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

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.

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/ .

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.

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.

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

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/.

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

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

LenVarDB: database of length-variant protein domains.

PubMed

Mutt, Eshita; Mathew, Oommen K; Sowdhamini, Ramanathan

2014-01-01

Protein domains are functionally and structurally independent modules, which add to the functional variety of proteins. This array of functional diversity has been enabled by evolutionary changes, such as amino acid substitutions or insertions or deletions, occurring in these protein domains. Length variations (indels) can introduce changes at structural, functional and interaction levels. LenVarDB (freely available at http://caps.ncbs.res.in/lenvardb/) traces these length variations, starting from structure-based sequence alignments in our Protein Alignments organized as Structural Superfamilies (PASS2) database, across 731 structural classification of proteins (SCOP)-based protein domain superfamilies connected to 2 730 625 sequence homologues. Alignment of sequence homologues corresponding to a structural domain is available, starting from a structure-based sequence alignment of the superfamily. Orientation of the length-variant (indel) regions in protein domains can be visualized by mapping them on the structure and on the alignment. Knowledge about location of length variations within protein domains and their visual representation will be useful in predicting changes within structurally or functionally relevant sites, which may ultimately regulate protein function. Non-technical summary: Evolutionary changes bring about natural changes to proteins that may be found in many organisms. Such changes could be reflected as amino acid substitutions or insertions-deletions (indels) in protein sequences. LenVarDB is a database that provides an early overview of observed length variations that were set among 731 protein families and after examining >2 million sequences. Indels are followed up to observe if they are close to the active site such that they can affect the activity of proteins. Inclusion of such information can aid the design of bioengineering experiments.

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

PubMed

Tan, Yen Hock; Huang, He; Kihara, Daisuke

2006-08-15

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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

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

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

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/

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

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

Robust prediction of consensus secondary structures using averaged base pairing probability matrices.

PubMed

Kiryu, Hisanori; Kin, Taishin; Asai, Kiyoshi

2007-02-15

Recent transcriptomic studies have revealed the existence of a considerable number of non-protein-coding RNA transcripts in higher eukaryotic cells. To investigate the functional roles of these transcripts, it is of great interest to find conserved secondary structures from multiple alignments on a genomic scale. Since multiple alignments are often created using alignment programs that neglect the special conservation patterns of RNA secondary structures for computational efficiency, alignment failures can cause potential risks of overlooking conserved stem structures. We investigated the dependence of the accuracy of secondary structure prediction on the quality of alignments. We compared three algorithms that maximize the expected accuracy of secondary structures as well as other frequently used algorithms. We found that one of our algorithms, called McCaskill-MEA, was more robust against alignment failures than others. The McCaskill-MEA method first computes the base pairing probability matrices for all the sequences in the alignment and then obtains the base pairing probability matrix of the alignment by averaging over these matrices. The consensus secondary structure is predicted from this matrix such that the expected accuracy of the prediction is maximized. We show that the McCaskill-MEA method performs better than other methods, particularly when the alignment quality is low and when the alignment consists of many sequences. Our model has a parameter that controls the sensitivity and specificity of predictions. We discussed the uses of that parameter for multi-step screening procedures to search for conserved secondary structures and for assigning confidence values to the predicted base pairs. The C++ source code that implements the McCaskill-MEA algorithm and the test dataset used in this paper are available at http://www.ncrna.org/papers/McCaskillMEA/. Supplementary data are available at Bioinformatics online.

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

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.

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

Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns

PubMed Central

2013-01-01

Background It is well known that the search for homologous RNAs is more effective if both sequence and structure information is incorporated into the search. However, current tools for searching with RNA sequence-structure patterns cannot fully handle mutations occurring on both these levels or are simply not fast enough for searching large sequence databases because of the high computational costs of the underlying sequence-structure alignment problem. Results We present new fast index-based and online algorithms for approximate matching of RNA sequence-structure patterns supporting a full set of edit operations on single bases and base pairs. Our methods efficiently compute semi-global alignments of structural RNA patterns and substrings of the target sequence whose costs satisfy a user-defined sequence-structure edit distance threshold. For this purpose, we introduce a new computing scheme to optimally reuse the entries of the required dynamic programming matrices for all substrings and combine it with a technique for avoiding the alignment computation of non-matching substrings. Our new index-based methods exploit suffix arrays preprocessed from the target database and achieve running times that are sublinear in the size of the searched sequences. To support the description of RNA molecules that fold into complex secondary structures with multiple ordered sequence-structure patterns, we use fast algorithms for the local or global chaining of approximate sequence-structure pattern matches. The chaining step removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our improved online algorithm is faster than the best previous method by up to factor 45. Our best new index-based algorithm achieves a speedup of factor 560. Conclusions The presented methods achieve considerable speedups compared to the best previous method. This, together with the expected sublinear running time of the presented index-based algorithms, allows for the first time approximate matching of RNA sequence-structure patterns in large sequence databases. Beyond the algorithmic contributions, we provide with RaligNAtor a robust and well documented open-source software package implementing the algorithms presented in this manuscript. The RaligNAtor software is available at http://www.zbh.uni-hamburg.de/ralignator. PMID:23865810

Phylo-mLogo: an interactive and hierarchical multiple-logo visualization tool for alignment of many sequences

PubMed Central

Shih, Arthur Chun-Chieh; Lee, DT; Peng, Chin-Lin; Wu, Yu-Wei

2007-01-01

Background When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences. Results A multiple-logo alignment visualization tool, called Phylo-mLogo, is presented in this paper. Phylo-mLogo calculates the variabilities and homogeneities of alignment sequences by base frequencies or entropies. Different from the traditional representations of sequence logos, Phylo-mLogo not only displays the global logo patterns of the whole alignment of multiple sequences, but also demonstrates their local homologous logos for each clade hierarchically. In addition, Phylo-mLogo also allows the user to focus only on the analysis of some important, structurally or functionally constrained sites in the alignment selected by the user or by built-in automatic calculation. Conclusion With Phylo-mLogo, the user can symbolically and hierarchically visualize hundreds of aligned sequences simultaneously and easily check the changes of their amino acid sites when analyzing many homologous/orthologous or influenza virus sequences. More information of Phylo-mLogo can be found at URL . PMID:17319966

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.

RaptorX server: a resource for template-based protein structure modeling.

PubMed

Källberg, Morten; Margaryan, Gohar; Wang, Sheng; Ma, Jianzhu; Xu, Jinbo

2014-01-01

Assigning functional properties to a newly discovered protein is a key challenge in modern biology. To this end, computational modeling of the three-dimensional atomic arrangement of the amino acid chain is often crucial in determining the role of the protein in biological processes. We present a community-wide web-based protocol, RaptorX server ( http://raptorx.uchicago.edu ), for automated protein secondary structure prediction, template-based tertiary structure modeling, and probabilistic alignment sampling.Given a target sequence, RaptorX server is able to detect even remotely related template sequences by means of a novel nonlinear context-specific alignment potential and probabilistic consistency algorithm. Using the protocol presented here it is thus possible to obtain high-quality structural models for many target protein sequences when only distantly related protein domains have experimentally solved structures. At present, RaptorX server can perform secondary and tertiary structure prediction of a 200 amino acid target sequence in approximately 30 min.

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.

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

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

Implementation of a parallel protein structure alignment service on cloud.

PubMed

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Implementation of a Parallel Protein Structure Alignment Service on Cloud

PubMed Central

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform. PMID:23671842

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.

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

PFAAT version 2.0: a tool for editing, annotating, and analyzing multiple sequence alignments.

PubMed

Caffrey, Daniel R; Dana, Paul H; Mathur, Vidhya; Ocano, Marco; Hong, Eun-Jong; Wang, Yaoyu E; Somaroo, Shyamal; Caffrey, Brian E; Potluri, Shobha; Huang, Enoch S

2007-10-11

By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis. Here we describe the release of PFAAT version 2.0, a tool for editing, analyzing, and annotating multiple sequence alignments. Support for multiple annotations is a key component of this release as it provides a framework for most of the new functionalities. The sequence annotations are accessible from the alignment and tree, where they are typically used to label sequences or hyperlink them to related databases. Sequence annotations can be created manually or extracted automatically from UniProt entries. Once a multiple sequence alignment is populated with sequence annotations, sequences can be easily selected and sorted through a sophisticated search dialog. The selected sequences can be further analyzed using statistical methods that explicitly model relationships between the sequence annotations and residue properties. Residue annotations are accessible from the alignment viewer and are typically used to designate binding sites or properties for a particular residue. Residue annotations are also searchable, and allow one to quickly select alignment columns for further sequence analysis, e.g. computing percent identities. Other features include: novel algorithms to compute sequence conservation, mapping conservation scores to a 3D structure in Jmol, displaying secondary structure elements, and sorting sequences by residue composition. PFAAT provides a framework whereby end-users can specify knowledge for a protein family in the form of annotation. The annotations can be combined with sophisticated analysis to test hypothesis that relate to sequence, structure and function.

The limits of protein sequence comparison?

PubMed Central

Pearson, William R; Sierk, Michael L

2010-01-01

Modern sequence alignment algorithms are used routinely to identify homologous proteins, proteins that share a common ancestor. Homologous proteins always share similar structures and often have similar functions. Over the past 20 years, sequence comparison has become both more sensitive, largely because of profile-based methods, and more reliable, because of more accurate statistical estimates. As sequence and structure databases become larger, and comparison methods become more powerful, reliable statistical estimates will become even more important for distinguishing similarities that are due to homology from those that are due to analogy (convergence). The newest sequence alignment methods are more sensitive than older methods, but more accurate statistical estimates are needed for their full power to be realized. PMID:15919194

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.

iPARTS2: an improved tool for pairwise alignment of RNA tertiary structures, version 2.

PubMed

Yang, Chung-Han; Shih, Cheng-Ting; Chen, Kun-Tze; Lee, Po-Han; Tsai, Ping-Han; Lin, Jian-Cheng; Yen, Ching-Yu; Lin, Tiao-Yin; Lu, Chin Lung

2016-07-08

Since its first release in 2010, iPARTS has become a valuable tool for globally or locally aligning two RNA 3D structures. It was implemented by a structural alphabet (SA)-based approach, which uses an SA of 23 letters to reduce RNA 3D structures into 1D sequences of SA letters and applies traditional sequence alignment to these SA-encoded sequences for determining their global or local similarity. In this version, we have re-implemented iPARTS into a new web server iPARTS2 by constructing a totally new SA, which consists of 92 elements with each carrying both information of base and backbone geometry for a representative nucleotide. This SA is significantly different from the one used in iPARTS, because the latter consists of only 23 elements with each carrying only the backbone geometry information of a representative nucleotide. Our experimental results have shown that iPARTS2 outperforms its previous version iPARTS and also achieves better accuracy than other popular tools, such as SARA, SETTER and RASS, in RNA alignment quality and function prediction. iPARTS2 takes as input two RNA 3D structures in the PDB format and outputs their global or local alignments with graphical display. iPARTS2 is now available online at http://genome.cs.nthu.edu.tw/iPARTS2/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

The protein structure prediction problem could be solved using the current PDB library

PubMed Central

Zhang, Yang; Skolnick, Jeffrey

2005-01-01

For single-domain proteins, we examine the completeness of the structures in the current Protein Data Bank (PDB) library for use in full-length model construction of unknown sequences. To address this issue, we employ a comprehensive benchmark set of 1,489 medium-size proteins that cover the PDB at the level of 35% sequence identity and identify templates by structure alignment. With homologous proteins excluded, we can always find similar folds to native with an average rms deviation (RMSD) from native of 2.5 Å with ≈82% alignment coverage. These template structures often contain a significant number of insertions/deletions. The tasser algorithm was applied to build full-length models, where continuous fragments are excised from the top-scoring templates and reassembled under the guide of an optimized force field, which includes consensus restraints taken from the templates and knowledge-based statistical potentials. For almost all targets (except for 2/1,489), the resultant full-length models have an RMSD to native below 6 Å (97% of them below 4 Å). On average, the RMSD of full-length models is 2.25 Å, with aligned regions improved from 2.5 Å to 1.88 Å, comparable with the accuracy of low-resolution experimental structures. Furthermore, starting from state-of-the-art structural alignments, we demonstrate a methodology that can consistently bring template-based alignments closer to native. These results are highly suggestive that the protein-folding problem can in principle be solved based on the current PDB library by developing efficient fold recognition algorithms that can recover such initial alignments. PMID:15653774

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.

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.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

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.

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.

Four RNA families with functional transient structures

PubMed Central

Zhu, Jing Yun A; Meyer, Irmtraud M

2015-01-01

Protein-coding and non-coding RNA transcripts perform a wide variety of cellular functions in diverse organisms. Several of their functional roles are expressed and modulated via RNA structure. A given transcript, however, can have more than a single functional RNA structure throughout its life, a fact which has been previously overlooked. Transient RNA structures, for example, are only present during specific time intervals and cellular conditions. We here introduce four RNA families with transient RNA structures that play distinct and diverse functional roles. Moreover, we show that these transient RNA structures are structurally well-defined and evolutionarily conserved. Since Rfam annotates one structure for each family, there is either no annotation for these transient structures or no such family. Thus, our alignments either significantly update and extend the existing Rfam families or introduce a new RNA family to Rfam. For each of the four RNA families, we compile a multiple-sequence alignment based on experimentally verified transient and dominant (dominant in terms of either the thermodynamic stability and/or attention received so far) RNA secondary structures using a combination of automated search via covariance model and manual curation. The first alignment is the Trp operon leader which regulates the operon transcription in response to tryptophan abundance through alternative structures. The second alignment is the HDV ribozyme which we extend to the 5′ flanking sequence. This flanking sequence is involved in the regulation of the transcript's self-cleavage activity. The third alignment is the 5′ UTR of the maturation protein from Levivirus which contains a transient structure that temporarily postpones the formation of the final inhibitory structure to allow translation of maturation protein. The fourth and last alignment is the SAM riboswitch which regulates the downstream gene expression by assuming alternative structures upon binding of SAM. All transient and dominant structures are mapped to our new alignments introduced here. PMID:25751035

Four RNA families with functional transient structures.

PubMed

Zhu, Jing Yun A; Meyer, Irmtraud M

2015-01-01

Protein-coding and non-coding RNA transcripts perform a wide variety of cellular functions in diverse organisms. Several of their functional roles are expressed and modulated via RNA structure. A given transcript, however, can have more than a single functional RNA structure throughout its life, a fact which has been previously overlooked. Transient RNA structures, for example, are only present during specific time intervals and cellular conditions. We here introduce four RNA families with transient RNA structures that play distinct and diverse functional roles. Moreover, we show that these transient RNA structures are structurally well-defined and evolutionarily conserved. Since Rfam annotates one structure for each family, there is either no annotation for these transient structures or no such family. Thus, our alignments either significantly update and extend the existing Rfam families or introduce a new RNA family to Rfam. For each of the four RNA families, we compile a multiple-sequence alignment based on experimentally verified transient and dominant (dominant in terms of either the thermodynamic stability and/or attention received so far) RNA secondary structures using a combination of automated search via covariance model and manual curation. The first alignment is the Trp operon leader which regulates the operon transcription in response to tryptophan abundance through alternative structures. The second alignment is the HDV ribozyme which we extend to the 5' flanking sequence. This flanking sequence is involved in the regulation of the transcript's self-cleavage activity. The third alignment is the 5' UTR of the maturation protein from Levivirus which contains a transient structure that temporarily postpones the formation of the final inhibitory structure to allow translation of maturation protein. The fourth and last alignment is the SAM riboswitch which regulates the downstream gene expression by assuming alternative structures upon binding of SAM. All transient and dominant structures are mapped to our new alignments introduced here.

R3D-2-MSA: the RNA 3D structure-to-multiple sequence alignment server

PubMed Central

Cannone, Jamie J.; Sweeney, Blake A.; Petrov, Anton I.; Gutell, Robin R.; Zirbel, Craig L.; Leontis, Neocles

2015-01-01

The RNA 3D Structure-to-Multiple Sequence Alignment Server (R3D-2-MSA) is a new web service that seamlessly links RNA three-dimensional (3D) structures to high-quality RNA multiple sequence alignments (MSAs) from diverse biological sources. In this first release, R3D-2-MSA provides manual and programmatic access to curated, representative ribosomal RNA sequence alignments from bacterial, archaeal, eukaryal and organellar ribosomes, using nucleotide numbers from representative atomic-resolution 3D structures. A web-based front end is available for manual entry and an Application Program Interface for programmatic access. Users can specify up to five ranges of nucleotides and 50 nucleotide positions per range. The R3D-2-MSA server maps these ranges to the appropriate columns of the corresponding MSA and returns the contents of the columns, either for display in a web browser or in JSON format for subsequent programmatic use. The browser output page provides a 3D interactive display of the query, a full list of sequence variants with taxonomic information and a statistical summary of distinct sequence variants found. The output can be filtered and sorted in the browser. Previous user queries can be viewed at any time by resubmitting the output URL, which encodes the search and re-generates the results. The service is freely available with no login requirement at http://rna.bgsu.edu/r3d-2-msa. PMID:26048960

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.

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.

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.

AlignMe—a membrane protein sequence alignment web server

PubMed Central

Stamm, Marcus; Staritzbichler, René; Khafizov, Kamil; Forrest, Lucy R.

2014-01-01

We present a web server for pair-wise alignment of membrane protein sequences, using the program AlignMe. The server makes available two operational modes of AlignMe: (i) sequence to sequence alignment, taking two sequences in fasta format as input, combining information about each sequence from multiple sources and producing a pair-wise alignment (PW mode); and (ii) alignment of two multiple sequence alignments to create family-averaged hydropathy profile alignments (HP mode). For the PW sequence alignment mode, four different optimized parameter sets are provided, each suited to pairs of sequences with a specific similarity level. These settings utilize different types of inputs: (position-specific) substitution matrices, secondary structure predictions and transmembrane propensities from transmembrane predictions or hydrophobicity scales. In the second (HP) mode, each input multiple sequence alignment is converted into a hydrophobicity profile averaged over the provided set of sequence homologs; the two profiles are then aligned. The HP mode enables qualitative comparison of transmembrane topologies (and therefore potentially of 3D folds) of two membrane proteins, which can be useful if the proteins have low sequence similarity. In summary, the AlignMe web server provides user-friendly access to a set of tools for analysis and comparison of membrane protein sequences. Access is available at http://www.bioinfo.mpg.de/AlignMe PMID:24753425

Indel PDB: a database of structural insertions and deletions derived from sequence alignments of closely related proteins.

PubMed

Hsing, Michael; Cherkasov, Artem

2008-06-25

Insertions and deletions (indels) represent a common type of sequence variations, which are less studied and pose many important biological questions. Recent research has shown that the presence of sizable indels in protein sequences may be indicative of protein essentiality and their role in protein interaction networks. Examples of utilization of indels for structure-based drug design have also been recently demonstrated. Nonetheless many structural and functional characteristics of indels remain less researched or unknown. We have created a web-based resource, Indel PDB, representing a structural database of insertions/deletions identified from the sequence alignments of highly similar proteins found in the Protein Data Bank (PDB). Indel PDB utilized large amounts of available structural information to characterize 1-, 2- and 3-dimensional features of indel sites. Indel PDB contains 117,266 non-redundant indel sites extracted from 11,294 indel-containing proteins. Unlike loop databases, Indel PDB features more indel sequences with secondary structures including alpha-helices and beta-sheets in addition to loops. The insertion fragments have been characterized by their sequences, lengths, locations, secondary structure composition, solvent accessibility, protein domain association and three dimensional structures. By utilizing the data available in Indel PDB, we have studied and presented here several sequence and structural features of indels. We anticipate that Indel PDB will not only enable future functional studies of indels, but will also assist protein modeling efforts and identification of indel-directed drug binding sites.

fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information

DTIC Science & Technology

2007-04-04

machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel

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/.

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.

Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

R3D-2-MSA: the RNA 3D structure-to-multiple sequence alignment server.

PubMed

Cannone, Jamie J; Sweeney, Blake A; Petrov, Anton I; Gutell, Robin R; Zirbel, Craig L; Leontis, Neocles

2015-07-01

The RNA 3D Structure-to-Multiple Sequence Alignment Server (R3D-2-MSA) is a new web service that seamlessly links RNA three-dimensional (3D) structures to high-quality RNA multiple sequence alignments (MSAs) from diverse biological sources. In this first release, R3D-2-MSA provides manual and programmatic access to curated, representative ribosomal RNA sequence alignments from bacterial, archaeal, eukaryal and organellar ribosomes, using nucleotide numbers from representative atomic-resolution 3D structures. A web-based front end is available for manual entry and an Application Program Interface for programmatic access. Users can specify up to five ranges of nucleotides and 50 nucleotide positions per range. The R3D-2-MSA server maps these ranges to the appropriate columns of the corresponding MSA and returns the contents of the columns, either for display in a web browser or in JSON format for subsequent programmatic use. The browser output page provides a 3D interactive display of the query, a full list of sequence variants with taxonomic information and a statistical summary of distinct sequence variants found. The output can be filtered and sorted in the browser. Previous user queries can be viewed at any time by resubmitting the output URL, which encodes the search and re-generates the results. The service is freely available with no login requirement at http://rna.bgsu.edu/r3d-2-msa. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Prediction of protein secondary structure content for the twilight zone sequences.

PubMed

Homaeian, Leila; Kurgan, Lukasz A; Ruan, Jishou; Cios, Krzysztof J; Chen, Ke

2007-11-15

Secondary protein structure carries information about local structural arrangements, which include three major conformations: alpha-helices, beta-strands, and coils. Significant majority of successful methods for prediction of the secondary structure is based on multiple sequence alignment. However, multiple alignment fails to provide accurate results when a sequence comes from the twilight zone, that is, it is characterized by low (<30%) homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation, called PSSC-core. The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands for sequences from the twilight zone. The PSSC-core method was tested and compared with two other state-of-the-art prediction methods on a set of 2187 twilight zone sequences. The results indicate that our method provides better predictions for both helix and strand content. The PSSC-core is shown to provide statistically significantly better results when compared with the competing methods, reducing the prediction error by 5-7% for helix and 7-9% for strand content predictions. The proposed feature-based sequence representation uses a comprehensive set of physicochemical properties that are custom-designed for each of the helix and strand content predictions. It includes composition and composition moment vectors, frequency of tetra-peptides associated with helical and strand conformations, various property-based groups like exchange groups, chemical groups of the side chains and hydrophobic group, auto-correlations based on hydrophobicity, side-chain masses, hydropathy, and conformational patterns for beta-sheets. The PSSC-core method provides an alternative for predicting the secondary structure content that can be used to validate and constrain results of other structure prediction methods. At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure. (c) 2007 Wiley-Liss, Inc.

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

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

A bacterial Argonaute with noncanonical guide RNA specificity

PubMed Central

Kaya, Emine; Doxzen, Kevin W.; Knoll, Kilian R.; Wilson, Ross C.; Strutt, Steven C.; Kranzusch, Philip J.; Doudna, Jennifer A.

2016-01-01

Eukaryotic Argonaute proteins induce gene silencing by small RNA-guided recognition and cleavage of mRNA targets. Although structural similarities between human and prokaryotic Argonautes are consistent with shared mechanistic properties, sequence and structure-based alignments suggested that Argonautes encoded within CRISPR-cas [clustered regularly interspaced short palindromic repeats (CRISPR)-associated] bacterial immunity operons have divergent activities. We show here that the CRISPR-associated Marinitoga piezophila Argonaute (MpAgo) protein cleaves single-stranded target sequences using 5′-hydroxylated guide RNAs rather than the 5′-phosphorylated guides used by all known Argonautes. The 2.0-Å resolution crystal structure of an MpAgo–RNA complex reveals a guide strand binding site comprising residues that block 5′ phosphate interactions. Using structure-based sequence alignment, we were able to identify other putative MpAgo-like proteins, all of which are encoded within CRISPR-cas loci. Taken together, our data suggest the evolution of an Argonaute subclass with noncanonical specificity for a 5′-hydroxylated guide. PMID:27035975

DsaV methyltransferase and its isoschizomers contain a conserved segment that is similar to the segment in Hhai methyltransferase that is in contact with DNA bases.

PubMed Central

Gopal, J; Yebra, M J; Bhagwat, A S

1994-01-01

The methyltransferase (MTase) in the DsaV restriction--modification system methylates within 5'-CCNGG sequences. We have cloned the gene for this MTase and determined its sequence. The predicted sequence of the MTase protein contains sequence motifs conserved among all cytosine-5 MTases and is most similar to other MTases that methylate CCNGG sequences, namely M.ScrFI and M.SsoII. All three MTases methylate the internal cytosine within their recognition sequence. The 'variable' region within the three enzymes that methylate CCNGG can be aligned with the sequences of two enzymes that methylate CCWGG sequences. Remarkably, two segments within this region contain significant similarity with the region of M.HhaI that is known to contact DNA bases. These alignments suggest that many cytosine-5 MTases are likely to interact with DNA using a similar structural framework. Images PMID:7971279

A greedy, graph-based algorithm for the alignment of multiple homologous gene lists.

PubMed

Fostier, Jan; Proost, Sebastian; Dhoedt, Bart; Saeys, Yvan; Demeester, Piet; Van de Peer, Yves; Vandepoele, Klaas

2011-03-15

Many comparative genomics studies rely on the correct identification of homologous genomic regions using accurate alignment tools. In such case, the alphabet of the input sequences consists of complete genes, rather than nucleotides or amino acids. As optimal multiple sequence alignment is computationally impractical, a progressive alignment strategy is often employed. However, such an approach is susceptible to the propagation of alignment errors in early pairwise alignment steps, especially when dealing with strongly diverged genomic regions. In this article, we present a novel accurate and efficient greedy, graph-based algorithm for the alignment of multiple homologous genomic segments, represented as ordered gene lists. Based on provable properties of the graph structure, several heuristics are developed to resolve local alignment conflicts that occur due to gene duplication and/or rearrangement events on the different genomic segments. The performance of the algorithm is assessed by comparing the alignment results of homologous genomic segments in Arabidopsis thaliana to those obtained by using both a progressive alignment method and an earlier graph-based implementation. Especially for datasets that contain strongly diverged segments, the proposed method achieves a substantially higher alignment accuracy, and proves to be sufficiently fast for large datasets including a few dozens of eukaryotic genomes. http://bioinformatics.psb.ugent.be/software. The algorithm is implemented as a part of the i-ADHoRe 3.0 package.

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.

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

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

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

PubMed

Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential information pertaining to an RBP, like overall function annotations, are provided. The web server can be accessed at the following link: http://caps.ncbs.res.in/rstrucfam .

An alternative view of protein fold space.

PubMed

Shindyalov, I N; Bourne, P E

2000-02-15

Comparing and subsequently classifying protein structures information has received significant attention concurrent with the increase in the number of experimentally derived 3-dimensional structures. Classification schemes have focused on biological function found within protein domains and on structure classification based on topology. Here an alternative view is presented that groups substructures. Substructures are long (50-150 residue) highly repetitive near-contiguous pieces of polypeptide chain that occur frequently in a set of proteins from the PDB defined as structurally non-redundant over the complete polypeptide chain. The substructure classification is based on a previously reported Combinatorial Extension (CE) algorithm that provides a significantly different set of structure alignments than those previously described, having, for example, only a 40% overlap with FSSP. Qualitatively the algorithm provides longer contiguous aligned segments at the price of a slightly higher root-mean-square deviation (rmsd). Clustering these alignments gives a discreet and highly repetitive set of substructures not detectable by sequence similarity alone. In some cases different substructures represent all or different parts of well known folds indicative of the Russian doll effect--the continuity of protein fold space. In other cases they fall into different structure and functional classifications. It is too early to determine whether these newly classified substructures represent new insights into the evolution of a structural framework important to many proteins. What is apparent from on-going work is that these substructures have the potential to be useful probes in finding remote sequence homology and in structure prediction studies. The characteristics of the complete all-by-all comparison of the polypeptide chains present in the PDB and details of the filtering procedure by pair-wise structure alignment that led to the emergent substructure gallery are discussed. Substructure classification, alignments, and tools to analyze them are available at http://cl.sdsc.edu/ce.html.

Template-Based Modeling of Protein-RNA Interactions

PubMed Central

Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

2016-01-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

PubMed Central

Li, Pinghao; Jiang, Xiaoqian; Wang, Shuang; Kim, Jihoon; Xiong, Hongkai; Ohno-Machado, Lucila

2014-01-01

Background and objective Short-read sequencing is becoming the standard of practice for the study of structural variants associated with disease. However, with the growth of sequence data largely surpassing reasonable storage capability, the biomedical community is challenged with the management, transfer, archiving, and storage of sequence data. Methods We developed Hierarchical mUlti-reference Genome cOmpression (HUGO), a novel compression algorithm for aligned reads in the sorted Sequence Alignment/Map (SAM) format. We first aligned short reads against a reference genome and stored exactly mapped reads for compression. For the inexact mapped or unmapped reads, we realigned them against different reference genomes using an adaptive scheme by gradually shortening the read length. Regarding the base quality value, we offer lossy and lossless compression mechanisms. The lossy compression mechanism for the base quality values uses k-means clustering, where a user can adjust the balance between decompression quality and compression rate. The lossless compression can be produced by setting k (the number of clusters) to the number of different quality values. Results The proposed method produced a compression ratio in the range 0.5–0.65, which corresponds to 35–50% storage savings based on experimental datasets. The proposed approach achieved 15% more storage savings over CRAM and comparable compression ratio with Samcomp (CRAM and Samcomp are two of the state-of-the-art genome compression algorithms). The software is freely available at https://sourceforge.net/projects/hierachicaldnac/with a General Public License (GPL) license. Limitation Our method requires having different reference genomes and prolongs the execution time for additional alignments. Conclusions The proposed multi-reference-based compression algorithm for aligned reads outperforms existing single-reference based algorithms. PMID:24368726

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/.

Insights into the fold organization of TIM barrel from interaction energy based structure networks.

PubMed

Vijayabaskar, M S; Vishveshwara, Saraswathi

2012-01-01

There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or "sequence conservation" as the basis for their understanding. Recently "interaction energy" based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the "interaction conservation" viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.

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.;

Defining and predicting structurally conserved regions in protein superfamilies

PubMed Central

Huang, Ivan K.; Grishin, Nick V.

2013-01-01

Motivation: The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment. Results: Using pairwise DaliLite alignments among a set of homologous structures, we devised a simple measure of structural conservation, termed structural conservation index (SCI). SCI was used to distinguish SCRs from non-SCRs. A database of SCRs was compiled from 386 SCOP superfamilies containing 6489 protein domains. Artificial neural networks were then trained to predict SCRs with various features deduced from a single structure and homologous sequences. Assessment of the predictions via a 5-fold cross-validation method revealed that predictions based on features derived from a single structure perform similarly to ones based on homologous sequences, while combining sequence and structural features was optimal in terms of accuracy (0.755) and Matthews correlation coefficient (0.476). These results suggest that even without information from multiple structures, it is still possible to effectively predict SCRs for a protein. Finally, inspection of the structures with the worst predictions pinpoints difficulties in SCR definitions. Availability: The SCR database and the prediction server can be found at http://prodata.swmed.edu/SCR. Contact: 91huangi@gmail.com or grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics Online PMID:23193223

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

Comparative Protein Structure Modeling Using MODELLER

PubMed Central

Webb, Benjamin; Sali, Andrej

2016-01-01

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. PMID:27322406

Towards Long-Range RNA Structure Prediction in Eukaryotic Genes.

PubMed

Pervouchine, Dmitri D

2018-06-15

The ability to form an intramolecular structure plays a fundamental role in eukaryotic RNA biogenesis. Proximate regions in the primary transcripts fold into a local secondary structure, which is then hierarchically assembled into a tertiary structure that is stabilized by RNA-binding proteins and long-range intramolecular base pairings. While the local RNA structure can be predicted reasonably well for short sequences, long-range structure at the scale of eukaryotic genes remains problematic from the computational standpoint. The aim of this review is to list functional examples of long-range RNA structures, to summarize current comparative methods of structure prediction, and to highlight their advances and limitations in the context of long-range RNA structures. Most comparative methods implement the “first-align-then-fold” principle, i.e., they operate on multiple sequence alignments, while functional RNA structures often reside in non-conserved parts of the primary transcripts. The opposite “first-fold-then-align” approach is currently explored to a much lesser extent. Developing novel methods in both directions will improve the performance of comparative RNA structure analysis and help discover novel long-range structures, their higher-order organization, and RNA⁻RNA interactions across the transcriptome.

Elman RNN based classification of proteins sequences on account of their mutual information.

PubMed

Mishra, Pooja; Nath Pandey, Paras

2012-10-21

In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening.

PubMed

Hu, Jun; Liu, Zi; Yu, Dong-Jun; Zhang, Yang

2018-02-15

Sequence-order independent structural comparison, also called structural alignment, of small ligand molecules is often needed for computer-aided virtual drug screening. Although many ligand structure alignment programs are proposed, most of them build the alignments based on rigid-body shape comparison which cannot provide atom-specific alignment information nor allow structural variation; both abilities are critical to efficient high-throughput virtual screening. We propose a novel ligand comparison algorithm, LS-align, to generate fast and accurate atom-level structural alignments of ligand molecules, through an iterative heuristic search of the target function that combines inter-atom distance with mass and chemical bond comparisons. LS-align contains two modules of Rigid-LS-align and Flexi-LS-align, designed for rigid-body and flexible alignments, respectively, where a ligand-size independent, statistics-based scoring function is developed to evaluate the similarity of ligand molecules relative to random ligand pairs. Large-scale benchmark tests are performed on prioritizing chemical ligands of 102 protein targets involving 1,415,871 candidate compounds from the DUD-E (Database of Useful Decoys: Enhanced) database, where LS-align achieves an average enrichment factor (EF) of 22.0 at the 1% cutoff and the AUC score of 0.75, which are significantly higher than other state-of-the-art methods. Detailed data analyses show that the advanced performance is mainly attributed to the design of the target function that combines structural and chemical information to enhance the sensitivity of recognizing subtle difference of ligand molecules and the introduces of structural flexibility that help capture the conformational changes induced by the ligand-receptor binding interactions. These data demonstrate a new avenue to improve the virtual screening efficiency through the development of sensitive ligand structural alignments. http://zhanglab.ccmb.med.umich.edu/LS-align/. njyudj@njust.edu.cn or zhng@umich.edu. Supplementary data are available at Bioinformatics online.

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

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

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...

A new graph-based method for pairwise global network alignment

PubMed Central

Klau, Gunnar W

2009-01-01

Background In addition to component-based comparative approaches, network alignments provide the means to study conserved network topology such as common pathways and more complex network motifs. Yet, unlike in classical sequence alignment, the comparison of networks becomes computationally more challenging, as most meaningful assumptions instantly lead to NP-hard problems. Most previous algorithmic work on network alignments is heuristic in nature. Results We introduce the graph-based maximum structural matching formulation for pairwise global network alignment. We relate the formulation to previous work and prove NP-hardness of the problem. Based on the new formulation we build upon recent results in computational structural biology and present a novel Lagrangian relaxation approach that, in combination with a branch-and-bound method, computes provably optimal network alignments. The Lagrangian algorithm alone is a powerful heuristic method, which produces solutions that are often near-optimal and – unlike those computed by pure heuristics – come with a quality guarantee. Conclusion Computational experiments on the alignment of protein-protein interaction networks and on the classification of metabolic subnetworks demonstrate that the new method is reasonably fast and has advantages over pure heuristics. Our software tool is freely available as part of the LISA library. PMID:19208162

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

ITS2 data corroborate a monophyletic chlorophycean DO-group (Sphaeropleales)

PubMed Central

2008-01-01

Background Within Chlorophyceae the ITS2 secondary structure shows an unbranched helix I, except for the 'Hydrodictyon' and the 'Scenedesmus' clade having a ramified first helix. The latter two are classified within the Sphaeropleales, characterised by directly opposed basal bodies in their flagellar apparatuses (DO-group). Previous studies could not resolve the taxonomic position of the 'Sphaeroplea' clade within the Chlorophyceae without ambiguity and two pivotal questions remain open: (1) Is the DO-group monophyletic and (2) is a branched helix I an apomorphic feature of the DO-group? In the present study we analysed the secondary structure of three newly obtained ITS2 sequences classified within the 'Sphaeroplea' clade and resolved sphaeroplealean relationships by applying different phylogenetic approaches based on a combined sequence-structure alignment. Results The newly obtained ITS2 sequences of Ankyra judayi, Atractomorpha porcata and Sphaeroplea annulina of the 'Sphaeroplea' clade do not show any branching in the secondary structure of their helix I. All applied phylogenetic methods highly support the 'Sphaeroplea' clade as a sister group to the 'core Sphaeropleales'. Thus, the DO-group is monophyletic. Furthermore, based on characteristics in the sequence-structure alignment one is able to distinguish distinct lineages within the green algae. Conclusion In green algae, a branched helix I in the secondary structure of the ITS2 evolves past the 'Sphaeroplea' clade. A branched helix I is an apomorph characteristic within the monophyletic DO-group. Our results corroborate the fundamental relevance of including the secondary structure in sequence analysis and phylogenetics. PMID:18655698

Improved measurements of RNA structure conservation with generalized centroid estimators.

PubMed

Okada, Yohei; Saito, Yutaka; Sato, Kengo; Sakakibara, Yasubumi

2011-01-01

Identification of non-protein-coding RNAs (ncRNAs) in genomes is a crucial task for not only molecular cell biology but also bioinformatics. Secondary structures of ncRNAs are employed as a key feature of ncRNA analysis since biological functions of ncRNAs are deeply related to their secondary structures. Although the minimum free energy (MFE) structure of an RNA sequence is regarded as the most stable structure, MFE alone could not be an appropriate measure for identifying ncRNAs since the free energy is heavily biased by the nucleotide composition. Therefore, instead of MFE itself, several alternative measures for identifying ncRNAs have been proposed such as the structure conservation index (SCI) and the base pair distance (BPD), both of which employ MFE structures. However, these measurements are unfortunately not suitable for identifying ncRNAs in some cases including the genome-wide search and incur high false discovery rate. In this study, we propose improved measurements based on SCI and BPD, applying generalized centroid estimators to incorporate the robustness against low quality multiple alignments. Our experiments show that our proposed methods achieve higher accuracy than the original SCI and BPD for not only human-curated structural alignments but also low quality alignments produced by CLUSTAL W. Furthermore, the centroid-based SCI on CLUSTAL W alignments is more accurate than or comparable with that of the original SCI on structural alignments generated with RAF, a high quality structural aligner, for which twofold expensive computational time is required on average. We conclude that our methods are more suitable for genome-wide alignments which are of low quality from the point of view on secondary structures than the original SCI and BPD.

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.

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.

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

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.

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.

ModeRNA: a tool for comparative modeling of RNA 3D structure

PubMed Central

Rother, Magdalena; Rother, Kristian; Puton, Tomasz; Bujnicki, Janusz M.

2011-01-01

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available. PMID:21300639

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/.

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 > ).

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.

Isosteric And Non-Isosteric Base Pairs In RNA Motifs: Molecular Dynamics And Bioinformatics Study Of The Sarcin-Ricin Internal Loop

PubMed Central

Havrila, Marek; Réblová, Kamila; Zirbel, Craig L.; Leontis, Neocles B.; Šponer, Jiří

2013-01-01

The Sarcin-Ricin RNA motif (SR motif) is one of the most prominent recurrent RNA building blocks that occurs in many different RNA contexts and folds autonomously, i.e., in a context-independent manner. In this study, we combined bioinformatics analysis with explicit-solvent molecular dynamics (MD) simulations to better understand the relation between the RNA sequence and the evolutionary patterns of SR motif. SHAPE probing experiment was also performed to confirm fidelity of MD simulations. We identified 57 instances of the SR motif in a non-redundant subset of the RNA X-ray structure database and analyzed their basepairing, base-phosphate, and backbone-backbone interactions. We extracted sequences aligned to these instances from large ribosomal RNA alignments to determine frequency of occurrence for different sequence variants. We then used a simple scoring scheme based on isostericity to suggest 10 sequence variants with highly variable expected degree of compatibility with the SR motif 3D structure. We carried out MD simulations of SR motifs with these base substitutions. Non isosteric base substitutions led to unstable structures, but so did isosteric substitutions which were unable to make key base-phosphate interactions. MD technique explains why some potentially isosteric SR motifs are not realized during evolution. We also found that inability to form stable cWW geometry is an important factor in case of the first base pair of the flexible region of the SR motif. Comparison of structural, bioinformatics, SHAPE probing and MD simulation data reveals that explicit solvent MD simulations neatly reflect viability of different sequence variants of the SR motif. Thus, MD simulations can efficiently complement bioinformatics tools in studies of conservation patterns of RNA motifs and provide atomistic insight into the role of their different signature interactions. PMID:24144333

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.

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.

Tree decomposition based fast search of RNA structures including pseudoknots in genomes.

PubMed

Song, Yinglei; Liu, Chunmei; Malmberg, Russell; Pan, Fangfang; Cai, Liming

2005-01-01

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.

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.

Evolutionary profiles derived from the QR factorization of multiple structural alignments gives an economy of information.

PubMed

O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-02-25

We present a new algorithm, based on the multidimensional QR factorization, to remove redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form Ax=b, was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q(H), is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.

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.

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

Inferences from structural comparison: flexibility, secondary structure wobble and sequence alignment optimization.

PubMed

Zhang, Gaihua; Su, Zhen

2012-01-01

Work on protein structure prediction is very useful in biological research. To evaluate their accuracy, experimental protein structures or their derived data are used as the 'gold standard'. However, as proteins are dynamic molecular machines with structural flexibility such a standard may be unreliable. To investigate the influence of the structure flexibility, we analysed 3,652 protein structures of 137 unique sequences from 24 protein families. The results showed that (1) the three-dimensional (3D) protein structures were not rigid: the root-mean-square deviation (RMSD) of the backbone Cα of structures with identical sequences was relatively large, with the average of the maximum RMSD from each of the 137 sequences being 1.06 Å; (2) the derived data of the 3D structure was not constant, e.g. the highest ratio of the secondary structure wobble site was 60.69%, with the sequence alignments from structural comparisons of two proteins in the same family sometimes being completely different. Proteins may have several stable conformations and the data derived from resolved structures as a 'gold standard' should be optimized before being utilized as criteria to evaluate the prediction methods, e.g. sequence alignment from structural comparison. Helix/β-sheet transition exists in normal free proteins. The coil ratio of the 3D structure could affect its resolution as determined by X-ray crystallography.

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.

Historian: accurate reconstruction of ancestral sequences and evolutionary rates.

PubMed

Holmes, Ian H

2017-04-15

Reconstruction of ancestral sequence histories, and estimation of parameters like indel rates, are improved by using explicit evolutionary models and summing over uncertain alignments. The previous best tool for this purpose (according to simulation benchmarks) was ProtPal, but this tool was too slow for practical use. Historian combines an efficient reimplementation of the ProtPal algorithm with performance-improving heuristics from other alignment tools. Simulation results on fidelity of rate estimation via ancestral reconstruction, along with evaluations on the structurally informed alignment dataset BAliBase 3.0, recommend Historian over other alignment tools for evolutionary applications. Historian is available at https://github.com/evoldoers/historian under the Creative Commons Attribution 3.0 US license. ihholmes+historian@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Conserved thioredoxin fold is present in Pisum sativum L. sieve element occlusion-1 protein

PubMed Central

Umate, Pavan; Tuteja, Renu

2010-01-01

Homology-based three-dimensional model for Pisum sativum sieve element occlusion 1 (Ps.SEO1) (forisomes) protein was constructed. A stretch of amino acids (residues 320 to 456) which is well conserved in all known members of forisomes proteins was used to model the 3D structure of Ps.SEO1. The structural prediction was done using Protein Homology/analogY Recognition Engine (PHYRE) web server. Based on studies of local sequence alignment, the thioredoxin-fold containing protein [Structural Classification of Proteins (SCOP) code d1o73a_], a member of the glutathione peroxidase family was selected as a template for modeling the spatial structure of Ps.SEO1. Selection was based on comparison of primary sequence, higher match quality and alignment accuracy. Motif 1 (EVF) is conserved in Ps.SEO1, Vicia faba (Vf.For1) and Medicago truncatula (MT.SEO3); motif 2 (KKED) is well conserved across all forisomes proteins and motif 3 (IGYIGNP) is conserved in Ps.SEO1 and Vf.For1. PMID:20404566

Sequence to Structure (S2S): display, manipulate and interconnect RNA data from sequence to structure.

PubMed

Jossinet, Fabrice; Westhof, Eric

2005-08-01

Efficient RNA sequence manipulations (such as multiple alignments) need to be constrained by rules of RNA structure folding. The structural knowledge has increased dramatically in the last years with the accumulation of several large RNA structures similar to those of the bacterial ribosome subunits. However, no tool in the RNA community provides an easy way to link and integrate progress made at the sequence level using the available three-dimensional information. Sequence to Structure (S2S) proposes a framework in which an user can easily display, manipulate and interconnect heterogeneous RNA data, such as multiple sequence alignments, secondary and tertiary structures. S2S has been implemented using the Java language and has been developed and tested under UNIX systems, such as Linux and MacOSX. S2S is available at http://bioinformatics.org/S2S/.

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.

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.

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.

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

Invariant glycines and prolines flanking in loops the strand beta 2 of various (alpha/beta)8-barrel enzymes: a hidden homology?

PubMed Central

Janecek, S.

1996-01-01

The question of parallel (alpha/beta)8-barrel fold evolution remains unclear, owing mainly to the lack of sequence homology throughout the amino acid sequences of (alpha/beta)8-barrel enzymes. The "classical" approaches used in the search for homologies among (alpha/beta)8-barrels (e.g., production of structurally based alignments) have yielded alignments perfect from the structural point of view, but the approaches have been unable to reveal the homologies. These are proposed to be "hidden" in (alpha/beta)8-barrel enzymes. The term "hidden homology" means that the alignment of sequence stretches proposed to be homologous need not be structurally fully satisfactory. This is due to the very long evolutionary history of all (alpha/beta)8-barrels. This work identifies so-called hidden homology around the strand beta 2 that is flanked by loops containing invariant glycines and prolines in 17 different (alpha/beta)8-barrel enzymes, i.e., roughly in half of all currently known (alpha/beta)8-barrel proteins. The search was based on the idea that a conserved sequence region of an (alpha/beta)8-barrel enzyme should be more or less conserved also in the equivalent part of the structure of the other enzymes with this folding motif, given their mutual evolutionary relatedness. For this purpose, the sequence region around the well-conserved second beta-strand of alpha-amylase flanked by the invariant glycine and proline (56_GFTAIWITP, Aspergillus oryzae alpha-amylase numbering), was used as the sequence-structural template. The proposal that the second beta-strand of (alpha/beta)8-barrel fold is important from the evolutionary point of view is strongly supported by the increasing trend of the observed beta 2-strand structural similarity for the pairs of (alpha/beta)8-barrel enzymes: alpha-amylase and the alpha-subunit of tryptophan synthase, alpha-amylase and mandelate racemase, and alpha-amylase and cyclodextrin glycosyltransferase. This trend is also in agreement with the existing evolutionary division of the entire family of (alpha/beta)8-barrel proteins. PMID:8762144

Invariant glycines and prolines flanking in loops the strand beta 2 of various (alpha/beta)8-barrel enzymes: a hidden homology?

PubMed

Janecek, S

1996-06-01

The question of parallel (alpha/beta)8-barrel fold evolution remains unclear, owing mainly to the lack of sequence homology throughout the amino acid sequences of (alpha/beta)8-barrel enzymes. The "classical" approaches used in the search for homologies among (alpha/beta)8-barrels (e.g., production of structurally based alignments) have yielded alignments perfect from the structural point of view, but the approaches have been unable to reveal the homologies. These are proposed to be "hidden" in (alpha/beta)8-barrel enzymes. The term "hidden homology" means that the alignment of sequence stretches proposed to be homologous need not be structurally fully satisfactory. This is due to the very long evolutionary history of all (alpha/beta)8-barrels. This work identifies so-called hidden homology around the strand beta 2 that is flanked by loops containing invariant glycines and prolines in 17 different (alpha/beta)8-barrel enzymes, i.e., roughly in half of all currently known (alpha/beta)8-barrel proteins. The search was based on the idea that a conserved sequence region of an (alpha/beta)8-barrel enzyme should be more or less conserved also in the equivalent part of the structure of the other enzymes with this folding motif, given their mutual evolutionary relatedness. For this purpose, the sequence region around the well-conserved second beta-strand of alpha-amylase flanked by the invariant glycine and proline (56_GFTAIWITP, Aspergillus oryzae alpha-amylase numbering), was used as the sequence-structural template. The proposal that the second beta-strand of (alpha/beta)8-barrel fold is important from the evolutionary point of view is strongly supported by the increasing trend of the observed beta 2-strand structural similarity for the pairs of (alpha/beta)8-barrel enzymes: alpha-amylase and the alpha-subunit of tryptophan synthase, alpha-amylase and mandelate racemase, and alpha-amylase and cyclodextrin glycosyltransferase. This trend is also in agreement with the existing evolutionary division of the entire family of (alpha/beta)8-barrel proteins.

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.

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.

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.

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.

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.

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.

Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

PubMed

Garrido-Martín, Diego; Pazos, Florencio

2018-02-27

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.

MultiSETTER: web server for multiple RNA structure comparison.

PubMed

Čech, Petr; Hoksza, David; Svozil, Daniel

2015-08-12

Understanding the architecture and function of RNA molecules requires methods for comparing and analyzing their tertiary and quaternary structures. While structural superposition of short RNAs is achievable in a reasonable time, large structures represent much bigger challenge. Therefore, we have developed a fast and accurate algorithm for RNA pairwise structure superposition called SETTER and implemented it in the SETTER web server. However, though biological relationships can be inferred by a pairwise structure alignment, key features preserved by evolution can be identified only from a multiple structure alignment. Thus, we extended the SETTER algorithm to the alignment of multiple RNA structures and developed the MultiSETTER algorithm. In this paper, we present the updated version of the SETTER web server that implements a user friendly interface to the MultiSETTER algorithm. The server accepts RNA structures either as the list of PDB IDs or as user-defined PDB files. After the superposition is computed, structures are visualized in 3D and several reports and statistics are generated. To the best of our knowledge, the MultiSETTER web server is the first publicly available tool for a multiple RNA structure alignment. The MultiSETTER server offers the visual inspection of an alignment in 3D space which may reveal structural and functional relationships not captured by other multiple alignment methods based either on a sequence or on secondary structure motifs.

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.

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.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

Web-Beagle: a web server for the alignment of RNA secondary structures.

PubMed

Mattei, Eugenio; Pietrosanto, Marco; Ferrè, Fabrizio; Helmer-Citterich, Manuela

2015-07-01

Web-Beagle (http://beagle.bio.uniroma2.it) is a web server for the pairwise global or local alignment of RNA secondary structures. The server exploits a new encoding for RNA secondary structure and a substitution matrix of RNA structural elements to perform RNA structural alignments. The web server allows the user to compute up to 10 000 alignments in a single run, taking as input sets of RNA sequences and structures or primary sequences alone. In the latter case, the server computes the secondary structure prediction for the RNAs on-the-fly using RNAfold (free energy minimization). The user can also compare a set of input RNAs to one of five pre-compiled RNA datasets including lncRNAs and 3' UTRs. All types of comparison produce in output the pairwise alignments along with structural similarity and statistical significance measures for each resulting alignment. A graphical color-coded representation of the alignments allows the user to easily identify structural similarities between RNAs. Web-Beagle can be used for finding structurally related regions in two or more RNAs, for the identification of homologous regions or for functional annotation. Benchmark tests show that Web-Beagle has lower computational complexity, running time and better performances than other available methods. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Phylogenic inference using alignment-free methods for applications in microbial community surveys using 16s rRNA gene

PubMed Central

2017-01-01

The diversity of microbiota is best explored by understanding the phylogenetic structure of the microbial communities. Traditionally, sequence alignment has been used for phylogenetic inference. However, alignment-based approaches come with significant challenges and limitations when massive amounts of data are analyzed. In the recent decade, alignment-free approaches have enabled genome-scale phylogenetic inference. Here we evaluate three alignment-free methods: ACS, CVTree, and Kr for phylogenetic inference with 16s rRNA gene data. We use a taxonomic gold standard to compare the accuracy of alignment-free phylogenetic inference with that of common microbiome-wide phylogenetic inference pipelines based on PyNAST and MUSCLE alignments with FastTree and RAxML. We re-simulate fecal communities from Human Microbiome Project data to evaluate the performance of the methods on datasets with properties of real data. Our comparisons show that alignment-free methods are not inferior to alignment-based methods in giving accurate and robust phylogenic trees. Moreover, consensus ensembles of alignment-free phylogenies are superior to those built from alignment-based methods in their ability to highlight community differences in low power settings. In addition, the overall running times of alignment-based and alignment-free phylogenetic inference are comparable. Taken together our empirical results suggest that alignment-free methods provide a viable approach for microbiome-wide phylogenetic inference. PMID:29136663

NoFold: RNA structure clustering without folding or alignment.

PubMed

Middleton, Sarah A; Kim, Junhyong

2014-11-01

Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures. © 2014 Middleton and Kim; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Correlations of nucleotide substitution rates and base composition of mammalian coding sequences with protein structure.

PubMed

Chiusano, M L; D'Onofrio, G; Alvarez-Valin, F; Jabbari, K; Colonna, G; Bernardi, G

1999-09-30

We investigated the relationships between the nucleotide substitution rates and the predicted secondary structures in the three states representation (alpha-helix, beta-sheet, and coil). The analysis was carried out on 34 alignments, each of which comprised sequences belonging to at least four different mammalian orders. The rates of synonymous substitution were found to be significantly different in regions predicted to be alpha-helix, beta-sheet, or coil. Likewise, the nonsynonymous rates also differ, although expectedly at a lower extent, in the three types of secondary structure, suggesting that different selective constraints associated with the different structures are affecting in a similar way the synonymous and nonsynonymous rates. Moreover, the base composition of the third codon positions is different in coding sequence regions corresponding to different secondary structures of proteins.

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.

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

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

Chakraborty, Sandeep; Rao, Basuthkar J.; Baker, Nathan A.

2013-04-01

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits themore » MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins.« less

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment

PubMed Central

2013-01-01

Background Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. Results In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Conclusion Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA. PMID:24564200

Fast discovery and visualization of conserved regions in DNA sequences using quasi-alignment.

PubMed

Nagar, Anurag; Hahsler, Michael

2013-01-01

Next Generation Sequencing techniques are producing enormous amounts of biological sequence data and analysis becomes a major computational problem. Currently, most analysis, especially the identification of conserved regions, relies heavily on Multiple Sequence Alignment and its various heuristics such as progressive alignment, whose run time grows with the square of the number and the length of the aligned sequences and requires significant computational resources. In this work, we present a method to efficiently discover regions of high similarity across multiple sequences without performing expensive sequence alignment. The method is based on approximating edit distance between segments of sequences using p-mer frequency counts. Then, efficient high-throughput data stream clustering is used to group highly similar segments into so called quasi-alignments. Quasi-alignments have numerous applications such as identifying species and their taxonomic class from sequences, comparing sequences for similarities, and, as in this paper, discovering conserved regions across related sequences. In this paper, we show that quasi-alignments can be used to discover highly similar segments across multiple sequences from related or different genomes efficiently and accurately. Experiments on a large number of unaligned 16S rRNA sequences obtained from the Greengenes database show that the method is able to identify conserved regions which agree with known hypervariable regions in 16S rRNA. Furthermore, the experiments show that the proposed method scales well for large data sets with a run time that grows only linearly with the number and length of sequences, whereas for existing multiple sequence alignment heuristics the run time grows super-linearly. Quasi-alignment-based algorithms can detect highly similar regions and conserved areas across multiple sequences. Since the run time is linear and the sequences are converted into a compact clustering model, we are able to identify conserved regions fast or even interactively using a standard PC. Our method has many potential applications such as finding characteristic signature sequences for families of organisms and studying conserved and variable regions in, for example, 16S rRNA.

Dinucleotide controlled null models for comparative RNA gene prediction.

PubMed

Gesell, Tanja; Washietl, Stefan

2008-05-27

Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: http://sourceforge.net/projects/sissiz.

G protein-coupled odorant receptors: From sequence to structure.

PubMed

de March, Claire A; Kim, Soo-Kyung; Antonczak, Serge; Goddard, William A; Golebiowski, Jérôme

2015-09-01

Odorant receptors (ORs) are the largest subfamily within class A G protein-coupled receptors (GPCRs). No experimental structural data of any OR is available to date and atomic-level insights are likely to be obtained by means of molecular modeling. In this article, we critically align sequences of ORs with those GPCRs for which a structure is available. Here, an alignment consistent with available site-directed mutagenesis data on various ORs is proposed. Using this alignment, the choice of the template is deemed rather minor for identifying residues that constitute the wall of the binding cavity or those involved in G protein recognition. © 2015 The Protein Society.

G protein-coupled odorant receptors: From sequence to structure

PubMed Central

de March, Claire A; Kim, Soo-Kyung; Antonczak, Serge; Goddard, William A; Golebiowski, Jérôme

2015-01-01

Odorant receptors (ORs) are the largest subfamily within class A G protein-coupled receptors (GPCRs). No experimental structural data of any OR is available to date and atomic-level insights are likely to be obtained by means of molecular modeling. In this article, we critically align sequences of ORs with those GPCRs for which a structure is available. Here, an alignment consistent with available site-directed mutagenesis data on various ORs is proposed. Using this alignment, the choice of the template is deemed rather minor for identifying residues that constitute the wall of the binding cavity or those involved in G protein recognition. PMID:26044705

CAFE: aCcelerated Alignment-FrEe sequence analysis.

PubMed

Lu, Yang Young; Tang, Kujin; Ren, Jie; Fuhrman, Jed A; Waterman, Michael S; Sun, Fengzhu

2017-07-03

Alignment-free genome and metagenome comparisons are increasingly important with the development of next generation sequencing (NGS) technologies. Recently developed state-of-the-art k-mer based alignment-free dissimilarity measures including CVTree, $d_2^*$ and $d_2^S$ are more computationally expensive than measures based solely on the k-mer frequencies. Here, we report a standalone software, aCcelerated Alignment-FrEe sequence analysis (CAFE), for efficient calculation of 28 alignment-free dissimilarity measures. CAFE allows for both assembled genome sequences and unassembled NGS shotgun reads as input, and wraps the output in a standard PHYLIP format. In downstream analyses, CAFE can also be used to visualize the pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. CAFE serves as a general k-mer based alignment-free analysis platform for studying the relationships among genomes and metagenomes, and is freely available at https://github.com/younglululu/CAFE. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Recapitulating phylogenies using k-mers: from trees to networks.

PubMed

Bernard, Guillaume; Ragan, Mark A; Chan, Cheong Xin

2016-01-01

Ernst Haeckel based his landmark Tree of Life on the supposed ontogenic recapitulation of phylogeny, i.e. that successive embryonic stages during the development of an organism re-trace the morphological forms of its ancestors over the course of evolution. Much of this idea has since been discredited. Today, phylogenies are often based on families of molecular sequences. The standard approach starts with a multiple sequence alignment, in which the sequences are arranged relative to each other in a way that maximises a measure of similarity position-by-position along their entire length. A tree (or sometimes a network) is then inferred. Rigorous multiple sequence alignment is computationally demanding, and evolutionary processes that shape the genomes of many microbes (bacteria, archaea and some morphologically simple eukaryotes) can add further complications. In particular, recombination, genome rearrangement and lateral genetic transfer undermine the assumptions that underlie multiple sequence alignment, and imply that a tree-like structure may be too simplistic. Here, using genome sequences of 143 bacterial and archaeal genomes, we construct a network of phylogenetic relatedness based on the number of shared k -mers (subsequences at fixed length k ). Our findings suggest that the network captures not only key aspects of microbial genome evolution as inferred from a tree, but also features that are not treelike. The method is highly scalable, allowing for investigation of genome evolution across a large number of genomes. Instead of using specific regions or sequences from genome sequences, or indeed Haeckel's idea of ontogeny, we argue that genome phylogenies can be inferred using k -mers from whole-genome sequences. Representing these networks dynamically allows biological questions of interest to be formulated and addressed quickly and in a visually intuitive manner.

Sequence similarities and evolutionary relationships of microbial, plant and animal alpha-amylases.

PubMed

Janecek, S

1994-09-01

Amino acid sequence comparison of 37 alpha-amylases from microbial, plant and animal sources was performed to identify their mutual sequence similarities in addition to the five already described conserved regions. These sequence regions were examined from structure/function and evolutionary perspectives. An unrooted evolutionary tree of alpha-amylases was constructed on a subset of 55 residues from the alignment of sequence similarities along with conserved regions. The most important new information extracted from the tree was as follows: (a) the close evolutionary relationship of Alteromonas haloplanctis alpha-amylase (thermolabile enzyme from an antarctic psychrotroph) with the already known group of homologous alpha-amylases from streptomycetes, Thermomonospora curvata, insects and mammals, and (b) the remarkable 40.1% identity between starch-saccharifying Bacillus subtilis alpha-amylase and the enzyme from the ruminal bacterium Butyrivibrio fibrisolvens, an alpha-amylase with an unusually large polypeptide chain (943 residues in the mature enzyme). Due to a very high degree of similarity, the whole amino acid sequences of three groups of alpha-amylases, namely (a) fungi and yeasts, (b) plants, and (c) A. haloplanctis, streptomycetes, T. curvata, insects and mammals, were aligned independently and their unrooted distance trees were calculated using these alignments. Possible rooting of the trees was also discussed. Based on the knowledge of the location of the five disulfide bonds in the structure of pig pancreatic alpha-amylase, the possible disulfide bridges were established for each of these groups of homologous alpha-amylases.

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/.

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

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation

PubMed Central

Casadio, Rita

2017-01-01

Abstract BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. PMID:28453653

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

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.

Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

PubMed Central

2010-01-01

Background In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA. Results Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection. Discussion The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction. PMID:20550657

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.

Evolutionarily conserved regions and hydrophobic contacts at the superfamily level: The case of the fold-type I, pyridoxal-5′-phosphate-dependent enzymes

PubMed Central

Paiardini, Alessandro; Bossa, Francesco; Pascarella, Stefano

2004-01-01

The wealth of biological information provided by structural and genomic projects opens new prospects of understanding life and evolution at the molecular level. In this work, it is shown how computational approaches can be exploited to pinpoint protein structural features that remain invariant upon long evolutionary periods in the fold-type I, PLP-dependent enzymes. A nonredundant set of 23 superposed crystallographic structures belonging to this superfamily was built. Members of this family typically display high-structural conservation despite low-sequence identity. For each structure, a multiple-sequence alignment of orthologous sequences was obtained, and the 23 alignments were merged using the structural information to obtain a comprehensive multiple alignment of 921 sequences of fold-type I enzymes. The structurally conserved regions (SCRs), the evolutionarily conserved residues, and the conserved hydrophobic contacts (CHCs) were extracted from this data set, using both sequence and structural information. The results of this study identified a structural pattern of hydrophobic contacts shared by all of the superfamily members of fold-type I enzymes and involved in native interactions. This profile highlights the presence of a nucleus for this fold, in which residues participating in the most conserved native interactions exhibit preferential evolutionary conservation, that correlates significantly (r = 0.70) with the extent of mean hydrophobic contact value of their apolar fraction. PMID:15498941

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.

MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

PubMed Central

Zhou, Quan

2017-01-01

An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples. PMID:28350876

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

Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology

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

Taylor, R.C.

This thesis involved the construction of (1) a grammar that incorporates knowledge on base invariancy and secondary structure in a molecule and (2) a parser engine that uses the grammar to position bases into the structural subunits of the molecule. These concepts were combined with a novel pinning technique to form a tool that semi-automates insertion of a new species into the alignment for the 16S rRNA molecule (a component of the ribosome) maintained by Dr. Carl Woese's group at the University of Illinois at Urbana. The tool was tested on species extracted from the alignment and on a groupmore » of entirely new species. The results were very encouraging, and the tool should be substantial aid to the curators of the 16S alignment. The construction of the grammar was itself automated, allowing application of the tool to alignments for other molecules. The logic programming language Prolog was used to construct all programs involved. The computational linguistics approach used here was found to be a useful way to attach the problem of insertion into an alignment.« less

Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology

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

Taylor, Ronald C.

This thesis involved the construction of (1) a grammar that incorporates knowledge on base invariancy and secondary structure in a molecule and (2) a parser engine that uses the grammar to position bases into the structural subunits of the molecule. These concepts were combined with a novel pinning technique to form a tool that semi-automates insertion of a new species into the alignment for the 16S rRNA molecule (a component of the ribosome) maintained by Dr. Carl Woese`s group at the University of Illinois at Urbana. The tool was tested on species extracted from the alignment and on a groupmore » of entirely new species. The results were very encouraging, and the tool should be substantial aid to the curators of the 16S alignment. The construction of the grammar was itself automated, allowing application of the tool to alignments for other molecules. The logic programming language Prolog was used to construct all programs involved. The computational linguistics approach used here was found to be a useful way to attach the problem of insertion into an alignment.« less

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/.

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.

Statistical Evaluation of the Rodin–Ohno Hypothesis: Sense/Antisense Coding of Ancestral Class I and II Aminoacyl-tRNA Synthetases

PubMed Central

Chandrasekaran, Srinivas Niranj; Yardimci, Galip Gürkan; Erdogan, Ozgün; Roach, Jeffrey; Carter, Charles W.

2013-01-01

We tested the idea that ancestral class I and II aminoacyl-tRNA synthetases arose on opposite strands of the same gene. We assembled excerpted 94-residue Urgenes for class I tryptophanyl-tRNA synthetase (TrpRS) and class II Histidyl-tRNA synthetase (HisRS) from a diverse group of species, by identifying and catenating three blocks coding for secondary structures that position the most highly conserved, active-site residues. The codon middle-base pairing frequency was 0.35 ± 0.0002 in all-by-all sense/antisense alignments for 211 TrpRS and 207 HisRS sequences, compared with frequencies between 0.22 ± 0.0009 and 0.27 ± 0.0005 for eight different representations of the null hypothesis. Clustering algorithms demonstrate further that profiles of middle-base pairing in the synthetase antisense alignments are correlated along the sequences from one species-pair to another, whereas this is not the case for similar operations on sets representing the null hypothesis. Most probable reconstructed sequences for ancestral nodes of maximum likelihood trees show that middle-base pairing frequency increases to approximately 0.42 ± 0.002 as bacterial trees approach their roots; ancestral nodes from trees including archaeal sequences show a less pronounced increase. Thus, contemporary and reconstructed sequences all validate important bioinformatic predictions based on descent from opposite strands of the same ancestral gene. They further provide novel evidence for the hypothesis that bacteria lie closer than archaea to the origin of translation. Moreover, the inverse polarity of genetic coding, together with a priori α-helix propensities suggest that in-frame coding on opposite strands leads to similar secondary structures with opposite polarity, as observed in TrpRS and HisRS crystal structures. PMID:23576570

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.

GenomeVista

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

Poliakov, Alexander; Couronne, Olivier

2002-11-04

Aligning large vertebrate genomes that are structurally complex poses a variety of problems not encountered on smaller scales. Such genomes are rich in repetitive elements and contain multiple segmental duplications, which increases the difficulty of identifying true orthologous SNA segments in alignments. The sizes of the sequences make many alignment algorithms designed for comparing single proteins extremely inefficient when processing large genomic intervals. We integrated both local and global alignment tools and developed a suite of programs for automatically aligning large vertebrate genomes and identifying conserved non-coding regions in the alignments. Our method uses the BLAT local alignment program tomore » find anchors on the base genome to identify regions of possible homology for a query sequence. These regions are postprocessed to find the best candidates which are then globally aligned using the AVID global alignment program. In the last step conserved non-coding segments are identified using VISTA. Our methods are fast and the resulting alignments exhibit a high degree of sensitivity, covering more than 90% of known coding exons in the human genome. The GenomeVISTA software is a suite of Perl programs that is built on a MySQL database platform. The scheduler gets control data from the database, builds a queve of jobs, and dispatches them to a PC cluster for execution. The main program, running on each node of the cluster, processes individual sequences. A Perl library acts as an interface between the database and the above programs. The use of a separate library allows the programs to function independently of the database schema. The library also improves on the standard Perl MySQL database interfere package by providing auto-reconnect functionality and improved error handling.« 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.

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.

SAbPred: a structure-based antibody prediction server

PubMed Central

Dunbar, James; Krawczyk, Konrad; Leem, Jinwoo; Marks, Claire; Nowak, Jaroslaw; Regep, Cristian; Georges, Guy; Kelm, Sebastian; Popovic, Bojana; Deane, Charlotte M.

2016-01-01

SAbPred is a server that makes predictions of the properties of antibodies focusing on their structures. Antibody informatics tools can help improve our understanding of immune responses to disease and aid in the design and engineering of therapeutic molecules. SAbPred is a single platform containing multiple applications which can: number and align sequences; automatically generate antibody variable fragment homology models; annotate such models with estimated accuracy alongside sequence and structural properties including potential developability issues; predict paratope residues; and predict epitope patches on protein antigens. The server is available at http://opig.stats.ox.ac.uk/webapps/sabpred. PMID:27131379

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.

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

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

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

PubMed

Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

2017-07-03

BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

PubMed Central

2012-01-01

Background The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches. Results Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day. Conclusions This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain annotation by identifying those pattern residues that most distinguish each protein domain subgroup from other related subgroups. PMID:22726767

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

[Comparative analysis of clustered regularly interspaced short palindromic repeats (CRISPRs) loci in the genomes of halophilic archaea].

PubMed

Zhang, Fan; Zhang, Bing; Xiang, Hua; Hu, Songnian

2009-11-01

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a widespread system that provides acquired resistance against phages in bacteria and archaea. Here we aim to genome-widely analyze the CRISPR in extreme halophilic archaea, of which the whole genome sequences are available at present time. We used bioinformatics methods including alignment, conservation analysis, GC content and RNA structure prediction to analyze the CRISPR structures of 7 haloarchaeal genomes. We identified the CRISPR structures in 5 halophilic archaea and revealed a conserved palindromic motif in the flanking regions of these CRISPR structures. In addition, we found that the repeat sequences of large CRISPR structures in halophilic archaea were greatly conserved, and two types of predicted RNA secondary structures derived from the repeat sequences were likely determined by the fourth base of the repeat sequence. Our results support the proposal that the leader sequence may function as recognition site by having palindromic structures in flanking regions, and the stem-loop secondary structure formed by repeat sequences may function in mediating the interaction between foreign genetic elements and CAS-encoded proteins.

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.

Detection and Alignment of 3D Domain Swapping Proteins Using Angle-Distance Image-Based Secondary Structural Matching Techniques

PubMed Central

Wang, Hsin-Wei; Hsu, Yen-Chu; Hwang, Jenn-Kang; Lyu, Ping-Chiang; Pai, Tun-Wen; Tang, Chuan Yi

2010-01-01

This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had “opened” their “closed” structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications. PMID:20976204

SA-Search: a web tool for protein structure mining based on a Structural Alphabet

PubMed Central

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-01-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search. PMID:15215446

SA-Search: a web tool for protein structure mining based on a Structural Alphabet.

PubMed

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-07-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search.

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.

Multiple sequence alignment in HTML: colored, possibly hyperlinked, compact representations.

PubMed

Campagne, F; Maigret, B

1998-02-01

Protein sequence alignments are widely used in protein structure prediction, protein engineering, modeling of proteins, etc. This type of representation is useful at different stages of scientific activity: looking at previous results, working on a research project, and presenting the results. There is a need to make it available through a network (intranet or WWW), in a way that allows biologists, chemists, and noncomputer specialists to look at the data and carry on research--possibly in a collaborative research. Previous methods (text-based, Java-based) are reported and their advantages are discussed. We have developed two novel approaches to represent the alignments as colored, hyper-linked HTML pages. The first method creates an HTML page that uses efficiently the image cache mechanism of a WWW browser, thereby allowing the user to browse different alignments without waiting for the images to be loaded through the network, but only for the first viewed alignment. The generated pages can be browsed with any HTML2.0-compliant browser. The second method that we propose uses W3C-CSS1-style sheets to render alignments. This new method generates pages that require recent browsers to be viewed. We implemented these methods in the Viseur program and made a WWW service available that allows a user to convert an MSF alignment file in HTML for WWW publishing. The latter service is available at http:@www.lctn.u-nancy.fr/viseur/services.htm l.

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.

SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform.

PubMed

Lin, Jie; Wei, Jing; Adjeroh, Donald; Jiang, Bing-Hua; Jiang, Yue

2018-05-02

Alignment-free sequence similarity analysis methods often lead to significant savings in computational time over alignment-based counterparts. A new alignment-free sequence similarity analysis method, called SSAW is proposed. SSAW stands for Sequence Similarity Analysis using the Stationary Discrete Wavelet Transform (SDWT). It extracts k-mers from a sequence, then maps each k-mer to a complex number field. Then, the series of complex numbers formed are transformed into feature vectors using the stationary discrete wavelet transform. After these steps, the original sequence is turned into a feature vector with numeric values, which can then be used for clustering and/or classification. Using two different types of applications, namely, clustering and classification, we compared SSAW against the the-state-of-the-art alignment free sequence analysis methods. SSAW demonstrates competitive or superior performance in terms of standard indicators, such as accuracy, F-score, precision, and recall. The running time was significantly better in most cases. These make SSAW a suitable method for sequence analysis, especially, given the rapidly increasing volumes of sequence data required by most modern applications.

De novo identification of highly diverged protein repeats by probabilistic consistency.

PubMed

Biegert, A; Söding, J

2008-03-15

An estimated 25% of all eukaryotic proteins contain repeats, which underlines the importance of duplication for evolving new protein functions. Internal repeats often correspond to structural or functional units in proteins. Methods capable of identifying diverged repeated segments or domains at the sequence level can therefore assist in predicting domain structures, inferring hypotheses about function and mechanism, and investigating the evolution of proteins from smaller fragments. We present HHrepID, a method for the de novo identification of repeats in protein sequences. It is able to detect the sequence signature of structural repeats in many proteins that have not yet been known to possess internal sequence symmetry, such as outer membrane beta-barrels. HHrepID uses HMM-HMM comparison to exploit evolutionary information in the form of multiple sequence alignments of homologs. In contrast to a previous method, the new method (1) generates a multiple alignment of repeats; (2) utilizes the transitive nature of homology through a novel merging procedure with fully probabilistic treatment of alignments; (3) improves alignment quality through an algorithm that maximizes the expected accuracy; (4) is able to identify different kinds of repeats within complex architectures by a probabilistic domain boundary detection method and (5) improves sensitivity through a new approach to assess statistical significance. Server: http://toolkit.tuebingen.mpg.de/hhrepid; Executables: ftp://ftp.tuebingen.mpg.de/pub/protevo/HHrepID

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

Efficient computation of the phylogenetic likelihood function on multi-gene alignments and multi-core architectures.

PubMed

Stamatakis, Alexandros; Ott, Michael

2008-12-27

The continuous accumulation of sequence data, for example, due to novel wet-laboratory techniques such as pyrosequencing, coupled with the increasing popularity of multi-gene phylogenies and emerging multi-core processor architectures that face problems of cache congestion, poses new challenges with respect to the efficient computation of the phylogenetic maximum-likelihood (ML) function. Here, we propose two approaches that can significantly speed up likelihood computations that typically represent over 95 per cent of the computational effort conducted by current ML or Bayesian inference programs. Initially, we present a method and an appropriate data structure to efficiently compute the likelihood score on 'gappy' multi-gene alignments. By 'gappy' we denote sampling-induced gaps owing to missing sequences in individual genes (partitions), i.e. not real alignment gaps. A first proof-of-concept implementation in RAXML indicates that this approach can accelerate inferences on large and gappy alignments by approximately one order of magnitude. Moreover, we present insights and initial performance results on multi-core architectures obtained during the transition from an OpenMP-based to a Pthreads-based fine-grained parallelization of the ML function.

Representation and alignment of sung queries for music information retrieval

NASA Astrophysics Data System (ADS)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

PubMed

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

@TOME-2: a new pipeline for comparative modeling of protein–ligand complexes

PubMed Central

Pons, Jean-Luc; Labesse, Gilles

2009-01-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein–protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein–ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/ PMID:19443448

Template-based structure modeling of protein-protein interactions

PubMed Central

Szilagyi, Andras; Zhang, Yang

2014-01-01

The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput experimental data. Nevertheless, bottlenecks exist due to the incompleteness of the proteinprotein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement. PMID:24721449

Comparative study of topological indices of macro/supramolecular RNA complex networks.

PubMed

Agüero-Chapín, Guillermín; Antunes, Agostinho; Ubeira, Florencio M; Chou, Kuo-Chen; González-Díaz, Humberto

2008-11-01

RNA function annotation is often based on alignment to a previously studied template. In contrast to the study of proteins, there are not many alignment-free methods to predict RNA functions if alignment fails. The use of topological indices (TIs) of RNA complex networks (CNs) to find quantitative structure-activity relationships (QSAR) may be an alternative to incorporate secondary structure or sequence-to-sequence similarity. Here, we introduce new QSAR-like techniques using RNA macromolecular CNs (mmCNs), where nodes are nucleotides, or RNA supramolecular CNs (smCNs), where nodes are RNA sequences. We studied a data set of 198 sequences including 18S-rRNAs (important phylogenetic molecular biomarkers). We constructed three types of RNA mmCNs: sequence-linear (SL), Cartesian-lattice (CL), and sequence-folding CNs (SF-CNs) and two smCNs: sequence-sequence disagreement CN (SSD) and sequence-sequence similarity (SSS-smCN). We reported the first comparative QSAR study with all these CIs and CNs, which includes: (i) spectral moments ( ( i )micro d ( w)) of SL-mmCNs (accuracy = 75.3%), (ii) electrostatic CIs (xi d ) of CL-mmCNs (>90%), (iii) thermodynamic parameters (Delta G, Delta H, Delta S, and T m) of SF-mmCNs (64.7%), (iv) disagreement-distribution moments ( M k ) of the SSD-smCN (79.3%), and (v) node centralities of the SSD-smCN (78.0%). Furthermore, we reported the experimental isolation of a new RNA sequence from Psidum guajava leaf tissue and its QSAR and BLAST prediction to illustrate the practical use of these methods. We also investigated the use of these CNs to explore rRNA diversity on bacteria, plants, and parasites from the Dactylogyrus genus. The HPL-mmCNs model was the best of all found. All the CNs and TIs, except SF-mmCNs, were introduced here by the first time for the QSAR study of RNA, which allowed a comparative study for RNA classification.

GATA: A graphic alignment tool for comparative sequenceanalysis

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

Nix, David A.; Eisen, Michael B.

2005-01-01

Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dotmore » plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.« less

CAFE: aCcelerated Alignment-FrEe sequence analysis

PubMed Central

Lu, Yang Young; Tang, Kujin; Ren, Jie; Fuhrman, Jed A.; Waterman, Michael S.

2017-01-01

Abstract Alignment-free genome and metagenome comparisons are increasingly important with the development of next generation sequencing (NGS) technologies. Recently developed state-of-the-art k-mer based alignment-free dissimilarity measures including CVTree, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$d_2^*$\\end{document} and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$d_2^S$\\end{document} are more computationally expensive than measures based solely on the k-mer frequencies. Here, we report a standalone software, aCcelerated Alignment-FrEe sequence analysis (CAFE), for efficient calculation of 28 alignment-free dissimilarity measures. CAFE allows for both assembled genome sequences and unassembled NGS shotgun reads as input, and wraps the output in a standard PHYLIP format. In downstream analyses, CAFE can also be used to visualize the pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. CAFE serves as a general k-mer based alignment-free analysis platform for studying the relationships among genomes and metagenomes, and is freely available at https://github.com/younglululu/CAFE. PMID:28472388

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.

Iterative non-sequential protein structural alignment.

PubMed

Salem, Saeed; Zaki, Mohammed J; Bystroff, Christopher

2009-06-01

Structural similarity between proteins gives us insights into their evolutionary relationships when there is low sequence similarity. In this paper, we present a novel approach called SNAP for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process consisting of a superposition step and an alignment step, until convergence. We propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of SNAP alignments were assessed by comparing against the manually curated reference alignments in the challenging SISY and RIPC datasets. Moreover, when applied to a dataset of 4410 protein pairs selected from the CATH database, SNAP produced longer alignments with lower rmsd than several state-of-the-art alignment methods. Classification of folds using SNAP alignments was both highly sensitive and highly selective. The SNAP software along with the datasets are available online at http://www.cs.rpi.edu/~zaki/software/SNAP.

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/.

Why Is There a Glass Ceiling for Threading Based Protein Structure Prediction Methods?

PubMed

Skolnick, Jeffrey; Zhou, Hongyi

2017-04-20

Despite their different implementations, comparison of the best threading approaches to the prediction of evolutionary distant protein structures reveals that they tend to succeed or fail on the same protein targets. This is true despite the fact that the structural template library has good templates for all cases. Thus, a key question is why are certain protein structures threadable while others are not. Comparison with threading results on a set of artificial sequences selected for stability further argues that the failure of threading is due to the nature of the protein structures themselves. Using a new contact map based alignment algorithm, we demonstrate that certain folds are highly degenerate in that they can have very similar coarse grained fractions of native contacts aligned and yet differ significantly from the native structure. For threadable proteins, this is not the case. Thus, contemporary threading approaches appear to have reached a plateau, and new approaches to structure prediction are required.

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.

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.

MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

PubMed

Lee, Wan-Ping; Stromberg, Michael P; Ward, Alistair; Stewart, Chip; Garrison, Erik P; Marth, Gabor T

2014-01-01

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me).

MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

PubMed Central

Lee, Wan-Ping; Stromberg, Michael P.; Ward, Alistair; Stewart, Chip; Garrison, Erik P.; Marth, Gabor T.

2014-01-01

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me). PMID:24599324

JDet: interactive calculation and visualization of function-related conservation patterns in multiple sequence alignments and structures.

PubMed

Muth, Thilo; García-Martín, Juan A; Rausell, Antonio; Juan, David; Valencia, Alfonso; Pazos, Florencio

2012-02-15

We have implemented in a single package all the features required for extracting, visualizing and manipulating fully conserved positions as well as those with a family-dependent conservation pattern in multiple sequence alignments. The program allows, among other things, to run different methods for extracting these positions, combine the results and visualize them in protein 3D structures and sequence spaces. JDet is a multiplatform application written in Java. It is freely available, including the source code, at http://csbg.cnb.csic.es/JDet. The package includes two of our recently developed programs for detecting functional positions in protein alignments (Xdet and S3Det), and support for other methods can be added as plug-ins. A help file and a guided tutorial for JDet are also available.

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.

Accurate estimation of short read mapping quality for next-generation genome sequencing

PubMed Central

Ruffalo, Matthew; Koyutürk, Mehmet; Ray, Soumya; LaFramboise, Thomas

2012-01-01

Motivation: Several software tools specialize in the alignment of short next-generation sequencing reads to a reference sequence. Some of these tools report a mapping quality score for each alignment—in principle, this quality score tells researchers the likelihood that the alignment is correct. However, the reported mapping quality often correlates weakly with actual accuracy and the qualities of many mappings are underestimated, encouraging the researchers to discard correct mappings. Further, these low-quality mappings tend to correlate with variations in the genome (both single nucleotide and structural), and such mappings are important in accurately identifying genomic variants. Approach: We develop a machine learning tool, LoQuM (LOgistic regression tool for calibrating the Quality of short read mappings, to assign reliable mapping quality scores to mappings of Illumina reads returned by any alignment tool. LoQuM uses statistics on the read (base quality scores reported by the sequencer) and the alignment (number of matches, mismatches and deletions, mapping quality score returned by the alignment tool, if available, and number of mappings) as features for classification and uses simulated reads to learn a logistic regression model that relates these features to actual mapping quality. Results: We test the predictions of LoQuM on an independent dataset generated by the ART short read simulation software and observe that LoQuM can ‘resurrect’ many mappings that are assigned zero quality scores by the alignment tools and are therefore likely to be discarded by researchers. We also observe that the recalibration of mapping quality scores greatly enhances the precision of called single nucleotide polymorphisms. Availability: LoQuM is available as open source at http://compbio.case.edu/loqum/. Contact: matthew.ruffalo@case.edu. PMID:22962451

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.

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

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

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.

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

Freiburg RNA tools: a central online resource for RNA-focused research and teaching.

PubMed

Raden, Martin; Ali, Syed M; Alkhnbashi, Omer S; Busch, Anke; Costa, Fabrizio; Davis, Jason A; Eggenhofer, Florian; Gelhausen, Rick; Georg, Jens; Heyne, Steffen; Hiller, Michael; Kundu, Kousik; Kleinkauf, Robert; Lott, Steffen C; Mohamed, Mostafa M; Mattheis, Alexander; Miladi, Milad; Richter, Andreas S; Will, Sebastian; Wolff, Joachim; Wright, Patrick R; Backofen, Rolf

2018-05-21

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

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

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.

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/

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.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Song, Jiangning; Burrage, Kevin; Yuan, Zheng; Huber, Thomas

2006-03-09

The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

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.

STING Millennium: a web-based suite of programs for comprehensive and simultaneous analysis of protein structure and sequence

PubMed Central

Neshich, Goran; Togawa, Roberto C.; Mancini, Adauto L.; Kuser, Paula R.; Yamagishi, Michel E. B.; Pappas, Georgios; Torres, Wellington V.; Campos, Tharsis Fonseca e; Ferreira, Leonardo L.; Luna, Fabio M.; Oliveira, Adilton G.; Miura, Ronald T.; Inoue, Marcus K.; Horita, Luiz G.; de Souza, Dimas F.; Dominiquini, Fabiana; Álvaro, Alexandre; Lima, Cleber S.; Ogawa, Fabio O.; Gomes, Gabriel B.; Palandrani, Juliana F.; dos Santos, Gabriela F.; de Freitas, Esther M.; Mattiuz, Amanda R.; Costa, Ivan C.; de Almeida, Celso L.; Souza, Savio; Baudet, Christian; Higa, Roberto H.

2003-01-01

STING Millennium Suite (SMS) is a new web-based suite of programs and databases providing visualization and a complex analysis of molecular sequence and structure for the data deposited at the Protein Data Bank (PDB). SMS operates with a collection of both publicly available data (PDB, HSSP, Prosite) and its own data (contacts, interface contacts, surface accessibility). Biologists find SMS useful because it provides a variety of algorithms and validated data, wrapped-up in a user friendly web interface. Using SMS it is now possible to analyze sequence to structure relationships, the quality of the structure, nature and volume of atomic contacts of intra and inter chain type, relative conservation of amino acids at the specific sequence position based on multiple sequence alignment, indications of folding essential residue (FER) based on the relationship of the residue conservation to the intra-chain contacts and Cα–Cα and Cβ–Cβ distance geometry. Specific emphasis in SMS is given to interface forming residues (IFR)—amino acids that define the interactive portion of the protein surfaces. SMS may simultaneously display and analyze previously superimposed structures. PDB updates trigger SMS updates in a synchronized fashion. SMS is freely accessible for public data at http://www.cbi.cnptia.embrapa.br, http://mirrors.rcsb.org/SMS and http://trantor.bioc.columbia.edu/SMS. PMID:12824333

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 .

Structure/Function Analyses of Human Serum Paraoxonase (HuPON1) Mutants Designed from a DFPase-Like Homology Model

DTIC Science & Technology

2004-08-23

purified HuPON1 Substitution of amino acid residues in the HuPONI enzyme was accomplished by PCR-based site-directed Two methods were utilized to...including organophosphates and lactones, and exhibits anti-atherogenic properties. A few amino acids have been shown to be essential for the enzyme’s...not been assigned to those residues. Based on scquence-structure alignment studies, we have folded the amino acid sequence of HuPON I onto the sixfold

Hidden Markov models-based system (HMMSPECTR) for detecting structural homologies on the basis of sequential information.

PubMed

Tsigelny, Igor; Sharikov, Yuriy; Ten Eyck, Lynn F

2002-05-01

HMMSPECTR is a tool for finding putative structural homologs for proteins with known primary sequences. HMMSPECTR contains four major components: a data warehouse with the hidden Markov models (HMM) and alignment libraries; a search program which compares the initial protein sequences with the libraries of HMMs; a secondary structure prediction and comparison program; and a dominant protein selection program that prepares the set of 10-15 "best" proteins from the chosen HMMs. The data warehouse contains four libraries of HMMs. The first two libraries were constructed using different HHM preparation options of the HAMMER program. The third library contains parts ("partial HMM") of initial alignments. The fourth library contains trained HMMs. We tested our program against all of the protein targets proposed in the CASP4 competition. The data warehouse included libraries of structural alignments and HMMs constructed on the basis of proteins publicly available in the Protein Data Bank before the CASP4 meeting. The newest fully automated versions of HMMSPECTR 1.02 and 1.02ss produced better results than the best result reported at CASP4 either by r.m.s.d. or by length (or both) in 64% (HMMSPECTR 1.02) and 79% (HMMSPECTR 1.02ss) of the cases. The improvement is most notable for the targets with complexity 4 (difficult fold recognition cases).

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

ModeRNA server: an online tool for modeling RNA 3D structures.

PubMed

Rother, Magdalena; Milanowska, Kaja; Puton, Tomasz; Jeleniewicz, Jaroslaw; Rother, Kristian; Bujnicki, Janusz M

2011-09-01

The diverse functional roles of non-coding RNA molecules are determined by their underlying structure. ModeRNA server is an online tool for RNA 3D structure modeling by the comparative approach, based on a template RNA structure and a user-defined target-template sequence alignment. It offers an option to search for potential templates, given the target sequence. The server also provides tools for analyzing, editing and formatting of RNA structure files. It facilitates the use of the ModeRNA software and offers new options in comparison to the standalone program. ModeRNA server was implemented using the Python language and the Django web framework. It is freely available at http://iimcb.genesilico.pl/modernaserver. iamb@genesilico.pl.

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

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/

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.

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/.

LookSeq: a browser-based viewer for deep sequencing data.

PubMed

Manske, Heinrich Magnus; Kwiatkowski, Dominic P

2009-11-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an overview of a genomic region to fine details such as heterogeneity within the sample. A specific problem, particularly if the sample is heterogeneous, is how to depict information about structural variation. LookSeq provides a simple graphical representation of paired sequence reads that is more revealing about potential insertions and deletions than are conventional methods.

Nearly complete rRNA genes assembled from across the metazoan animals: effects of more taxa, a structure-based alignment, and paired-sites evolutionary models on phylogeny reconstruction.

PubMed

Mallatt, Jon; Craig, Catherine Waggoner; Yoder, Matthew J

2010-04-01

This study (1) uses nearly complete rRNA-gene sequences from across Metazoa (197 taxa) to reconstruct animal phylogeny; (2) presents a highly annotated, manual alignment of these sequences with special reference to rRNA features including paired sites (http://purl.oclc.org/NET/rRNA/Metazoan_alignment) and (3) tests, after eliminating as few disruptive, rogue sequences as possible, if a likelihood framework can recover the main metazoan clades. We found that systematic elimination of approximately 6% of the sequences, including the divergent or unstably placed sequences of cephalopods, arrowworm, symphylan and pauropod myriapods, and of myzostomid and nemertodermatid worms, led to a tree that supported Ecdysozoa, Lophotrochozoa, Protostomia, and Bilateria. Deuterostomia, however, was never recovered, because the rRNA of urochordates goes (nonsignificantly) near the base of the Bilateria. Counterintuitively, when we modeled the evolution of the paired sites, phylogenetic resolution was not increased over traditional tree-building models that assume all sites in rRNA evolve independently. The rRNA genes of non-bilaterians contain a higher % AT than do those of most bilaterians. The rRNA genes of Acoela and Myzostomida were found to be secondarily shortened, AT-enriched, and highly modified, throwing some doubt on the location of these worms at the base of Bilateria in the rRNA tree--especially myzostomids, which other evidence suggests are annelids instead. Other findings are marsupial-with-placental mammals, arrowworms in Ecdysozoa (well supported here but contradicted by morphology), and Placozoa as sister to Cnidaria. Finally, despite the difficulties, the rRNA-gene trees are in strong concordance with trees derived from multiple protein-coding genes in supporting the new animal phylogeny. (c) 2009 Elsevier Inc. All rights reserved.

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.

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.

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

GeneBee-net: Internet-based server for analyzing biopolymers

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

Brodsky, L.I.; Ivanov, V.V.; Nikolaev, V.K.

This work describes a network server for searching databanks of biopolymer structures and performing other biocomputing procedures; it is available via direct Internet connection. Basic server procedures are dedicated to homology (similarity) search of sequence and 3D structure of proteins. The homologies found could be used to build multiple alignments, predict protein and RNA secondary structure, and construct phylogenetic trees. In addition to traditional methods of sequence similarity search, the authors propose {open_quotes}non-matrix{close_quotes} (correlational) search. An analogous approach is used to identify regions of similar tertiary structure of proteins. Algorithm concepts and usage examples are presented for new methods. Servicemore » logic is based upon interaction of a client program and server procedures. The client program allows the compilation of queries and the processing of results of an analysis.« less

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

Use of conserved key amino acid positions to morph protein folds.

PubMed

Reddy, Boojala V B; Li, Wilfred W; Bourne, Philip E

2002-07-15

By using three-dimensional (3D) structure alignments and a previously published method to determine Conserved Key Amino Acid Positions (CKAAPs) we propose a theoretical method to design mutations that can be used to morph the protein folds. The original Paracelsus challenge, met by several groups, called for the engineering of a stable but different structure by modifying less than 50% of the amino acid residues. We have used the sequences from the Protein Data Bank (PDB) identifiers 1ROP, and 2CRO, which were previously used in the Paracelsus challenge by those groups, and suggest mutation to CKAAPs to morph the protein fold. The total number of mutations suggested is less than 40% of the starting sequence theoretically improving the challenge results. From secondary structure prediction experiments of the proposed mutant sequence structures, we observe that each of the suggested mutant protein sequences likely folds to a different, non-native potentially stable target structure. These results are an early indicator that analyses using structure alignments leading to CKAAPs of a given structure are of value in protein engineering experiments. Copyright 2002 Wiley Periodicals, Inc.

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.

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

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.

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.

Unique phylogenetic position of Diplomonadida based on the complete small subunit ribosomal RNA sequence of Giardia ardeae, G. muris, G. duodenalis and Hexamita sp.

PubMed

van Keulen, H; Gutell, R R; Gates, M A; Campbell, S R; Erlandsen, S L; Jarroll, E L; Kulda, J; Meyer, E A

1993-01-01

Complete small-subunit rRNA (SSU-rRNA) coding region sequences were determined for two species of the intestinal parasite Giardia: G. ardeae and G. muris, both belonging to the order Diplomonadida, and a free-living member of this order, Hexamita sp. These sequences were compared to published SSU-rDNA sequences from a third member of the genus Giardia, G. duodenalis (often called G. intestinalis or G. lamblia) and various representative organisms from other taxa. Of the three Giardia sequences analyzed, the SSU-rRNA from G. muris is the smallest (1432 bases as compared to 1435 and 1453 for G. ardeae and G. duodenalis, respectively) and has the lowest G+C content (58.9%). The Hexamita SSU-rRNA is the largest in this group, containing 1550 bases. Because the sizes of the SSU-rRNA are prokaryotic rather than typically eukaryotic, the secondary structures of the SSU-rRNAs were constructed. These structures show a number of typically eukaryotic signature sequences. Sequence alignments based on constraints imposed by secondary structure were used for construction of a phylogenetic tree for these four taxa. The results show that of the four diplomonads represented, the Giardia species form a distinct group. The other diplomonad Hexamita and the microsporidium Vairimorpha necatrix appear to be distinct from Giardia.

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.

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

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

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.

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.

High-resolution comparative modeling with RosettaCM.

PubMed

Song, Yifan; DiMaio, Frank; Wang, Ray Yu-Ruei; Kim, David; Miles, Chris; Brunette, Tj; Thompson, James; Baker, David

2013-10-08

We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ∼15%. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

Genetic algorithms for protein threading.

PubMed

Yadgari, J; Amir, A; Unger, R

1998-01-01

Despite many years of efforts, a direct prediction of protein structure from sequence is still not possible. As a result, in the last few years researchers have started to address the "inverse folding problem": Identifying and aligning a sequence to the fold with which it is most compatible, a process known as "threading". In two meetings in which protein folding predictions were objectively evaluated, it became clear that threading as a concept promises a real breakthrough, but that much improvement is still needed in the technique itself. Threading is a NP-hard problem, and thus no general polynomial solution can be expected. Still a practical approach with demonstrated ability to find optimal solutions in many cases, and acceptable solutions in other cases, is needed. We applied the technique of Genetic Algorithms in order to significantly improve the ability of threading algorithms to find the optimal alignment of a sequence to a structure, i.e. the alignment with the minimum free energy. A major progress reported here is the design of a representation of the threading alignment as a string of fixed length. With this representation validation of alignments and genetic operators are effectively implemented. Appropriate data structure and parameters have been selected. It is shown that Genetic Algorithm threading is effective and is able to find the optimal alignment in a few test cases. Furthermore, the described algorithm is shown to perform well even without pre-definition of core elements. Existing threading methods are dependent on such constraints to make their calculations feasible. But the concept of core elements is inherently arbitrary and should be avoided if possible. While a rigorous proof is hard to submit yet an, we present indications that indeed Genetic Algorithm threading is capable of finding consistently good solutions of full alignments in search spaces of size up to 10(70).

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.

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.

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

Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A web-based tool for addressing the challenges of cross-species extrapolation of chemical toxicity

EPA Science Inventory

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 quantitat...

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.

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

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.

Quantitation of base substitutions in eukaryotic 5S rRNA: selection for the maintenance of RNA secondary structure.

PubMed

Curtiss, W C; Vournakis, J N

1984-01-01

Eukaryotic 5S rRNA sequences from 34 diverse species were compared by the following method: (1) The sequences were aligned; (2) the positions of substitutions were located by comparison of all possible pairs of sequences; (3) the substitution sites were mapped to an assumed general base pairing model; and (4) the R-Y model of base stacking was used to study stacking pattern relationships in the structure. An analysis of the sequence and structure variability in each region of the molecule is presented. It was found that the degree of base substitution varies over a wide range, from absolute conservation to occurrence of over 90% of the possible observable substitutions. The substitutions are located primarily in stem regions of the 5S rRNA secondary structure. More than 88% of the substitutions in helical regions maintain base pairing. The disruptive substitutions are primarily located at the edges of helical regions, resulting in shortening of the helical regions and lengthening of the adjacent nonpaired regions. Base stacking patterns determined by the R-Y model are mapped onto the general secondary structure. Intrastrand and interstrand stacking could stabilize alternative coaxial structures and limit the conformational flexibility of nonpaired regions. Two short contiguous regions are 100% conserved in all species. This may reflect evolutionary constraints imposed at the DNA level by the requirement for binding of a 5S gene transcription initiation factor during gene expression.

MODBASE, a database of annotated comparative protein structure models

PubMed Central

Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C.; Ilyin, Valentin A.; Sali, Andrej

2002-01-01

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10–4) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server. PMID:11752309

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

PubMed

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and diversity of the template dataset, but, given the rapid accumulation of solved protein complex structures, its scope and utility are expected to keep steadily improving.

Molecular Phylogenetics and Systematics of the Bivalve Family Ostreidae Based on rRNA Sequence-Structure Models and Multilocus Species Tree

PubMed Central

Salvi, Daniele; Macali, Armando; Mariottini, Paolo

2014-01-01

The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassotreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics. PMID:25250663

Molecular phylogenetics and systematics of the bivalve family Ostreidae based on rRNA sequence-structure models and multilocus species tree.

PubMed

Salvi, Daniele; Macali, Armando; Mariottini, Paolo

2014-01-01

The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassostreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized [corrected]. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics.

Kotai Antibody Builder: automated high-resolution structural modeling of antibodies.

PubMed

Yamashita, Kazuo; Ikeda, Kazuyoshi; Amada, Karlou; Liang, Shide; Tsuchiya, Yuko; Nakamura, Haruki; Shirai, Hiroki; Standley, Daron M

2014-11-15

Kotai Antibody Builder is a Web service for tertiary structural modeling of antibody variable regions. It consists of three main steps: hybrid template selection by sequence alignment and canonical rules, 3D rendering of alignments and CDR-H3 loop modeling. For the last step, in addition to rule-based heuristics used to build the initial model, a refinement option is available that uses fragment assembly followed by knowledge-based scoring. Using targets from the Second Antibody Modeling Assessment, we demonstrate that Kotai Antibody Builder generates models with an overall accuracy equal to that of the best-performing semi-automated predictors using expert knowledge. Kotai Antibody Builder is available at http://kotaiab.org standley@ifrec.osaka-u.ac.jp. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Data on publications, structural analyses, and queries used to build and utilize the AlloRep database.

PubMed

Sousa, Filipa L; Parente, Daniel J; Hessman, Jacob A; Chazelle, Allen; Teichmann, Sarah A; Swint-Kruse, Liskin

2016-09-01

The AlloRep database (www.AlloRep.org) (Sousa et al., 2016) [1] compiles extensive sequence, mutagenesis, and structural information for the LacI/GalR family of transcription regulators. Sequence alignments are presented for >3000 proteins in 45 paralog subfamilies and as a subsampled alignment of the whole family. Phenotypic and biochemical data on almost 6000 mutants have been compiled from an exhaustive search of the literature; citations for these data are included herein. These data include information about oligomerization state, stability, DNA binding and allosteric regulation. Protein structural data for 65 proteins are presented as easily-accessible, residue-contact networks. Finally, this article includes example queries to enable the use of the AlloRep database. See the related article, "AlloRep: a repository of sequence, structural and mutagenesis data for the LacI/GalR transcription regulators" (Sousa et al., 2016) [1].

Analyses of the radiation of birnaviruses from diverse host phyla and of their evolutionary affinities with other double-stranded RNA and positive strand RNA viruses using robust structure-based multiple sequence alignments and advanced phylogenetic methods

PubMed Central

2013-01-01

Background Birnaviruses form a distinct family of double-stranded RNA viruses infecting animals as different as vertebrates, mollusks, insects and rotifers. With such a wide host range, they constitute a good model for studying the adaptation to the host. Additionally, several lines of evidence link birnaviruses to positive strand RNA viruses and suggest that phylogenetic analyses may provide clues about transition. Results We characterized the genome of a birnavirus from the rotifer Branchionus plicalitis. We used X-ray structures of RNA-dependent RNA polymerases and capsid proteins to obtain multiple structure alignments that allowed us to obtain reliable multiple sequence alignments and we employed “advanced” phylogenetic methods to study the evolutionary relationships between some positive strand and double-stranded RNA viruses. We showed that the rotifer birnavirus genome exhibited an organization remarkably similar to other birnaviruses. As this host was phylogenetically very distant from the other known species targeted by birnaviruses, we revisited the evolutionary pathways within the Birnaviridae family using phylogenetic reconstruction methods. We also applied a number of phylogenetic approaches based on structurally conserved domains/regions of the capsid and RNA-dependent RNA polymerase proteins to study the evolutionary relationships between birnaviruses, other double-stranded RNA viruses and positive strand RNA viruses. Conclusions We show that there is a good correlation between the phylogeny of the birnaviruses and that of their hosts at the phylum level using the RNA-dependent RNA polymerase (genomic segment B) on the one hand and a concatenation of the capsid protein, protease and ribonucleoprotein (genomic segment A) on the other hand. This correlation tends to vanish within phyla. The use of advanced phylogenetic methods and robust structure-based multiple sequence alignments allowed us to obtain a more accurate picture (in terms of probability of the tree topologies) of the evolutionary affinities between double-stranded RNA and positive strand RNA viruses. In particular, we were able to show that there exists a good statistical support for the claims that dsRNA viruses are not monophyletic and that viruses with permuted RdRps belong to a common evolution lineage as previously proposed by other groups. We also propose a tree topology with a good statistical support describing the evolutionary relationships between the Picornaviridae, Caliciviridae, Flaviviridae families and a group including the Alphatetraviridae, Nodaviridae, Permutotretraviridae, Birnaviridae, and Cystoviridae families. PMID:23865988

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.

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.

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.

Free energy minimization to predict RNA secondary structures and computational RNA design.

PubMed

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Identification and sequence analyses of novel lipase encoding novel thermophillic bacilli isolated from Armenian geothermal springs.

PubMed

Shahinyan, Grigor; Margaryan, Armine; Panosyan, Hovik; Trchounian, Armen

2017-05-02

Among the huge diversity of thermophilic bacteria mainly bacilli have been reported as active thermostable lipase producers. Geothermal springs serve as the main source for isolation of thermostable lipase producing bacilli. Thermostable lipolytic enzymes, functioning in the harsh conditions, have promising applications in processing of organic chemicals, detergent formulation, synthesis of biosurfactants, pharmaceutical processing etc. In order to study the distribution of lipase-producing thermophilic bacilli and their specific lipase protein primary structures, three lipase producers from different genera were isolated from mesothermal (27.5-70 °C) springs distributed on the territory of Armenia and Nagorno Karabakh. Based on phenotypic characteristics and 16S rRNA gene sequencing the isolates were identified as Geobacillus sp., Bacillus licheniformis and Anoxibacillus flavithermus strains. The lipase genes of isolates were sequenced by using initially designed primer sets. Multiple alignments generated from primary structures of the lipase proteins and annotated lipase protein sequences, conserved regions analysis and amino acid composition have illustrated the similarity (98-99%) of the lipases with true lipases (family I) and GDSL esterase family (family II). A conserved sequence block that determines the thermostability has been identified in the multiple alignments of the lipase proteins. The results are spreading light on the lipase producing bacilli distribution in geothermal springs in Armenia and Nagorno Karabakh. Newly isolated bacilli strains could be prospective source for thermostable lipases and their genes.

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.

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

PubMed

Nagarajan, Niranjan; Yona, Golan

2004-06-12

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

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

StrBioLib: a Java library for development of custom computational structural biology applications.

PubMed

Chandonia, John-Marc

2007-08-01

StrBioLib is a library of Java classes useful for developing software for computational structural biology research. StrBioLib contains classes to represent and manipulate protein structures, biopolymer sequences, sets of biopolymer sequences, and alignments between biopolymers based on either sequence or structure. Interfaces are provided to interact with commonly used bioinformatics applications, including (psi)-blast, modeller, muscle and Primer3, and tools are provided to read and write many file formats used to represent bioinformatic data. The library includes a general-purpose neural network object with multiple training algorithms, the Hooke and Jeeves non-linear optimization algorithm, and tools for efficient C-style string parsing and formatting. StrBioLib is the basis for the Pred2ary secondary structure prediction program, is used to build the astral compendium for sequence and structure analysis, and has been extensively tested through use in many smaller projects. Examples and documentation are available at the site below. StrBioLib may be obtained under the terms of the GNU LGPL license from http://strbio.sourceforge.net/

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

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

PubMed

Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

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.

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.

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

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

Insights into the phylogenetic positions of photosynthetic bacteria obtained from 5S rRNA and 16S rRNA sequence data

NASA Technical Reports Server (NTRS)

Fox, G. E.

1985-01-01

Comparisons of complete 16S ribosomal ribonucleic acid (rRNA) sequences established that the secondary structure of these molecules is highly conserved. Earlier work with 5S rRNA secondary structure revealed that when structural conservation exists the alignment of sequences is straightforward. The constancy of structure implies minimal functional change. Under these conditions a uniform evolutionary rate can be expected so that conditions are favorable for phylogenetic tree construction.

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

A Stochastic Evolutionary Model for Protein Structure Alignment and Phylogeny

PubMed Central

Challis, Christopher J.; Schmidler, Scott C.

2012-01-01

We present a stochastic process model for the joint evolution of protein primary and tertiary structure, suitable for use in alignment and estimation of phylogeny. Indels arise from a classic Links model, and mutations follow a standard substitution matrix, whereas backbone atoms diffuse in three-dimensional space according to an Ornstein–Uhlenbeck process. The model allows for simultaneous estimation of evolutionary distances, indel rates, structural drift rates, and alignments, while fully accounting for uncertainty. The inclusion of structural information enables phylogenetic inference on time scales not previously attainable with sequence evolution models. The model also provides a tool for testing evolutionary hypotheses and improving our understanding of protein structural evolution. PMID:22723302

Pre-calculated protein structure alignments at the RCSB PDB website.

PubMed

Prlic, Andreas; Bliven, Spencer; Rose, Peter W; Bluhm, Wolfgang F; Bizon, Chris; Godzik, Adam; Bourne, Philip E

2010-12-01

With the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user. A web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.org andreas@sdsc.edu; pbourne@ucsd.edu.

The identification and functional annotation of RNA structures conserved in vertebrates

PubMed Central

Seemann, Stefan E.; Mirza, Aashiq H.; Hansen, Claus; Bang-Berthelsen, Claus H.; Garde, Christian; Christensen-Dalsgaard, Mikkel; Torarinsson, Elfar; Yao, Zizhen; Workman, Christopher T.; Pociot, Flemming; Nielsen, Henrik; Tommerup, Niels; Ruzzo, Walter L.; Gorodkin, Jan

2017-01-01

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for conserved RNA structures (CRSs), leveraging structure-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ∼516,000 human genomic regions containing CRSs. We find that a substantial fraction of human–mouse CRS regions (1) colocalize consistently with binding sites of the same RNA binding proteins (RBPs) or (2) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared expression and shared structure despite low abundance and low sequence identity. About 30,000 CRS regions are located near coding or long noncoding RNA genes or within enhancers. Structured (CRS overlapping) enhancer RNAs and extended 3′ ends have significantly increased expression levels over their nonstructured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality. PMID:28487280

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

YAHA: fast and flexible long-read alignment with optimal breakpoint detection.

PubMed

Faust, Gregory G; Hall, Ira M

2012-10-01

With improved short-read assembly algorithms and the recent development of long-read sequencers, split mapping will soon be the preferred method for structural variant (SV) detection. Yet, current alignment tools are not well suited for this. We present YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints. YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA. imh4y@virginia.edu.

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

Scop3D: three-dimensional visualization of sequence conservation.

PubMed

Vermeire, Tessa; Vermaere, Stijn; Schepens, Bert; Saelens, Xavier; Van Gucht, Steven; Martens, Lennart; Vandermarliere, Elien

2015-04-01

The integration of a protein's structure with its known sequence variation provides insight on how that protein evolves, for instance in terms of (changing) function or immunogenicity. Yet, collating the corresponding sequence variants into a multiple sequence alignment, calculating each position's conservation, and mapping this information back onto a relevant structure is not straightforward. We therefore built the Sequence Conservation on Protein 3D structure (scop3D) tool to perform these tasks automatically. The output consists of two modified PDB files in which the B-values for each position are replaced by the percentage sequence conservation, or the information entropy for each position, respectively. Furthermore, text files with absolute and relative amino acid occurrences for each position are also provided, along with snapshots of the protein from six distinct directions in space. The visualization provided by scop3D can for instance be used as an aid in vaccine development or to identify antigenic hotspots, which we here demonstrate based on an analysis of the fusion proteins of human respiratory syncytial virus and mumps virus. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

MollDE: a homology modeling framework you can click with.

PubMed

Canutescu, Adrian A; Dunbrack, Roland L

2005-06-15

Molecular Integrated Development Environment (MolIDE) is an integrated application designed to provide homology modeling tools and protocols under a uniform, user-friendly graphical interface. Its main purpose is to combine the most frequent modeling steps in a semi-automatic, interactive way, guiding the user from the target protein sequence to the final three-dimensional protein structure. The typical basic homology modeling process is composed of building sequence profiles of the target sequence family, secondary structure prediction, sequence alignment with PDB structures, assisted alignment editing, side-chain prediction and loop building. All of these steps are available through a graphical user interface. MolIDE's user-friendly and streamlined interactive modeling protocol allows the user to focus on the important modeling questions, hiding from the user the raw data generation and conversion steps. MolIDE was designed from the ground up as an open-source, cross-platform, extensible framework. This allows developers to integrate additional third-party programs to MolIDE. http://dunbrack.fccc.edu/molide/molide.php rl_dunbrack@fccc.edu.

CAB-Align: A Flexible Protein Structure Alignment Method Based on the Residue-Residue Contact Area.

PubMed

Terashi, Genki; Takeda-Shitaka, Mayuko

2015-01-01

Proteins are flexible, and this flexibility has an essential functional role. Flexibility can be observed in loop regions, rearrangements between secondary structure elements, and conformational changes between entire domains. However, most protein structure alignment methods treat protein structures as rigid bodies. Thus, these methods fail to identify the equivalences of residue pairs in regions with flexibility. In this study, we considered that the evolutionary relationship between proteins corresponds directly to the residue-residue physical contacts rather than the three-dimensional (3D) coordinates of proteins. Thus, we developed a new protein structure alignment method, contact area-based alignment (CAB-align), which uses the residue-residue contact area to identify regions of similarity. The main purpose of CAB-align is to identify homologous relationships at the residue level between related protein structures. The CAB-align procedure comprises two main steps: First, a rigid-body alignment method based on local and global 3D structure superposition is employed to generate a sufficient number of initial alignments. Then, iterative dynamic programming is executed to find the optimal alignment. We evaluated the performance and advantages of CAB-align based on four main points: (1) agreement with the gold standard alignment, (2) alignment quality based on an evolutionary relationship without 3D coordinate superposition, (3) consistency of the multiple alignments, and (4) classification agreement with the gold standard classification. Comparisons of CAB-align with other state-of-the-art protein structure alignment methods (TM-align, FATCAT, and DaliLite) using our benchmark dataset showed that CAB-align performed robustly in obtaining high-quality alignments and generating consistent multiple alignments with high coverage and accuracy rates, and it performed extremely well when discriminating between homologous and nonhomologous pairs of proteins in both single and multi-domain comparisons. The CAB-align software is freely available to academic users as stand-alone software at http://www.pharm.kitasato-u.ac.jp/bmd/bmd/Publications.html.

Simultaneous gene finding in multiple genomes.

PubMed

König, Stefanie; Romoth, Lars W; Gerischer, Lizzy; Stanke, Mario

2016-11-15

As the tree of life is populated with sequenced genomes ever more densely, the new challenge is the accurate and consistent annotation of entire clades of genomes. We address this problem with a new approach to comparative gene finding that takes a multiple genome alignment of closely related species and simultaneously predicts the location and structure of protein-coding genes in all input genomes, thereby exploiting negative selection and sequence conservation. The model prefers potential gene structures in the different genomes that are in agreement with each other, or-if not-where the exon gains and losses are plausible given the species tree. We formulate the multi-species gene finding problem as a binary labeling problem on a graph. The resulting optimization problem is NP hard, but can be efficiently approximated using a subgradient-based dual decomposition approach. The proposed method was tested on whole-genome alignments of 12 vertebrate and 12 Drosophila species. The accuracy was evaluated for human, mouse and Drosophila melanogaster and compared to competing methods. Results suggest that our method is well-suited for annotation of (a large number of) genomes of closely related species within a clade, in particular, when RNA-Seq data are available for many of the genomes. The transfer of existing annotations from one genome to another via the genome alignment is more accurate than previous approaches that are based on protein-spliced alignments, when the genomes are at close to medium distances. The method is implemented in C ++ as part of Augustus and available open source at http://bioinf.uni-greifswald.de/augustus/ CONTACT: stefaniekoenig@ymail.com or mario.stanke@uni-greifswald.deSupplementary information: 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.

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

Equivalent Indels – Ambiguous Functional Classes and Redundancy in Databases

PubMed Central

Assmus, Jens; Kleffe, Jürgen; Schmitt, Armin O.; Brockmann, Gudrun A.

2013-01-01

There is considerable interest in studying sequenced variations. However, while the positions of substitutions are uniquely identifiable by sequence alignment, the location of insertions and deletions still poses problems. Each insertion and deletion causes a change of sequence. Yet, due to low complexity or repetitive sequence structures, the same indel can sometimes be annotated in different ways. Two indels which differ in allele sequence and position can be one and the same, i.e. the alternative sequence of the whole chromosome is identical in both cases and, therefore, the two deletions are biologically equivalent. In such a case, it is impossible to identify the exact position of an indel merely based on sequence alignment. Thus, variation entries in a mutation database are not necessarily uniquely defined. We prove the existence of a contiguous region around an indel in which all deletions of the same length are biologically identical. Databases often show only one of several possible locations for a given variation. Furthermore, different data base entries can represent equivalent variation events. We identified 1,045,590 such problematic entries of insertions and deletions out of 5,860,408 indel entries in the current human database of Ensembl. Equivalent indels are found in sequence regions of different functions like exons, introns or 5' and 3' UTRs. One and the same variation can be assigned to several different functional classifications of which only one is correct. We implemented an algorithm that determines for each indel database entry its complete set of equivalent indels which is uniquely characterized by the indel itself and a given interval of the reference sequence. PMID:23658777

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

RBT-GA: a novel metaheuristic for solving the Multiple Sequence Alignment problem.

PubMed

Taheri, Javid; Zomaya, Albert Y

2009-07-07

Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences.

Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments

PubMed Central

Haas, Brian J; Salzberg, Steven L; Zhu, Wei; Pertea, Mihaela; Allen, Jonathan E; Orvis, Joshua; White, Owen; Buell, C Robin; Wortman, Jennifer R

2008-01-01

EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation. PMID:18190707

Describing sequencing results of structural chromosome rearrangements with a suggested next-generation cytogenetic nomenclature.

PubMed

Ordulu, Zehra; Wong, Kristen E; Currall, Benjamin B; Ivanov, Andrew R; Pereira, Shahrin; Althari, Sara; Gusella, James F; Talkowski, Michael E; Morton, Cynthia C

2014-05-01

With recent rapid advances in genomic technologies, precise delineation of structural chromosome rearrangements at the nucleotide level is becoming increasingly feasible. In this era of "next-generation cytogenetics" (i.e., an integration of traditional cytogenetic techniques and next-generation sequencing), a consensus nomenclature is essential for accurate communication and data sharing. Currently, nomenclature for describing the sequencing data of these aberrations is lacking. Herein, we present a system called Next-Gen Cytogenetic Nomenclature, which is concordant with the International System for Human Cytogenetic Nomenclature (2013). This system starts with the alignment of rearrangement sequences by BLAT or BLAST (alignment tools) and arrives at a concise and detailed description of chromosomal changes. To facilitate usage and implementation of this nomenclature, we are developing a program designated BLA(S)T Output Sequence Tool of Nomenclature (BOSToN), a demonstrative version of which is accessible online. A standardized characterization of structural chromosomal rearrangements is essential both for research analyses and for application in the clinical setting. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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.

Bioinformatics prediction of siRNAs as potential antiviral agents against dengue viruses

PubMed Central

Villegas-Rosales, Paula M; Méndez-Tenorio, Alfonso; Ortega-Soto, Elizabeth; Barrón, Blanca L

2012-01-01

Dengue virus (DENV 1-4) represents the major emerging arthropod-borne viral infection in the world. Currently, there is neither an available vaccine nor a specific treatment. Hence, there is a need of antiviral drugs for these viral infections; we describe the prediction of short interfering RNA (siRNA) as potential therapeutic agents against the four DENV serotypes. Our strategy was to carry out a series of multiple alignments using ClustalX program to find conserved sequences among the four DENV serotype genomes to obtain a consensus sequence for siRNAs design. A highly conserved sequence among the four DENV serotypes, located in the encoding sequence for NS4B and NS5 proteins was found. A total of 2,893 complete DENV genomes were downloaded from the NCBI, and after a depuration procedure to identify identical sequences, 220 complete DENV genomes were left. They were edited to select the NS4B and NS5 sequences, which were aligned to obtain a consensus sequence. Three different servers were used for siRNA design, and the resulting siRNAs were aligned to identify the most prevalent sequences. Three siRNAs were chosen, one targeted the genome region that codifies for NS4B protein and the other two; the region for NS5 protein. Predicted secondary structure for DENV genomes was used to demonstrate that the siRNAs were able to target the viral genome forming double stranded structures, necessary to activate the RNA silencing machinery. PMID:22829722

Exploring Dance Movement Data Using Sequence Alignment Methods

PubMed Central

Chavoshi, Seyed Hossein; De Baets, Bernard; Neutens, Tijs; De Tré, Guy; Van de Weghe, Nico

2015-01-01

Despite the abundance of research on knowledge discovery from moving object databases, only a limited number of studies have examined the interaction between moving point objects in space over time. This paper describes a novel approach for measuring similarity in the interaction between moving objects. The proposed approach consists of three steps. First, we transform movement data into sequences of successive qualitative relations based on the Qualitative Trajectory Calculus (QTC). Second, sequence alignment methods are applied to measure the similarity between movement sequences. Finally, movement sequences are grouped based on similarity by means of an agglomerative hierarchical clustering method. The applicability of this approach is tested using movement data from samba and tango dancers. PMID:26181435

GRIL: genome rearrangement and inversion locator.

PubMed

Darling, Aaron E; Mau, Bob; Blattner, Frederick R; Perna, Nicole T

2004-01-01

GRIL is a tool to automatically identify collinear regions in a set of bacterial-size genome sequences. GRIL uses three basic steps. First, regions of high sequence identity are located. Second, some of these regions are filtered based on user-specified criteria. Finally, the remaining regions of sequence identity are used to define significant collinear regions among the sequences. By locating collinear regions of sequence, GRIL provides a basis for multiple genome alignment using current alignment systems. GRIL also provides a basis for using current inversion distance tools to infer phylogeny. GRIL is implemented in C++ and runs on any x86-based Linux or Windows platform. It is available from http://asap.ahabs.wisc.edu/gril

Compression of next-generation sequencing reads aided by highly efficient de novo assembly

PubMed Central

Jones, Daniel C.; Ruzzo, Walter L.; Peng, Xinxia

2012-01-01

We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data structure is used to dramatically reduce the memory required by traditional de Bruijn graph assemblers, allowing millions of reads to be assembled very efficiently. Read sequences are then stored as positions within the assembled contigs. This is combined with statistical compression of read identifiers, quality scores, alignment information and sequences, effectively collapsing very large data sets to <15% of their original size with no loss of information. Availability: Quip is freely available under the 3-clause BSD license from http://cs.washington.edu/homes/dcjones/quip. PMID:22904078

Mining of haplotype-based expressed sequence tag single nucleotide polymorphisms in citrus

PubMed Central

2013-01-01

Background Single nucleotide polymorphisms (SNPs), the most abundant variations in a genome, have been widely used in various studies. Detection and characterization of citrus haplotype-based expressed sequence tag (EST) SNPs will greatly facilitate further utilization of these gene-based resources. Results In this paper, haplotype-based SNPs were mined out of publicly available citrus expressed sequence tags (ESTs) from different citrus cultivars (genotypes) individually and collectively for comparison. There were a total of 567,297 ESTs belonging to 27 cultivars in varying numbers and consequentially yielding different numbers of haplotype-based quality SNPs. Sweet orange (SO) had the most (213,830) ESTs, generating 11,182 quality SNPs in 3,327 out of 4,228 usable contigs. Summed from all the individually mining results, a total of 25,417 quality SNPs were discovered – 15,010 (59.1%) were transitions (AG and CT), 9,114 (35.9%) were transversions (AC, GT, CG, and AT), and 1,293 (5.0%) were insertion/deletions (indels). A vast majority of SNP-containing contigs consisted of only 2 haplotypes, as expected, but the percentages of 2 haplotype contigs varied widely in these citrus cultivars. BLAST of the 25,417 25-mer SNP oligos to the Clementine reference genome scaffolds revealed 2,947 SNPs had “no hits found”, 19,943 had 1 unique hit / alignment, 1,571 had one hit and 2+ alignments per hit, and 956 had 2+ hits and 1+ alignment per hit. Of the total 24,293 scaffold hits, 23,955 (98.6%) were on the main scaffolds 1 to 9, and only 338 were on 87 minor scaffolds. Most alignments had 100% (25/25) or 96% (24/25) nucleotide identities, accounting for 93% of all the alignments. Considering almost all the nucleotide discrepancies in the 24/25 alignments were at the SNP sites, it served well as in silico validation of these SNPs, in addition to and consistent with the rate (81%) validated by sequencing and SNaPshot assay. Conclusions High-quality EST-SNPs from different citrus genotypes were detected, and compared to estimate the heterozygosity of each genome. All the SNP oligo sequences were aligned with the Clementine citrus genome to determine their distribution and uniqueness and for in silico validation, in addition to SNaPshot and sequencing validation of selected SNPs. PMID:24175923

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

ABACAS: algorithm-based automatic contiguation of assembled sequences

PubMed Central

Assefa, Samuel; Keane, Thomas M.; Otto, Thomas D.; Newbold, Chris; Berriman, Matthew

2009-01-01

Summary: Due to the availability of new sequencing technologies, we are now increasingly interested in sequencing closely related strains of existing finished genomes. Recently a number of de novo and mapping-based assemblers have been developed to produce high quality draft genomes from new sequencing technology reads. New tools are necessary to take contigs from a draft assembly through to a fully contiguated genome sequence. ABACAS is intended as a tool to rapidly contiguate (align, order, orientate), visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. The input to ABACAS is a set of contigs which will be aligned to the reference genome, ordered and orientated, visualized in the ACT comparative browser, and optimal primer sequences are automatically generated. Availability and Implementation: ABACAS is implemented in Perl and is freely available for download from http://abacas.sourceforge.net Contact: sa4@sanger.ac.uk PMID:19497936

Population entropies estimates of proteins

NASA Astrophysics Data System (ADS)

Low, Wai Yee

2017-05-01

The Shannon entropy equation provides a way to estimate variability of amino acids sequences in a multiple sequence alignment of proteins. Knowledge of protein variability is useful in many areas such as vaccine design, identification of antibody binding sites, and exploration of protein 3D structural properties. In cases where the population entropies of a protein are of interest but only a small sample size can be obtained, a method based on linear regression and random subsampling can be used to estimate the population entropy. This method is useful for comparisons of entropies where the actual sequence counts differ and thus, correction for alignment size bias is needed. In the current work, an R based package named EntropyCorrect that enables estimation of population entropy is presented and an empirical study on how well this new algorithm performs on simulated dataset of various combinations of population and sample sizes is discussed. The package is available at https://github.com/lloydlow/EntropyCorrect. This article, which was originally published online on 12 May 2017, contained an error in Eq. (1), where the summation sign was missing. The corrected equation appears in the Corrigendum attached to the pdf.

QuickProbs—A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

PubMed Central

Gudyś, Adam; Deorowicz, Sebastian

2014-01-01

Multiple sequence alignment is a crucial task in a number of biological analyses like secondary structure prediction, domain searching, phylogeny, etc. MSAProbs is currently the most accurate alignment algorithm, but its effectiveness is obtained at the expense of computational time. In the paper we present QuickProbs, the variant of MSAProbs customised for graphics processors. We selected the two most time consuming stages of MSAProbs to be redesigned for GPU execution: the posterior matrices calculation and the consistency transformation. Experiments on three popular benchmarks (BAliBASE, PREFAB, OXBench-X) on quad-core PC equipped with high-end graphics card show QuickProbs to be 5.7 to 9.7 times faster than original CPU-parallel MSAProbs. Additional tests performed on several protein families from Pfam database give overall speed-up of 6.7. Compared to other algorithms like MAFFT, MUSCLE, or ClustalW, QuickProbs proved to be much more accurate at similar speed. Additionally we introduce a tuned variant of QuickProbs which is significantly more accurate on sets of distantly related sequences than MSAProbs without exceeding its computation time. The GPU part of QuickProbs was implemented in OpenCL, thus the package is suitable for graphics processors produced by all major vendors. PMID:24586435

Computational approaches for identification of conserved/unique binding pockets in the A chain of ricin

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

Ecale Zhou, C L; Zemla, A T; Roe, D

2005-01-29

Specific and sensitive ligand-based protein detection assays that employ antibodies or small molecules such as peptides, aptamers, or other small molecules require that the corresponding surface region of the protein be accessible and that there be minimal cross-reactivity with non-target proteins. To reduce the time and cost of laboratory screening efforts for diagnostic reagents, we developed new methods for evaluating and selecting protein surface regions for ligand targeting. We devised combined structure- and sequence-based methods for identifying 3D epitopes and binding pockets on the surface of the A chain of ricin that are conserved with respect to a set ofmore » ricin A chains and unique with respect to other proteins. We (1) used structure alignment software to detect structural deviations and extracted from this analysis the residue-residue correspondence, (2) devised a method to compare corresponding residues across sets of ricin structures and structures of closely related proteins, (3) devised a sequence-based approach to determine residue infrequency in local sequence context, and (4) modified a pocket-finding algorithm to identify surface crevices in close proximity to residues determined to be conserved/unique based on our structure- and sequence-based methods. In applying this combined informatics approach to ricin A we identified a conserved/unique pocket in close proximity (but not overlapping) the active site that is suitable for bi-dentate ligand development. These methods are generally applicable to identification of surface epitopes and binding pockets for development of diagnostic reagents, therapeutics, and vaccines.« less

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

PubMed

Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

2006-03-31

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

PubMed

Bastien, Olivier; Ortet, Philippe; Roy, Sylvaine; Maréchal, Eric

2005-03-10

Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

PubMed

Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

2018-01-01

T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95.125% and an AUC of 0.987 on the HLA-DRB1*0101 allele of the Wang benchmark dataset. The results indicate that the proposed prediction technique "GAPES" is a promising technique that will help researchers and scientists to predict the protein structure and it will assist them in the intelligent design of new epitope-based vaccines. Copyright © 2017 Elsevier B.V. All rights reserved.

Alignment-free genome tree inference by learning group-specific distance metrics.

PubMed

Patil, Kaustubh R; McHardy, Alice C

2013-01-01

Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

A comparison of different functions for predicted protein model quality assessment.

PubMed

Li, Juan; Fang, Huisheng

2016-07-01

In protein structure prediction, a considerable number of models are usually produced by either the Template-Based Method (TBM) or the ab initio prediction. The purpose of this study is to find the critical parameter in assessing the quality of the predicted models. A non-redundant template library was developed and 138 target sequences were modeled. The target sequences were all distant from the proteins in the template library and were aligned with template library proteins on the basis of the transformation matrix. The quality of each model was first assessed with QMEAN and its six parameters, which are C_β interaction energy (C_beta), all-atom pairwise energy (PE), solvation energy (SE), torsion angle energy (TAE), secondary structure agreement (SSA), and solvent accessibility agreement (SAE). Finally, the alignment score (score) was also used to assess the quality of model. Hence, a total of eight parameters (i.e., QMEAN, C_beta, PE, SE, TAE, SSA, SAE, score) were independently used to assess the quality of each model. The results indicate that SSA is the best parameter to estimate the quality of the model.

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.

Using Common Spatial Distributions of Atoms to Relate Functionally Divergent Influenza Virus N10 and N11 Protein Structures to Functionally Characterized Neuraminidase Structures, Toxin Cell Entry Domains, and Non-Influenza Virus Cell Entry Domains

PubMed Central

Weininger, Arthur; Weininger, Susan

2015-01-01

The ability to identify the functional correlates of structural and sequence variation in proteins is a critical capability. We related structures of influenza A N10 and N11 proteins that have no established function to structures of proteins with known function by identifying spatially conserved atoms. We identified atoms with common distributed spatial occupancy in PDB structures of N10 protein, N11 protein, an influenza A neuraminidase, an influenza B neuraminidase, and a bacterial neuraminidase. By superposing these spatially conserved atoms, we aligned the structures and associated molecules. We report spatially and sequence invariant residues in the aligned structures. Spatially invariant residues in the N6 and influenza B neuraminidase active sites were found in previously unidentified spatially equivalent sites in the N10 and N11 proteins. We found the corresponding secondary and tertiary structures of the aligned proteins to be largely identical despite significant sequence divergence. We found structural precedent in known non-neuraminidase structures for residues exhibiting structural and sequence divergence in the aligned structures. In N10 protein, we identified staphylococcal enterotoxin I-like domains. In N11 protein, we identified hepatitis E E2S-like domains, SARS spike protein-like domains, and toxin components shared by alpha-bungarotoxin, staphylococcal enterotoxin I, anthrax lethal factor, clostridium botulinum neurotoxin, and clostridium tetanus toxin. The presence of active site components common to the N6, influenza B, and S. pneumoniae neuraminidases in the N10 and N11 proteins, combined with the absence of apparent neuraminidase function, suggests that the role of neuraminidases in H17N10 and H18N11 emerging influenza A viruses may have changed. The presentation of E2S-like, SARS spike protein-like, or toxin-like domains by the N10 and N11 proteins in these emerging viruses may indicate that H17N10 and H18N11 sialidase-facilitated cell entry has been supplemented or replaced by sialidase-independent receptor binding to an expanded cell population that may include neurons and T-cells. PMID:25706124

Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone

PubMed Central

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-01-01

Protein–protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein–protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein–protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein–protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach. PMID:27965389

Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone.

PubMed

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-12-27

Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework.

PubMed

Zheng, Qi; Grice, Elizabeth A

2016-10-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost's algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost.

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

PubMed

Ferragina, Paolo; Giancarlo, Raffaele; Greco, Valentina; Manzini, Giovanni; Valiente, Gabriel

2007-07-13

Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity), NCD (Normalized Compression Dissimilarity) and CD (Compression Dissimilarity). Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at assessing the intrinsic ability of the methodology to discriminate and classify biological sequences and structures. A second set of experiments aims at assessing how well two commonly available classification algorithms, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) and NJ (Neighbor Joining), can use the methodology to perform their task, their performance being evaluated against gold standards and with the use of well known statistical indexes, i.e., the F-measure and the partition distance. Based on the experiments, several conclusions can be drawn and, from them, novel valuable guidelines for the use of USM on biological data. The main ones are reported next. UCD and NCD are indistinguishable, i.e., they yield nearly the same values of the statistical indexes we have used, accross experiments and data sets, while CD is almost always worse than both. UPGMA seems to yield better classification results with respect to NJ, i.e., better values of the statistical indexes (10% difference or above), on a substantial fraction of experiments, compressors and USM approximation choices. The compression program PPMd, based on PPM (Prediction by Partial Matching), for generic data and Gencompress for DNA, are the best performers among the compression algorithms we have used, although the difference in performance, as measured by statistical indexes, between them and the other algorithms depends critically on the data set and may not be as large as expected. PPMd used with UCD or NCD and UPGMA, on sequence data is very close, although worse, in performance with the alignment methods (less than 2% difference on the F-measure). Yet, it scales well with data set size and it can work on data other than sequences. In summary, our quantitative analysis naturally complements the rich theory behind USM and supports the conclusion that the methodology is worth using because of its robustness, flexibility, scalability, and competitiveness with existing techniques. In particular, the methodology applies to all biological data in textual format. The software and data sets are available under the GNU GPL at the supplementary material web page.

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment

PubMed Central

Ferragina, Paolo; Giancarlo, Raffaele; Greco, Valentina; Manzini, Giovanni; Valiente, Gabriel

2007-01-01

Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity), NCD (Normalized Compression Dissimilarity) and CD (Compression Dissimilarity). Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available. Results We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at assessing the intrinsic ability of the methodology to discriminate and classify biological sequences and structures. A second set of experiments aims at assessing how well two commonly available classification algorithms, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) and NJ (Neighbor Joining), can use the methodology to perform their task, their performance being evaluated against gold standards and with the use of well known statistical indexes, i.e., the F-measure and the partition distance. Based on the experiments, several conclusions can be drawn and, from them, novel valuable guidelines for the use of USM on biological data. The main ones are reported next. Conclusion UCD and NCD are indistinguishable, i.e., they yield nearly the same values of the statistical indexes we have used, accross experiments and data sets, while CD is almost always worse than both. UPGMA seems to yield better classification results with respect to NJ, i.e., better values of the statistical indexes (10% difference or above), on a substantial fraction of experiments, compressors and USM approximation choices. The compression program PPMd, based on PPM (Prediction by Partial Matching), for generic data and Gencompress for DNA, are the best performers among the compression algorithms we have used, although the difference in performance, as measured by statistical indexes, between them and the other algorithms depends critically on the data set and may not be as large as expected. PPMd used with UCD or NCD and UPGMA, on sequence data is very close, although worse, in performance with the alignment methods (less than 2% difference on the F-measure). Yet, it scales well with data set size and it can work on data other than sequences. In summary, our quantitative analysis naturally complements the rich theory behind USM and supports the conclusion that the methodology is worth using because of its robustness, flexibility, scalability, and competitiveness with existing techniques. In particular, the methodology applies to all biological data in textual format. The software and data sets are available under the GNU GPL at the supplementary material web page. PMID:17629909

RBT-GA: a novel metaheuristic for solving the multiple sequence alignment problem

PubMed Central

Taheri, Javid; Zomaya, Albert Y

2009-01-01

Background Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. Results This paper presents a novel approach, namely RBT-GA, to solve the MSA problem using a hybrid solution methodology combining the Rubber Band Technique (RBT) and the Genetic Algorithm (GA) metaheuristic. RBT is inspired by the behavior of an elastic Rubber Band (RB) on a plate with several poles, which is analogues to locations in the input sequences that could potentially be biologically related. A GA attempts to mimic the evolutionary processes of life in order to locate optimal solutions in an often very complex landscape. RBT-GA is a population based optimization algorithm designed to find the optimal alignment for a set of input protein sequences. In this novel technique, each alignment answer is modeled as a chromosome consisting of several poles in the RBT framework. These poles resemble locations in the input sequences that are most likely to be correlated and/or biologically related. A GA-based optimization process improves these chromosomes gradually yielding a set of mostly optimal answers for the MSA problem. Conclusion RBT-GA is tested with one of the well-known benchmarks suites (BALiBASE 2.0) in this area. The obtained results show that the superiority of the proposed technique even in the case of formidable sequences. PMID:19594869

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

AllergenFP: allergenicity prediction by descriptor fingerprints.

PubMed

Dimitrov, Ivan; Naneva, Lyudmila; Doytchinova, Irini; Bangov, Ivan

2014-03-15

Allergenicity, like antigenicity and immunogenicity, is a property encoded linearly and non-linearly, and therefore the alignment-based approaches are not able to identify this property unambiguously. A novel alignment-free descriptor-based fingerprint approach is presented here and applied to identify allergens and non-allergens. The approach was implemented into a four step algorithm. Initially, the protein sequences are described by amino acid principal properties as hydrophobicity, size, relative abundance, helix and β-strand forming propensities. Then, the generated strings of different length are converted into vectors with equal length by auto- and cross-covariance (ACC). The vectors were transformed into binary fingerprints and compared in terms of Tanimoto coefficient. The approach was applied to a set of 2427 known allergens and 2427 non-allergens and identified correctly 88% of them with Matthews correlation coefficient of 0.759. The descriptor fingerprint approach presented here is universal. It could be applied for any classification problem in computational biology. The set of E-descriptors is able to capture the main structural and physicochemical properties of amino acids building the proteins. The ACC transformation overcomes the main problem in the alignment-based comparative studies arising from the different length of the aligned protein sequences. The conversion of protein ACC values into binary descriptor fingerprints allows similarity search and classification. The algorithm described in the present study was implemented in a specially designed Web site, named AllergenFP (FP stands for FingerPrint). AllergenFP is written in Python, with GIU in HTML. It is freely accessible at http://ddg-pharmfac.net/Allergen FP. idoytchinova@pharmfac.net or ivanbangov@shu-bg.net.

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

MUBII-TB-DB: a database of mutations associated with antibiotic resistance in Mycobacterium tuberculosis.

PubMed

Flandrois, Jean-Pierre; Lina, Gérard; Dumitrescu, Oana

2014-04-14

Tuberculosis is an infectious bacterial disease caused by Mycobacterium tuberculosis. It remains a major health threat, killing over one million people every year worldwide. An early antibiotic therapy is the basis of the treatment, and the emergence and spread of multidrug and extensively drug-resistant mutant strains raise significant challenges. As these bacteria grow very slowly, drug resistance mutations are currently detected using molecular biology techniques. Resistance mutations are identified by sequencing the resistance-linked genes followed by a comparison with the literature data. The only online database is the TB Drug Resistance Mutation database (TBDReaM database); however, it requires mutation detection before use, and its interrogation is complex due to its loose syntax and grammar. The MUBII-TB-DB database is a simple, highly structured text-based database that contains a set of Mycobacterium tuberculosis mutations (DNA and proteins) occurring at seven loci: rpoB, pncA, katG; mabA(fabG1)-inhA, gyrA, gyrB, and rrs. Resistance mutation data were extracted after the systematic review of MEDLINE referenced publications before March 2013. MUBII analyzes the query sequence obtained by PCR-sequencing using two parallel strategies: i) a BLAST search against a set of previously reconstructed mutated sequences and ii) the alignment of the query sequences (DNA and its protein translation) with the wild-type sequences. The post-treatment includes the extraction of the aligned sequences together with their descriptors (position and nature of mutations). The whole procedure is performed using the internet. The results are graphs (alignments) and text (description of the mutation, therapeutic significance). The system is quick and easy to use, even for technicians without bioinformatics training. MUBII-TB-DB is a structured database of the mutations occurring at seven loci of major therapeutic value in tuberculosis management. Moreover, the system provides interpretation of the mutations in biological and therapeutic terms and can evolve by the addition of newly described mutations. Its goal is to provide easy and comprehensive access through a client-server model over the Web to an up-to-date database of mutations that lead to the resistance of M. tuberculosis to antibiotics.

First observation of rotational structures in Re 168

DOE PAGES

Hartley, D. J.; Janssens, R. V. F.; Riedinger, L. L.; ...

2016-11-30

We assigned first rotational sequences to the odd-odd nucleus 168Re. Coincidence relationships of these structures with rhenium x rays confirm the isotopic assignment, while arguments based on the γ-ray multiplicity (K-fold) distributions observed with the new bands lead to the mass assignment. Configurations for the two bands were determined through analysis of the rotational alignments of the structures and a comparison of the experimental B(M1)/B(E2) ratios with theory. Tentative spin assignments are proposed for the πh 11/2νi 13/2 band, based on energy level systematics for other known sequences in neighboring odd-odd rhenium nuclei, as well as on systematics seen formore » the signature inversion feature that is well known in this region. Furthermore, the spin assignment for the πh 11/2ν(h 9/2/f 7/2) structure provides additional validation of the proposed spins and configurations for isomers in the 176Au → 172Ir → 168Re α-decay chain.« less

Approximate matching of structured motifs in DNA sequences.

PubMed

El-Mabrouk, Nadia; Raffinot, Mathieu; Duchesne, Jean-Eudes; Lajoie, Mathieu; Luc, Nicolas

2005-04-01

Several methods have been developed for identifying more or less complex RNA structures in a genome. All these methods are based on the search for conserved primary and secondary sub-structures. In this paper, we present a simple formal representation of a helix, which is a combination of sequence and folding constraints, as a constrained regular expression. This representation allows us to develop a well-founded algorithm that searches for all approximate matches of a helix in a genome. The algorithm is based on an alignment graph constructed from several copies of a pushdown automaton, arranged one on top of another. This is a first attempt to take advantage of the possibilities of pushdown automata in the context of approximate matching. The worst time complexity is O(krpn), where k is the error threshold, n the size of the genome, p the size of the secondary expression, and r its number of union symbols. We then extend the algorithm to search for pseudo-knots and secondary structures containing an arbitrary number of helices.

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

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.

The identification and functional annotation of RNA structures conserved in vertebrates.

PubMed

Seemann, Stefan E; Mirza, Aashiq H; Hansen, Claus; Bang-Berthelsen, Claus H; Garde, Christian; Christensen-Dalsgaard, Mikkel; Torarinsson, Elfar; Yao, Zizhen; Workman, Christopher T; Pociot, Flemming; Nielsen, Henrik; Tommerup, Niels; Ruzzo, Walter L; Gorodkin, Jan

2017-08-01

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for conserved RNA structures (CRSs), leveraging structure-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ∼516,000 human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (1) colocalize consistently with binding sites of the same RNA binding proteins (RBPs) or (2) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared expression and shared structure despite low abundance and low sequence identity. About 30,000 CRS regions are located near coding or long noncoding RNA genes or within enhancers. Structured (CRS overlapping) enhancer RNAs and extended 3' ends have significantly increased expression levels over their nonstructured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality. © 2017 Seemann et al.; Published by Cold Spring Harbor Laboratory Press.

CodonLogo: a sequence logo-based viewer for codon patterns.

PubMed

Sharma, Virag; Murphy, David P; Provan, Gregory; Baranov, Pavel V

2012-07-15

Conserved patterns across a multiple sequence alignment can be visualized by generating sequence logos. Sequence logos show each column in the alignment as stacks of symbol(s) where the height of a stack is proportional to its informational content, whereas the height of each symbol within the stack is proportional to its frequency in the column. Sequence logos use symbols of either nucleotide or amino acid alphabets. However, certain regulatory signals in messenger RNA (mRNA) act as combinations of codons. Yet no tool is available for visualization of conserved codon patterns. We present the first application which allows visualization of conserved regions in a multiple sequence alignment in the context of codons. CodonLogo is based on WebLogo3 and uses the same heuristics but treats codons as inseparable units of a 64-letter alphabet. CodonLogo can discriminate patterns of codon conservation from patterns of nucleotide conservation that appear indistinguishable in standard sequence logos. The CodonLogo source code and its implementation (in a local version of the Galaxy Browser) are available at http://recode.ucc.ie/CodonLogo and through the Galaxy Tool Shed at http://toolshed.g2.bx.psu.edu/.

Recurring sequence-structure motifs in (βα)8-barrel proteins and experimental optimization of a chimeric protein designed based on such motifs.

PubMed

Wang, Jichao; Zhang, Tongchuan; Liu, Ruicun; Song, Meilin; Wang, Juncheng; Hong, Jiong; Chen, Quan; Liu, Haiyan

2017-02-01

An interesting way of generating novel artificial proteins is to combine sequence motifs from natural proteins, mimicking the evolutionary path suggested by natural proteins comprising recurring motifs. We analyzed the βα and αβ modules of TIM barrel proteins by structure alignment-based sequence clustering. A number of preferred motifs were identified. A chimeric TIM was designed by using recurring elements as mutually compatible interfaces. The foldability of the designed TIM protein was then significantly improved by six rounds of directed evolution. The melting temperature has been improved by more than 20°C. A variety of characteristics suggested that the resulting protein is well-folded. Our analysis provided a library of peptide motifs that is potentially useful for different protein engineering studies. The protein engineering strategy of using recurring motifs as interfaces to connect partial natural proteins may be applied to other protein folds. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

TIM Barrel Protein Structure Classification Using Alignment Approach and Best Hit Strategy

NASA Astrophysics Data System (ADS)

Chu, Jia-Han; Lin, Chun Yuan; Chang, Cheng-Wen; Lee, Chihan; Yang, Yuh-Shyong; Tang, Chuan Yi

2007-11-01

The classification of protein structures is essential for their function determination in bioinformatics. It has been estimated that around 10% of all known enzymes have TIM barrel domains from the Structural Classification of Proteins (SCOP) database. With its high sequence variation and diverse functionalities, TIM barrel protein becomes to be an attractive target for protein engineering and for the evolution study. Hence, in this paper, an alignment approach with the best hit strategy is proposed to classify the TIM barrel protein structure in terms of superfamily and family levels in the SCOP. This work is also used to do the classification for class level in the Enzyme nomenclature (ENZYME) database. Two testing data sets, TIM40D and TIM95D, both are used to evaluate this approach. The resulting classification has an overall prediction accuracy rate of 90.3% for the superfamily level in the SCOP, 89.5% for the family level in the SCOP and 70.1% for the class level in the ENZYME. These results demonstrate that the alignment approach with the best hit strategy is a simple and viable method for the TIM barrel protein structure classification, even only has the amino acid sequences information.

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes.

PubMed

Otto, Thomas Dan; Catanho, Marcos; Tristão, Cristian; Bezerra, Márcia; Fernandes, Renan Mathias; Elias, Guilherme Steinberger; Scaglia, Alexandre Capeletto; Bovermann, Bill; Berstis, Viktors; Lifschitz, Sergio; de Miranda, Antonio Basílio; Degrave, Wim

2010-03-01

Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith-Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community Grid, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective scores, is now made available. Users can download, compare and analyze the results, filtered by genomes, protein functions or clusters. ProteinWorldDB is integrated with annotations derived from Swiss-Prot, Pfam, KEGG, NCBI Taxonomy database and gene ontology. The database is a unique and valuable asset, representing a major effort to create a reliable and consistent dataset of cross-comparisons of the whole protein content encoded in hundreds of completely sequenced genomes using a rigorous dynamic programming approach. The database can be accessed through http://proteinworlddb.org

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

ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements.

PubMed

Taylor, James; Tyekucheva, Svitlana; King, David C; Hardison, Ross C; Miller, Webb; Chiaromonte, Francesca

2006-12-01

Genomic sequence signals - such as base composition, presence of particular motifs, or evolutionary constraint - have been used effectively to identify functional elements. However, approaches based only on specific signals known to correlate with function can be quite limiting. When training data are available, application of computational learning algorithms to multispecies alignments has the potential to capture broader and more informative sequence and evolutionary patterns that better characterize a class of elements. However, effective exploitation of patterns in multispecies alignments is impeded by the vast number of possible alignment columns and by a limited understanding of which particular strings of columns may characterize a given class. We have developed a computational method, called ESPERR (evolutionary and sequence pattern extraction through reduced representations), which uses training examples to learn encodings of multispecies alignments into reduced forms tailored for the prediction of chosen classes of functional elements. ESPERR produces a greatly improved Regulatory Potential score, which can discriminate regulatory regions from neutral sites with excellent accuracy ( approximately 94%). This score captures strong signals (GC content and conservation), as well as subtler signals (with small contributions from many different alignment patterns) that characterize the regulatory elements in our training set. ESPERR is also effective for predicting other classes of functional elements, as we show for DNaseI hypersensitive sites and highly conserved regions with developmental enhancer activity. Our software, training data, and genome-wide predictions are available from our Web site (http://www.bx.psu.edu/projects/esperr).

Estimation of relative effectiveness of phylogenetic programs by machine learning.

PubMed

Krivozubov, Mikhail; Goebels, Florian; Spirin, Sergei

2014-04-01

Reconstruction of phylogeny of a protein family from a sequence alignment can produce results of different quality. Our goal is to predict the quality of phylogeny reconstruction basing on features that can be extracted from the input alignment. We used Fitch-Margoliash (FM) method of phylogeny reconstruction and random forest as a predictor. For training and testing the predictor, alignments of orthologous series (OS) were used, for which the result of phylogeny reconstruction can be evaluated by comparison with trees of corresponding organisms. Our results show that the quality of phylogeny reconstruction can be predicted with more than 80% precision. Also, we tried to predict which phylogeny reconstruction method, FM or UPGMA, is better for a particular alignment. With the used set of features, among alignments for which the obtained predictor predicts a better performance of UPGMA, 56% really give a better result with UPGMA. Taking into account that in our testing set only for 34% alignments UPGMA performs better, this result shows a principal possibility to predict the better phylogeny reconstruction method basing on features of a sequence alignment.

SANSparallel: interactive homology search against Uniprot

PubMed Central

Somervuo, Panu; Holm, Liisa

2015-01-01

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest. PMID:25855811

The spatial alignment of time: Differences in alignment of deictic and sequence time along the sagittal and lateral axes.

PubMed

Walker, Esther J; Bergen, Benjamin K; Núñez, Rafael

2017-04-01

People use space in a variety of ways to structure their thoughts about time. The present report focuses on the different ways that space is employed when reasoning about deictic (past/future relationships) and sequence (earlier/later relationships) time. In the first study, we show that deictic and sequence time are aligned along the lateral axis in a manner consistent with previous work, with past and earlier events associated with left space and future and later events associated with right space. However, the alignment of time with space is different along the sagittal axis. Participants associated future events and earlier events-not later events-with the space in front of their body and past and later events with the space behind, consistent with the sagittal spatial terms (e.g., ahead, in front of) that we use to talk about deictic and sequence time. In the second study, we show that these associations between sequence time and sagittal space are sensitive to person-perspective. This suggests that the particular space-time associations observed in English speakers are influenced by a variety of different spatial properties, including spatial location and perspective. Copyright © 2016. Published by Elsevier B.V.

Background Adjusted Alignment-Free Dissimilarity Measures Improve the Detection of Horizontal Gene Transfer.

PubMed

Tang, Kujin; Lu, Yang Young; Sun, Fengzhu

2018-01-01

Horizontal gene transfer (HGT) plays an important role in the evolution of microbial organisms including bacteria. Alignment-free methods based on single genome compositional information have been used to detect HGT. Currently, Manhattan and Euclidean distances based on tetranucleotide frequencies are the most commonly used alignment-free dissimilarity measures to detect HGT. By testing on simulated bacterial sequences and real data sets with known horizontal transferred genomic regions, we found that more advanced alignment-free dissimilarity measures such as CVTree and [Formula: see text] that take into account the background Markov sequences can solve HGT detection problems with significantly improved performance. We also studied the influence of different factors such as evolutionary distance between host and donor sequences, size of sliding window, and host genome composition on the performances of alignment-free methods to detect HGT. Our study showed that alignment-free methods can predict HGT accurately when host and donor genomes are in different order levels. Among all methods, CVTree with word length of 3, [Formula: see text] with word length 3, Markov order 1 and [Formula: see text] with word length 4, Markov order 1 outperform others in terms of their highest F 1 -score and their robustness under the influence of different factors.

MSuPDA: A Memory Efficient Algorithm for Sequence Alignment.

PubMed

Khan, Mohammad Ibrahim; Kamal, Md Sarwar; Chowdhury, Linkon

2016-03-01

Space complexity is a million dollar question in DNA sequence alignments. In this regard, memory saving under pushdown automata can help to reduce the occupied spaces in computer memory. Our proposed process is that anchor seed (AS) will be selected from given data set of nucleotide base pairs for local sequence alignment. Quick splitting techniques will separate the AS from all the DNA genome segments. Selected AS will be placed to pushdown automata's (PDA) input unit. Whole DNA genome segments will be placed into PDA's stack. AS from input unit will be matched with the DNA genome segments from stack of PDA. Match, mismatch and indel of nucleotides will be popped from the stack under the control unit of pushdown automata. During the POP operation on stack, it will free the memory cell occupied by the nucleotide base pair.

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos.

PubMed

Roca, Alberto I

2014-01-01

The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org.

Prevalent Exon-Intron Structural Changes in the APETALA1/FRUITFULL, SEPALLATA, AGAMOUS-LIKE6, and FLOWERING LOCUS C MADS-Box Gene Subfamilies Provide New Insights into Their Evolution

PubMed Central

Yu, Xianxian; Duan, Xiaoshan; Zhang, Rui; Fu, Xuehao; Ye, Lingling; Kong, Hongzhi; Xu, Guixia; Shan, Hongyan

2016-01-01

AP1/FUL, SEP, AGL6, and FLC subfamily genes play important roles in flower development. The phylogenetic relationships among them, however, have been controversial, which impedes our understanding of the origin and functional divergence of these genes. One possible reason for the controversy may be the problems caused by changes in the exon-intron structure of genes, which, according to recent studies, may generate non-homologous sites and hamper the homology-based sequence alignment. In this study, we first performed exon-by-exon alignments of these and three outgroup subfamilies (SOC1, AG, and STK). Phylogenetic trees reconstructed based on these matrices show improved resolution and better congruence with species phylogeny. In the context of these phylogenies, we traced evolutionary changes of exon-intron structures in each subfamily. We found that structural changes have occurred frequently following gene duplication and speciation events. Notably, exons 7 and 8 (if present) suffered more structural changes than others. With the knowledge of exon-intron structural changes, we generated more reasonable alignments containing all the focal subfamilies. The resulting trees showed that the SEP subfamily is sister to the monophyletic group formed by AP1/FUL and FLC subfamily genes and that the AGL6 subfamily forms a sister group to the three abovementioned subfamilies. Based on this topology, we inferred the evolutionary history of exon-intron structural changes among different subfamilies. Particularly, we found that the eighth exon originated before the divergence of AP1/FUL, FLC, SEP, and AGL6 subfamilies and degenerated in the ancestral FLC-like gene. These results provide new insights into the origin and evolution of the AP1/FUL, FLC, SEP, and AGL6 subfamilies. PMID:27200066

Automated side-chain model building and sequence assignment by template matching.

PubMed

Terwilliger, Thomas C

2003-01-01

An algorithm is described for automated building of side chains in an electron-density map once a main-chain model is built and for alignment of the protein sequence to the map. The procedure is based on a comparison of electron density at the expected side-chain positions with electron-density templates. The templates are constructed from average amino-acid side-chain densities in 574 refined protein structures. For each contiguous segment of main chain, a matrix with entries corresponding to an estimate of the probability that each of the 20 amino acids is located at each position of the main-chain model is obtained. The probability that this segment corresponds to each possible alignment with the sequence of the protein is estimated using a Bayesian approach and high-confidence matches are kept. Once side-chain identities are determined, the most probable rotamer for each side chain is built into the model. The automated procedure has been implemented in the RESOLVE software. Combined with automated main-chain model building, the procedure produces a preliminary model suitable for refinement and extension by an experienced crystallographer.

NEP: web server for epitope prediction based on antibody neutralization of viral strains with diverse sequences

PubMed Central

Chuang, Gwo-Yu; Liou, David; Kwong, Peter D.; Georgiev, Ivelin S.

2014-01-01

Delineation of the antigenic site, or epitope, recognized by an antibody can provide clues about functional vulnerabilities and resistance mechanisms, and can therefore guide antibody optimization and epitope-based vaccine design. Previously, we developed an algorithm for antibody-epitope prediction based on antibody neutralization of viral strains with diverse sequences and validated the algorithm on a set of broadly neutralizing HIV-1 antibodies. Here we describe the implementation of this algorithm, NEP (Neutralization-based Epitope Prediction), as a web-based server. The users must supply as input: (i) an alignment of antigen sequences of diverse viral strains; (ii) neutralization data for the antibody of interest against the same set of antigen sequences; and (iii) (optional) a structure of the unbound antigen, for enhanced prediction accuracy. The prediction results can be downloaded or viewed interactively on the antigen structure (if supplied) from the web browser using a JSmol applet. Since neutralization experiments are typically performed as one of the first steps in the characterization of an antibody to determine its breadth and potency, the NEP server can be used to predict antibody-epitope information at no additional experimental costs. NEP can be accessed on the internet at http://exon.niaid.nih.gov/nep. PMID:24782517

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

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.

The proteome: structure, function and evolution

PubMed Central

Fleming, Keiran; Kelley, Lawrence A; Islam, Suhail A; MacCallum, Robert M; Muller, Arne; Pazos, Florencio; Sternberg, Michael J.E

2006-01-01

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family. PMID:16524832

AlignerBoost: A Generalized Software Toolkit for Boosting Next-Gen Sequencing Mapping Accuracy Using a Bayesian-Based Mapping Quality Framework

PubMed Central

Zheng, Qi; Grice, Elizabeth A.

2016-01-01

Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is crucial for almost all NGS applications and downstream analyses. Various repetitive elements in human and other higher eukaryotic genomes contribute in large part to ambiguously (non-uniquely) mapped reads. Most available NGS aligners attempt to address this by either removing all non-uniquely mapping reads, or reporting one random or "best" hit based on simple heuristics. Accurate estimation of the mapping quality of NGS reads is therefore critical albeit completely lacking at present. Here we developed a generalized software toolkit "AlignerBoost", which utilizes a Bayesian-based framework to accurately estimate mapping quality of ambiguously mapped NGS reads. We tested AlignerBoost with both simulated and real DNA-seq and RNA-seq datasets at various thresholds. In most cases, but especially for reads falling within repetitive regions, AlignerBoost dramatically increases the mapping precision of modern NGS aligners without significantly compromising the sensitivity even without mapping quality filters. When using higher mapping quality cutoffs, AlignerBoost achieves a much lower false mapping rate while exhibiting comparable or higher sensitivity compared to the aligner default modes, therefore significantly boosting the detection power of NGS aligners even using extreme thresholds. AlignerBoost is also SNP-aware, and higher quality alignments can be achieved if provided with known SNPs. AlignerBoost’s algorithm is computationally efficient, and can process one million alignments within 30 seconds on a typical desktop computer. AlignerBoost is implemented as a uniform Java application and is freely available at https://github.com/Grice-Lab/AlignerBoost. PMID:27706155

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

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.

Structure-based engineering of a pectate lyase with improved specific activity for ramie degumming.

PubMed

Zhou, Zhanping; Liu, Yang; Chang, Zhenying; Wang, Huilin; Leier, André; Marquez-Lago, Tatiana T; Ma, Yanhe; Li, Jian; Song, Jiangning

2017-04-01

Biotechnological applications of microbial pectate lyases (Pels) in plant fiber processing are promising, eco-friendly substitutes for conventional chemical degumming processes. However, to potentiate the enzymes' use for industrial applications, resolving the molecular structure to elucidate catalytic mechanisms becomes necessary. In this manuscript, we report the high resolution (1.45 Å) crystal structure of pectate lyase (pelN) from Paenibacillus sp. 0602 in apo form. Through sequence alignment and structural superposition with other members of the polysaccharide lyase (PL) family 1 (PL1), we determined that pelN shares the characteristic right-handed β-helix and is structurally similar to other members of the PL1 family, while exhibiting key differences in terms of catalytic and substrate binding residues. Then, based on information from structure alignments with other PLs, we engineered a novel pelN. Our rational design yielded a pelN mutant with a temperature for enzymatic activity optimally shifted from 67.5 to 60 °C. Most importantly, this pelN mutant displayed both higher specific activity and ramie fiber degumming ability when compared with the wild-type enzyme. Altogether, our rational design method shows great potential for industrial applications. Moreover, we expect the reported high-resolution crystal structure to provide a solid foundation for future rational, structure-based engineering of genetically enhanced pelNs.

SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

PubMed Central

Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

2001-01-01

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

Kablammo: an interactive, web-based BLAST results visualizer.

PubMed

Wintersinger, Jeff A; Wasmuth, James D

2015-04-15

Kablammo is a web-based application that produces interactive, vector-based visualizations of sequence alignments generated by BLAST. These visualizations can illustrate many features, including shared protein domains, chromosome structural modifications and genome misassembly. Kablammo can be used at http://kablammo.wasmuthlab.org. For a local installation, the source code and instructions are available under the MIT license at http://github.com/jwintersinger/kablammo. jeff@wintersinger.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

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

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less

A Systematic Analysis of the Structures of Heterologously Expressed Proteins and Those from Their Native Hosts in the RCSB PDB Archive.

PubMed

Zhou, Ren-Bin; Lu, Hui-Meng; Liu, Jie; Shi, Jian-Yu; Zhu, Jing; Lu, Qin-Qin; Yin, Da-Chuan

2016-01-01

Recombinant expression of proteins has become an indispensable tool in modern day research. The large yields of recombinantly expressed proteins accelerate the structural and functional characterization of proteins. Nevertheless, there are literature reported that the recombinant proteins show some differences in structure and function as compared with the native ones. Now there have been more than 100,000 structures (from both recombinant and native sources) publicly available in the Protein Data Bank (PDB) archive, which makes it possible to investigate if there exist any proteins in the RCSB PDB archive that have identical sequence but have some difference in structures. In this paper, we present the results of a systematic comparative study of the 3D structures of identical naturally purified versus recombinantly expressed proteins. The structural data and sequence information of the proteins were mined from the RCSB PDB archive. The combinatorial extension (CE), FATCAT-flexible and TM-Align methods were employed to align the protein structures. The root-mean-square distance (RMSD), TM-score, P-value, Z-score, secondary structural elements and hydrogen bonds were used to assess the structure similarity. A thorough analysis of the PDB archive generated five-hundred-seventeen pairs of native and recombinant proteins that have identical sequence. There were no pairs of proteins that had the same sequence and significantly different structural fold, which support the hypothesis that expression in a heterologous host usually could fold correctly into their native forms.

A Systematic Analysis of the Structures of Heterologously Expressed Proteins and Those from Their Native Hosts in the RCSB PDB Archive

PubMed Central

Zhou, Ren-Bin; Lu, Hui-Meng; Liu, Jie; Shi, Jian-Yu; Zhu, Jing; Lu, Qin-Qin; Yin, Da-Chuan

2016-01-01

Recombinant expression of proteins has become an indispensable tool in modern day research. The large yields of recombinantly expressed proteins accelerate the structural and functional characterization of proteins. Nevertheless, there are literature reported that the recombinant proteins show some differences in structure and function as compared with the native ones. Now there have been more than 100,000 structures (from both recombinant and native sources) publicly available in the Protein Data Bank (PDB) archive, which makes it possible to investigate if there exist any proteins in the RCSB PDB archive that have identical sequence but have some difference in structures. In this paper, we present the results of a systematic comparative study of the 3D structures of identical naturally purified versus recombinantly expressed proteins. The structural data and sequence information of the proteins were mined from the RCSB PDB archive. The combinatorial extension (CE), FATCAT-flexible and TM-Align methods were employed to align the protein structures. The root-mean-square distance (RMSD), TM-score, P-value, Z-score, secondary structural elements and hydrogen bonds were used to assess the structure similarity. A thorough analysis of the PDB archive generated five-hundred-seventeen pairs of native and recombinant proteins that have identical sequence. There were no pairs of proteins that had the same sequence and significantly different structural fold, which support the hypothesis that expression in a heterologous host usually could fold correctly into their native forms. PMID:27517583

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.

Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver.

PubMed

Wymant, Chris; Blanquart, François; Golubchik, Tanya; Gall, Astrid; Bakker, Margreet; Bezemer, Daniela; Croucher, Nicholas J; Hall, Matthew; Hillebregt, Mariska; Ong, Swee Hoe; Ratmann, Oliver; Albert, Jan; Bannert, Norbert; Fellay, Jacques; Fransen, Katrien; Gourlay, Annabelle; Grabowski, M Kate; Gunsenheimer-Bartmeyer, Barbara; Günthard, Huldrych F; Kivelä, Pia; Kouyos, Roger; Laeyendecker, Oliver; Liitsola, Kirsi; Meyer, Laurence; Porter, Kholoud; Ristola, Matti; van Sighem, Ard; Berkhout, Ben; Cornelissen, Marion; Kellam, Paul; Reiss, Peter; Fraser, Christophe

2018-01-01

Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver.

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

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

Genetic diversity of the captive Asian tapir population in Thailand, based on mitochondrial control region sequence data and the comparison of its nucleotide structure with Brazilian tapir.

PubMed

Muangkram, Yuttamol; Amano, Akira; Wajjwalku, Worawidh; Pinyopummintr, Tanu; Thongtip, Nikorn; Kaolim, Nongnid; Sukmak, Manakorn; Kamolnorranath, Sumate; Siriaroonrat, Boripat; Tipkantha, Wanlaya; Maikaew, Umaporn; Thomas, Warisara; Polsrila, Kanda; Dongsaard, Kwanreaun; Sanannu, Saowaphang; Wattananorrasate, Anuwat

2017-07-01

The Asian tapir (Tapirus indicus) has been classified as Endangered on the IUCN Red List of Threatened Species (2008). Genetic diversity data provide important information for the management of captive breeding and conservation of this species. We analyzed mitochondrial control region (CR) sequences from 37 captive Asian tapirs in Thailand. Multiple alignments of the full-length CR sequences sized 1268 bp comprised three domains as described in other mammal species. Analysis of 16 parsimony-informative variable sites revealed 11 haplotypes. Furthermore, the phylogenetic analysis using median-joining network clearly showed three clades correlated with our earlier cytochrome b gene study in this endangered species. The repetitive motif is located between first and second conserved sequence blocks, similar to the Brazilian tapir. The highest polymorphic site was located in the extended termination associated sequences domain. The results could be applied for future genetic management based in captivity and wild that shows stable populations.

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos

PubMed Central

2014-01-01

Background The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. Results The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. Conclusions The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org. PMID:25237393

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

B-MIC: An Ultrafast Three-Level Parallel Sequence Aligner Using MIC.

PubMed

Cui, Yingbo; Liao, Xiangke; Zhu, Xiaoqian; Wang, Bingqiang; Peng, Shaoliang

2016-03-01

Sequence alignment is the central process for sequence analysis, where mapping raw sequencing data to reference genome. The large amount of data generated by NGS is far beyond the process capabilities of existing alignment tools. Consequently, sequence alignment becomes the bottleneck of sequence analysis. Intensive computing power is required to address this challenge. Intel recently announced the MIC coprocessor, which can provide massive computing power. The Tianhe-2 is the world's fastest supercomputer now equipped with three MIC coprocessors each compute node. A key feature of sequence alignment is that different reads are independent. Considering this property, we proposed a MIC-oriented three-level parallelization strategy to speed up BWA, a widely used sequence alignment tool, and developed our ultrafast parallel sequence aligner: B-MIC. B-MIC contains three levels of parallelization: firstly, parallelization of data IO and reads alignment by a three-stage parallel pipeline; secondly, parallelization enabled by MIC coprocessor technology; thirdly, inter-node parallelization implemented by MPI. In this paper, we demonstrate that B-MIC outperforms BWA by a combination of those techniques using Inspur NF5280M server and the Tianhe-2 supercomputer. To the best of our knowledge, B-MIC is the first sequence alignment tool to run on Intel MIC and it can achieve more than fivefold speedup over the original BWA while maintaining the alignment precision.

G2S: a web-service for annotating genomic variants on 3D protein structures.

PubMed

Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-06-01

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that supports programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online.

Predicting turns in proteins with a unified model.

PubMed

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Predicting Turns in Proteins with a Unified Model

PubMed Central

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Motivation Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. Results In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications. PMID:23144872

MSuPDA: A memory efficient algorithm for sequence alignment.

PubMed

Khan, Mohammad Ibrahim; Kamal, Md Sarwar; Chowdhury, Linkon

2015-01-16

Space complexity is a million dollar question in DNA sequence alignments. In this regards, MSuPDA (Memory Saving under Pushdown Automata) can help to reduce the occupied spaces in computer memory. Our proposed process is that Anchor Seed (AS) will be selected from given data set of Nucleotides base pairs for local sequence alignment. Quick Splitting (QS) techniques will separate the Anchor Seed from all the DNA genome segments. Selected Anchor Seed will be placed to pushdown Automata's (PDA) input unit. Whole DNA genome segments will be placed into PDA's stack. Anchor Seed from input unit will be matched with the DNA genome segments from stack of PDA. Whatever matches, mismatches or Indel, of Nucleotides will be POP from the stack under the control of control unit of Pushdown Automata. During the POP operation on stack it will free the memory cell occupied by the Nucleotide base pair.

Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development.

PubMed

Bandyopadhyay, Deepak; Huan, Jun; Prins, Jan; Snoeyink, Jack; Wang, Wei; Tropsha, Alexander

2009-11-01

Protein function prediction is one of the central problems in computational biology. We present a novel automated protein structure-based function prediction method using libraries of local residue packing patterns that are common to most proteins in a known functional family. Critical to this approach is the representation of a protein structure as a graph where residue vertices (residue name used as a vertex label) are connected by geometrical proximity edges. The approach employs two steps. First, it uses a fast subgraph mining algorithm to find all occurrences of family-specific labeled subgraphs for all well characterized protein structural and functional families. Second, it queries a new structure for occurrences of a set of motifs characteristic of a known family, using a graph index to speed up Ullman's subgraph isomorphism algorithm. The confidence of function inference from structure depends on the number of family-specific motifs found in the query structure compared with their distribution in a large non-redundant database of proteins. This method can assign a new structure to a specific functional family in cases where sequence alignments, sequence patterns, structural superposition and active site templates fail to provide accurate annotation.

A low-complexity add-on score for protein remote homology search with COMER.

PubMed

Margelevicius, Mindaugas

2018-06-15

Protein sequence alignment forms the basis for comparative modeling, the most reliable approach to protein structure prediction, among many other applications. Alignment between sequence families, or profile-profile alignment, represents one of the most, if not the most, sensitive means for homology detection but still necessitates improvement. We aim at improving the quality of profile-profile alignments and the sensitivity induced by them by refining profile-profile substitution scores. We have developed a new score that represents an additional component of profile-profile substitution scores. A comprehensive evaluation shows that the new add-on score statistically significantly improves both the sensitivity and the alignment quality of the COMER method. We discuss why the score leads to the improvement and its almost optimal computational complexity that makes it easily implementable in any profile-profile alignment method. An implementation of the add-on score in the open-source COMER software and data are available at https://sourceforge.net/projects/comer. The COMER software is also available on Github at https://github.com/minmarg/comer and as a Docker image (minmar/comer). Supplementary data are available at Bioinformatics online.

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

Studying long 16S rDNA sequences with ultrafast-metagenomic sequence classification using exact alignments (Kraken).

PubMed

Valenzuela-González, Fabiola; Martínez-Porchas, Marcel; Villalpando-Canchola, Enrique; Vargas-Albores, Francisco

2016-03-01

Ultrafast-metagenomic sequence classification using exact alignments (Kraken) is a novel approach to classify 16S rDNA sequences. The classifier is based on mapping short sequences to the lowest ancestor and performing alignments to form subtrees with specific weights in each taxon node. This study aimed to evaluate the classification performance of Kraken with long 16S rDNA random environmental sequences produced by cloning and then Sanger sequenced. A total of 480 clones were isolated and expanded, and 264 of these clones formed contigs (1352 ± 153 bp). The same sequences were analyzed using the Ribosomal Database Project (RDP) classifier. Deeper classification performance was achieved by Kraken than by the RDP: 73% of the contigs were classified up to the species or variety levels, whereas 67% of these contigs were classified no further than the genus level by the RDP. The results also demonstrated that unassembled sequences analyzed by Kraken provide similar or inclusively deeper information. Moreover, sequences that did not form contigs, which are usually discarded by other programs, provided meaningful information when analyzed by Kraken. Finally, it appears that the assembly step for Sanger sequences can be eliminated when using Kraken. Kraken cumulates the information of both sequence senses, providing additional elements for the classification. In conclusion, the results demonstrate that Kraken is an excellent choice for use in the taxonomic assignment of sequences obtained by Sanger sequencing or based on third generation sequencing, of which the main goal is to generate larger sequences. Copyright © 2016 Elsevier B.V. All rights reserved.

Resolution of model Holliday junctions by yeast endonuclease: effect of DNA structure and sequence.

PubMed Central

Parsons, C A; Murchie, A I; Lilley, D M; West, S C

1989-01-01

The resolution of Holliday junctions in DNA involves specific cleavage at or close to the site of the junction. A nuclease from Saccharomyces cerevisiae cleaves model Holliday junctions in vitro by the introduction of nicks in regions of duplex DNA adjacent to the crossover point. In previous studies [Parsons and West (1988) Cell, 52, 621-629] it was shown that cleavage occurred within homologous arm sequences with precise symmetry across the junction. In contrast, junctions with heterologous arm sequences were cleaved asymmetrically. In this work, we have studied the effect of sequence changes and base modification upon the site of cleavage. It is shown that the specificity of cleavage is unchanged providing that perfect homology is maintained between opposing arm sequences. However, in the absence of homology, cleavage depends upon sequence context and is affected by minor changes such as base modification. These data support the proposed mechanism for cleavage of a Holliday junction, which requires homologous alignment of arm sequences in an enzyme--DNA complex as a prerequisite for symmetrical cleavage by the yeast endonuclease. Images PMID:2653810

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

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

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

Hartley, D. J.; Janssens, R. V. F.; Riedinger, L. L.

We assigned first rotational sequences to the odd-odd nucleus 168Re. Coincidence relationships of these structures with rhenium x rays confirm the isotopic assignment, while arguments based on the γ-ray multiplicity (K-fold) distributions observed with the new bands lead to the mass assignment. Configurations for the two bands were determined through analysis of the rotational alignments of the structures and a comparison of the experimental B(M1)/B(E2) ratios with theory. Tentative spin assignments are proposed for the πh 11/2νi 13/2 band, based on energy level systematics for other known sequences in neighboring odd-odd rhenium nuclei, as well as on systematics seen formore » the signature inversion feature that is well known in this region. Furthermore, the spin assignment for the πh 11/2ν(h 9/2/f 7/2) structure provides additional validation of the proposed spins and configurations for isomers in the 176Au → 172Ir → 168Re α-decay chain.« less

PASTA for Proteins.

PubMed

Collins, Kodi; Warnow, Tandy

2018-06-19

PASTA is a multiple sequence method that uses divide-and-conquer plus iteration to enable base alignment methods to scale with high accuracy to large sequence datasets. By default, PASTA included MAFFT L-INS-i; our new extension of PASTA enables the use of MAFFT G-INS-i, MAFFT Homologs, CONTRAlign, and ProbCons. We analyzed the performance of each base method and PASTA using these base methods on 224 datasets from BAliBASE 4 with at least 50 sequences. We show that PASTA enables the most accurate base methods to scale to larger datasets at reduced computational effort, and generally improves alignment and tree accuracy on the largest BAliBASE datasets. PASTA is available at https://github.com/kodicollins/pasta and has also been integrated into the original PASTA repository at https://github.com/smirarab/pasta. Supplementary data are available at Bioinformatics online.

Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison

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

Ovacik, Meric A.; Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu; Biomedical Engineering Department, Rutgers University, Piscataway, NJ 08854

2013-09-15

Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogeneticmore » relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.« less

GOSSIP: a method for fast and accurate global alignment of protein structures.

PubMed

Kifer, I; Nussinov, R; Wolfson, H J

2011-04-01

The database of known protein structures (PDB) is increasing rapidly. This results in a growing need for methods that can cope with the vast amount of structural data. To analyze the accumulating data, it is important to have a fast tool for identifying similar structures and clustering them by structural resemblance. Several excellent tools have been developed for the comparison of protein structures. These usually address the task of local structure alignment, an important yet computationally intensive problem due to its complexity. It is difficult to use such tools for comparing a large number of structures to each other at a reasonable time. Here we present GOSSIP, a novel method for a global all-against-all alignment of any set of protein structures. The method detects similarities between structures down to a certain cutoff (a parameter of the program), hence allowing it to detect similar structures at a much higher speed than local structure alignment methods. GOSSIP compares many structures in times which are several orders of magnitude faster than well-known available structure alignment servers, and it is also faster than a database scanning method. We evaluate GOSSIP both on a dataset of short structural fragments and on two large sequence-diverse structural benchmarks. Our conclusions are that for a threshold of 0.6 and above, the speed of GOSSIP is obtained with no compromise of the accuracy of the alignments or of the number of detected global similarities. A server, as well as an executable for download, are available at http://bioinfo3d.cs.tau.ac.il/gossip/.

CORAL: aligning conserved core regions across domain families.

PubMed

Fong, Jessica H; Marchler-Bauer, Aron

2009-08-01

Homologous protein families share highly conserved sequence and structure regions that are frequent targets for comparative analysis of related proteins and families. Many protein families, such as the curated domain families in the Conserved Domain Database (CDD), exhibit similar structural cores. To improve accuracy in aligning such protein families, we propose a profile-profile method CORAL that aligns individual core regions as gap-free units. CORAL computes optimal local alignment of two profiles with heuristics to preserve continuity within core regions. We benchmarked its performance on curated domains in CDD, which have pre-defined core regions, against COMPASS, HHalign and PSI-BLAST, using structure superpositions and comprehensive curator-optimized alignments as standards of truth. CORAL improves alignment accuracy on core regions over general profile methods, returning a balanced score of 0.57 for over 80% of all domain families in CDD, compared with the highest balanced score of 0.45 from other methods. Further, CORAL provides E-values to aid in detecting homologous protein families and, by respecting block boundaries, produces alignments with improved 'readability' that facilitate manual refinement. CORAL will be included in future versions of the NCBI Cn3D/CDTree software, which can be downloaded at http://www.ncbi.nlm.nih.gov/Structure/cdtree/cdtree.shtml. Supplementary data are available at Bioinformatics online.

L-GRAAL: Lagrangian graphlet-based network aligner.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2015-07-01

Discovering and understanding patterns in networks of protein-protein interactions (PPIs) is a central problem in systems biology. Alignments between these networks aid functional understanding as they uncover important information, such as evolutionary conserved pathways, protein complexes and functional orthologs. A few methods have been proposed for global PPI network alignments, but because of NP-completeness of underlying sub-graph isomorphism problem, producing topologically and biologically accurate alignments remains a challenge. We introduce a novel global network alignment tool, Lagrangian GRAphlet-based ALigner (L-GRAAL), which directly optimizes both the protein and the interaction functional conservations, using a novel alignment search heuristic based on integer programming and Lagrangian relaxation. We compare L-GRAAL with the state-of-the-art network aligners on the largest available PPI networks from BioGRID and observe that L-GRAAL uncovers the largest common sub-graphs between the networks, as measured by edge-correctness and symmetric sub-structures scores, which allow transferring more functional information across networks. We assess the biological quality of the protein mappings using the semantic similarity of their Gene Ontology annotations and observe that L-GRAAL best uncovers functionally conserved proteins. Furthermore, we introduce for the first time a measure of the semantic similarity of the mapped interactions and show that L-GRAAL also uncovers best functionally conserved interactions. In addition, we illustrate on the PPI networks of baker's yeast and human the ability of L-GRAAL to predict new PPIs. Finally, L-GRAAL's results are the first to show that topological information is more important than sequence information for uncovering functionally conserved interactions. L-GRAAL is coded in C++. Software is available at: http://bio-nets.doc.ic.ac.uk/L-GRAAL/. n.malod-dognin@imperial.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

The Structure of Rauvolfia serpentina Strictosidine Synthase Is a Novel Six-Bladed β-Propeller Fold in Plant Proteins[W

PubMed Central

Ma, Xueyan; Panjikar, Santosh; Koepke, Juergen; Loris, Elke; Stöckigt, Joachim

2006-01-01

The enzyme strictosidine synthase (STR1) from the Indian medicinal plant Rauvolfia serpentina is of primary importance for the biosynthetic pathway of the indole alkaloid ajmaline. Moreover, STR1 initiates all biosynthetic pathways leading to the entire monoterpenoid indole alkaloid family representing an enormous structural variety of ∼2000 compounds in higher plants. The crystal structures of STR1 in complex with its natural substrates tryptamine and secologanin provide structural understanding of the observed substrate preference and identify residues lining the active site surface that contact the substrates. STR1 catalyzes a Pictet-Spengler–type reaction and represents a novel six-bladed β-propeller fold in plant proteins. Structure-based sequence alignment revealed a common repetitive sequence motif (three hydrophobic residues are followed by a small residue and a hydrophilic residue), indicating a possible evolutionary relationship between STR1 and several sequence-unrelated six-bladed β-propeller structures. Structural analysis and site-directed mutagenesis experiments demonstrate the essential role of Glu-309 in catalysis. The data will aid in deciphering the details of the reaction mechanism of STR1 as well as other members of this enzyme family. PMID:16531499

The structure of Rauvolfia serpentina strictosidine synthase is a novel six-bladed beta-propeller fold in plant proteins.

PubMed

Ma, Xueyan; Panjikar, Santosh; Koepke, Juergen; Loris, Elke; Stöckigt, Joachim

2006-04-01

The enzyme strictosidine synthase (STR1) from the Indian medicinal plant Rauvolfia serpentina is of primary importance for the biosynthetic pathway of the indole alkaloid ajmaline. Moreover, STR1 initiates all biosynthetic pathways leading to the entire monoterpenoid indole alkaloid family representing an enormous structural variety of approximately 2000 compounds in higher plants. The crystal structures of STR1 in complex with its natural substrates tryptamine and secologanin provide structural understanding of the observed substrate preference and identify residues lining the active site surface that contact the substrates. STR1 catalyzes a Pictet-Spengler-type reaction and represents a novel six-bladed beta-propeller fold in plant proteins. Structure-based sequence alignment revealed a common repetitive sequence motif (three hydrophobic residues are followed by a small residue and a hydrophilic residue), indicating a possible evolutionary relationship between STR1 and several sequence-unrelated six-bladed beta-propeller structures. Structural analysis and site-directed mutagenesis experiments demonstrate the essential role of Glu-309 in catalysis. The data will aid in deciphering the details of the reaction mechanism of STR1 as well as other members of this enzyme family.

Aplysia attractin: biophysical characterization and modeling of a water-borne pheromone.

PubMed Central

Schein, C H; Nagle, G T; Page, J S; Sweedler, J V; Xu, Y; Painter, S D; Braun, W

2001-01-01

Attractin, a 58-residue protein secreted by the mollusk Aplysia californica, stimulates sexually mature animals to approach egg cordons. Attractin from five different Aplysia species are approximately 40% identical in sequence. Recombinant attractin, expressed in insect cells and purified by reverse-phase high-performance liquid chromatography (RP-HPLC), is active in a bioassay using A. brasiliana; its circular dichroism (CD) spectrum indicates a predominantly alpha-helical structure. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) characterization of proteolytic fragments identified disulfide bonds between the six conserved cysteines (I-VI, II-V, III-IV, where the Roman numeral indicates the order of occurrence in the primary sequence). Attractin has no significant similarity to any other sequence in the database. The protozoan Euplotes pheromones were selected by fold recognition as possible templates. These diverse proteins have three alpha-helices, with six cysteine residues disulfide-bonded in a different pattern from attractin. Model structures with good stereochemical parameters were prepared using the EXDIS/DIAMOD/FANTOM program suite and constraints based on sequence alignments with the Euplotes templates and the attractin disulfide bonds. A potential receptor-binding site is suggested based on these data. Future structural characterization of attractin will be needed to confirm these models. PMID:11423429

SANSparallel: interactive homology search against Uniprot.

PubMed

Somervuo, Panu; Holm, Liisa

2015-07-01

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

libgapmis: extending short-read alignments

PubMed Central

2013-01-01

Background A wide variety of short-read alignment programmes have been published recently to tackle the problem of mapping millions of short reads to a reference genome, focusing on different aspects of the procedure such as time and memory efficiency, sensitivity, and accuracy. These tools allow for a small number of mismatches in the alignment; however, their ability to allow for gaps varies greatly, with many performing poorly or not allowing them at all. The seed-and-extend strategy is applied in most short-read alignment programmes. After aligning a substring of the reference sequence against the high-quality prefix of a short read--the seed--an important problem is to find the best possible alignment between a substring of the reference sequence succeeding and the remaining suffix of low quality of the read--extend. The fact that the reads are rather short and that the gap occurrence frequency observed in various studies is rather low suggest that aligning (parts of) those reads with a single gap is in fact desirable. Results In this article, we present libgapmis, a library for extending pairwise short-read alignments. Apart from the standard CPU version, it includes ultrafast SSE- and GPU-based implementations. libgapmis is based on an algorithm computing a modified version of the traditional dynamic-programming matrix for sequence alignment. Extensive experimental results demonstrate that the functions of the CPU version provided in this library accelerate the computations by a factor of 20 compared to other programmes. The analogous SSE- and GPU-based implementations accelerate the computations by a factor of 6 and 11, respectively, compared to the CPU version. The library also provides the user the flexibility to split the read into fragments, based on the observed gap occurrence frequency and the length of the read, thereby allowing for a variable, but bounded, number of gaps in the alignment. Conclusions We present libgapmis, a library for extending pairwise short-read alignments. We show that libgapmis is better-suited and more efficient than existing algorithms for this task. The importance of our contribution is underlined by the fact that the provided functions may be seamlessly integrated into any short-read alignment pipeline. The open-source code of libgapmis is available at http://www.exelixis-lab.org/gapmis. PMID:24564250

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

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.

Gibbs motif sampling: detection of bacterial outer membrane protein repeats.

PubMed Central

Neuwald, A. F.; Liu, J. S.; Lawrence, C. E.

1995-01-01

The detection and alignment of locally conserved regions (motifs) in multiple sequences can provide insight into protein structure, function, and evolution. A new Gibbs sampling algorithm is described that detects motif-encoding regions in sequences and optimally partitions them into distinct motif models; this is illustrated using a set of immunoglobulin fold proteins. When applied to sequences sharing a single motif, the sampler can be used to classify motif regions into related submodels, as is illustrated using helix-turn-helix DNA-binding proteins. Other statistically based procedures are described for searching a database for sequences matching motifs found by the sampler. When applied to a set of 32 very distantly related bacterial integral outer membrane proteins, the sampler revealed that they share a subtle, repetitive motif. Although BLAST (Altschul SF et al., 1990, J Mol Biol 215:403-410) fails to detect significant pairwise similarity between any of the sequences, the repeats present in these outer membrane proteins, taken as a whole, are highly significant (based on a generally applicable statistical test for motifs described here). Analysis of bacterial porins with known trimeric beta-barrel structure and related proteins reveals a similar repetitive motif corresponding to alternating membrane-spanning beta-strands. These beta-strands occur on the membrane interface (as opposed to the trimeric interface) of the beta-barrel. The broad conservation and structural location of these repeats suggests that they play important functional roles. PMID:8520488

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

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

RNA 3D Modules in Genome-Wide Predictions of RNA 2D Structure

PubMed Central

Theis, Corinna; Zirbel, Craig L.; zu Siederdissen, Christian Höner; Anthon, Christian; Hofacker, Ivo L.; Nielsen, Henrik; Gorodkin, Jan

2015-01-01

Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence. PMID:26509713

Extracting DNA words based on the sequence features: non-uniform distribution and integrity.

PubMed

Li, Zhi; Cao, Hongyan; Cui, Yuehua; Zhang, Yanbo

2016-01-25

DNA sequence can be viewed as an unknown language with words as its functional units. Given that most sequence alignment algorithms such as the motif discovery algorithms depend on the quality of background information about sequences, it is necessary to develop an ab initio algorithm for extracting the "words" based only on the DNA sequences. We considered that non-uniform distribution and integrity were two important features of a word, based on which we developed an ab initio algorithm to extract "DNA words" that have potential functional meaning. A Kolmogorov-Smirnov test was used for consistency test of uniform distribution of DNA sequences, and the integrity was judged by the sequence and position alignment. Two random base sequences were adopted as negative control, and an English book was used as positive control to verify our algorithm. We applied our algorithm to the genomes of Saccharomyces cerevisiae and 10 strains of Escherichia coli to show the utility of the methods. The results provide strong evidences that the algorithm is a promising tool for ab initio building a DNA dictionary. Our method provides a fast way for large scale screening of important DNA elements and offers potential insights into the understanding of a genome.

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 .

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

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

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.

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

The practical evaluation of DNA barcode efficacy.

PubMed

Spouge, John L; Mariño-Ramírez, Leonardo

2012-01-01

This chapter describes a workflow for measuring the efficacy of a barcode in identifying species. First, assemble individual sequence databases corresponding to each barcode marker. A controlled collection of taxonomic data is preferable to GenBank data, because GenBank data can be problematic, particularly when comparing barcodes based on more than one marker. To ensure proper controls when evaluating species identification, specimens not having a sequence in every marker database should be discarded. Second, select a computer algorithm for assigning species to barcode sequences. No algorithm has yet improved notably on assigning a specimen to the species of its nearest neighbor within a barcode database. Because global sequence alignments (e.g., with the Needleman-Wunsch algorithm, or some related algorithm) examine entire barcode sequences, they generally produce better species assignments than local sequence alignments (e.g., with BLAST). No neighboring method (e.g., global sequence similarity, global sequence distance, or evolutionary distance based on a global alignment) has yet shown a notable superiority in identifying species. Finally, "the probability of correct identification" (PCI) provides an appropriate measurement of barcode efficacy. The overall PCI for a data set is the average of the species PCIs, taken over all species in the data set. This chapter states explicitly how to calculate PCI, how to estimate its statistical sampling error, and how to use data on PCR failure to set limits on how much improvements in PCR technology can improve species identification.

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 .

Assessment of Homology Templates and an Anesthetic Binding Site within the γ-Aminobutyric Acid Receptor

PubMed Central

Bertaccini, Edward J.; Yoluk, Ozge; Lindahl, Erik R.; Trudell, James R.

2013-01-01

Background Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). While its molecular structure remains unknown, significant progress has been made towards understanding its interactions with anesthetics via molecular modeling. Methods The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50’s. Results Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between alpha and beta subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Conclusion Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed correlation of ligand docking scores with experimentally measured GABAaR potentiation. PMID:23770602

Assessment of homology templates and an anesthetic binding site within the γ-aminobutyric acid receptor.

PubMed

Bertaccini, Edward J; Yoluk, Ozge; Lindahl, Erik R; Trudell, James R

2013-11-01

Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). Although its molecular structure remains unknown, significant progress has been made toward understanding its interactions with anesthetics via molecular modeling. The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH-sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50s. Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between α and β subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed a correlation of ligand docking scores with experimentally measured GABAaR potentiation.

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

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

Predicting helix orientation for coiled-coil dimers

PubMed Central

Apgar, James R.; Gutwin, Karl N.; Keating, Amy E.

2008-01-01

The alpha-helical coiled coil is a structurally simple protein oligomerization or interaction motif consisting of two or more alpha helices twisted into a supercoiled bundle. Coiled coils can differ in their stoichiometry, helix orientation and axial alignment. Because of the near degeneracy of many of these variants, coiled coils pose a challenge to fold recognition methods for structure prediction. Whereas distinctions between some protein folds can be discriminated on the basis of hydrophobic/polar patterning or secondary structure propensities, the sequence differences that encode important details of coiled-coil structure can be subtle. This is emblematic of a larger problem in the field of protein structure and interaction prediction: that of establishing specificity between closely similar structures. We tested the behavior of different computational models on the problem of recognizing the correct orientation - parallel vs. antiparallel - of pairs of alpha helices that can form a dimeric coiled coil. For each of 131 examples of known structure, we constructed a large number of both parallel and antiparallel structural models and used these to asses the ability of five energy functions to recognize the correct fold. We also developed and tested three sequenced-based approaches that make use of varying degrees of implicit structural information. The best structural methods performed similarly to the best sequence methods, correctly categorizing ∼81% of dimers. Steric compatibility with the fold was important for some coiled coils we investigated. For many examples, the correct orientation was determined by smaller energy differences between parallel and antiparallel structures distributed over many residues and energy components. Prediction methods that used structure but incorporated varying approximations and assumptions showed quite different behaviors when used to investigate energetic contributions to orientation preference. Sequence based methods were sensitive to the choice of residue-pair interactions scored. PMID:18506779

Interspecific variation in mitochondrial serine transfer RNA (UCN) in Euptychiina butterflies (Lepidoptera: Satyrinae): structure and alignment.

PubMed

Marín, Mario Alejandro; López, Andrés; Uribe, Sandra Inés

2012-06-01

The nucleotide variation and structural patterns of mitochondrial RNA molecule have been proposed as useful tools in molecular systematics; however, their usefulness is always subject to a proper assessment of homology in the sequence alignment. The present study describes the secondary structure of mitochondrial tRNA for the amino acid serine (UCN) on 13 Euptychiina species and the evaluation of its potential use for evolutionary studies in this group of butterflies. The secondary structure of tRNAs showed variation among the included species except between Hermeuptychia sp1 and sp2. Variation was concentrated in the ribotimidina-pseudouridine-cystosine (TψC), dihydrouridine (DHU) and variable loops and in the DHU and TψC arms. These results suggest this region as a potential marker useful for taxonomic differentiation of species in this group and also confirm the importance of including information from the secondary structure of tRNA to optimize the alignments.

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes

PubMed Central

Otto, Thomas Dan; Catanho, Marcos; Tristão, Cristian; Bezerra, Márcia; Fernandes, Renan Mathias; Elias, Guilherme Steinberger; Scaglia, Alexandre Capeletto; Bovermann, Bill; Berstis, Viktors; Lifschitz, Sergio; de Miranda, Antonio Basílio; Degrave, Wim

2010-01-01

Motivation: Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith–Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community Grid™, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective scores, is now made available. Users can download, compare and analyze the results, filtered by genomes, protein functions or clusters. ProteinWorldDB is integrated with annotations derived from Swiss-Prot, Pfam, KEGG, NCBI Taxonomy database and gene ontology. The database is a unique and valuable asset, representing a major effort to create a reliable and consistent dataset of cross-comparisons of the whole protein content encoded in hundreds of completely sequenced genomes using a rigorous dynamic programming approach. Availability: The database can be accessed through http://proteinworlddb.org Contact: otto@fiocruz.br PMID:20089515

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.

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.

ITS2 sequence-structure phylogeny reveals diverse endophytic Pseudocercospora fungi on poplars.

PubMed

Yan, Dong-Hui; Gao, Qian; Sun, Xiaoming; Song, Xiaoyu; Li, Hongchang

2018-04-01

For matching the new fungal nomenclature to abolish pleomorphic names for a fungus, a genus Pseudocercospora s. str. was suggested to host holomorphic Pseudocercosproa fungi. But the Pseudocercosproa fungi need extra phylogenetic loci to clarify their taxonomy and diversity for their existing and coming species. Internal transcribed spacer 2 (ITS2) secondary structures have been promising in charactering species phylogeny in plants, animals and fungi. In present study, a conserved model of ITS2 secondary structures was confirmed on fungi in Pseudocercospora s. str. genus using RNAshape program. The model has a typical eukaryotic four-helix ITS2 secondary structure. But a single U base occurred in conserved motif of U-U mismatch in Helix 2, and a UG emerged in UGGU motif in Helix 3 to Pseudocercospora fungi. The phylogeny analyses based on the ITS2 sequence-secondary structures with compensatory base change characterizations are able to delimit more species for Pseudocercospora s. str. than phylogenic inferences of traditional multi-loci alignments do. The model was employed to explore the diversity of endophytic Pseudocercospora fungi in poplar trees. The analysis results also showed that endophytic Pseudocercospora fungi were diverse in species and evolved a specific lineage in poplar trees. This work suggested that ITS2 sequence-structures could become as additionally significant loci for species phylogenetic and taxonomic studies on Pseudocerospora fungi, and that Pseudocercospora endophytes could be important roles to Pseudocercospora fungi's evolution and function in ecology.

The evolution of function within the Nudix homology clan

PubMed Central

Srouji, John R.; Xu, Anting; Park, Annsea; Kirsch, Jack F.

2017-01-01

ABSTRACT The Nudix homology clan encompasses over 80,000 protein domains from all three domains of life, defined by homology to each other. Proteins with a domain from this clan fall into four general functional classes: pyrophosphohydrolases, isopentenyl diphosphate isomerases (IDIs), adenine/guanine mismatch‐specific adenine glycosylases (A/G‐specific adenine glycosylases), and nonenzymatic activities such as protein/protein interaction and transcriptional regulation. The largest group, pyrophosphohydrolases, encompasses more than 100 distinct hydrolase specificities. To understand the evolution of this vast number of activities, we assembled and analyzed experimental and structural data for 205 Nudix proteins collected from the literature. We corrected erroneous functions or provided more appropriate descriptions for 53 annotations described in the Gene Ontology Annotation database in this family, and propose 275 new experimentally‐based annotations. We manually constructed a structure‐guided sequence alignment of 78 Nudix proteins. Using the structural alignment as a seed, we then made an alignment of 347 “select” Nudix homology domains, curated from structurally determined, functionally characterized, or phylogenetically important Nudix domains. Based on our review of Nudix pyrophosphohydrolase structures and specificities, we further analyzed a loop region downstream of the Nudix hydrolase motif previously shown to contact the substrate molecule and possess known functional motifs. This loop region provides a potential structural basis for the functional radiation and evolution of substrate specificity within the hydrolase family. Finally, phylogenetic analyses of the 347 select protein domains and of the complete Nudix homology clan revealed general monophyly with regard to function and a few instances of probable homoplasy. Proteins 2017; 85:775–811. © 2016 Wiley Periodicals, Inc. PMID:27936487

Mutation of domain III and domain VI in L gene conserved domain of Nipah virus

NASA Astrophysics Data System (ADS)

Jalani, Siti Aishah; Ibrahim, Nazlina

2016-11-01

Nipah virus (NiV) is the etiologic agent responsible for the respiratory illness and causes fatal encephalitis in human. NiV L protein subunit is thought to be responsible for the majority of enzymatic activities involved in viral transcription and replication. The L protein which is the viral RNA dependent RNA polymerase has high sequence homology among negative sense RNA viruses. In negative stranded RNA viruses, based on sequence alignment six conserved domain (domain I-IV) have been determined. Each domain is separated on variable regions that suggest the structure to consist concatenated functional domain. To directly address the roles of domains III and VI, site-directed mutations were constructed by the substitution of bases at sequences 2497, 2500, 5528 and 5532. Each mutated L gene can be used in future studies to test the ability for expression on in vitro translation.

Alignment-free microbial phylogenomics under scenarios of sequence divergence, genome rearrangement and lateral genetic transfer.

PubMed

Bernard, Guillaume; Chan, Cheong Xin; Ragan, Mark A

2016-07-01

Alignment-free (AF) approaches have recently been highlighted as alternatives to methods based on multiple sequence alignment in phylogenetic inference. However, the sensitivity of AF methods to genome-scale evolutionary scenarios is little known. Here, using simulated microbial genome data we systematically assess the sensitivity of nine AF methods to three important evolutionary scenarios: sequence divergence, lateral genetic transfer (LGT) and genome rearrangement. Among these, AF methods are most sensitive to the extent of sequence divergence, less sensitive to low and moderate frequencies of LGT, and most robust against genome rearrangement. We describe the application of AF methods to three well-studied empirical genome datasets, and introduce a new application of the jackknife to assess node support. Our results demonstrate that AF phylogenomics is computationally scalable to multi-genome data and can generate biologically meaningful phylogenies and insights into microbial evolution.

Gemi: PCR Primers Prediction from Multiple Alignments

PubMed Central

Sobhy, Haitham; Colson, Philippe

2012-01-01

Designing primers and probes for polymerase chain reaction (PCR) is a preliminary and critical step that requires the identification of highly conserved regions in a given set of sequences. This task can be challenging if the targeted sequences display a high level of diversity, as frequently encountered in microbiologic studies. We developed Gemi, an automated, fast, and easy-to-use bioinformatics tool with a user-friendly interface to design primers and probes based on multiple aligned sequences. This tool can be used for the purpose of real-time and conventional PCR and can deal efficiently with large sets of sequences of a large size. PMID:23316117

Accurate indel prediction using paired-end short reads

PubMed Central

2013-01-01

Background One of the major open challenges in next generation sequencing (NGS) is the accurate identification of structural variants such as insertions and deletions (indels). Current methods for indel calling assign scores to different types of evidence or counter-evidence for the presence of an indel, such as the number of split read alignments spanning the boundaries of a deletion candidate or reads that map within a putative deletion. Candidates with a score above a manually defined threshold are then predicted to be true indels. As a consequence, structural variants detected in this manner contain many false positives. Results Here, we present a machine learning based method which is able to discover and distinguish true from false indel candidates in order to reduce the false positive rate. Our method identifies indel candidates using a discriminative classifier based on features of split read alignment profiles and trained on true and false indel candidates that were validated by Sanger sequencing. We demonstrate the usefulness of our method with paired-end Illumina reads from 80 genomes of the first phase of the 1001 Genomes Project ( http://www.1001genomes.org) in Arabidopsis thaliana. Conclusion In this work we show that indel classification is a necessary step to reduce the number of false positive candidates. We demonstrate that missing classification may lead to spurious biological interpretations. The software is available at: http://agkb.is.tuebingen.mpg.de/Forschung/SV-M/. PMID:23442375

Identification of a Herbal Powder by Deoxyribonucleic Acid Barcoding and Structural Analyses.

PubMed

Sheth, Bhavisha P; Thaker, Vrinda S

2015-10-01

Authentic identification of plants is essential for exploiting their medicinal properties as well as to stop the adulteration and malpractices with the trade of the same. To identify a herbal powder obtained from a herbalist in the local vicinity of Rajkot, Gujarat, using deoxyribonucleic acid (DNA) barcoding and molecular tools. The DNA was extracted from a herbal powder and selected Cassia species, followed by the polymerase chain reaction (PCR) and sequencing of the rbcL barcode locus. Thereafter the sequences were subjected to National Center for Biotechnology Information (NCBI) basic local alignment search tool (BLAST) analysis, followed by the protein three-dimension structure determination of the rbcL protein from the herbal powder and Cassia species namely Cassia fistula, Cassia tora and Cassia javanica (sequences obtained in the present study), Cassia Roxburghii, and Cassia abbreviata (sequences retrieved from Genbank). Further, the multiple and pairwise structural alignment were carried out in order to identify the herbal powder. The nucleotide sequences obtained from the selected species of Cassia were submitted to Genbank (Accession No. JX141397, JX141405, JX141420). The NCBI BLAST analysis of the rbcL protein from the herbal powder showed an equal sequence similarity (with reference to different parameters like E value, maximum identity, total score, query coverage) to C. javanica and C. roxburghii. In order to solve the ambiguities of the BLAST result, a protein structural approach was implemented. The protein homology models obtained in the present study were submitted to the protein model database (PM0079748-PM0079753). The pairwise structural alignment of the herbal powder (as template) and C. javanica and C. roxburghii (as targets individually) revealed a close similarity of the herbal powder with C. javanica. A strategy as used here, incorporating the integrated use of DNA barcoding and protein structural analyses could be adopted, as a novel rapid and economic procedure, especially in cases when protein coding loci are considered. Authentic identification of plants is essential for exploiting their medicinal properties as well as to stop the adulteration and malpractices with the trade of the same. A herbal powder was obtained from a herbalist in the local vicinity of Rajkot, Gujarat. An integrated approach using DNA barcoding and structural analyses was carried out to identify the herbal powder. The herbal powder was identified as Cassia javanica L.

Secondary structure prediction for complete rDNA sequences (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, and comparison of divergent domains structures across Acari.

PubMed

Zhao, Ya-E; Wang, Zheng-Hang; Xu, Yang; Wu, Li-Ping; Hu, Li

2013-10-01

According to base pairing, the rRNA folds into corresponding secondary structures, which contain additional phylogenetic information. On the basis of sequencing for complete rDNA sequences (18S, ITS1, 5.8S, ITS2 and 28S rDNA) of Demodex, we predicted the secondary structure of the complete rDNA sequence (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, which was in concordance with that of the main arthropod lineages in past studies. And together with the sequence data from GenBank, we also predicted the secondary structures of divergent domains in SSU rRNA of 51 species and in LSU rRNA of 43 species from four superfamilies in Acari (Cheyletoidea, Tetranychoidea, Analgoidea and Ixodoidea). The multiple alignment among the four superfamilies in Acari showed that, insertions from Tetranychoidea SSU rRNA formed two newly proposed helixes, and helix c3-2b of LSU rRNA was absent in Demodex (Cheyletoidea) taxa. Generally speaking, LSU rRNA presented more remarkable differences than SSU rRNA did, mainly in D2, D3, D5, D7a, D7b, D8 and D10. Copyright © 2013 Elsevier Inc. All rights reserved.

Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences.

PubMed

Lentes, K U; Mathieu, E; Bischoff, R; Rasmussen, U B; Pavirani, A

1993-01-01

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%, since maximization of a homology score does not take into account any structural information. A new technique called Hydrophobic Cluster Analysis (HCA) has been developed by Lemesle-Varloot et al. (Biochimie 72, 555-574), 1990). This consists of comparing several sequences simultaneously and combining homology detection with secondary structure analysis. HCA is primarily based on the detection and comparison of structural segments constituting the hydrophobic core of globular protein domains, with or without transmembrane domains. We have applied HCA to the analysis of different families of G-protein coupled receptors, such as catecholamine receptors as well as peptide hormone receptors. Utilizing HCA the thrombin receptor, a new and as yet unique member of the family of G-protein coupled receptors, can be clearly classified as being closely related to the family of neuropeptide receptors rather than to the catecholamine receptors for which the shape of the hydrophobic clusters and the length of their third cytoplasmic loop are very different. Furthermore, the potential of HCA to predict relationships between new putative and already characterized members of this family of receptors will be presented.

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.

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.

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

The structure of TON1937 from archaeon Thermococcus onnurineus NA1 reveals a eukaryotic HEAT-like architecture.

PubMed

Jeong, Jae-Hee; Kim, Yi-Seul; Rojviriya, Catleya; Cha, Hyung Jin; Ha, Sung-Chul; Kim, Yeon-Gil

2013-10-01

The members of the ARM/HEAT repeat-containing protein superfamily in eukaryotes have been known to mediate protein-protein interactions by using their concave surface. However, little is known about the ARM/HEAT repeat proteins in prokaryotes. Here we report the crystal structure of TON1937, a hypothetical protein from the hyperthermophilic archaeon Thermococcus onnurineus NA1. The structure reveals a crescent-shaped molecule composed of a double layer of α-helices with seven anti-parallel α-helical repeats. A structure-based sequence alignment of the α-helical repeats identified a conserved pattern of hydrophobic or aliphatic residues reminiscent of the consensus sequence of eukaryotic HEAT repeats. The individual repeats of TON1937 also share high structural similarity with the canonical eukaryotic HEAT repeats. In addition, the concave surface of TON1937 is proposed to be its potential binding interface based on this structural comparison and its surface properties. These observations lead us to speculate that the archaeal HEAT-like repeats of TON1937 have evolved to engage in protein-protein interactions in the same manner as eukaryotic HEAT repeats. Copyright © 2013 Elsevier B.V. All rights reserved.

Physically motivated global alignment method for electron tomography

DOE PAGES

Sanders, Toby; Prange, Micah; Akatay, Cem; ...

2015-04-08

Electron tomography is widely used for nanoscale determination of 3-D structures in many areas of science. Determining the 3-D structure of a sample from electron tomography involves three major steps: acquisition of sequence of 2-D projection images of the sample with the electron microscope, alignment of the images to a common coordinate system, and 3-D reconstruction and segmentation of the sample from the aligned image data. The resolution of the 3-D reconstruction is directly influenced by the accuracy of the alignment, and therefore, it is crucial to have a robust and dependable alignment method. In this paper, we develop amore » new alignment method which avoids the use of markers and instead traces the computed paths of many identifiable ‘local’ center-of-mass points as the sample is rotated. Compared with traditional correlation schemes, the alignment method presented here is resistant to cumulative error observed from correlation techniques, has very rigorous mathematical justification, and is very robust since many points and paths are used, all of which inevitably improves the quality of the reconstruction and confidence in the scientific results.« less

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.

Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

PubMed Central

Gillespie, J J; Johnston, J S; Cannone, J J; Gutell, R R

2006-01-01

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)-encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non-conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements. PMID:17069639

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

Phylo: A Citizen Science Approach for Improving Multiple Sequence Alignment

PubMed Central

Kam, Alfred; Kwak, Daniel; Leung, Clarence; Wu, Chu; Zarour, Eleyine; Sarmenta, Luis; Blanchette, Mathieu; Waldispühl, Jérôme

2012-01-01

Background Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server. Methodology/Principal Findings We introduce Phylo, a human-based computing framework applying “crowd sourcing” techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered. Conclusions/Significance We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of “human-brain peta-flops” of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca. PMID:22412834

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 .

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

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.

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

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...

DNA sequence alignment by microhomology sampling during homologous recombination

PubMed Central

Qi, Zhi; Redding, Sy; Lee, Ja Yil; Gibb, Bryan; Kwon, YoungHo; Niu, Hengyao; Gaines, William A.; Sung, Patrick

2015-01-01

Summary Homologous recombination (HR) mediates the exchange of genetic information between sister or homologous chromatids. During HR, members of the RecA/Rad51 family of recombinases must somehow search through vast quantities of DNA sequence to align and pair ssDNA with a homologous dsDNA template. Here we use single-molecule imaging to visualize Rad51 as it aligns and pairs homologous DNA sequences in real-time. We show that Rad51 uses a length-based recognition mechanism while interrogating dsDNA, enabling robust kinetic selection of 8-nucleotide (nt) tracts of microhomology, which kinetically confines the search to sites with a high probability of being a homologous target. Successful pairing with a 9th nucleotide coincides with an additional reduction in binding free energy and subsequent strand exchange occurs in precise 3-nt steps, reflecting the base triplet organization of the presynaptic complex. These findings provide crucial new insights into the physical and evolutionary underpinnings of DNA recombination. PMID:25684365

Compilation of small ribosomal subunit RNA structures.

PubMed Central

Neefs, J M; Van de Peer, Y; De Rijk, P; Chapelle, S; De Wachter, R

1993-01-01

The database on small ribosomal subunit RNA structure contained 1804 nucleotide sequences on April 23, 1993. This number comprises 365 eukaryotic, 65 archaeal, 1260 bacterial, 30 plastidial, and 84 mitochondrial sequences. These are stored in the form of an alignment in order to facilitate the use of the database as input for comparative studies on higher-order structure and for reconstruction of phylogenetic trees. The elements of the postulated secondary structure for each molecule are indicated by special symbols. The database is available on-line directly from the authors by ftp and can also be obtained from the EMBL nucleotide sequence library by electronic mail, ftp, and on CD ROM disk. PMID:8332525

Aligning the unalignable: bacteriophage whole genome alignments.

PubMed

Bérard, Sèverine; Chateau, Annie; Pompidor, Nicolas; Guertin, Paul; Bergeron, Anne; Swenson, Krister M

2016-01-13

In recent years, many studies focused on the description and comparison of large sets of related bacteriophage genomes. Due to the peculiar mosaic structure of these genomes, few informative approaches for comparing whole genomes exist: dot plots diagrams give a mostly qualitative assessment of the similarity/dissimilarity between two or more genomes, and clustering techniques are used to classify genomes. Multiple alignments are conspicuously absent from this scene. Indeed, whole genome aligners interpret lack of similarity between sequences as an indication of rearrangements, insertions, or losses. This behavior makes them ill-prepared to align bacteriophage genomes, where even closely related strains can accomplish the same biological function with highly dissimilar sequences. In this paper, we propose a multiple alignment strategy that exploits functional collinearity shared by related strains of bacteriophages, and uses partial orders to capture mosaicism of sets of genomes. As classical alignments do, the computed alignments can be used to predict that genes have the same biological function, even in the absence of detectable similarity. The Alpha aligner implements these ideas in visual interactive displays, and is used to compute several examples of alignments of Staphylococcus aureus and Mycobacterium bacteriophages, involving up to 29 genomes. Using these datasets, we prove that Alpha alignments are at least as good as those computed by standard aligners. Comparison with the progressive Mauve aligner - which implements a partial order strategy, but whose alignments are linearized - shows a greatly improved interactive graphic display, while avoiding misalignments. Multiple alignments of whole bacteriophage genomes work, and will become an important conceptual and visual tool in comparative genomics of sets of related strains. A python implementation of Alpha, along with installation instructions for Ubuntu and OSX, is available on bitbucket (https://bitbucket.org/thekswenson/alpha).

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.

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

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

Origins and challenges of viral dark matter.

PubMed

Krishnamurthy, Siddharth R; Wang, David

2017-07-15

The accurate classification of viral dark matter - metagenomic sequences that originate from viruses but do not align to any reference virus sequences - is one of the major obstacles in comprehensively defining the virome. Depending on the sample, viral dark matter can make up from anywhere between 40 and 90% of sequences. This review focuses on the specific nature of dark matter as it relates to viral sequences. We identify three factors that contribute to the existence of viral dark matter: the divergence and length of virus sequences, the limitations of alignment based classification, and limited representation of viruses in reference sequence databases. We then discuss current methods that have been developed to at least partially circumvent these limitations and thereby reduce the extent of viral dark matter. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Consolidation of glycosyl hydrolase family 30 : a dual domain 4/7 hydrolase family consisting of two structurally distinct groups

Treesearch

Franz J. St John; Javier M. Gonzalez; Edwin Pozharski

2010-01-01

In this work glycosyl hydrolase (GH) family 30 (GH30) is analyzed and shown to consist of its currently classified member sequences as well as several homologous sequence groups currently assigned within family GH5. A large scale amino acid sequence alignment and a phylogenetic tree were generated and GH30 groups and subgroups were designated. A partial rearrangement...

Ichthyophonus parasite phylogeny based on ITS rDNA structure prediction and alignment identifies six clades, with a single dominant marine type

USGS Publications Warehouse

Gregg, Jacob; Thompson, Rachel L.; Purcell, Maureen; Friedman, Carolyn S.; Hershberger, Paul

2016-01-01

Despite their widespread, global impact in both wild and cultured fishes, little is known of the diversity, transmission patterns, and phylogeography of parasites generally identified as Ichthyophonus. This study constructed a phylogeny based on the structural alignment of internal transcribed spacer (ITS) rDNA sequences to compare Ichthyophonus isolates from fish hosts in the Atlantic and Pacific oceans, and several rivers and aquaculture sites in North America, Europe, and Japan. Structure of the Ichthyophonus ITS1–5.8S–ITS2 transcript exhibited several homologies with other eukaryotes, and 6 distinct clades were identified within Ichthyophonus. A single clade contained a majority (71 of 98) of parasite isolations. This ubiquitous Ichthyophonus type occurred in 13 marine and anadromous hosts and was associated with epizootics in Atlantic herring, Chinook salmon, and American shad. A second clade contained all isolates from aquaculture, despite great geographic separation of the freshwater hosts. Each of the 4 remaining clades contained isolates from single host species. This study is the first to evaluate the genetic relationships among Ichthyophonus species across a significant portion of their host and geographic range. Additionally, parasite infection prevalence is reported in 16 fish species.

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.

A new statistical framework to assess structural alignment quality using information compression

PubMed Central

Collier, James H.; Allison, Lloyd; Lesk, Arthur M.; Garcia de la Banda, Maria; Konagurthu, Arun S.

2014-01-01

Motivation: Progress in protein biology depends on the reliability of results from a handful of computational techniques, structural alignments being one. Recent reviews have highlighted substantial inconsistencies and differences between alignment results generated by the ever-growing stock of structural alignment programs. The lack of consensus on how the quality of structural alignments must be assessed has been identified as the main cause for the observed differences. Current methods assess structural alignment quality by constructing a scoring function that attempts to balance conflicting criteria, mainly alignment coverage and fidelity of structures under superposition. This traditional approach to measuring alignment quality, the subject of considerable literature, has failed to solve the problem. Further development along the same lines is unlikely to rectify the current deficiencies in the field. Results: This paper proposes a new statistical framework to assess structural alignment quality and significance based on lossless information compression. This is a radical departure from the traditional approach of formulating scoring functions. It links the structural alignment problem to the general class of statistical inductive inference problems, solved using the information-theoretic criterion of minimum message length. Based on this, we developed an efficient and reliable measure of structural alignment quality, I-value. The performance of I-value is demonstrated in comparison with a number of popular scoring functions, on a large collection of competing alignments. Our analysis shows that I-value provides a rigorous and reliable quantification of structural alignment quality, addressing a major gap in the field. Availability: http://lcb.infotech.monash.edu.au/I-value Contact: arun.konagurthu@monash.edu Supplementary information: Online supplementary data are available at http://lcb.infotech.monash.edu.au/I-value/suppl.html PMID:25161241

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

PubMed

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

2015-01-01

Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.

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

Phylogenetic study of Class Armophorea (Alveolata, Ciliophora) based on 18S-rDNA data.

PubMed

da Silva Paiva, Thiago; do Nascimento Borges, Bárbara; da Silva-Neto, Inácio Domingos

2013-12-01

The 18S rDNA phylogeny of Class Armophorea, a group of anaerobic ciliates, is proposed based on an analysis of 44 sequences (out of 195) retrieved from the NCBI/GenBank database. Emphasis was placed on the use of two nucleotide alignment criteria that involved variation in the gap-opening and gap-extension parameters and the use of rRNA secondary structure to orientate multiple-alignment. A sensitivity analysis of 76 data sets was run to assess the effect of variations in indel parameters on tree topologies. Bayesian inference, maximum likelihood and maximum parsimony phylogenetic analyses were used to explore how different analytic frameworks influenced the resulting hypotheses. A sensitivity analysis revealed that the relationships among higher taxa of the Intramacronucleata were dependent upon how indels were determined during multiple-alignment of nucleotides. The phylogenetic analyses rejected the monophyly of the Armophorea most of the time and consistently indicated that the Metopidae and Nyctotheridae were related to the Litostomatea. There was no consensus on the placement of the Caenomorphidae, which could be a sister group of the Metopidae + Nyctorheridae, or could have diverged at the base of the Spirotrichea branch or the Intramacronucleata tree.

Phylogenetic study of Class Armophorea (Alveolata, Ciliophora) based on 18S-rDNA data

PubMed Central

da Silva Paiva, Thiago; do Nascimento Borges, Bárbara; da Silva-Neto, Inácio Domingos

2013-01-01

The 18S rDNA phylogeny of Class Armophorea, a group of anaerobic ciliates, is proposed based on an analysis of 44 sequences (out of 195) retrieved from the NCBI/GenBank database. Emphasis was placed on the use of two nucleotide alignment criteria that involved variation in the gap-opening and gap-extension parameters and the use of rRNA secondary structure to orientate multiple-alignment. A sensitivity analysis of 76 data sets was run to assess the effect of variations in indel parameters on tree topologies. Bayesian inference, maximum likelihood and maximum parsimony phylogenetic analyses were used to explore how different analytic frameworks influenced the resulting hypotheses. A sensitivity analysis revealed that the relationships among higher taxa of the Intramacronucleata were dependent upon how indels were determined during multiple-alignment of nucleotides. The phylogenetic analyses rejected the monophyly of the Armophorea most of the time and consistently indicated that the Metopidae and Nyctotheridae were related to the Litostomatea. There was no consensus on the placement of the Caenomorphidae, which could be a sister group of the Metopidae + Nyctorheridae, or could have diverged at the base of the Spirotrichea branch or the Intramacronucleata tree. PMID:24385862

Metabarcoding of marine nematodes – evaluation of reference datasets used in tree-based taxonomy assignment approach

PubMed Central

2016-01-01

Abstract Background Metabarcoding is becoming a common tool used to assess and compare diversity of organisms in environmental samples. Identification of OTUs is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task. This publication evaluates the quality of reference datasets, alongside with several alignment and phylogeny inference methods used in one of the taxonomy assignment methods, called tree-based approach. This approach assigns anonymous OTUs to taxonomic categories based on relative placements of OTUs and reference sequences on the cladogram and support that these placements receive. New information In tree-based taxonomy assignment approach, reliable identification of anonymous OTUs is based on their placement in monophyletic and highly supported clades together with identified reference taxa. Therefore, it requires high quality reference dataset to be used. Resolution of phylogenetic trees is strongly affected by the presence of erroneous sequences as well as alignment and phylogeny inference methods used in the process. Two preparation steps are essential for the successful application of tree-based taxonomy assignment approach. Curated collections of genetic information do include erroneous sequences. These sequences have detrimental effect on the resolution of cladograms used in tree-based approach. They must be identified and excluded from the reference dataset beforehand. Various combinations of multiple sequence alignment and phylogeny inference methods provide cladograms with different topology and bootstrap support. These combinations of methods need to be tested in order to determine the one that gives highest resolution for the particular reference dataset. Completing the above mentioned preparation steps is expected to decrease the number of unassigned OTUs and thus improve the results of the tree-based taxonomy assignment approach. PMID:27932919

Metabarcoding of marine nematodes - evaluation of reference datasets used in tree-based taxonomy assignment approach.

PubMed

Holovachov, Oleksandr

2016-01-01

Metabarcoding is becoming a common tool used to assess and compare diversity of organisms in environmental samples. Identification of OTUs is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task. This publication evaluates the quality of reference datasets, alongside with several alignment and phylogeny inference methods used in one of the taxonomy assignment methods, called tree-based approach. This approach assigns anonymous OTUs to taxonomic categories based on relative placements of OTUs and reference sequences on the cladogram and support that these placements receive. In tree-based taxonomy assignment approach, reliable identification of anonymous OTUs is based on their placement in monophyletic and highly supported clades together with identified reference taxa. Therefore, it requires high quality reference dataset to be used. Resolution of phylogenetic trees is strongly affected by the presence of erroneous sequences as well as alignment and phylogeny inference methods used in the process. Two preparation steps are essential for the successful application of tree-based taxonomy assignment approach. Curated collections of genetic information do include erroneous sequences. These sequences have detrimental effect on the resolution of cladograms used in tree-based approach. They must be identified and excluded from the reference dataset beforehand.Various combinations of multiple sequence alignment and phylogeny inference methods provide cladograms with different topology and bootstrap support. These combinations of methods need to be tested in order to determine the one that gives highest resolution for the particular reference dataset.Completing the above mentioned preparation steps is expected to decrease the number of unassigned OTUs and thus improve the results of the tree-based taxonomy assignment approach.

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations.

PubMed

Zemali, El-Amine; Boukra, Abdelmadjid

2015-08-01

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.

Amino acid sequence analysis of the annexin super-gene family of proteins.

PubMed

Barton, G J; Newman, R H; Freemont, P S; Crumpton, M J

1991-06-15

The annexins are a widespread family of calcium-dependent membrane-binding proteins. No common function has been identified for the family and, until recently, no crystallographic data existed for an annexin. In this paper we draw together 22 available annexin sequences consisting of 88 similar repeat units, and apply the techniques of multiple sequence alignment, pattern matching, secondary structure prediction and conservation analysis to the characterisation of the molecules. The analysis clearly shows that the repeats cluster into four distinct families and that greatest variation occurs within the repeat 3 units. Multiple alignment of the 88 repeats shows amino acids with conserved physicochemical properties at 22 positions, with only Gly at position 23 being absolutely conserved in all repeats. Secondary structure prediction techniques identify five conserved helices in each repeat unit and patterns of conserved hydrophobic amino acids are consistent with one face of a helix packing against the protein core in predicted helices a, c, d, e. Helix b is generally hydrophobic in all repeats, but contains a striking pattern of repeat-specific residue conservation at position 31, with Arg in repeats 4 and Glu in repeats 2, but unconserved amino acids in repeats 1 and 3. This suggests repeats 2 and 4 may interact via a buried saltbridge. The loop between predicted helices a and b of repeat 3 shows features distinct from the equivalent loop in repeats 1, 2 and 4, suggesting an important structural and/or functional role for this region. No compelling evidence emerges from this study for uteroglobin and the annexins sharing similar tertiary structures, or for uteroglobin representing a derivative of a primordial one-repeat structure that underwent duplication to give the present day annexins. The analyses performed in this paper are re-evaluated in the Appendix, in the light of the recently published X-ray structure for human annexin V. The structure confirms most of the predictions and shows the power of techniques for the determination of tertiary structural information from the amino acid sequences of an aligned protein family.

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.

ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data

PubMed Central

Li, You; Heavican, Tayla B.; Vellichirammal, Neetha N.; Iqbal, Javeed

2017-01-01

Abstract The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The ‘fusion’ or ‘chimeric’ transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as k-mers) profiles of the RNA-Seq paired-end reads. Results on published datasets and in-house cancer cell line datasets followed by experimental validations demonstrate that ChimeRScope consistently outperforms other popular methods irrespective of the read lengths and sequencing depth. More importantly, results on our in-house datasets show that ChimeRScope is a better tool that is capable of identifying novel fusion transcripts with potential oncogenic functions. ChimeRScope is accessible as a standalone software at (https://github.com/ChimeRScope/ChimeRScope/wiki) or via the Galaxy web-interface at (https://galaxy.unmc.edu/). PMID:28472320

Using Variable-Length Aligned Fragment Pairs and an Improved Transition Function for Flexible Protein Structure Alignment.

PubMed

Cao, Hu; Lu, Yonggang

2017-01-01

With the rapid growth of known protein 3D structures in number, how to efficiently compare protein structures becomes an essential and challenging problem in computational structural biology. At present, many protein structure alignment methods have been developed. Among all these methods, flexible structure alignment methods are shown to be superior to rigid structure alignment methods in identifying structure similarities between proteins, which have gone through conformational changes. It is also found that the methods based on aligned fragment pairs (AFPs) have a special advantage over other approaches in balancing global structure similarities and local structure similarities. Accordingly, we propose a new flexible protein structure alignment method based on variable-length AFPs. Compared with other methods, the proposed method possesses three main advantages. First, it is based on variable-length AFPs. The length of each AFP is separately determined to maximally represent a local similar structure fragment, which reduces the number of AFPs. Second, it uses local coordinate systems, which simplify the computation at each step of the expansion of AFPs during the AFP identification. Third, it decreases the number of twists by rewarding the situation where nonconsecutive AFPs share the same transformation in the alignment, which is realized by dynamic programming with an improved transition function. The experimental data show that compared with FlexProt, FATCAT, and FlexSnap, the proposed method can achieve comparable results by introducing fewer twists. Meanwhile, it can generate results similar to those of the FATCAT method in much less running time due to the reduced number of AFPs.

Combining Physicochemical and Evolutionary Information for Protein Contact Prediction

PubMed Central

Schneider, Michael; Brock, Oliver

2014-01-01

We introduce a novel contact prediction method that achieves high prediction accuracy by combining evolutionary and physicochemical information about native contacts. We obtain evolutionary information from multiple-sequence alignments and physicochemical information from predicted ab initio protein structures. These structures represent low-energy states in an energy landscape and thus capture the physicochemical information encoded in the energy function. Such low-energy structures are likely to contain native contacts, even if their overall fold is not native. To differentiate native from non-native contacts in those structures, we develop a graph-based representation of the structural context of contacts. We then use this representation to train an support vector machine classifier to identify most likely native contacts in otherwise non-native structures. The resulting contact predictions are highly accurate. As a result of combining two sources of information—evolutionary and physicochemical—we maintain prediction accuracy even when only few sequence homologs are present. We show that the predicted contacts help to improve ab initio structure prediction. A web service is available at http://compbio.robotics.tu-berlin.de/epc-map/. PMID:25338092

Indexcov: fast coverage quality control for whole-genome sequencing.

PubMed

Pedersen, Brent S; Collins, Ryan L; Talkowski, Michael E; Quinlan, Aaron R

2017-11-01

The BAM and CRAM formats provide a supplementary linear index that facilitates rapid access to sequence alignments in arbitrary genomic regions. Comparing consecutive entries in a BAM or CRAM index allows one to infer the number of alignment records per genomic region for use as an effective proxy of sequence depth in each genomic region. Based on these properties, we have developed indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at https://github.com/brentp/goleft under the MIT license. © The Authors 2017. Published by Oxford University Press.

Authentication of an endangered herb Changium smyrnioides from different producing areas based on rDNA ITS sequences and allele-specific PCR.

PubMed

Sun, Xiaoqin; Wei, Yanglian; Qin, Minjian; Guo, Qiaosheng; Guo, Jianlin; Zhou, Yifeng; Hang, Yueyu

2012-03-01

The rDNA ITS region of 18 samples of Changium smyrnioides from 7 areas and of 2 samples of Chuanminshen violaceum were sequenced and analyzed. The amplified ITS region of the samples, including a partial sequence of ITS1 and complete sequences of 5.8S and ITS2, had a total length of 555 bp. After complete alignment, there were 49 variable sites, of which 45 were informative, when gaps were treated as missing data. Samples of C. smyrnioides from different locations could be identified exactly based on the variable sites. The maximum parsimony (MP) and neighbor joining (NJ) tree constructed from the ITS sequences based on Kumar's two-parameter model showed that the genetic distances of the C. smyrnioides samples from different locations were not always related to their geographical distances. A specific primer set for Allele-specific PCR authentication of C. violaceum from Jurong of Jiangsu was designed based on the SNP in the ITS sequence alignment. C. violaceum from the major genuine producing area in Jurong of Jiangsu could be identified exactly and quickly by Allele-specific PCR.

A Linked Series of Laboratory Exercises in Molecular Biology Utilizing Bioinformatics and GFP

ERIC Educational Resources Information Center

Medin, Carey L.; Nolin, Katie L.

2011-01-01

Molecular biologists commonly use bioinformatics to map and analyze DNA and protein sequences and to align different DNA and protein sequences for comparison. Additionally, biologists can create and view 3D models of protein structures to further understand intramolecular interactions. The primary goal of this 10-week laboratory was to introduce…

Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver

PubMed Central

Blanquart, François; Golubchik, Tanya; Gall, Astrid; Bakker, Margreet; Bezemer, Daniela; Croucher, Nicholas J; Hall, Matthew; Hillebregt, Mariska; Ratmann, Oliver; Albert, Jan; Bannert, Norbert; Fellay, Jacques; Fransen, Katrien; Gourlay, Annabelle; Grabowski, M Kate; Gunsenheimer-Bartmeyer, Barbara; Günthard, Huldrych F; Kivelä, Pia; Kouyos, Roger; Laeyendecker, Oliver; Liitsola, Kirsi; Meyer, Laurence; Porter, Kholoud; Ristola, Matti; van Sighem, Ard; Cornelissen, Marion; Kellam, Paul; Reiss, Peter

2018-01-01

Abstract Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user’s choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver’s constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver. PMID:29876136