Sequence Analysis Algorithms Research Articles

FANSe: an accurate algorithm for quantitative mapping of large scale sequencing reads

The most crucial step in data processing from high-throughput sequencing applications is the accurate and sensitive alignment of the sequencing reads to reference genomes or transcriptomes. The accurate detection of insertions and deletions (indels) and errors introduced by the sequencing platform or by misreading of modified nucleotides is essential for the quantitative processing of the RNA-based sequencing (RNA-Seq) datasets and for the identification of genetic variations and modification patterns. We developed a new, fast and accurate algorithm for nucleic acid sequence analysis, FANSe, with adjustable mismatch allowance settings and ability to handle indels to accurately and quantitatively map millions of reads to small or large reference genomes. It is a seed-based algorithm which uses the whole read information for mapping and high sensitivity and low ambiguity are achieved by using short and non-overlapping reads. Furthermore, FANSe uses hotspot score to prioritize the processing of highly possible matches and implements modified Smith–Watermann refinement with reduced scoring matrix to accelerate the calculation without compromising its sensitivity. The FANSe algorithm stably processes datasets from various sequencing platforms, masked or unmasked and small or large genomes. It shows a remarkable coverage of low-abundance mRNAs which is important for quantitative processing of RNA-Seq datasets.

Plasma Membrane Topology of the Insulin Receptor: Insights from Computational Modeling

The insulin receptor in the plasma membrane is composed of two alpha-subunits, each linked to a beta-subunit and to each other by disulfide bonds. It has been proposed that both alpha-subunits are extracellular and anchored to the plasma membrane via a single transmembrane (TM) helix in the N-terminal region of each beta-subunit. However, we find that newer sequence analysis algorithms predict that the alpha-subunits of human insulin receptor (P06213) are largely intracellular and each contains a single TM helix in the N-terminal region. The MEMSAT-SVM method predicts (after correcting for a 19 residue N-terminal signal peptide) that the alpha-subunit contains a TM helix between residues 64 and 79, with a 63 amino acid ectodomain and a large 676 residue cytoplasmic domain. The existence of a large intracellular domain is consistent with the presence of 10 caveolin-binding (CB) motifs (OxOxxxxO, OxxxxOxxO, where O is the aromatic amino acid F, Y, or W), which exist within most caveolin-associated proteins where caveolin is accessible only intracellularly. Our computational analysis of the insulin receptor beta-subunit sequence confirms a single TM helix between residues 194 - 218 (UniProtKB places the TM helix within residues 194-213), with 1 CB motif proximal to the TM helix (W175 - Y182). Similar topologies were obtained with insulin receptor sequences from a variety of species. The insulin receptor co-isolates with lipids and the purified insulin receptor readily forms lipid complexes. Thus, caveolin binding motifs may direct the insulin receptor tetramer to caveolin-rich lipid rafts. The topology of the insulin receptor and CB motifs is relevant to understanding the microdynamics of insulin receptor movement between caveolar and non-caveolar regions of the plasma membrane as well as insulin-mediated events such as endocytosis, membrane hyperpolarization, and regulation of Na+/K+/H+ ions.

DNA Lossless Differential Compression Alogorithm Based on Similarity of Genomic Sequence Database

Modern biological science produces vast amounts of genomic sequence data. This is fuelling the need for efficient algorithms for sequence compression and analysis. Data compression and the associated techniques coming from information theory are often perceived as being of interest for data communication and storage. In recent years, a substantial effort has been made for the application of textual data compression techniques to various computational biology tasks, ranging from storage and indexing of large datasets to comparison of genomic databases. This paper presents a differential compression algorithm that is based on production of difference sequences according to op-code table in order to optimize the compression of homologous sequences in dataset. Therefore, the stored data are composed of reference sequence, the set of differences, and differences locations, instead of storing each sequence individually. This algorithm does not require a priori knowledge about the statistics of the sequence set. The algorithm was applied to three different datasets of genomic sequences, it achieved up to 195-fold compression rate corresponding to 99.4% space saving.

GeCo++: a C++ library for genomic features computation and annotation in the presence of variants

We propose a C++ class library developed to the purpose of making the implementation of sequence analysis algorithms easier and faster when genomic annotations and variations need to be considered. The library provides a class hierarchy to seamlessly bind together annotations of genomic elements to sequences and to algorithm results; it allows to evaluate the effect of mutations/variations in terms of both element position shifts and of algorithm results, limiting recalculation to the minimum. Particular care has been posed to keep memory and time overhead into acceptable limits. A complete tutorial as well as a detailed doxygen generated documentation and source code is freely available at http://bioinformatics.emedea.it/geco, under the GPL license. The library was written in standard ISO C++, and does not depend on external libraries.

Plasma Membrane Topology of Caveolins: Insights from Computational Modeling

Caveolins (CAV-1, CAV-2, CAV-3) are a family of integral membrane proteins, so-called because they are principal components of caveolae. They are known to facitate endocytosis and are involved in a number of biological functions, including signal transduction, cholesterol homeostasis, and transport. We find that the TOPCONS consensus sequence analysis algorithm as well as both the SVMtop and MEMSAT methods predict that each 22 kDa caveolin molecule contains two plasma membrane spanning helices (TM-1 and TM-2), separated by 1-2 amino acid residues at the membrane surface. Chem 3D Ultra visualization indicates that the transmembrane domains of all three caveolins are highly ordered α-helices. NetSurfP (Protein Surface Accessibility and Secondary Structure Predictions) analysis of the amino acid sequence further confirms the existence of two membrane spanning α-helices. These results conflict with the widely cited theory that caveolin forms a single 32 amino acid hydrophobic hairpin loop which is inserted into, but does not traverse, the plasma membrane. Based on our model, we find that TM-1,TM-2 and the interconnecting amino acid(s) in CAV-1, CAV-2 and CAV-3 of several vertebrate species are highly conserved. However, there are significant sequence differences between TM-1 and TM-2 of CAV-1 and CAV-2. The TMhit method, heptad repeat analysis and the coiled-coil prediction algorithm further indicate that helix-helix interactions occur both within and between these integral membrane proteins. The N-attachment (scaffold) domain also has a large intracellular helical content, contiguous with the TM-1 transmembrane helix. In contrast, the C-terminal attachment contains a disrupted helix, the first helical region being contiguous with transmembrane helix TM-2. The topology of the transmembrane helices described here is relevant to understanding caveolae formation and the mechanism of endocytosis as well as sequestration and release of membrane signaling molecules.

Disease Risk of Missense Mutations Using Structural Inference from Predicted Function

Advancements in sequencing techniques place personalized genomic medicine upon the horizon, bringing along the responsibility of clinicians to understand the likelihood for a mutation to cause disease, and of scientists to separate etiology from nonpathologic variability. Pathogenicity is discernable from patterns of interactions between a missense mutation, the surrounding protein structure, and intermolecular interactions. Physicochemical stability calculations are not accessible without structures, as is the case for the vast majority of human proteins, so diagnostic accuracy remains in infancy. To model the effects of missense mutations on functional stability without structure, we combine novel protein sequence analysis algorithms to discern spatial distributions of sequence, evolutionary, and physicochemical conservation, through a new approach to optimize component selection. Novel components include a combinatory substitution matrix and two heuristic algorithms that detect positions which confer structural support to interaction interfaces. The method reaches 0.91 AUC in ten-fold cross-validation to predict alteration of function for 6,392 in vitro mutations. For clinical utility we trained the method on 7,022 disease associated missense mutations within the Online Mendelian inheritance in man amongst a larger randomized set. In a blinded prospective test to delineate mutations unique to 186 patients with craniosynostosis from those in the 95 highly variant Coriell controls and 1000 age matched controls, we achieved roughly 1/3 sensitivity and perfect specificity. The component algorithms retained during machine learning constitute novel protein sequence analysis techniques to describe environments supporting neutrality or pathology of mutations. This approach to pathogenetics enables new insight into the mechanistic relationship of missense mutations to disease phenotypes in our patients.

Bioinformática en Colombia: presente y futuro de la investigación biocomputacional

Bioinformatics emerged about 50 years ago, but it was developed greatly during the early 1980s by robust databases such as GenBank, EMBL, and DNA Database of Japan (DDBJ). Bioinformatic routines were rapidly adapted once the main algorithms for sequence analysis became available worldwide. As in other science fields, bioinformatics had minimal impact in low-income countries of Latin America until the last decade. We revised the bioinformatics state of art in Colombia and found a few bioinformatics groups carrying out basic computational biology research. Nowadays, bioinformatics in Colombia has a hopeful scenario thanks to recent science policies adopted by the Colombian Government. Such policies have been adopted in order to establish a new model of sustainable scientific research. In this brief report we revise the bioinformatics state of the art in Colombia. Finally, we conclude with some considerations for the proposed science model and we describe different perspectives of interest for the Colombian scientific community.

Classification of DNA sequences using Bloom filters

Motivation: New generation sequencing technologies producing increasingly complex datasets demand new efficient and specialized sequence analysis algorithms. Often, it is only the ‘novel’ sequences in a complex dataset that are of interest and the superfluous sequences need to be removed.Results: A novel algorithm, fast and accurate classification of sequences (FACSs), is introduced that can accurately and rapidly classify sequences as belonging or not belonging to a reference sequence. FACS was first optimized and validated using a synthetic metagenome dataset. An experimental metagenome dataset was then used to show that FACS achieves comparable accuracy as BLAT and SSAHA2 but is at least 21 times faster in classifying sequences.Availability: Source code for FACS, Bloom filters and MetaSim dataset used is available at http://facs.biotech.kth.se. The Bloom::Faster 1.6 Perl module can be downloaded from CPAN at http://search.cpan.org/∼palvaro/Bloom-Faster-1.6/Contacts: henrik.stranneheim@biotech.kth.se; joakiml@biotech.kth.seSupplementary information: Supplementary data are available at Bioinformatics online.

A practical algorithm for finding maximal exact matches in large sequence datasets using sparse suffix arrays

High-throughput sequencing technologies place ever increasing demands on existing algorithms for sequence analysis. Algorithms for computing maximal exact matches (MEMs) between sequences appear in two contexts where high-throughput sequencing will vastly increase the volume of sequence data: (i) seeding alignments of high-throughput reads for genome assembly and (ii) designating anchor points for genome-genome comparisons. We introduce a new algorithm for finding MEMs. The algorithm leverages a sparse suffix array (SA), a text index that stores every K-th position of the text. In contrast to a full text index that stores every position of the text, a sparse SA occupies much less memory. Even though we use a sparse index, the output of our algorithm is the same as a full text index algorithm as long as the space between the indexed suffixes is not greater than a minimum length of a MEM. By relying on partial matches and additional text scanning between indexed positions, the algorithm trades memory for extra computation. The reduced memory usage makes it possible to determine MEMs between significantly longer sequences. Source code for the algorithm is available under a BSD open source license at http://compbio.cs.princeton.edu/mems. The implementation can serve as a drop-in replacement for the MEMs algorithm in MUMmer 3.

Sequence progressive alignment, a framework for practical large-scale probabilistic consistency alignment

Multiple sequence alignment is a cornerstone of comparative genomics. Much work has been done to improve methods for this task, particularly for the alignment of small sequences, and especially for amino acid sequences. However, less work has been done in making promising methods that work on the small-scale practically for the alignment of much larger genomic sequences. We take the method of probabilistic consistency alignment and make it practical for the alignment of large genomic sequences. In so doing we develop a set of new technical methods, combined in a framework we term 'sequence progressive alignment', because it allows us to iteratively compute an alignment by passing over the input sequences from left to right. The result is that we massively decrease the memory consumption of the program relative to a naive implementation. The general engineering of the challenges faced in scaling such a computationally intensive process offer valuable lessons for planning related large-scale sequence analysis algorithms. We also further show the strong performance of Pecan using an extended analysis of ancient repeat alignments. Pecan is now one of the default alignment programs that has and is being used by a number of whole-genome comparative genomic projects. The Pecan program is freely available at http://www.ebi.ac.uk/ approximately bjp/pecan/ Pecan whole genome alignments can be found in the Ensembl genome browser.

SeqAn An efficient, generic C++ library for sequence analysis

BackgroundThe use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome [1] would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use.ResultsTo remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use.ConclusionWe anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms.

ON ABOUT WHAT CAN BE DONE AND WHAT CANNOT BE DONE WITH GENETIC ALGORITHMS IN PHYLOGENETIC TREE AND GENE SEQUENCE ANALYSES

Genetic algorithms, a sort of algorithms belonging to a more general category, so called meta-heuristics, know today a great expansion in terms of target applications, including biology, chemistry and medicine. They are inspired from primary observations in nature (Lamarck, 1809; Darwin, 1859; Mendel, 1865; Fisher, 1918), and started with simulation of artificial selection of organisms with multiple loci that controls a measurable trait (Fraser, 1957). Genetic algorithms evolved into complex and strong informatics tools capable to deal with hard problems of decision, classification, optimization, and simulation in fields as biology, chemistry and medicine. The aim of the present article was to introduce genetic algorithms and to present their suitability for biological hard problems. Some important results reported in the literature about the use of genetic algorithms for phylogenetic and gene sequence analysis are discussed.

An automated, high-throughput sequence read classification pipeline for preliminary genome characterization

In the absence of a complete genome sequence, considerable insight into genome structure can be gained from survey sequencing of genomic DNA. To facilitate high-throughput characterization of genome structure based on shotgun sequence reads, we have developed an automated sequence read classification pipeline (SRCP). The SRCP uses a battery of novel and standard sequence analysis algorithms along with a sophisticated decision tree to place reads into “best fit” functional/descriptive categories. Once “primed” with genomic sequence data, the SRCP also permits estimation of gene/repeat enrichment afforded by reduced-representation sequencing techniques. To our knowledge, the SRCP is the only tool that has been designed to provide a description of a genome or a genome component based on sample sequence reads. In an initial test of the SRCP using sequence data from Sorghum bicolor, it was shown to provide results similar in quality to results generated by manual classification. Although the SRCP is not a replacement for manual sequence characterization, it can provide a rapid, high-quality overview of genome sequence content and facilitate subsequent annotation. The SRCP presumably can be adapted for analysis of any eukaryotic genome.

Interharmonics Analysis Based on Interpolating Windowed FFT Algorithm

The interharmonics, which are the same as integer harmonics, have serious impacts on the design of harmonics compensation equipment. Therefore, it is important to measure interharmonics accurately. The interharmonics cannot be obtained accurately by using fast Fourier transform (FFT) for an unsynchronized sample sequence analysis because of large errors in such cases. To reduce the errors caused by using FFT for an unsynchronized sample sequence analysis and to improve the measuring precision of interharmonics in electric power systems, an interharmonics estimation method based on the interpolation FFT algorithm is proposed. An algorithm for estimating interharmonics parameters based on the Blackman-Harris window, Rife-Vincent (I) window, and Rife-Vincent (III) window is given. Simulation results demonstrate that by using the proposed algorithm for the unsynchronized sample sequence analysis, the estimated interharmonics frequency, amplitude, and phase are highly accurate

Ancestral genomes reconstruction: An integrated, multi-disciplinary approach is needed

Ancestral genomes reconstruction: An integrated, multi-disciplinary approach is needed

Towards plant systems biology – novel mathematical approaches to enable quantitative analysis of growth processes

Towards plant systems biology – novel mathematical approaches to enable quantitative analysis of growth processes

Analysis of and function predictions for previously conserved hypothetical or putative proteins in Blochmannia floridanus.

BackgroundThere is an increasing interest to better understand endosymbiont capabilities in insects both from an ecological point of view and for pest control. Blochmannia floridanus provides important nutrients for its host, the ant Camponotus, while the bacterium in return is provided with a niche to proliferate. Blochmannia floridanus proteins and metabolites are difficult to study due to its endosymbiontic life style; however, its complete genome sequence became recently available.ResultsImproved sequence analysis algorithms, databanks and gene and pathway context methods allowed us to reveal new information on various enzyme and pathways from the Blochmannia floridanus genome sequence [EMBL-ID BX248583]. Furthermore, these predictions are supported and linked to experimental data for instance from structural genomics projects (e.g. Bfl341, Bfl 499) or available biochemical data on proteins from other species which we show here to be related. We were able to assign a confirmed or at least a putative molecular function for 21 from 27 previously conserved hypothetical proteins. For 48 proteins of 66 with a previous putative assignment the function was further clarified. Several of these proteins occur in many proteobacteria and are found to be conserved even in the compact genome of this endosymbiont. To extend and re-test predictions and links to experimentally verified protein functions, functional clusters and interactions were assembled. These included septum initiation and cell division (Bfl165, Bfl303, Bfl248 et al.); translation; transport; the ubiquinone (Bfl547 et al.), the inositol and nitrogen pathways.ConclusionTaken together, our data allow a better and more complete description of the pathway capabilities and life style of this typical endosymbiont.

Apolipoprotein L6, a Novel Proapoptotic Bcl-2 Homology 3–Only Protein, Induces Mitochondria-Mediated Apoptosis in Cancer Cells

Cancer cells frequently possess defects in the genetic and biochemical pathways of apoptosis. Members of the Bcl-2 family play pivotal roles in regulating apoptosis and possess at least one of four Bcl-2 homology (BH) domains, designated BH1 to BH4. The BH3 domain is the only one conserved in proapoptotic BH3-only proteins and plays an important role in protein-protein interactions in apoptosis by regulating homodimerization and heterodimerization of the Bcl-2 family members. To date, 10 BH3-only proapoptotic proteins have been identified and characterized in the human genome. The completion of the Human Genome Project and the availability of various public databases and sequence analysis algorithms allowed us to use the bioinformatic database-mining approach to identify one novel BH3-only protein, apolipoprotein L6 (ApoL6). The full-length cDNA of ApoL6 was identified, cloned, and functionally expressed in p53-null colorectal cancer cells (DLD-1). We found that overexpression of wild-type ApoL6 induced mitochondria-mediated apoptosis in DLD-1 cells characterized by release of cytochrome c and Smac/DIABLO from mitochondria and activation of caspase-9, whereas ApoL6 BH3 domain deletion allele did not. In addition, overexpression of ApoL6 also induced activation of caspase-8. Furthermore, we showed that adenovirus harboring the full-length cDNA of ApoL6 induced marked apoptosis in a variety of cancer cell types, and ApoL6 recruited and interacted with lipid/fatty acid components during the induction of apoptosis. To our knowledge, this is the first example that intracellular overproduction of an apolipoprotein induces marked apoptosis.

The longest common subsequence problem for arc-annotated sequences

Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. The Longest Arc-Preserving Common Subsequence (LAPCS) problem has recently been introduced in [P.A. Evans, Algorithms and complexity for annotated sequence analysis, PhD Thesis, University of Victoria, 1999; P.A. Evans, Finding common subsequences with arcs and pseudoknots, in: Proceedings of 10th Annual Symposium on Combinatorial Pattern Matching (CPM'99), in: Lecture Notes in Comput. Sci., vol. 1645, 1999, pp. 270–280] as a framework for studying the similarity of arc-annotated sequences. In this paper, we consider arc-annotated sequences with various arc structures and present some new algorithmic and complexity results on the LAPCS problem. Some of our results answer an open question in [P.A. Evans, Algorithms and complexity for annotated sequence analysis, PhD Thesis, University of Victoria, 1999; P.A. Evans, Finding common subsequences with arcs and pseudoknots, in: Proceedings of 10th Annual Symposium on Combinatorial Pattern Matching (CPM'99), in: Lecture Notes in Comput. Sci., vol. 1645, 1999, pp. 270–280] and some others improve the hardness results in [P.A. Evans, Algorithms and complexity for annotated sequence analysis, PhD Thesis, University of Victoria, 1999; P.A. Evans, Finding common subsequences with arcs and pseudoknots, in: Proceedings of 10th Annual Symposium on Combinatorial Pattern Matching (CPM'99), in Lecture Notes in Comput. Sci., vol. 1645, 1999, pp. 270–280].

MPEG-4 Authoring Tool Using Moving Object Segmentation and Tracking in Video Shots

An Authoring tool for the MPEG-4 multimedia standard integrated with image sequence analysis algorithms is described. MPEG-4 offers numerous capabilities and is expected to be the future standard for multimedia applications. However, the implementation of these capabilities requires a complex authoring process, employing many different competencies from image sequence analysis and encoding of audio/visual/BIFS to the implementation of different delivery scenarios: local access on CD/DVD-ROM, Internet, or broadcast. However powerful the technologies underlying multimedia computing are, the success of these systems depends on their ease of authoring. In this paper, a novel Authoring tool fully exploiting the object-based coding and 3D synthetic functionalities of the MPEG-4 standard is described. It is based upon an open and modular architecture able to progress with MPEG-4 versions and it is easily adaptable to newly emerging better and higher-level authoring and image sequence analysis features.