed Central

Gudyś, Adam; Deorowicz, Sebastian

2017-01-01

The ever-increasing size of sequence databases caused by the development of high throughput sequencing, poses to multiple alignment algorithms one of the greatest challenges yet. As we show, well-established techniques employed for increasing alignment quality, i.e., refinement and consistency, are ineffective when large protein families are investigated. We present QuickProbs 2, an algorithm for multiple sequence alignment. Based on probabilistic models, equipped with novel column-oriented refinement and selective consistency, it offers outstanding accuracy. When analysing hundreds of sequences, Quick-Probs 2 is noticeably better than ClustalΩ and MAFFT, the previous leaders for processing numerous protein families. In the case of smaller sets, for which consistency-based methods are the best performing, QuickProbs 2 is also superior to the competitors. Due to low computational requirements of selective consistency and utilization of massively parallel architectures, presented algorithm has similar execution times to ClustalΩ, and is orders of magnitude faster than full consistency approaches, like MSAProbs or PicXAA. All these make QuickProbs 2 an excellent tool for aligning families ranging from few, to hundreds of proteins. PMID:28139687

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.

Open Reading Frame Phylogenetic Analysis on the Cloud

PubMed Central

2013-01-01

Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus. PMID:23671843

A novel mutation in PRPF31, causative of autosomal dominant retinitis pigmentosa, using the BGISEQ-500 sequencer.

PubMed

Zheng, Yu; Wang, Hai-Lin; Li, Jian-Kang; Xu, Li; Tellier, Laurent; Li, Xiao-Lin; Huang, Xiao-Yan; Li, Wei; Niu, Tong-Tong; Yang, Huan-Ming; Zhang, Jian-Guo; Liu, Dong-Ning

2018-01-01

To study the genes responsible for retinitis pigmentosa. A total of 15 Chinese families with retinitis pigmentosa, containing 94 sporadically afflicted cases, were recruited. The targeted sequences were captured using the Target_Eye_365_V3 chip and sequenced using the BGISEQ-500 sequencer, according to the manufacturer's instructions. Data were aligned to UCSC Genome Browser build hg19, using the Burroughs Wheeler Aligner MEM algorithm. Local realignment was performed with the Genome Analysis Toolkit (GATK v.3.3.0) IndelRealigner, and variants were called with the Genome Analysis Toolkit Haplotypecaller, without any use of imputation. Variants were filtered against a panel derived from 1000 Genomes Project, 1000G_ASN, ESP6500, ExAC and dbSNP138. In all members of Family ONE and Family TWO with available DNA samples, the genetic variant was validated using Sanger sequencing. A novel, pathogenic variant of retinitis pigmentosa, c.357_358delAA (p.Ser119SerfsX5) was identified in PRPF31 in 2 of 15 autosomal-dominant retinitis pigmentosa (ADRP) families, as well as in one, sporadic case. Sanger sequencing was performed upon probands, as well as upon other family members. This novel, pathogenic genotype co-segregated with retinitis pigmentosa phenotype in these two families. ADRP is a subtype of retinitis pigmentosa, defined by its genotype, which accounts for 20%-40% of the retinitis pigmentosa patients. Our study thus expands the spectrum of PRPF31 mutations known to occur in ADRP, and provides further demonstration of the applicability of the BGISEQ500 sequencer for genomics research.

DNA Barcode Sequence Identification Incorporating Taxonomic Hierarchy and within Taxon Variability

PubMed Central

Little, Damon P.

2011-01-01

For DNA barcoding to succeed as a scientific endeavor an accurate and expeditious query sequence identification method is needed. Although a global multiple–sequence alignment can be generated for some barcoding markers (e.g. COI, rbcL), not all barcoding markers are as structurally conserved (e.g. matK). Thus, algorithms that depend on global multiple–sequence alignments are not universally applicable. Some sequence identification methods that use local pairwise alignments (e.g. BLAST) are unable to accurately differentiate between highly similar sequences and are not designed to cope with hierarchic phylogenetic relationships or within taxon variability. Here, I present a novel alignment–free sequence identification algorithm–BRONX–that accounts for observed within taxon variability and hierarchic relationships among taxa. BRONX identifies short variable segments and corresponding invariant flanking regions in reference sequences. These flanking regions are used to score variable regions in the query sequence without the production of a global multiple–sequence alignment. By incorporating observed within taxon variability into the scoring procedure, misidentifications arising from shared alleles/haplotypes are minimized. An explicit treatment of more inclusive terminals allows for separate identifications to be made for each taxonomic level and/or for user–defined terminals. BRONX performs better than all other methods when there is imperfect overlap between query and reference sequences (e.g. mini–barcode queries against a full–length barcode database). BRONX consistently produced better identifications at the genus–level for all query types. PMID:21857897

Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

PubMed

Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

2016-07-19

Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

The VirusBanker database uses a Java program to allow flexible searching through Bunyaviridae sequences.

PubMed

Fourment, Mathieu; Gibbs, Mark J

2008-02-05

Viruses of the Bunyaviridae have segmented negative-stranded RNA genomes and several of them cause significant disease. Many partial sequences have been obtained from the segments so that GenBank searches give complex results. Sequence databases usually use HTML pages to mediate remote sorting, but this approach can be limiting and may discourage a user from exploring a database. The VirusBanker database contains Bunyaviridae sequences and alignments and is presented as two spreadsheets generated by a Java program that interacts with a MySQL database on a server. Sequences are displayed in rows and may be sorted using information that is displayed in columns and includes data relating to the segment, gene, protein, species, strain, sequence length, terminal sequence and date and country of isolation. Bunyaviridae sequences and alignments may be downloaded from the second spreadsheet with titles defined by the user from the columns, or viewed when passed directly to the sequence editor, Jalview. VirusBanker allows large datasets of aligned nucleotide and protein sequences from the Bunyaviridae to be compiled and winnowed rapidly using criteria that are formulated heuristically.

A novel progesterone receptor membrane component (PGRMC) in the human and swine parasite Taenia solium: implications to the host-parasite relationship.

PubMed

Aguilar-Díaz, Hugo; Nava-Castro, Karen E; Escobedo, Galileo; Domínguez-Ramírez, Lenin; García-Varela, Martín; Del Río-Araiza, Víctor H; Palacios-Arreola, Margarita I; Morales-Montor, Jorge

2018-03-09

We have previously reported that progesterone (P 4 ) has a direct in vitro effect on the scolex evagination and growth of Taenia solium cysticerci. Here, we explored the hypothesis that the P 4 direct effect on T. solium might be mediated by a novel steroid-binding parasite protein. By way of using immunofluorescent confocal microscopy, flow cytometry analysis, double-dimension electrophoresis analysis, and sequencing the corresponding protein spot, we detected a novel PGRMC in T. solium. Molecular modeling studies accompanied by computer docking using the sequenced protein, together with phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is from parasite origin. Our results show that P 4 in vitro increases parasite evagination and scolex size. Using immunofluorescent confocal microscopy, we detected that parasite cells showed expression of a P 4 -binding like protein exclusively located at the cysticercus subtegumental tissue. Presence of the P 4 -binding protein in cyst cells was also confirmed by flow cytometry. Double-dimension electrophoresis analysis, followed by sequencing the corresponding protein spot, revealed a protein that was previously reported in the T. solium genome belonging to a membrane-associated progesterone receptor component (PGRMC). Molecular modeling studies accompanied by computer docking using the sequenced protein showed that PGRMC is potentially able to bind steroid hormones such as progesterone, estradiol, testosterone and dihydrodrotestosterone with different affinities. Phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is related to a steroid-binding protein of Echinoccocus granulosus, both of them being nested within a cluster including similar proteins present in platyhelminths such as Schistocephalus solidus and Schistosoma haematobium. Progesterone may directly act upon T. solium cysticerci probably by binding to PGRMC. This research has implications in the field of host-parasite co-evolution as well as the sex-associated susceptibility to this infection. In a more practical matter, present results may contribute to the molecular design of new drugs with anti-parasite actions.

Non-lethal sampling for the detection of Myxobolus cerebralis in asymptomatic rainbow trout

USGS Publications Warehouse

Schill, Bane; Waldrop, Thomas; Densmore, Christine; Blazer, Vicki

1999-01-01

We have described in previous reports (Schill et al., 1998) the development of a polymerase chain reaction (PCR) amplification of 18S ribosomal RNA for the detection of Myxozoan parasites. Oligonucleotide primers were developed by multiple alignment of Myxozoan sequence information and analysis by a custom-written computer program (PRIM). Candidate pairs of primer sequences were then analyzed for specificity by BLAST (Basic Local Alignment Search Tool). From these, a set of promising primers (MYXFWD and MYXREV) was chosen for further testing. These were chosen because they should direct detection of a number of Myxozoan species (Table 1). PCR using MXYFWD and MYXREV proved to be robust and relatively free of artifact products. Further, we were able to routinely detect Myxobolus cerebralis in fish tissues (Figure 1).

Cover song identification by sequence alignment algorithms

NASA Astrophysics Data System (ADS)

Wang, Chih-Li; Zhong, Qian; Wang, Szu-Ying; Roychowdhury, Vwani

2011-10-01

Content-based music analysis has drawn much attention due to the rapidly growing digital music market. This paper describes a method that can be used to effectively identify cover songs. A cover song is a song that preserves only the crucial melody of its reference song but different in some other acoustic properties. Hence, the beat/chroma-synchronous chromagram, which is insensitive to the variation of the timber or rhythm of songs but sensitive to the melody, is chosen. The key transposition is achieved by cyclically shifting the chromatic domain of the chromagram. By using the Hidden Markov Model (HMM) to obtain the time sequences of songs, the system is made even more robust. Similar structure or length between the cover songs and its reference are not necessary by the Smith-Waterman Alignment Algorithm.

Matrix metalloproteinases: structures, evolution, and diversification.

PubMed

Massova, I; Kotra, L P; Fridman, R; Mobashery, S

1998-09-01

A comprehensive sequence alignment of 64 members of the family of matrix metalloproteinases (MMPs) for the entire sequences, and subsequently the catalytic and the hemopexin-like domains, have been performed. The 64 MMPs were selected from plants, invertebrates, and vertebrates. The analyses disclosed that as many as 23 distinct subfamilies of these proteins are known to exist. Information from the sequence alignments was correlated with structures, both crystallographic as well as computational, of the catalytic domains for the 23 representative members of the MMP family. A survey of the metal binding sites and two loops containing variable sequences of amino acids, which are important for substrate interactions, are discussed. The collective data support the proposal that the assembly of the domains into multidomain enzymes was likely to be an early evolutionary event. This was followed by diversification, perhaps in parallel among the MMPs, in a subsequent evolutionary time scale. Analysis indicates that a retrograde structure simplification may have accounted for the evolution of MMPs with simple domain constituents, such as matrilysin, from the larger and more elaborate enzymes.

RNAcode: Robust discrimination of coding and noncoding regions in comparative sequence data

PubMed Central

Washietl, Stefan; Findeiß, Sven; Müller, Stephan A.; Kalkhof, Stefan; von Bergen, Martin; Hofacker, Ivo L.; Stadler, Peter F.; Goldman, Nick

2011-01-01

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied “out of the box,” without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as “noncoding.” RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode. PMID:21357752

RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data.

PubMed

Washietl, Stefan; Findeiss, Sven; Müller, Stephan A; Kalkhof, Stefan; von Bergen, Martin; Hofacker, Ivo L; Stadler, Peter F; Goldman, Nick

2011-04-01

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied "out of the box," without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as "noncoding." RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.

ChromatoGate: A Tool for Detecting Base Mis-Calls in Multiple Sequence Alignments by Semi-Automatic Chromatogram Inspection

PubMed Central

Alachiotis, Nikolaos; Vogiatzi, Emmanouella; Pavlidis, Pavlos; Stamatakis, Alexandros

2013-01-01

Automated DNA sequencers generate chromatograms that contain raw sequencing data. They also generate data that translates the chromatograms into molecular sequences of A, C, G, T, or N (undetermined) characters. Since chromatogram translation programs frequently introduce errors, a manual inspection of the generated sequence data is required. As sequence numbers and lengths increase, visual inspection and manual correction of chromatograms and corresponding sequences on a per-peak and per-nucleotide basis becomes an error-prone, time-consuming, and tedious process. Here, we introduce ChromatoGate (CG), an open-source software that accelerates and partially automates the inspection of chromatograms and the detection of sequencing errors for bidirectional sequencing runs. To provide users full control over the error correction process, a fully automated error correction algorithm has not been implemented. Initially, the program scans a given multiple sequence alignment (MSA) for potential sequencing errors, assuming that each polymorphic site in the alignment may be attributed to a sequencing error with a certain probability. The guided MSA assembly procedure in ChromatoGate detects chromatogram peaks of all characters in an alignment that lead to polymorphic sites, given a user-defined threshold. The threshold value represents the sensitivity of the sequencing error detection mechanism. After this pre-filtering, the user only needs to inspect a small number of peaks in every chromatogram to correct sequencing errors. Finally, we show that correcting sequencing errors is important, because population genetic and phylogenetic inferences can be misled by MSAs with uncorrected mis-calls. Our experiments indicate that estimates of population mutation rates can be affected two- to three-fold by uncorrected errors. PMID:24688709

ChromatoGate: A Tool for Detecting Base Mis-Calls in Multiple Sequence Alignments by Semi-Automatic Chromatogram Inspection.

PubMed

Alachiotis, Nikolaos; Vogiatzi, Emmanouella; Pavlidis, Pavlos; Stamatakis, Alexandros

2013-01-01

Automated DNA sequencers generate chromatograms that contain raw sequencing data. They also generate data that translates the chromatograms into molecular sequences of A, C, G, T, or N (undetermined) characters. Since chromatogram translation programs frequently introduce errors, a manual inspection of the generated sequence data is required. As sequence numbers and lengths increase, visual inspection and manual correction of chromatograms and corresponding sequences on a per-peak and per-nucleotide basis becomes an error-prone, time-consuming, and tedious process. Here, we introduce ChromatoGate (CG), an open-source software that accelerates and partially automates the inspection of chromatograms and the detection of sequencing errors for bidirectional sequencing runs. To provide users full control over the error correction process, a fully automated error correction algorithm has not been implemented. Initially, the program scans a given multiple sequence alignment (MSA) for potential sequencing errors, assuming that each polymorphic site in the alignment may be attributed to a sequencing error with a certain probability. The guided MSA assembly procedure in ChromatoGate detects chromatogram peaks of all characters in an alignment that lead to polymorphic sites, given a user-defined threshold. The threshold value represents the sensitivity of the sequencing error detection mechanism. After this pre-filtering, the user only needs to inspect a small number of peaks in every chromatogram to correct sequencing errors. Finally, we show that correcting sequencing errors is important, because population genetic and phylogenetic inferences can be misled by MSAs with uncorrected mis-calls. Our experiments indicate that estimates of population mutation rates can be affected two- to three-fold by uncorrected errors.

Unexpected effects of different genetic backgrounds on identification of genomic rearrangements via whole-genome next generation sequencing.

PubMed

Chen, Zhangguo; Gowan, Katherine; Leach, Sonia M; Viboolsittiseri, Sawanee S; Mishra, Ameet K; Kadoishi, Tanya; Diener, Katrina; Gao, Bifeng; Jones, Kenneth; Wang, Jing H

2016-10-21

Whole genome next generation sequencing (NGS) is increasingly employed to detect genomic rearrangements in cancer genomes, especially in lymphoid malignancies. We recently established a unique mouse model by specifically deleting a key non-homologous end-joining DNA repair gene, Xrcc4, and a cell cycle checkpoint gene, Trp53, in germinal center B cells. This mouse model spontaneously develops mature B cell lymphomas (termed G1XP lymphomas). Here, we attempt to employ whole genome NGS to identify novel structural rearrangements, in particular inter-chromosomal translocations (CTXs), in these G1XP lymphomas. We sequenced six lymphoma samples, aligned our NGS data with mouse reference genome (in C57BL/6J (B6) background) and identified CTXs using CREST algorithm. Surprisingly, we detected widespread CTXs in both lymphomas and wildtype control samples, majority of which were false positive and attributable to different genetic backgrounds. In addition, we validated our NGS pipeline by sequencing multiple control samples from distinct tissues of different genetic backgrounds of mouse (B6 vs non-B6). Lastly, our studies showed that widespread false positive CTXs can be generated by simply aligning sequences from different genetic backgrounds of mouse. We conclude that mapping and alignment with reference genome might not be a preferred method for analyzing whole-genome NGS data obtained from a genetic background different from reference genome. Given the complex genetic background of different mouse strains or the heterogeneity of cancer genomes in human patients, in order to minimize such systematic artifacts and uncover novel CTXs, a preferred method might be de novo assembly of personalized normal control genome and cancer cell genome, instead of mapping and aligning NGS data to mouse or human reference genome. Thus, our studies have critical impact on the manner of data analysis for cancer genomics.

Molecular analysis of the human faecal archaea in a southern Indian population.

PubMed

Rani, Sandya B; Balamurugan, Ramadass; Ramakrishna, Balakrishnan S

2017-03-01

Archaea are an important constituent of the human gut microbiota, but there is no information on human gut archaea in an Indian population. In this study, faecal samples were obtained from different age groups (neonatal babies, preschool children, school-going children, adolescents, adults and elderly) of a southern Indian population, and from a tribal population also resident in southern India). 16S rRNA gene sequences specific to Archaea were amplified from pooled faecal DNA in each group, sequenced, and aligned against the NCBI database. Of the 806 adequate sequences in the study, most aligned with 22 known sequences. There were 9 novel sequences in the present study. All sequences were deposited in the GenBank nucleotide sequence database with the following accession numbers: KF607113 - KF607918. Methanobrevibacter was the most prevalent genus among all the age groups accounting for 98% in neonates, 96% in post-weaning, and 100% each in preschool, school and adult population. In the elderly, Methanobrevibacter accounted for 96% and in tribal adults, 99% of the clones belonged to Methanobrevibacter genus. Other genera detected included Caldisphaera, Halobaculum, Methanosphaeraand Thermogymnomonas. Methanobrevibacter smithii predominated in all age groups, accounting for 749 (92.9%) of the 806 sequences. Archaea can be found in the faeces of southern Indian residents immediately after birth. Methanobrevibacter smithii was the dominant faecal archeon in all age groups, with other genera being found at the extremes of age.

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

A transcriptome resource for the koala (Phascolarctos cinereus): insights into koala retrovirus transcription and sequence diversity.

PubMed

Hobbs, Matthew; Pavasovic, Ana; King, Andrew G; Prentis, Peter J; Eldridge, Mark D B; Chen, Zhiliang; Colgan, Donald J; Polkinghorne, Adam; Wilkins, Marc R; Flanagan, Cheyne; Gillett, Amber; Hanger, Jon; Johnson, Rebecca N; Timms, Peter

2014-09-11

The koala, Phascolarctos cinereus, is a biologically unique and evolutionarily distinct Australian arboreal marsupial. The goal of this study was to sequence the transcriptome from several tissues of two geographically separate koalas, and to create the first comprehensive catalog of annotated transcripts for this species, enabling detailed analysis of the unique attributes of this threatened native marsupial, including infection by the koala retrovirus. RNA-Seq data was generated from a range of tissues from one male and one female koala and assembled de novo into transcripts using Velvet-Oases. Transcript abundance in each tissue was estimated. Transcripts were searched for likely protein-coding regions and a non-redundant set of 117,563 putative protein sequences was produced. In similarity searches there were 84,907 (72%) sequences that aligned to at least one sequence in the NCBI nr protein database. The best alignments were to sequences from other marsupials. After applying a reciprocal best hit requirement of koala sequences to those from tammar wallaby, Tasmanian devil and the gray short-tailed opossum, we estimate that our transcriptome dataset represents approximately 15,000 koala genes. The marsupial alignment information was used to look for potential gene duplications and we report evidence for copy number expansion of the alpha amylase gene, and of an aldehyde reductase gene.Koala retrovirus (KoRV) transcripts were detected in the transcriptomes. These were analysed in detail and the structure of the spliced envelope gene transcript was determined. There was appreciable sequence diversity within KoRV, with 233 sites in the KoRV genome showing small insertions/deletions or single nucleotide polymorphisms. Both koalas had sequences from the KoRV-A subtype, but the male koala transcriptome has, in addition, sequences more closely related to the KoRV-B subtype. This is the first report of a KoRV-B-like sequence in a wild population. This transcriptomic dataset is a useful resource for molecular genetic studies of the koala, for evolutionary genetic studies of marsupials, for validation and annotation of the koala genome sequence, and for investigation of koala retrovirus. Annotated transcripts can be browsed and queried at http://koalagenome.org.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

The identification of complete domains within protein sequences using accurate E-values for semi-global alignment

PubMed Central

Kann, Maricel G.; Sheetlin, Sergey L.; Park, Yonil; Bryant, Stephen H.; Spouge, John L.

2007-01-01

The sequencing of complete genomes has created a pressing need for automated annotation of gene function. Because domains are the basic units of protein function and evolution, a gene can be annotated from a domain database by aligning domains to the corresponding protein sequence. Ideally, complete domains are aligned to protein subsequences, in a ‘semi-global alignment’. Local alignment, which aligns pieces of domains to subsequences, is common in high-throughput annotation applications, however. It is a mature technique, with the heuristics and accurate E-values required for screening large databases and evaluating the screening results. Hidden Markov models (HMMs) provide an alternative theoretical framework for semi-global alignment, but their use is limited because they lack heuristic acceleration and accurate E-values. Our new tool, GLOBAL, overcomes some limitations of previous semi-global HMMs: it has accurate E-values and the possibility of the heuristic acceleration required for high-throughput applications. Moreover, according to a standard of truth based on protein structure, two semi-global HMM alignment tools (GLOBAL and HMMer) had comparable performance in identifying complete domains, but distinctly outperformed two tools based on local alignment. When searching for complete protein domains, therefore, GLOBAL avoids disadvantages commonly associated with HMMs, yet maintains their superior retrieval performance. PMID:17596268

Improving pairwise comparison of protein sequences with domain co-occurrence

PubMed Central

Gascuel, Olivier

2018-01-01

Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence PMID:29293498

Acceleration of the Smith-Waterman algorithm using single and multiple graphics processors

NASA Astrophysics Data System (ADS)

Khajeh-Saeed, Ali; Poole, Stephen; Blair Perot, J.

2010-06-01

Finding regions of similarity between two very long data streams is a computationally intensive problem referred to as sequence alignment. Alignment algorithms must allow for imperfect sequence matching with different starting locations and some gaps and errors between the two data sequences. Perhaps the most well known application of sequence matching is the testing of DNA or protein sequences against genome databases. The Smith-Waterman algorithm is a method for precisely characterizing how well two sequences can be aligned and for determining the optimal alignment of those two sequences. Like many applications in computational science, the Smith-Waterman algorithm is constrained by the memory access speed and can be accelerated significantly by using graphics processors (GPUs) as the compute engine. In this work we show that effective use of the GPU requires a novel reformulation of the Smith-Waterman algorithm. The performance of this new version of the algorithm is demonstrated using the SSCA#1 (Bioinformatics) benchmark running on one GPU and on up to four GPUs executing in parallel. The results indicate that for large problems a single GPU is up to 45 times faster than a CPU for this application, and the parallel implementation shows linear speed up on up to 4 GPUs.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks*

PubMed Central

Bandeira, Nuno

2016-01-01

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software. PMID:27609420

Whale song analyses using bioinformatics sequence analysis approaches

NASA Astrophysics Data System (ADS)

Chen, Yian A.; Almeida, Jonas S.; Chou, Lien-Siang

2005-04-01

Animal songs are frequently analyzed using discrete hierarchical units, such as units, themes and songs. Because animal songs and bio-sequences may be understood as analogous, bioinformatics analysis tools DNA/protein sequence alignment and alignment-free methods are proposed to quantify the theme similarities of the songs of false killer whales recorded off northeast Taiwan. The eighteen themes with discrete units that were identified in an earlier study [Y. A. Chen, masters thesis, University of Charleston, 2001] were compared quantitatively using several distance metrics. These metrics included the scores calculated using the Smith-Waterman algorithm with the repeated procedure; the standardized Euclidian distance and the angle metrics based on word frequencies. The theme classifications based on different metrics were summarized and compared in dendrograms using cluster analyses. The results agree with earlier classifications derived by human observation qualitatively. These methods further quantify the similarities among themes. These methods could be applied to the analyses of other animal songs on a larger scale. For instance, these techniques could be used to investigate song evolution and cultural transmission quantifying the dissimilarities of humpback whale songs across different seasons, years, populations, and geographic regions. [Work supported by SC Sea Grant, and Ilan County Government, Taiwan.

Genotyping-by-sequencing enables linkage mapping in three octoploid cultivated strawberry families

PubMed Central

Salinas, Natalia; Tennessen, Jacob A.; Zurn, Jason D.; Sargent, Daniel James; Hancock, James; Bassil, Nahla V.

2017-01-01

Genotyping-by-sequencing (GBS) was used to survey genome-wide single-nucleotide polymorphisms (SNPs) in three biparental strawberry (Fragaria × ananassa) populations with the goal of evaluating this technique in a species with a complex octoploid genome. GBS sequence data were aligned to the F. vesca ‘Fvb’ reference genome in order to call SNPs. Numbers of polymorphic SNPs per population ranged from 1,163 to 3,190. Linkage maps consisting of 30–65 linkage groups were produced from the SNP sets derived from each parent. The linkage groups covered 99% of the Fvb reference genome, with three to seven linkage groups from a given parent aligned to any particular chromosome. A phylogenetic analysis performed using the POLiMAPS pipeline revealed linkage groups that were most similar to ancestral species F. vesca for each chromosome. Linkage groups that were most similar to a second ancestral species, F. iinumae, were only resolved for Fvb 4. The quantity of missing data and heterogeneity in genome coverage inherent in GBS complicated the analysis, but POLiMAPS resolved F. × ananassa chromosomal regions derived from diploid ancestor F. vesca. PMID:28875078

Genomic characterization and taxonomic position of a rhabdovirus from a hybrid snakehead.

PubMed

Zeng, Weiwei; Wang, Qing; Wang, Yingying; Liu, Cun; Liang, Hongru; Fang, Xiang; Wu, Shuqin

2014-09-01

A new rhabdovirus, tentatively designated as hybrid snakehead rhabdovirus C1207 (HSHRV-C1207), was first isolated from a moribund hybrid snakehead (Channa maculata×Channa argus) in China. We present the complete genome sequence of HSHRV-C1207 and a comprehensive sequence comparison between HSHRV-C1207 and other rhabdoviruses. Sequence alignment and phylogenetic analysis revealed that HSHRV-C1207 shared the highest degree of homology with Monopterus albus rhabdovirus and Siniperca chuatsi rhabdovirus. All three viruses clustered into a single group that was distinct from the recognized genera in the family Rhabdoviridae. Our analysis suggests that HSHRV-C1207, as well as MARV and SCRV, should be assigned to a new rhabdovirus genus.

An improved model for whole genome phylogenetic analysis by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees and demonstrates that the improved DFT dissimilarity measure is an efficient and effective similarity measure of DNA sequences. Due to its high efficiency and accuracy, the proposed DFT similarity measure is successfully applied on phylogenetic analysis for individual genes and large whole bacterial genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

DCODE.ORG Anthology of Comparative Genomic Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loots, G G; Ovcharenko, I

2005-01-11

Comparative genomics provides the means to demarcate functional regions in anonymous DNA sequences. The successful application of this method to identifying novel genes is currently shifting to deciphering the noncoding encryption of gene regulation across genomes. To facilitate the use of comparative genomics to practical applications in genetics and genomics we have developed several analytical and visualization tools for the analysis of arbitrary sequences and whole genomes. These tools include two alignment tools: zPicture and Mulan; a phylogenetic shadowing tool: eShadow for identifying lineage- and species-specific functional elements; two evolutionary conserved transcription factor analysis tools: rVista and multiTF; a toolmore » for extracting cis-regulatory modules governing the expression of co-regulated genes, CREME; and a dynamic portal to multiple vertebrate and invertebrate genome alignments, the ECR Browser. Here we briefly describe each one of these tools and provide specific examples on their practical applications. All the tools are publicly available at the http://www.dcode.org/ web site.« less

New Insight Into the Diversity of SemiSWEET Sugar Transporters and the Homologs in Prokaryotes

PubMed Central

Jia, Baolei; Hao, Lujiang; Xuan, Yuan Hu; Jeon, Che Ok

2018-01-01

Sugars will eventually be exported transporters (SWEETs) and SemiSWEETs represent a family of sugar transporters in eukaryotes and prokaryotes, respectively. SWEETs contain seven transmembrane helices (TMHs), while SemiSWEETs contain three. The functions of SemiSWEETs are less studied. In this perspective article, we analyzed the diversity and conservation of SemiSWEETs and further proposed the possible functions. 1,922 SemiSWEET homologs were retrieved from the UniProt database, which is not proportional to the sequenced prokaryotic genomes. However, these proteins are very diverse in sequences and can be classified into 19 clusters when >50% sequence identity is required. Moreover, a gene context analysis indicated that several SemiSWEETs are located in the operons that are related to diverse carbohydrate metabolism. Several proteins with seven TMHs can be found in bacteria, and sequence alignment suggested that these proteins in bacteria may be formed by the duplication and fusion. Multiple sequence alignments showed that the amino acids for sugar translocation are still conserved and coevolved, although the sequences show diversity. Among them, the functions of a few amino acids are still not clear. These findings highlight the challenges that exist in SemiSWEETs and provide future researchers the foundation to explore these uncharted areas. PMID:29872447

New Insight Into the Diversity of SemiSWEET Sugar Transporters and the Homologs in Prokaryotes.

PubMed

Jia, Baolei; Hao, Lujiang; Xuan, Yuan Hu; Jeon, Che Ok

2018-01-01

Sugars will eventually be exported transporters (SWEETs) and SemiSWEETs represent a family of sugar transporters in eukaryotes and prokaryotes, respectively. SWEETs contain seven transmembrane helices (TMHs), while SemiSWEETs contain three. The functions of SemiSWEETs are less studied. In this perspective article, we analyzed the diversity and conservation of SemiSWEETs and further proposed the possible functions. 1,922 SemiSWEET homologs were retrieved from the UniProt database, which is not proportional to the sequenced prokaryotic genomes. However, these proteins are very diverse in sequences and can be classified into 19 clusters when >50% sequence identity is required. Moreover, a gene context analysis indicated that several SemiSWEETs are located in the operons that are related to diverse carbohydrate metabolism. Several proteins with seven TMHs can be found in bacteria, and sequence alignment suggested that these proteins in bacteria may be formed by the duplication and fusion. Multiple sequence alignments showed that the amino acids for sugar translocation are still conserved and coevolved, although the sequences show diversity. Among them, the functions of a few amino acids are still not clear. These findings highlight the challenges that exist in SemiSWEETs and provide future researchers the foundation to explore these uncharted areas.

Bioinformatic Workflows for Generating Complete Plastid Genome Sequences-An Example from Cabomba (Cabombaceae) in the Context of the Phylogenomic Analysis of the Water-Lily Clade.

PubMed

Gruenstaeudl, Michael; Gerschler, Nico; Borsch, Thomas

2018-06-21

The sequencing and comparison of plastid genomes are becoming a standard method in plant genomics, and many researchers are using this approach to infer plant phylogenetic relationships. Due to the widespread availability of next-generation sequencing, plastid genome sequences are being generated at breakneck pace. This trend towards massive sequencing of plastid genomes highlights the need for standardized bioinformatic workflows. In particular, documentation and dissemination of the details of genome assembly, annotation, alignment and phylogenetic tree inference are needed, as these processes are highly sensitive to the choice of software and the precise settings used. Here, we present the procedure and results of sequencing, assembling, annotating and quality-checking of three complete plastid genomes of the aquatic plant genus Cabomba as well as subsequent gene alignment and phylogenetic tree inference. We accompany our findings by a detailed description of the bioinformatic workflow employed. Importantly, we share a total of eleven software scripts for each of these bioinformatic processes, enabling other researchers to evaluate and replicate our analyses step by step. The results of our analyses illustrate that the plastid genomes of Cabomba are highly conserved in both structure and gene content.

Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.

PubMed

Squires, R Burke; Pickett, Brett E; Das, Sajal; Scheuermann, Richard H

2014-12-01

In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. Copyright © 2014 Elsevier B.V. All rights reserved.

An Alignment-Free Algorithm in Comparing the Similarity of Protein Sequences Based on Pseudo-Markov Transition Probabilities among Amino Acids

PubMed Central

Li, Yushuang; Yang, Jiasheng; Zhang, Yi

2016-01-01

In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector. PMID:27918587

Identification of Novel Sequence Types among Staphylococcus haemolyticus Isolated from Variety of Infections in India.

PubMed

Panda, Sasmita; Jena, Smrutiti; Sharma, Savitri; Dhawan, Benu; Nath, Gopal; Singh, Durg Vijai

2016-01-01

The aim of this study was to determine sequence types of 34 S. haemolyticus strains isolated from a variety of infections between 2013 and 2016 in India by MLST. The MEGA5.2 software was used to align and compare the nucleotide sequences. The advanced cluster analysis was performed to define the clonal complexes. MLST analysis showed 24 new sequence types (ST) among S. haemolyticus isolates, irrespective of sources and place of isolation. The finding of this study allowed to set up an MLST database on the PubMLST.org website using BIGSdb software and made available at http://pubmlst.org/shaemolyticus/. The data of this study thus suggest that MLST can be used to study population structure and diversity among S. haemolyticus isolates.

Identification of Novel Sequence Types among Staphylococcus haemolyticus Isolated from Variety of Infections in India

PubMed Central

Panda, Sasmita; Jena, Smrutiti; Sharma, Savitri; Dhawan, Benu; Nath, Gopal

2016-01-01

The aim of this study was to determine sequence types of 34 S. haemolyticus strains isolated from a variety of infections between 2013 and 2016 in India by MLST. The MEGA5.2 software was used to align and compare the nucleotide sequences. The advanced cluster analysis was performed to define the clonal complexes. MLST analysis showed 24 new sequence types (ST) among S. haemolyticus isolates, irrespective of sources and place of isolation. The finding of this study allowed to set up an MLST database on the PubMLST.org website using BIGSdb software and made available at http://pubmlst.org/shaemolyticus/. The data of this study thus suggest that MLST can be used to study population structure and diversity among S. haemolyticus isolates. PMID:27824930

PVT: an efficient computational procedure to speed up next-generation sequence analysis.

PubMed

Maji, Ranjan Kumar; Sarkar, Arijita; Khatua, Sunirmal; Dasgupta, Subhasis; Ghosh, Zhumur

2014-06-04

High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat's serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during 'spliced alignment' and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an improved performance of ~41% over TopHat (for the chosen data) with respect to execution time. Moreover we propose PVT-Cloud which implements PVT pipeline in cloud computing system.

Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data.

PubMed

Dunn, Joshua G; Weissman, Jonathan S

2016-11-22

Next-generation sequencing (NGS) informs many biological questions with unprecedented depth and nucleotide resolution. These assays have created a need for analytical tools that enable users to manipulate data nucleotide-by-nucleotide robustly and easily. Furthermore, because many NGS assays encode information jointly within multiple properties of read alignments - for example, in ribosome profiling, the locations of ribosomes are jointly encoded in alignment coordinates and length - analytical tools are often required to extract the biological meaning from the alignments before analysis. Many assay-specific pipelines exist for this purpose, but there remains a need for user-friendly, generalized, nucleotide-resolution tools that are not limited to specific experimental regimes or analytical workflows. Plastid is a Python library designed specifically for nucleotide-resolution analysis of genomics and NGS data. As such, Plastid is designed to extract assay-specific information from read alignments while retaining generality and extensibility to novel NGS assays. Plastid represents NGS and other biological data as arrays of values associated with genomic or transcriptomic positions, and contains configurable tools to convert data from a variety of sources to such arrays. Plastid also includes numerous tools to manipulate even discontinuous genomic features, such as spliced transcripts, with nucleotide precision. Plastid automatically handles conversion between genomic and feature-centric coordinates, accounting for splicing and strand, freeing users of burdensome accounting. Finally, Plastid's data models use consistent and familiar biological idioms, enabling even beginners to develop sophisticated analytical workflows with minimal effort. Plastid is a versatile toolkit that has been used to analyze data from multiple NGS assays, including RNA-seq, ribosome profiling, and DMS-seq. It forms the genomic engine of our ORF annotation tool, ORF-RATER, and is readily adapted to novel NGS assays. Examples, tutorials, and extensive documentation can be found at https://plastid.readthedocs.io .

CRISPR-DAV: CRISPR NGS data analysis and visualization pipeline.

PubMed

Wang, Xuning; Tilford, Charles; Neuhaus, Isaac; Mintier, Gabe; Guo, Qi; Feder, John N; Kirov, Stefan

2017-12-01

The simplicity and precision of CRISPR/Cas9 system has brought in a new era of gene editing. Screening for desired clones with CRISPR-mediated genomic edits in a large number of samples is made possible by next generation sequencing (NGS) due to its multiplexing. Here we present CRISPR-DAV (CRISPR Data Analysis and Visualization) pipeline to analyze the CRISPR NGS data in a high throughput manner. In the pipeline, Burrows-Wheeler Aligner and Assembly Based ReAlignment are used for small and large indel detection, and results are presented in a comprehensive set of charts and interactive alignment view. CRISPR-DAV is available at GitHub and Docker Hub repositories: https://github.com/pinetree1/crispr-dav.git and https://hub.docker.com/r/pinetree1/crispr-dav/. xuning.wang@bms.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Missing Data and Influential Sites: Choice of Sites for Phylogenetic Analysis Can Be As Important As Taxon Sampling and Model Choice

PubMed Central

Shavit Grievink, Liat; Penny, David; Holland, Barbara R.

2013-01-01

Phylogenetic studies based on molecular sequence alignments are expected to become more accurate as the number of sites in the alignments increases. With the advent of genomic-scale data, where alignments have very large numbers of sites, bootstrap values close to 100% and posterior probabilities close to 1 are the norm, suggesting that the number of sites is now seldom a limiting factor on phylogenetic accuracy. This provokes the question, should we be fussy about the sites we choose to include in a genomic-scale phylogenetic analysis? If some sites contain missing data, ambiguous character states, or gaps, then why not just throw them away before conducting the phylogenetic analysis? Indeed, this is exactly the approach taken in many phylogenetic studies. Here, we present an example where the decision on how to treat sites with missing data is of equal importance to decisions on taxon sampling and model choice, and we introduce a graphical method for illustrating this. PMID:23471508

On the Impact of Widening Vector Registers on Sequence Alignment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.; Kalyanaraman, Anantharaman; Krishnamoorthy, Sriram

2016-09-22

Vector extensions, such as SSE, have been part of the x86 since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. In this paper, we demonstrate that the trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based onmore » striped data layouts. We present a practically efficient SIMD implementation of a parallel scan based sequence alignment algorithm that can better exploit wider SIMD units. We conduct comprehensive workload and use case analyses to characterize the relative behavior of the striped and scan approaches and identify the best choice of algorithm based on input length and SIMD width.« less

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.

Molecular characterization and combined genotype association study of bovine cluster of differentiation 14 gene with clinical mastitis in crossbred dairy cattle

PubMed Central

Selvan, A. Sakthivel; Gupta, I. D.; Verma, A.; Chaudhari, M. V.; Magotra, A.

2016-01-01

Aim: The present study was undertaken with the objectives to characterize and to analyze combined genotypes of cluster of differentiation 14 (CD14) gene to explore its association with clinical mastitis in Karan Fries (KF) cows maintained in the National Dairy Research Institute herd, Karnal. Materials and Methods: Genomic DNA was extracted using blood of randomly selected 94 KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR) was carried out using six sets of reported gene-specific primers to amplify complete KF CD14 gene. The forward and reverse sequences for each PCR fragments were assembled to form complete sequence for the respective region of KF CD14 gene. The multiple sequence alignments of the edited sequence with the corresponding reference with reported Bos taurus sequence (EU148610.1) were performed with ClustalW software to identify single nucleotide polymorphisms (SNPs). Basic Local Alignment Search Tool analysis was performed to compare the sequence identity of KF CD14 gene with other species. The restriction fragment length polymorphism (RFLP) analysis was carried out in all KF cows using Helicobacter pylori 188I (Hpy188I) (contig 2) and Haemophilus influenzae I (HinfI) (contig 4) restriction enzyme (RE). Cows were assigned genotypes obtained by PCR-RFLP analysis, and association study was done using Chi-square (χ2) test. The genotypes of both contigs (loci) number 2 and 4 were combined with respect to each animal to construct combined genotype patterns. Results: Two types of sequences of KF were obtained: One with 2630 bp having one insertion at 616 nucleotide (nt) position and one deletion at 1117 nt position, and the another sequence was of 2629 bp having only one deletion at 615 nt position. ClustalW, multiple alignments of KF CD14 gene sequence with B. taurus cattle sequence (EU148610.1), revealed 24 nt changes (SNPs). Cows were also screened using PCR-RFLP with Hpy188I (contig 2) and HinfI (contig 4) RE, which revealed three genotypes each that differed significantly regarding mastitis incidence. The maximum possible combination of these two loci shown nine combined genotype patterns and it was observed only eight combined genotypes out of nine: AACC, AACD, AADD, ABCD, ABDD, BBCC, BBCD, and BBDD. The combined genotype ABCC was not observed in the studied population of KF cows. Out of 94 animals, AACD combined genotype animals (10.63%) were found to be not affected with mastitis, and ABDD combined genotyped animals was observed having the highest mastitis incidence of 15.96%. Conclusion: AACD typed cows were found to be least susceptible to mastitis incidence as compared to other combined genotypes. PMID:27536026

Molecular characterization and combined genotype association study of bovine cluster of differentiation 14 gene with clinical mastitis in crossbred dairy cattle.

PubMed

Selvan, A Sakthivel; Gupta, I D; Verma, A; Chaudhari, M V; Magotra, A

2016-07-01

The present study was undertaken with the objectives to characterize and to analyze combined genotypes of cluster of differentiation 14 (CD14) gene to explore its association with clinical mastitis in Karan Fries (KF) cows maintained in the National Dairy Research Institute herd, Karnal. Genomic DNA was extracted using blood of randomly selected 94 KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR) was carried out using six sets of reported gene-specific primers to amplify complete KF CD14 gene. The forward and reverse sequences for each PCR fragments were assembled to form complete sequence for the respective region of KF CD14 gene. The multiple sequence alignments of the edited sequence with the corresponding reference with reported Bos taurus sequence (EU148610.1) were performed with ClustalW software to identify single nucleotide polymorphisms (SNPs). Basic Local Alignment Search Tool analysis was performed to compare the sequence identity of KF CD14 gene with other species. The restriction fragment length polymorphism (RFLP) analysis was carried out in all KF cows using Helicobacter pylori 188I (Hpy188I) (contig 2) and Haemophilus influenzae I (HinfI) (contig 4) restriction enzyme (RE). Cows were assigned genotypes obtained by PCR-RFLP analysis, and association study was done using Chi-square (χ (2)) test. The genotypes of both contigs (loci) number 2 and 4 were combined with respect to each animal to construct combined genotype patterns. Two types of sequences of KF were obtained: One with 2630 bp having one insertion at 616 nucleotide (nt) position and one deletion at 1117 nt position, and the another sequence was of 2629 bp having only one deletion at 615 nt position. ClustalW, multiple alignments of KF CD14 gene sequence with B. taurus cattle sequence (EU148610.1), revealed 24 nt changes (SNPs). Cows were also screened using PCR-RFLP with Hpy188I (contig 2) and HinfI (contig 4) RE, which revealed three genotypes each that differed significantly regarding mastitis incidence. The maximum possible combination of these two loci shown nine combined genotype patterns and it was observed only eight combined genotypes out of nine: AACC, AACD, AADD, ABCD, ABDD, BBCC, BBCD, and BBDD. The combined genotype ABCC was not observed in the studied population of KF cows. Out of 94 animals, AACD combined genotype animals (10.63%) were found to be not affected with mastitis, and ABDD combined genotyped animals was observed having the highest mastitis incidence of 15.96%. AACD typed cows were found to be least susceptible to mastitis incidence as compared to other combined genotypes.

T-BAS: Tree-Based Alignment Selector toolkit for phylogenetic-based placement, alignment downloads and metadata visualization: an example with the Pezizomycotina tree of life.

PubMed

Carbone, Ignazio; White, James B; Miadlikowska, Jolanta; Arnold, A Elizabeth; Miller, Mark A; Kauff, Frank; U'Ren, Jana M; May, Georgiana; Lutzoni, François

2017-04-15

High-quality phylogenetic placement of sequence data has the potential to greatly accelerate studies of the diversity, systematics, ecology and functional biology of diverse groups. We developed the Tree-Based Alignment Selector (T-BAS) toolkit to allow evolutionary placement and visualization of diverse DNA sequences representing unknown taxa within a robust phylogenetic context, and to permit the downloading of highly curated, single- and multi-locus alignments for specific clades. In its initial form, T-BAS v1.0 uses a core phylogeny of 979 taxa (including 23 outgroup taxa, as well as 61 orders, 175 families and 496 genera) representing all 13 classes of largest subphylum of Fungi-Pezizomycotina (Ascomycota)-based on sequence alignments for six loci (nr5.8S, nrLSU, nrSSU, mtSSU, RPB1, RPB2 ). T-BAS v1.0 has three main uses: (i) Users may download alignments and voucher tables for members of the Pezizomycotina directly from the reference tree, facilitating systematics studies of focal clades. (ii) Users may upload sequence files with reads representing unknown taxa and place these on the phylogeny using either BLAST or phylogeny-based approaches, and then use the displayed tree to select reference taxa to include when downloading alignments. The placement of unknowns can be performed for large numbers of Sanger sequences obtained from fungal cultures and for alignable, short reads of environmental amplicons. (iii) User-customizable metadata can be visualized on the tree. T-BAS Version 1.0 is available online at http://tbas.hpc.ncsu.edu . Registration is required to access the CIPRES Science Gateway and NSF XSEDE's large computational resources. icarbon@ncsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic.

PubMed

Derkach, Andriy; Chiang, Theodore; Gong, Jiafen; Addis, Laura; Dobbins, Sara; Tomlinson, Ian; Houlston, Richard; Pal, Deb K; Strug, Lisa J

2014-08-01

Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. lisa.strug@utoronto.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SPHINX--an algorithm for taxonomic binning of metagenomic sequences.

PubMed

Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Singh, Nitin Kumar; Mande, Sharmila S

2011-01-01

Compared with composition-based binning algorithms, the binning accuracy and specificity of alignment-based binning algorithms is significantly higher. However, being alignment-based, the latter class of algorithms require enormous amount of time and computing resources for binning huge metagenomic datasets. The motivation was to develop a binning approach that can analyze metagenomic datasets as rapidly as composition-based approaches, but nevertheless has the accuracy and specificity of alignment-based algorithms. This article describes a hybrid binning approach (SPHINX) that achieves high binning efficiency by utilizing the principles of both 'composition'- and 'alignment'-based binning algorithms. Validation results with simulated sequence datasets indicate that SPHINX is able to analyze metagenomic sequences as rapidly as composition-based algorithms. Furthermore, the binning efficiency (in terms of accuracy and specificity of assignments) of SPHINX is observed to be comparable with results obtained using alignment-based algorithms. A web server for the SPHINX algorithm is available at http://metagenomics.atc.tcs.com/SPHINX/.

Adaptive Local Realignment of Protein Sequences.

PubMed

DeBlasio, Dan; Kececioglu, John

2018-06-11

While mutation rates can vary markedly over the residues of a protein, multiple sequence alignment tools typically use the same values for their scoring-function parameters across a protein's entire length. We present a new approach, called adaptive local realignment, that in contrast automatically adapts to the diversity of mutation rates along protein sequences. This builds upon a recent technique known as parameter advising, which finds global parameter settings for an aligner, to now adaptively find local settings. Our approach in essence identifies local regions with low estimated accuracy, constructs a set of candidate realignments using a carefully-chosen collection of parameter settings, and replaces the region if a realignment has higher estimated accuracy. This new method of local parameter advising, when combined with prior methods for global advising, boosts alignment accuracy as much as 26% over the best default setting on hard-to-align protein benchmarks, and by 6.4% over global advising alone. Adaptive local realignment has been implemented within the Opal aligner using the Facet accuracy estimator.

Integrative network alignment reveals large regions of global network similarity in yeast and human.

PubMed

Kuchaiev, Oleksii; Przulj, Natasa

2011-05-15

High-throughput methods for detecting molecular interactions have produced large sets of biological network data with much more yet to come. Analogous to sequence alignment, efficient and reliable network alignment methods are expected to improve our understanding of biological systems. Unlike sequence alignment, network alignment is computationally intractable. Hence, devising efficient network alignment heuristics is currently a foremost challenge in computational biology. We introduce a novel network alignment algorithm, called Matching-based Integrative GRAph ALigner (MI-GRAAL), which can integrate any number and type of similarity measures between network nodes (e.g. proteins), including, but not limited to, any topological network similarity measure, sequence similarity, functional similarity and structural similarity. Hence, we resolve the ties in similarity measures and find a combination of similarity measures yielding the largest contiguous (i.e. connected) and biologically sound alignments. MI-GRAAL exposes the largest functional, connected regions of protein-protein interaction (PPI) network similarity to date: surprisingly, it reveals that 77.7% of proteins in the baker's yeast high-confidence PPI network participate in such a subnetwork that is fully contained in the human high-confidence PPI network. This is the first demonstration that species as diverse as yeast and human contain so large, continuous regions of global network similarity. We apply MI-GRAAL's alignments to predict functions of un-annotated proteins in yeast, human and bacteria validating our predictions in the literature. Furthermore, using network alignment scores for PPI networks of different herpes viruses, we reconstruct their phylogenetic relationship. This is the first time that phylogeny is exactly reconstructed from purely topological alignments of PPI networks. Supplementary files and MI-GRAAL executables: http://bio-nets.doc.ic.ac.uk/MI-GRAAL/.

Aptaligner: automated software for aligning pseudorandom DNA X-aptamers from next-generation sequencing data.

PubMed

Lu, Emily; Elizondo-Riojas, Miguel-Angel; Chang, Jeffrey T; Volk, David E

2014-06-10

Next-generation sequencing results from bead-based aptamer libraries have demonstrated that traditional DNA/RNA alignment software is insufficient. This is particularly true for X-aptamers containing specialty bases (W, X, Y, Z, ...) that are identified by special encoding. Thus, we sought an automated program that uses the inherent design scheme of bead-based X-aptamers to create a hypothetical reference library and Markov modeling techniques to provide improved alignments. Aptaligner provides this feature as well as length error and noise level cutoff features, is parallelized to run on multiple central processing units (cores), and sorts sequences from a single chip into projects and subprojects.

Comparative genome analysis in the integrated microbial genomes (IMG) system.

PubMed

Markowitz, Victor M; Kyrpides, Nikos C

2007-01-01

Comparative genome analysis is critical for the effective exploration of a rapidly growing number of complete and draft sequences for microbial genomes. The Integrated Microbial Genomes (IMG) system (img.jgi.doe.gov) has been developed as a community resource that provides support for comparative analysis of microbial genomes in an integrated context. IMG allows users to navigate the multidimensional microbial genome data space and focus their analysis on a subset of genes, genomes, and functions of interest. IMG provides graphical viewers, summaries, and occurrence profile tools for comparing genes, pathways, and functions (terms) across specific genomes. Genes can be further examined using gene neighborhoods and compared with sequence alignment tools.

The VirusBanker database uses a Java program to allow flexible searching through Bunyaviridae sequences

PubMed Central

Fourment, Mathieu; Gibbs, Mark J

2008-01-01

Background Viruses of the Bunyaviridae have segmented negative-stranded RNA genomes and several of them cause significant disease. Many partial sequences have been obtained from the segments so that GenBank searches give complex results. Sequence databases usually use HTML pages to mediate remote sorting, but this approach can be limiting and may discourage a user from exploring a database. Results The VirusBanker database contains Bunyaviridae sequences and alignments and is presented as two spreadsheets generated by a Java program that interacts with a MySQL database on a server. Sequences are displayed in rows and may be sorted using information that is displayed in columns and includes data relating to the segment, gene, protein, species, strain, sequence length, terminal sequence and date and country of isolation. Bunyaviridae sequences and alignments may be downloaded from the second spreadsheet with titles defined by the user from the columns, or viewed when passed directly to the sequence editor, Jalview. Conclusion VirusBanker allows large datasets of aligned nucleotide and protein sequences from the Bunyaviridae to be compiled and winnowed rapidly using criteria that are formulated heuristically. PMID:18251994

A comprehensive aligned nifH gene database: a multipurpose tool for studies of nitrogen-fixing bacteria.

PubMed

Gaby, John Christian; Buckley, Daniel H

2014-01-01

We describe a nitrogenase gene sequence database that facilitates analysis of the evolution and ecology of nitrogen-fixing organisms. The database contains 32 954 aligned nitrogenase nifH sequences linked to phylogenetic trees and associated sequence metadata. The database includes 185 linked multigene entries including full-length nifH, nifD, nifK and 16S ribosomal RNA (rRNA) gene sequences. Evolutionary analyses enabled by the multigene entries support an ancient horizontal transfer of nitrogenase genes between Archaea and Bacteria and provide evidence that nifH has a different history of horizontal gene transfer from the nifDK enzyme core. Further analyses show that lineages in nitrogenase cluster I and cluster III have different rates of substitution within nifD, suggesting that nifD is under different selection pressure in these two lineages. Finally, we find that that the genetic divergence of nifH and 16S rRNA genes does not correlate well at sequence dissimilarity values used commonly to define microbial species, as stains having <3% sequence dissimilarity in their 16S rRNA genes can have up to 23% dissimilarity in nifH. The nifH database has a number of uses including phylogenetic and evolutionary analyses, the design and assessment of primers/probes and the evaluation of nitrogenase sequence diversity. Database URL: http://www.css.cornell.edu/faculty/buckley/nifh.htm.

A comprehensive aligned nifH gene database: a multipurpose tool for studies of nitrogen-fixing bacteria

PubMed Central

Gaby, John Christian; Buckley, Daniel H.

2014-01-01

We describe a nitrogenase gene sequence database that facilitates analysis of the evolution and ecology of nitrogen-fixing organisms. The database contains 32 954 aligned nitrogenase nifH sequences linked to phylogenetic trees and associated sequence metadata. The database includes 185 linked multigene entries including full-length nifH, nifD, nifK and 16S ribosomal RNA (rRNA) gene sequences. Evolutionary analyses enabled by the multigene entries support an ancient horizontal transfer of nitrogenase genes between Archaea and Bacteria and provide evidence that nifH has a different history of horizontal gene transfer from the nifDK enzyme core. Further analyses show that lineages in nitrogenase cluster I and cluster III have different rates of substitution within nifD, suggesting that nifD is under different selection pressure in these two lineages. Finally, we find that that the genetic divergence of nifH and 16S rRNA genes does not correlate well at sequence dissimilarity values used commonly to define microbial species, as stains having <3% sequence dissimilarity in their 16S rRNA genes can have up to 23% dissimilarity in nifH. The nifH database has a number of uses including phylogenetic and evolutionary analyses, the design and assessment of primers/probes and the evaluation of nitrogenase sequence diversity. Database URL: http://www.css.cornell.edu/faculty/buckley/nifh.htm PMID:24501396

New Challenges of the Computation of Multiple Sequence Alignments in the High-Throughput Era (2010 JGI/ANL HPC Workshop)

ScienceCinema

Notredame, Cedric

2018-05-02

Cedric Notredame from the Centre for Genomic Regulation gives a presentation on New Challenges of the Computation of Multiple Sequence Alignments in the High-Throughput Era at the JGI/Argonne HPC Workshop on January 26, 2010.

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

PubMed

Myschyshyn, Mike; Farren-Dai, Marco; Chuang, Tien-Jui; Vocadlo, David

2017-11-25

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically relevant data analysis, and the uncovering of variations in the time-dependent behavior of chromatin. TDCA automates the analysis of TC ChIP-seq experiments, permitting researchers to easily obtain raw and modeled data for specific loci or groups of loci with similar behavior while also enhancing consistency of data analysis of TC data within the genomics field.

A novel mutation in PRPF31, causative of autosomal dominant retinitis pigmentosa, using the BGISEQ-500 sequencer

PubMed Central

Zheng, Yu; Wang, Hai-Lin; Li, Jian-Kang; Xu, Li; Tellier, Laurent; Li, Xiao-Lin; Huang, Xiao-Yan; Li, Wei; Niu, Tong-Tong; Yang, Huan-Ming; Zhang, Jian-Guo; Liu, Dong-Ning

2018-01-01

AIM To study the genes responsible for retinitis pigmentosa. METHODS A total of 15 Chinese families with retinitis pigmentosa, containing 94 sporadically afflicted cases, were recruited. The targeted sequences were captured using the Target_Eye_365_V3 chip and sequenced using the BGISEQ-500 sequencer, according to the manufacturer's instructions. Data were aligned to UCSC Genome Browser build hg19, using the Burroughs Wheeler Aligner MEM algorithm. Local realignment was performed with the Genome Analysis Toolkit (GATK v.3.3.0) IndelRealigner, and variants were called with the Genome Analysis Toolkit Haplotypecaller, without any use of imputation. Variants were filtered against a panel derived from 1000 Genomes Project, 1000G_ASN, ESP6500, ExAC and dbSNP138. In all members of Family ONE and Family TWO with available DNA samples, the genetic variant was validated using Sanger sequencing. RESULTS A novel, pathogenic variant of retinitis pigmentosa, c.357_358delAA (p.Ser119SerfsX5) was identified in PRPF31 in 2 of 15 autosomal-dominant retinitis pigmentosa (ADRP) families, as well as in one, sporadic case. Sanger sequencing was performed upon probands, as well as upon other family members. This novel, pathogenic genotype co-segregated with retinitis pigmentosa phenotype in these two families. CONCLUSION ADRP is a subtype of retinitis pigmentosa, defined by its genotype, which accounts for 20%-40% of the retinitis pigmentosa patients. Our study thus expands the spectrum of PRPF31 mutations known to occur in ADRP, and provides further demonstration of the applicability of the BGISEQ500 sequencer for genomics research. PMID:29375987

Comparative Analysis and Distribution of Omega-3 lcPUFA Biosynthesis Genes in Marine Molluscs

PubMed Central

Surm, Joachim M.; Prentis, Peter J.; Pavasovic, Ana

2015-01-01

Recent research has identified marine molluscs as an excellent source of omega-3 long-chain polyunsaturated fatty acids (lcPUFAs), based on their potential for endogenous synthesis of lcPUFAs. In this study we generated a representative list of fatty acyl desaturase (Fad) and elongation of very long-chain fatty acid (Elovl) genes from major orders of Phylum Mollusca, through the interrogation of transcriptome and genome sequences, and various publicly available databases. We have identified novel and uncharacterised Fad and Elovl sequences in the following species: Anadara trapezia, Nerita albicilla, Nerita melanotragus, Crassostrea gigas, Lottia gigantea, Aplysia californica, Loligo pealeii and Chlamys farreri. Based on alignments of translated protein sequences of Fad and Elovl genes, the haeme binding motif and histidine boxes of Fad proteins, and the histidine box and seventeen important amino acids in Elovl proteins, were highly conserved. Phylogenetic analysis of aligned reference sequences was used to reconstruct the evolutionary relationships for Fad and Elovl genes separately. Multiple, well resolved clades for both the Fad and Elovl sequences were observed, suggesting that repeated rounds of gene duplication best explain the distribution of Fad and Elovl proteins across the major orders of molluscs. For Elovl sequences, one clade contained the functionally characterised Elovl5 proteins, while another clade contained proteins hypothesised to have Elovl4 function. Additional well resolved clades consisted only of uncharacterised Elovl sequences. One clade from the Fad phylogeny contained only uncharacterised proteins, while the other clade contained functionally characterised delta-5 desaturase proteins. The discovery of an uncharacterised Fad clade is particularly interesting as these divergent proteins may have novel functions. Overall, this paper presents a number of novel Fad and Elovl genes suggesting that many mollusc groups possess most of the required enzymes for the synthesis of lcPUFAs. PMID:26308548

Improvements on a privacy-protection algorithm for DNA sequences with generalization lattices.

PubMed

Li, Guang; Wang, Yadong; Su, Xiaohong

2012-10-01

When developing personal DNA databases, there must be an appropriate guarantee of anonymity, which means that the data cannot be related back to individuals. DNA lattice anonymization (DNALA) is a successful method for making personal DNA sequences anonymous. However, it uses time-consuming multiple sequence alignment and a low-accuracy greedy clustering algorithm. Furthermore, DNALA is not an online algorithm, and so it cannot quickly return results when the database is updated. This study improves the DNALA method. Specifically, we replaced the multiple sequence alignment in DNALA with global pairwise sequence alignment to save time, and we designed a hybrid clustering algorithm comprised of a maximum weight matching (MWM)-based algorithm and an online algorithm. The MWM-based algorithm is more accurate than the greedy algorithm in DNALA and has the same time complexity. The online algorithm can process data quickly when the database is updated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Bringing the fathead minnow (Pimephales promelas) into the ...

EPA Pesticide Factsheets

The fathead minnow (Pimephales promelas) is a well-established ecotoxicological model organism that has been widely used for regulatory ecotoxicity testing and research for over a half century. Throughout this time, a lot of knowledge has been gained about the fathead minnow’s biological responses to various xenobiotics. However, despite its importance as a model organism, the fathead minnow still has few publicly available gene sequences. Recently, Burns et al. (2015; Environ. Toxicol. Chem. 35:212) described the sequencing and de-novo assembly of the fathead minnow genome. Two draft genome assemblies are now publicly available on the GenBank database. However, on their own the draft assemblies remain of limited use to researchers who are primarily interested in the functional units of the genome, i.e. the genes. In the present study, an annotation pipeline, consisting of gene prediction, evidence alignment, and data synthesis, was applied to the fathead minnow SOAPdenovo assembly. Ab initio gene prediction was performed using AUGUSTUS, which provided a starting point of 43,345 gene predictions. Fathead minnow Expressed Sequence Tags (ESTs) and zebrafish protein-coding sequences (CDSs) were then aligned to the assembly using the corresponding spliced alignment methods of the program Exonerate. Of the over 240,000 EST alignments, 73% were successfully aligned with 90% or greater sequence identity and query coverage. Similarly, 39% of nearly 45,000 zebrafish co

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

PubMed

Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W

2018-01-01

Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. dtww@ucla.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Genetic analysis of duck circovirus in Pekin ducks from South Korea.

PubMed

Cha, S-Y; Kang, M; Cho, J-G; Jang, H-K

2013-11-01

The genetic organization of the 24 duck circovirus (DuCV) strains detected in commercial Pekin ducks from South Korea between 2011 and 2012 is described in this study. Multiple sequence alignment and phylogenetic analyses were performed on the 24 viral genome sequences as well as on 45 genome sequences available from the GenBank database. Phylogenetic analyses based on the genomic and open reading frame 2/cap sequences demonstrated that all DuCV strains belonged to genotype 1 and were designated in a subcluster under genotype 1. Analysis of the capsid protein amino acid sequences of the 24 Korean DuCV strains showed 10 substitutions compared with that of other genotype 1 strains. Our analysis showed that genotype 1 is predominant and circulating in South Korea. These present results serve as incentive to add more data to the DuCV database and provide insight to conduct further intensive study on the geographic relationships among these virus strains.

Rebelling for a Reason: Protein Structural “Outliers”

PubMed Central

Arumugam, Gandhimathi; Nair, Anu G.; Hariharaputran, Sridhar; Ramanathan, Sowdhamini

2013-01-01

Analysis of structural variation in domain superfamilies can reveal constraints in protein evolution which aids protein structure prediction and classification. Structure-based sequence alignment of distantly related proteins, organized in PASS2 database, provides clues about structurally conserved regions among different functional families. Some superfamily members show large structural differences which are functionally relevant. This paper analyses the impact of structural divergence on function for multi-member superfamilies, selected from the PASS2 superfamily alignment database. Functional annotations within superfamilies, with structural outliers or ‘rebels’, are discussed in the context of structural variations. Overall, these data reinforce the idea that functional similarities cannot be extrapolated from mere structural conservation. The implication for fold-function prediction is that the functional annotations can only be inherited with very careful consideration, especially at low sequence identities. PMID:24073209

Integrated databanks access and sequence/structure analysis services at the PBIL.

PubMed

Perrière, Guy; Combet, Christophe; Penel, Simon; Blanchet, Christophe; Thioulouse, Jean; Geourjon, Christophe; Grassot, Julien; Charavay, Céline; Gouy, Manolo; Duret, Laurent; Deléage, Gilbert

2003-07-01

The World Wide Web server of the PBIL (Pôle Bioinformatique Lyonnais) provides on-line access to sequence databanks and to many tools of nucleic acid and protein sequence analyses. This server allows to query nucleotide sequence banks in the EMBL and GenBank formats and protein sequence banks in the SWISS-PROT and PIR formats. The query engine on which our data bank access is based is the ACNUC system. It allows the possibility to build complex queries to access functional zones of biological interest and to retrieve large sequence sets. Of special interest are the unique features provided by this system to query the data banks of gene families developed at the PBIL. The server also provides access to a wide range of sequence analysis methods: similarity search programs, multiple alignments, protein structure prediction and multivariate statistics. An originality of this server is the integration of these two aspects: sequence retrieval and sequence analysis. Indeed, thanks to the introduction of re-usable lists, it is possible to perform treatments on large sets of data. The PBIL server can be reached at: http://pbil.univ-lyon1.fr.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data.

PubMed

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S; Molyneaux, Adam; Xu, Zhenyu; Fellay, Jacques; Steinmetz, Lars M; Hubaux, Jean-Pierre

2016-12-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. © 2016 Huang et al.; Published by Cold Spring Harbor Laboratory Press.

OrthoMaM v8: a database of orthologous exons and coding sequences for comparative genomics in mammals.

PubMed

Douzery, Emmanuel J P; Scornavacca, Celine; Romiguier, Jonathan; Belkhir, Khalid; Galtier, Nicolas; Delsuc, Frédéric; Ranwez, Vincent

2014-07-01

Comparative genomic studies extensively rely on alignments of orthologous sequences. Yet, selecting, gathering, and aligning orthologous exons and protein-coding sequences (CDS) that are relevant for a given evolutionary analysis can be a difficult and time-consuming task. In this context, we developed OrthoMaM, a database of ORTHOlogous MAmmalian Markers describing the evolutionary dynamics of orthologous genes in mammalian genomes using a phylogenetic framework. Since its first release in 2007, OrthoMaM has regularly evolved, not only to include newly available genomes but also to incorporate up-to-date software in its analytic pipeline. This eighth release integrates the 40 complete mammalian genomes available in Ensembl v73 and provides alignments, phylogenies, evolutionary descriptor information, and functional annotations for 13,404 single-copy orthologous CDS and 6,953 long exons. The graphical interface allows to easily explore OrthoMaM to identify markers with specific characteristics (e.g., taxa availability, alignment size, %G+C, evolutionary rate, chromosome location). It hence provides an efficient solution to sample preprocessed markers adapted to user-specific needs. OrthoMaM has proven to be a valuable resource for researchers interested in mammalian phylogenomics, evolutionary genomics, and has served as a source of benchmark empirical data sets in several methodological studies. OrthoMaM is available for browsing, query and complete or filtered downloads at http://www.orthomam.univ-montp2.fr/. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data

PubMed Central

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S.; Molyneaux, Adam; Xu, Zhenyu; Hubaux, Jean-Pierre

2016-01-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients’ complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. PMID:27789525

Molecular variability analysis of five new complete cacao swollen shoot virus genomic sequences.

PubMed

Muller, E; Sackey, S

2005-01-01

Cacao swollen shoot virus (CSSV), a member of the family Caulimovi-ridae, genus Badnavirus occurs in all the main cacao-growing areas of West Africa. We amplified, cloned and sequenced complete genomes of five new isolates, two originating from Togo and three originating from Ghana. The genome of these five newly sequenced isolates all contain the five putative open reading frames I, II, III, X and Y described for the first sequenced CSSV isolate, Agou1 originating from Togo. Their genomes have been aligned with the genome of Agou1. The nucleotide and amino acid sequence identities between isolates have been calculated and a phylogenetic analysis has been made including other pararetroviruses. Maximum nucleotide sequence variability between complete genomes of CSSV isolates was 29.4%. Geographical differentiation between isolates appears more important than differentiation between mild and severe isolates. ORF X differs greatly in size and sequence between the Togolese isolates Nyongbo2 and Agou1, and the four other isolates, its functional role is therefore clearly questionable.

D-GENIES: dot plot large genomes in an interactive, efficient and simple way.

PubMed

Cabanettes, Floréal; Klopp, Christophe

2018-01-01

Dot plots are widely used to quickly compare sequence sets. They provide a synthetic similarity overview, highlighting repetitions, breaks and inversions. Different tools have been developed to easily generated genomic alignment dot plots, but they are often limited in the input sequence size. D-GENIES is a standalone and web application performing large genome alignments using minimap2 software package and generating interactive dot plots. It enables users to sort query sequences along the reference, zoom in the plot and download several image, alignment or sequence files. D-GENIES is an easy-to-install, open-source software package (GPL) developed in Python and JavaScript. The source code is available at https://github.com/genotoul-bioinfo/dgenies and it can be tested at http://dgenies.toulouse.inra.fr/.

Characterization of tannase protein sequences of bacteria and fungi: an in silico study.

PubMed

Banerjee, Amrita; Jana, Arijit; Pati, Bikash R; Mondal, Keshab C; Das Mohapatra, Pradeep K

2012-04-01

The tannase protein sequences of 149 bacteria and 36 fungi were retrieved from NCBI database. Among them only 77 bacterial and 31 fungal tannase sequences were taken which have different amino acid compositions. These sequences were analysed for different physical and chemical properties, superfamily search, multiple sequence alignment, phylogenetic tree construction and motif finding to find out the functional motif and the evolutionary relationship among them. The superfamily search for these tannase exposed the occurrence of proline iminopeptidase-like, biotin biosynthesis protein BioH, O-acetyltransferase, carboxylesterase/thioesterase 1, carbon-carbon bond hydrolase, haloperoxidase, prolyl oligopeptidase, C-terminal domain and mycobacterial antigens families and alpha/beta hydrolase superfamily. Some bacterial and fungal sequence showed similarity with different families individually. The multiple sequence alignment of these tannase protein sequences showed conserved regions at different stretches with maximum homology from amino acid residues 389-469 and 482-523 which could be used for designing degenerate primers or probes specific for tannase producing bacterial and fungal species. Phylogenetic tree showed two different clusters; one has only bacteria and another have both fungi and bacteria showing some relationship between these different genera. Although in second cluster near about all fungal species were found together in a corner which indicates the sequence level similarity among fungal genera. The distributions of fourteen motifs analysis revealed Motif 1 with a signature amino acid sequence of 29 amino acids, i.e. GCSTGGREALKQAQRWPHDYDGIIANNPA, was uniformly observed in 83.3 % of studied tannase sequences representing its participation with the structure and enzymatic function.

New Tools For Understanding Microbial Diversity Using High-throughput Sequence Data

NASA Astrophysics Data System (ADS)

Knight, R.; Hamady, M.; Liu, Z.; Lozupone, C.

2007-12-01

High-throughput sequencing techniques such as 454 are straining the limits of tools traditionally used to build trees, choose OTUs, and perform other essential sequencing tasks. We have developed a workflow for phylogenetic analysis of large-scale sequence data sets that combines existing tools, such as the Arb phylogeny package and the NAST multiple sequence alignment tool, with new methods for choosing and clustering OTUs and for performing phylogenetic community analysis with UniFrac. This talk discusses the cyberinfrastructure we are developing to support the human microbiome project, and the application of these workflows to analyze very large data sets that contrast the gut microbiota with a range of physical environments. These tools will ultimately help to define core and peripheral microbiomes in a range of environments, and will allow us to understand the physical and biotic factors that contribute most to differences in microbial diversity.

GWFASTA: server for FASTA search in eukaryotic and microbial genomes.

PubMed

Issac, Biju; Raghava, G P S

2002-09-01

Similarity searches are a powerful method for solving important biological problems such as database scanning, evolutionary studies, gene prediction, and protein structure prediction. FASTA is a widely used sequence comparison tool for rapid database scanning. Here we describe the GWFASTA server that was developed to assist the FASTA user in similarity searches against partially and/or completely sequenced genomes. GWFASTA consists of more than 60 microbial genomes, eight eukaryote genomes, and proteomes of annotatedgenomes. Infact, it provides the maximum number of databases for similarity searching from a single platform. GWFASTA allows the submission of more than one sequence as a single query for a FASTA search. It also provides integrated post-processing of FASTA output, including compositional analysis of proteins, multiple sequences alignment, and phylogenetic analysis. Furthermore, it summarizes the search results organism-wise for prokaryotes and chromosome-wise for eukaryotes. Thus, the integration of different tools for sequence analyses makes GWFASTA a powerful toolfor biologists.

Alignment-Independent Comparisons of Human Gastrointestinal Tract Microbial Communities in a Multidimensional 16S rRNA Gene Evolutionary Space▿

PubMed Central

Rudi, Knut; Zimonja, Monika; Kvenshagen, Bente; Rugtveit, Jarle; Midtvedt, Tore; Eggesbø, Merete

2007-01-01

We present a novel approach for comparing 16S rRNA gene clone libraries that is independent of both DNA sequence alignment and definition of bacterial phylogroups. These steps are the major bottlenecks in current microbial comparative analyses. We used direct comparisons of taxon density distributions in an absolute evolutionary coordinate space. The coordinate space was generated by using alignment-independent bilinear multivariate modeling. Statistical analyses for clone library comparisons were based on multivariate analysis of variance, partial least-squares regression, and permutations. Clone libraries from both adult and infant gastrointestinal tract microbial communities were used as biological models. We reanalyzed a library consisting of 11,831 clones covering complete colons from three healthy adults in addition to a smaller 390-clone library from infant feces. We show that it is possible to extract detailed information about microbial community structures using our alignment-independent method. Our density distribution analysis is also very efficient with respect to computer operation time, meeting the future requirements of large-scale screenings to understand the diversity and dynamics of microbial communities. PMID:17337554

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

Dali server update.

PubMed

Holm, Liisa; Laakso, Laura M

2016-07-08

The Dali server (http://ekhidna2.biocenter.helsinki.fi/dali) is a network service for comparing protein structures in 3D. In favourable cases, comparing 3D structures may reveal biologically interesting similarities that are not detectable by comparing sequences. The Dali server has been running in various places for over 20 years and is used routinely by crystallographers on newly solved structures. The latest update of the server provides enhanced analytics for the study of sequence and structure conservation. The server performs three types of structure comparisons: (i) Protein Data Bank (PDB) search compares one query structure against those in the PDB and returns a list of similar structures; (ii) pairwise comparison compares one query structure against a list of structures specified by the user; and (iii) all against all structure comparison returns a structural similarity matrix, a dendrogram and a multidimensional scaling projection of a set of structures specified by the user. Structural superimpositions are visualized using the Java-free WebGL viewer PV. The structural alignment view is enhanced by sequence similarity searches against Uniprot. The combined structure-sequence alignment information is compressed to a stack of aligned sequence logos. In the stack, each structure is structurally aligned to the query protein and represented by a sequence logo. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Immunoglobulin from Antarctic fish species of Rajidae family.

PubMed

Coscia, Maria Rosaria; Cocca, Ennio; Giacomelli, Stefano; Cuccaro, Fausta; Oreste, Umberto

2012-03-01

Immunoglobulins (Ig) of Chondroichthyes have been extensively studied in sharks; in contrast, in skates investigations on Ig remain scarce and fragmentary despite the high occurrence of skates in all of the major oceans of the world. To focus on Rajidae Igμ, the most abundant heavy chain isotype, we have chosen the Antarctic species Bathyraja eatonii, Bathyraja albomaculata, Bathyraja brachyurops, and Amblyraja georgiana which live at high latitudes in the Southern Ocean, and at very low temperatures. We prepared mRNA from the spleen of individuals of each species and performed RT-PCR experiments using two oligonucleotides designed on the alignment of various elasmobranch Igμ heavy chain sequences available in GenBank. The PCR products, about 1400-nt long, were cloned and sequenced. Nucleotide sequence identities calculated for the constant region domains ranged from 88.5% to 97.5% between species, and from 91.1% to 99.7% within species. In a distance tree, including also Raja erinacea sequences, two major branches were obtained, one containing Arhynchobatinae sequences, the other one Rajinae sequences. Four presumptive D gene segments were identified in the region of the VH/D/JH recombination; two different D segments were often found in the same sequence. Moreover, 5-15 genomic fragments of different lengths, carrying the gene locus encoding Igμ chain were revealed by Southern blotting analysis. B. eatonii amino acid sequences were analyzed for the positional diversity by Shannon entropy analysis, showing CH4 as the most conserved domain, and CH3 as the most variable one. B. eatonii CDR3 region length varied between 11 and 15 amino acid residues; the mean length (13.4 aa) was greater than that of Leucoraja eglanteria sequences (7.7 aa). An alignment of representative sequences of Antarctic species and R. erinacea showed that more cysteine residues not involved in the intradomain disulfide bridges were present in Antarctic species. Copyright © 2011 Elsevier B.V. All rights reserved.

Information theory applications for biological sequence analysis.

PubMed

Vinga, Susana

2014-05-01

Information theory (IT) addresses the analysis of communication systems and has been widely applied in molecular biology. In particular, alignment-free sequence analysis and comparison greatly benefited from concepts derived from IT, such as entropy and mutual information. This review covers several aspects of IT applications, ranging from genome global analysis and comparison, including block-entropy estimation and resolution-free metrics based on iterative maps, to local analysis, comprising the classification of motifs, prediction of transcription factor binding sites and sequence characterization based on linguistic complexity and entropic profiles. IT has also been applied to high-level correlations that combine DNA, RNA or protein features with sequence-independent properties, such as gene mapping and phenotype analysis, and has also provided models based on communication systems theory to describe information transmission channels at the cell level and also during evolutionary processes. While not exhaustive, this review attempts to categorize existing methods and to indicate their relation with broader transversal topics such as genomic signatures, data compression and complexity, time series analysis and phylogenetic classification, providing a resource for future developments in this promising area.

TotalReCaller: improved accuracy and performance via integrated alignment and base-calling.

PubMed

Menges, Fabian; Narzisi, Giuseppe; Mishra, Bud

2011-09-01

Currently, re-sequencing approaches use multiple modules serially to interpret raw sequencing data from next-generation sequencing platforms, while remaining oblivious to the genomic information until the final alignment step. Such approaches fail to exploit the full information from both raw sequencing data and the reference genome that can yield better quality sequence reads, SNP-calls, variant detection, as well as an alignment at the best possible location in the reference genome. Thus, there is a need for novel reference-guided bioinformatics algorithms for interpreting analog signals representing sequences of the bases ({A, C, G, T}), while simultaneously aligning possible sequence reads to a source reference genome whenever available. Here, we propose a new base-calling algorithm, TotalReCaller, to achieve improved performance. A linear error model for the raw intensity data and Burrows-Wheeler transform (BWT) based alignment are combined utilizing a Bayesian score function, which is then globally optimized over all possible genomic locations using an efficient branch-and-bound approach. The algorithm has been implemented in soft- and hardware [field-programmable gate array (FPGA)] to achieve real-time performance. Empirical results on real high-throughput Illumina data were used to evaluate TotalReCaller's performance relative to its peers-Bustard, BayesCall, Ibis and Rolexa-based on several criteria, particularly those important in clinical and scientific applications. Namely, it was evaluated for (i) its base-calling speed and throughput, (ii) its read accuracy and (iii) its specificity and sensitivity in variant calling. A software implementation of TotalReCaller as well as additional information, is available at: http://bioinformatics.nyu.edu/wordpress/projects/totalrecaller/ fabian.menges@nyu.edu.

cljam: a library for handling DNA sequence alignment/map (SAM) with parallel processing.

PubMed

Takeuchi, Toshiki; Yamada, Atsuo; Aoki, Takashi; Nishimura, Kunihiro

2016-01-01

Next-generation sequencing can determine DNA bases and the results of sequence alignments are generally stored in files in the Sequence Alignment/Map (SAM) format and the compressed binary version (BAM) of it. SAMtools is a typical tool for dealing with files in the SAM/BAM format. SAMtools has various functions, including detection of variants, visualization of alignments, indexing, extraction of parts of the data and loci, and conversion of file formats. It is written in C and can execute fast. However, SAMtools requires an additional implementation to be used in parallel with, for example, OpenMP (Open Multi-Processing) libraries. For the accumulation of next-generation sequencing data, a simple parallelization program, which can support cloud and PC cluster environments, is required. We have developed cljam using the Clojure programming language, which simplifies parallel programming, to handle SAM/BAM data. Cljam can run in a Java runtime environment (e.g., Windows, Linux, Mac OS X) with Clojure. Cljam can process and analyze SAM/BAM files in parallel and at high speed. The execution time with cljam is almost the same as with SAMtools. The cljam code is written in Clojure and has fewer lines than other similar tools.

PCV: An Alignment Free Method for Finding Homologous Nucleotide Sequences and its Application in Phylogenetic Study.

PubMed

Kumar, Rajnish; Mishra, Bharat Kumar; Lahiri, Tapobrata; Kumar, Gautam; Kumar, Nilesh; Gupta, Rahul; Pal, Manoj Kumar

2017-06-01

Online retrieval of the homologous nucleotide sequences through existing alignment techniques is a common practice against the given database of sequences. The salient point of these techniques is their dependence on local alignment techniques and scoring matrices the reliability of which is limited by computational complexity and accuracy. Toward this direction, this work offers a novel way for numerical representation of genes which can further help in dividing the data space into smaller partitions helping formation of a search tree. In this context, this paper introduces a 36-dimensional Periodicity Count Value (PCV) which is representative of a particular nucleotide sequence and created through adaptation from the concept of stochastic model of Kolekar et al. (American Institute of Physics 1298:307-312, 2010. doi: 10.1063/1.3516320 ). The PCV construct uses information on physicochemical properties of nucleotides and their positional distribution pattern within a gene. It is observed that PCV representation of gene reduces computational cost in the calculation of distances between a pair of genes while being consistent with the existing methods. The validity of PCV-based method was further tested through their use in molecular phylogeny constructs in comparison with that using existing sequence alignment methods.

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

PubMed Central

Budavari, Tamas; Langmead, Ben; Wheelan, Sarah J.; Salzberg, Steven L.; Szalay, Alexander S.

2015-01-01

When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU) hardware.We followed this approach in implementing a read aligner called Arioc that uses GPU-based parallel sort and reduction techniques to identify high-priority locations where potential alignments may be found. We then carried out a read-by-read comparison of Arioc’s reported alignments with the alignments found by several leading read aligners. With simulated reads, Arioc has comparable or better accuracy than the other read aligners we tested. With human sequencing reads, Arioc demonstrates significantly greater throughput than the other aligners we evaluated across a wide range of sensitivity settings. The Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license. PMID:25780763

Sequence and phylogenetic analysis of chicken anaemia virus obtained from backyard and commercial chickens in Nigeria.

PubMed

Oluwayelu, D O; Todd, D; Olaleye, O D

2008-12-01

This work reports the first molecular analysis study of chicken anaemia virus (CAV) in backyard chickens in Africa using molecular cloning and sequence analysis to characterize CAV strains obtained from commercial chickens and Nigerian backyard chickens. Partial VP1 gene sequences were determined for three CAVs from commercial chickens and for six CAV variants present in samples from a backyard chicken. Multiple alignment analysis revealed that the 6% and 4% nucleotide diversity obtained respectively for the commercial and backyard chicken strains translated to only 2% amino acid diversity for each breed. Overall, the amino acid composition of Nigerian CAVs was found to be highly conserved. Since the partial VP1 gene sequence of two backyard chicken cloned CAV strains (NGR/CI-8 and NGR/CI-9) were almost identical and evolutionarily closely related to the commercial chicken strains NGR-1, and NGR-4 and NGR-5, respectively, we concluded that CAV infections had crossed the farm boundary.

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis.

PubMed

Cornwell, MacIntosh; Vangala, Mahesh; Taing, Len; Herbert, Zachary; Köster, Johannes; Li, Bo; Sun, Hanfei; Li, Taiwen; Zhang, Jian; Qiu, Xintao; Pun, Matthew; Jeselsohn, Rinath; Brown, Myles; Liu, X Shirley; Long, Henry W

2018-04-12

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences

PubMed Central

2017-01-01

Abstract Motifs of only 1–4 letters can play important roles when present at key locations within macromolecules. Because existing motif-discovery tools typically miss these position-specific short motifs, we developed kpLogo, a probability-based logo tool for integrated detection and visualization of position-specific ultra-short motifs from a set of aligned sequences. kpLogo also overcomes the limitations of conventional motif-visualization tools in handling positional interdependencies and utilizing ranked or weighted sequences increasingly available from high-throughput assays. kpLogo can be found at http://kplogo.wi.mit.edu/. PMID:28460012

Establishing homologies in protein sequences

NASA Technical Reports Server (NTRS)

Dayhoff, M. O.; Barker, W. C.; Hunt, L. T.

1983-01-01

Computer-based statistical techniques used to determine homologies between proteins occurring in different species are reviewed. The technique is based on comparison of two protein sequences, either by relating all segments of a given length in one sequence to all segments of the second or by finding the best alignment of the two sequences. Approaches discussed include selection using printed tabulations, identification of very similar sequences, and computer searches of a database. The use of the SEARCH, RELATE, and ALIGN programs (Dayhoff, 1979) is explained; sample data are presented in graphs, diagrams, and tables and the construction of scoring matrices is considered.

[Hydrophidae identification through analysis on Cyt b gene barcode].

PubMed

Liao, Li-xi; Zeng, Ke-wu; Tu, Peng-fei

2015-08-01

Hydrophidae, one of the precious traditional Chinese medicines, is generally drily preserved to prevent corruption, but it is hard to identify the species of Hydrophidae through the appearance because of the change due to the drying process. The identification through analysis on gene barcode, a new technique in species identification, can avoid the problem. The gene barcodes of the 6 species of Hydrophidae like Lapemis hardwickii were aquired through DNA extraction and gene sequencing. These barcodes were then in sequence alignment and test the identification efficency by BLAST. Our results revealed that the barcode sequences performed high identification efficiency, and had obvious difference between intra- and inter-species. These all indicated that Cyt b DNA barcoding can confirm the Hydrophidae identification.

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

DOE PAGES

McNair, Katelyn; Edwards, Robert A.

2015-06-16

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping errormore » rates low, as well as offering unique data visualization options.« less

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring

PubMed Central

2012-01-01

Background Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. Results The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Conclusions Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family. PMID:22793672

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.

PubMed

Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl

2012-07-13

Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family.

RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproduction-related genes.

PubMed

Lan, DaoLiang; Xiong, XianRong; Wei, YanLi; Xu, Tong; Zhong, JinCheng; Zhi, XiangDong; Wang, Yong; Li, Jian

2014-09-01

RNA-Seq, a high-throughput (HT) sequencing technique, has been used effectively in large-scale transcriptomic studies, and is particularly useful for improving gene structure information and mining of new genes. In this study, RNA-Seq HT technology was employed to analyze the transcriptome of yak ovary. After Illumina-Solexa deep sequencing, 26826516 clean reads with a total of 4828772880 bp were obtained from the ovary library. Alignment analysis showed that 16992 yak genes mapped to the yak genome and 3734 of these genes were involved in alternative splicing. Gene structure refinement analysis showed that 7340 genes that were annotated in the yak genome could be extended at the 5' or 3' ends based on the alignments been the transcripts and the genome sequence. Novel transcript prediction analysis identified 6321 new transcripts with lengths ranging from 180 to 14884 bp, and 2267 of them were predicted to code proteins. BLAST analysis of the new transcripts showed that 1200?4933 mapped to the non-redundant (nr), nucleotide (nt) and/or SwissProt sequence databases. Comparative statistical analysis of the new mapped transcripts showed that the majority of them were similar to genes in Bos taurus (41.4%), Bos grunniens mutus (33.0%), Ovis aries (6.3%), Homo sapiens (2.8%), Mus musculus (1.6%) and other species. Functional analysis showed that these expressed genes were involved in various Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes pathways. GO analysis of the new transcripts found that the largest proportion of them was associated with reproduction. The results of this study will provide a basis for describing the normal transcriptome map of yak ovary and for future studies on yak breeding performance. Moreover, the results confirmed that RNA-Seq HT technology is highly advantageous in improving gene structure information and mining of new genes, as well as in providing valuable data to expand the yak genome information.

Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

DOE PAGES

Tian, Wenhong; Samatova, Nagiza F.

2013-01-01

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based onmore » a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.« less

CoSMoS: Conserved Sequence Motif Search in the proteome

PubMed Central

Liu, Xiao I; Korde, Neeraj; Jakob, Ursula; Leichert, Lars I

2006-01-01

Background With the ever-increasing number of gene sequences in the public databases, generating and analyzing multiple sequence alignments becomes increasingly time consuming. Nevertheless it is a task performed on a regular basis by researchers in many labs. Results We have now created a database called CoSMoS to find the occurrences and at the same time evaluate the significance of sequence motifs and amino acids encoded in the whole genome of the model organism Escherichia coli K12. We provide a precomputed set of multiple sequence alignments for each individual E. coli protein with all of its homologues in the RefSeq database. The alignments themselves, information about the occurrence of sequence motifs together with information on the conservation of each of the more than 1.3 million amino acids encoded in the E. coli genome can be accessed via the web interface of CoSMoS. Conclusion CoSMoS is a valuable tool to identify highly conserved sequence motifs, to find regions suitable for mutational studies in functional analyses and to predict important structural features in E. coli proteins. PMID:16433915

Combining conversation analysis and event sequencing to study health communication.

PubMed

Pecanac, Kristen E

2018-06-01

Good communication is essential in patient-centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision-making regarding life-sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed-methods approach to identify beneficial conversational practices and design interventions to improve health communication. © 2018 Wiley Periodicals, Inc.

In silico analysis of subtilisin from Glaciozyma antarctica PI12

NASA Astrophysics Data System (ADS)

Mustafha, Siti Mardhiah; Murad, Abdul Munir Abdul; Mahadi, Nor Muhammad; Kamaruddin, Shazilah; Bakar, Farah Diba Abu

2015-09-01

Subtilisin constitute as a major player in industrial enzymes that has a wide range of application especially in the detergent industry. In this study, a cDNA encoding for subtilisin (GaSUBT) was extracted from the psychrophilic yeast, Glaciozyma antarctica PI12, PCR amplified and sequenced. Various bioinformatics tools were used to characterize the GaSUBT. GaSUBT contains 1587 bp nucleotides encoding for 529 amino acids. The predicted molecular weight of the deduced protein is 55.34 kDa with an isoelectric point of 6.25. GaSUBT was predicted to possess a signal peptide and pro-peptide consisting of a peptidase inhibitor I9 sequence. From the sequence alignment analysis of deduced amino acids with other subtilisins in the NCBI database showed that the sequences surrounding the catalytic triad that forms the catalytic domain are well conserved.

Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files.

PubMed

Finney, Richard P; Chen, Qing-Rong; Nguyen, Cu V; Hsu, Chih Hao; Yan, Chunhua; Hu, Ying; Abawi, Massih; Bian, Xiaopeng; Meerzaman, Daoud M

2015-01-01

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview. The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview.

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances.

PubMed

Domazet-Lošo, Mirjana; Domazet-Lošo, Tomislav

2016-01-01

Prokaryotic and viral genomes are often altered by recombination and horizontal gene transfer. The existing methods for detecting recombination are primarily aimed at viral genomes or sets of loci, since the expensive computation of underlying statistical models often hinders the comparison of complete prokaryotic genomes. As an alternative, alignment-free solutions are more efficient, but cannot map (align) a query to subject genomes. To address this problem, we have developed gmos (Genome MOsaic Structure), a new program that determines the mosaic structure of query genomes when compared to a set of closely related subject genomes. The program first computes local alignments between query and subject genomes and then reconstructs the query mosaic structure by choosing the best local alignment for each query region. To accomplish the analysis quickly, the program mostly relies on pairwise alignments and constructs multiple sequence alignments over short overlapping subject regions only when necessary. This fine-tuned implementation achieves an efficiency comparable to an alignment-free tool. The program performs well for simulated and real data sets of closely related genomes and can be used for fast recombination detection; for instance, when a new prokaryotic pathogen is discovered. As an example, gmos was used to detect genome mosaicism in a pathogenic Enterococcus faecium strain compared to seven closely related genomes. The analysis took less than two minutes on a single 2.1 GHz processor. The output is available in fasta format and can be visualized using an accessory program, gmosDraw (freely available with gmos).

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances

PubMed Central

Domazet-Lošo, Mirjana; Domazet-Lošo, Tomislav

2016-01-01

Prokaryotic and viral genomes are often altered by recombination and horizontal gene transfer. The existing methods for detecting recombination are primarily aimed at viral genomes or sets of loci, since the expensive computation of underlying statistical models often hinders the comparison of complete prokaryotic genomes. As an alternative, alignment-free solutions are more efficient, but cannot map (align) a query to subject genomes. To address this problem, we have developed gmos (Genome MOsaic Structure), a new program that determines the mosaic structure of query genomes when compared to a set of closely related subject genomes. The program first computes local alignments between query and subject genomes and then reconstructs the query mosaic structure by choosing the best local alignment for each query region. To accomplish the analysis quickly, the program mostly relies on pairwise alignments and constructs multiple sequence alignments over short overlapping subject regions only when necessary. This fine-tuned implementation achieves an efficiency comparable to an alignment-free tool. The program performs well for simulated and real data sets of closely related genomes and can be used for fast recombination detection; for instance, when a new prokaryotic pathogen is discovered. As an example, gmos was used to detect genome mosaicism in a pathogenic Enterococcus faecium strain compared to seven closely related genomes. The analysis took less than two minutes on a single 2.1 GHz processor. The output is available in fasta format and can be visualized using an accessory program, gmosDraw (freely available with gmos). PMID:27846272

RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries.

PubMed

Habegger, Lukas; Sboner, Andrea; Gianoulis, Tara A; Rozowsky, Joel; Agarwal, Ashish; Snyder, Michael; Gerstein, Mark

2011-01-15

The advent of next-generation sequencing for functional genomics has given rise to quantities of sequence information that are often so large that they are difficult to handle. Moreover, sequence reads from a specific individual can contain sufficient information to potentially identify and genetically characterize that person, raising privacy concerns. In order to address these issues, we have developed the Mapped Read Format (MRF), a compact data summary format for both short and long read alignments that enables the anonymization of confidential sequence information, while allowing one to still carry out many functional genomics studies. We have developed a suite of tools (RSEQtools) that use this format for the analysis of RNA-Seq experiments. These tools consist of a set of modules that perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads and segmenting that signal into actively transcribed regions. Moreover, the tools can readily be used to build customizable RNA-Seq workflows. In addition to the anonymization afforded by MRF, this format also facilitates the decoupling of the alignment of reads from downstream analyses. RSEQtools is implemented in C and the source code is available at http://rseqtools.gersteinlab.org/.

Global Network Alignment in the Context of Aging.

PubMed

Faisal, Fazle Elahi; Zhao, Han; Milenkovic, Tijana

2015-01-01

Analogous to sequence alignment, network alignment (NA) can be used to transfer biological knowledge across species between conserved network regions. NA faces two algorithmic challenges: 1) Which cost function to use to capture "similarities" between nodes in different networks? 2) Which alignment strategy to use to rapidly identify "high-scoring" alignments from all possible alignments? We "break down" existing state-of-the-art methods that use both different cost functions and different alignment strategies to evaluate each combination of their cost functions and alignment strategies. We find that a combination of the cost function of one method and the alignment strategy of another method beats the existing methods. Hence, we propose this combination as a novel superior NA method. Then, since human aging is hard to study experimentally due to long lifespan, we use NA to transfer aging-related knowledge from well annotated model species to poorly annotated human. By doing so, we produce novel human aging-related knowledge, which complements currently available knowledge about aging that has been obtained mainly by sequence alignment. We demonstrate significant similarity between topological and functional properties of our novel predictions and those of known aging-related genes. We are the first to use NA to learn more about aging.

A parallel approach of COFFEE objective function to multiple sequence alignment

NASA Astrophysics Data System (ADS)

Zafalon, G. F. D.; Visotaky, J. M. V.; Amorim, A. R.; Valêncio, C. R.; Neves, L. A.; de Souza, R. C. G.; Machado, J. M.

2015-09-01

The computational tools to assist genomic analyzes show even more necessary due to fast increasing of data amount available. With high computational costs of deterministic algorithms for sequence alignments, many works concentrate their efforts in the development of heuristic approaches to multiple sequence alignments. However, the selection of an approach, which offers solutions with good biological significance and feasible execution time, is a great challenge. Thus, this work aims to show the parallelization of the processing steps of MSA-GA tool using multithread paradigm in the execution of COFFEE objective function. The standard objective function implemented in the tool is the Weighted Sum of Pairs (WSP), which produces some distortions in the final alignments when sequences sets with low similarity are aligned. Then, in studies previously performed we implemented the COFFEE objective function in the tool to smooth these distortions. Although the nature of COFFEE objective function implies in the increasing of execution time, this approach presents points, which can be executed in parallel. With the improvements implemented in this work, we can verify the execution time of new approach is 24% faster than the sequential approach with COFFEE. Moreover, the COFFEE multithreaded approach is more efficient than WSP, because besides it is slightly fast, its biological results are better.

Sequence-similar, structure-dissimilar protein pairs in the PDB.

PubMed

Kosloff, Mickey; Kolodny, Rachel

2008-05-01

It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which "redundant" structures have been removed, based on a sequence-based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence-similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence-based structural superpositions and geometry-based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence-based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry-based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence-based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry-based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence-similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm).

Identification of true EST alignments for recognising transcribed regions.

PubMed

Ma, Chuang; Wang, Jia; Li, Lun; Duan, Mo-Jie; Zhou, Yan-Hong

2011-01-01

Transcribed regions can be determined by aligning Expressed Sequence Tags (ESTs) with genome sequences. The kernel of this strategy is to effectively distinguish true EST alignments from spurious ones. In this study, three measures including Direction Check, Identity Check and Terminal Check were introduced to more effectively eliminate spurious EST alignments. On the basis of these introduced measures and other widely used measures, a computational tool, named ESTCleanser, has been developed to identify true EST alignments for obtaining reliable transcribed regions. The performance of ESTCleanser has been evaluated on the well-annotated human ENCyclopedia of DNA Elements (ENCODE) regions using human ESTs in the dbEST database. The evaluation results show that the accuracy of ESTCleanser at exon and intron levels is more remarkably enhanced than that of UCSC-spliced EST alignments. This work would be helpful to EST-based researches on finding new genes, complementing genome annotation, recognising alternative splicing events and Single Nucleotide Polymorphisms (SNPs), etc.

Molecular Phylogenetics: Concepts for a Newcomer.

PubMed

Ajawatanawong, Pravech

Molecular phylogenetics is the study of evolutionary relationships among organisms using molecular sequence data. The aim of this review is to introduce the important terminology and general concepts of tree reconstruction to biologists who lack a strong background in the field of molecular evolution. Some modern phylogenetic programs are easy to use because of their user-friendly interfaces, but understanding the phylogenetic algorithms and substitution models, which are based on advanced statistics, is still important for the analysis and interpretation without a guide. Briefly, there are five general steps in carrying out a phylogenetic analysis: (1) sequence data preparation, (2) sequence alignment, (3) choosing a phylogenetic reconstruction method, (4) identification of the best tree, and (5) evaluating the tree. Concepts in this review enable biologists to grasp the basic ideas behind phylogenetic analysis and also help provide a sound basis for discussions with expert phylogeneticists.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Online interactive analysis of protein structure ensembles with Bio3D-web.

PubMed

Skjærven, Lars; Jariwala, Shashank; Yao, Xin-Qiu; Grant, Barry J

2016-11-15

Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics. Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no. © The Author 2016. Published by Oxford University Press.

CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping.

PubMed

Nguyen, Tung; Shi, Weisong; Ruden, Douglas

2011-06-06

Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80%) mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http://cloudaligner.sourceforge.net/ and its web version is at http://mine.cs.wayne.edu:8080/CloudAligner/. Our results show that CloudAligner is faster than CloudBurst, provides more accurate results than RMAP, and supports various input as well as output formats. In addition, with the web-based interface, it is easier to use than its counterparts.