Information and sequence extraction around the 5'-end and translation initiation site of human genes

FIE (5'-end Information Extraction) is a web-based program designed primarily to extract the sequence of the regions around the 5'-end and around the translation initiation sites for a particular gene, based on information provided by LocusLink.     

Tcoffee@igs: A web server for computing,evaluating and combining multiple sequence alignments

This paper presents Tcoffee@igs, a new server provided to the community by Hewlet Packard computers and the Centre National de la Recherche Scientifique. This server is a web-based tool dedicated to the computation, the evaluation and the combination of multiple sequence alignments. It uses the latest version of the T-Coffee package. Given a set of unaligned sequences, the server returns an evaluated multiple sequence alignment and the associated phylogenetic tree. This server also makes it possible to evaluate the local reliability of an existing alignment and to combine several alternative multiple alignments into a single new one. Tcoffee@igs can be used for aligning protein, RNA or DNA sequences. Datasets of up to 100 sequences (2000 residues long) can be processed. The server and its documentation are available from: http://igs-server.cnrs-mrs.fr/Tcoffee/.     

APDB: a web server to evaluate the accuracy of sequence alignments using structural information

The APDB webserver uses structural information to evaluate the alignment of sequences with known structures. It returns a score correlated to the overall alignment accuracy as well as a local evaluation. Any sequence alignment can be analyzed with APDB provided it includes at least two proteins with known structures. Sequences without a known structure are simply ignored and do not contribute to the scoring procedure. AVAILABILITY: APDB is part of the T-Coffee suite of tools for alignment analysis, it is available on www.tcoffee.org. A stand-alone version of the package is also available as a freeware open source from the same address.     

RTPrimerDB: the real-time PCR primer and probe database

The real-time polymerase chain reaction (PCR) methodology has become increasingly popular for nucleic acids detection and/or quantification. As primer/probe design and experimental evaluation is time-consuming, we developed a public database application for the storage and retrieval of validated real-time PCR primer and probe sequence records. The integrity and accuracy of the data are maintained by linking to and querying other reference databases. RTPrimerDB provides free public access through the Web to perform queries and submit user based information. Primer/probe records can be searched for by official gene symbol, nucleotide sequence, type of application, detection chemistry, LocusLink or Single Nucleotide Polymorphism (SNP) identifier, and submitter's name. Each record is directly linked to LocusLink, dbSNP and/or PubMed to retrieve additional information on the gene/SNP for which the primers/probes are designed. Currently, the database contains primer/probe records for human, mouse, rat, fruit fly and zebrafish, and all current detection chemistries such as intercalating dyes (SYBR Green I), hydrolysis probes (Taqman), adjacent hybridizations probes and molecular beacons. Real-time PCR primer/probe records are available at http://www.realtimeprimerdatabase.ht.st.     

Homology-extended sequence alignment

We present a profile–profile multiple alignment strategy that uses database searching to collect homologues for each sequence in a given set, in order to enrich their available evolutionary information for the alignment. For each of the alignment sequences, the putative homologous sequences that score above a pre-defined threshold are incorporated into a position-specific pre-alignment profile. The enriched position-specific profile is used for standard progressive alignment, thereby more accurately describing the characteristic features of the given sequence set. We show that owing to the incorporation of the pre-alignment information into a standard progressive multiple alignment routine, the alignment quality between distant sequences increases significantly and outperforms state-of-the-art methods, such as T-COFFEE and MUSCLE. We also show that although entirely sequence-based, our novel strategy is better at aligning distant sequences when compared with a recent contact-based alignment method. Therefore, our pre-alignment profile strategy should be advantageous for applications that rely on high alignment accuracy such as local structure prediction, comparative modelling and threading.     

R-Coffee: a method for multiple alignment of non-coding RNA

R-Coffee is a multiple RNA alignment package, derived from T-Coffee, designed to align RNA sequences while exploiting secondary structure information. R-Coffee uses an alignment-scoring scheme that incorporates secondary structure information within the alignment. It works particularly well as an alignment improver and can be combined with any existing sequence alignment method. In this work, we used R-Coffee to compute multiple sequence alignments combining the pairwise output of sequence aligners and structural aligners. We show that R-Coffee can improve the accuracy of all the sequence aligners. We also show that the consistency-based component of T-Coffee can improve the accuracy of several structural aligners. R-Coffee was tested on 388 BRAliBase reference datasets and on 11 longer Cmfinder datasets. Altogether our results suggest that the best protocol for aligning short sequences (less than 200 nt) is the combination of R-Coffee with the RNA pairwise structural aligner Consan. We also show that the simultaneous combination of the four best sequence alignment programs with R-Coffee produces alignments almost as accurate as those obtained with R-Coffee/Consan. Finally, we show that R-Coffee can also be used to align longer datasets beyond the usual scope of structural aligners. R-Coffee is freely available for download, along with documentation, from the T-Coffee web site (www.tcoffee.org).     

Accuracy improvement for identifying translation initiation sites in microbial genomes

MOTIVATION: At present the computational gene identification methods in microbial genomes have a high prediction accuracy of verified translation termination site (3' end), but a much lower accuracy of the translation initiation site (TIS, 5' end). The latter is important to the analysis and the understanding of the putative protein of a gene and the regulatory machinery of the translation. Improving the accuracy of prediction of TIS is one of the remaining open problems. RESULTS: In this paper, we develop a four-component statistical model to describe the TIS of prokaryotic genes. The model incorporates several features with biological meanings, including the correlation between translation termination site and TIS of genes, the sequence content around the start codon; the sequence content of the consensus signal related to ribosomal binding sites (RBSs), and the correlation between TIS and the upstream consensus signal. An entirely non-supervised training system is constructed, which takes as input a set of annotated coding open reading frames (ORFs) by any gene finder, and gives as output a set of organism-specific parameters (without any prior knowledge or empirical constants and formulas). The novel algorithm is tested on a set of reliable datasets of genes from Escherichia coli and Bacillus subtillis. MED-Start may correctly predict 95.4% of the start sites of 195 experimentally confirmed E.coli genes, 96.6% of 58 reliable B.subtillis genes. Moreover, the test results indicate that the algorithm gives higher accuracy for more reliable datasets, and is robust to the variation of gene length. MED-Start may be used as a postprocessor for a gene finder. After processing by our program, the improvement of gene start prediction of gene finder system is remarkable, e.g. the accuracy of TIS predicted by MED 1.0 increases from 61.7 to 91.5% for 854 E.coli verified genes, while that by GLIMMER 2.02 increases from 63.2 to 92.0% for the same dataset. These results show that our algorithm is one of the most accurate methods to identify TIS of prokaryotic genomes. AVAILABILITY: The program MED-Start can be accessed through the website of CTB at Peking University: http://ctb.pku.edu.cn/main/SheGroup/MED_Start.htm.     

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

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

Look-Align: an interactive web-based multiple sequence alignment viewer with polymorphism analysis support

SUMMARY: We have developed Look-Align, an interactive web-based viewer to display pre-computed multiple sequence alignments. Although initially developed to support the visualization needs of the maize diversity website Panzea (http://www.panzea.org), the viewer is a generic stand-alone tool that can be easily integrated into other websites. AVAILABILITY: Look-Align is written in Perl using open-source components and is available under an open-source license. Live installation and download information can be found at the Panzea website (http://www.panzea.org/software/alignment_viewer.html). CONTACT: ware@cshl.edu SUPPLEMENTARY INFORMATION: The Supplementary information includes sample lists of multiple sequence alignment software and sample screenshots of the viewer.     

A novel tool for the prediction of transmembrane protein topology based on a statistical analysis of the SwissProt database: the OrienTM algorithm

OrienTM is a computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods. A web-based version of OrienTM is publicly available at the address http://biophysics.biol.uoa.gr/OrienTM.     

Recent developments in the MAFFT multiple sequence alignment program

The accuracy and scalability of multiple sequence alignment (MSA) of DNAs and proteins have long been and are still important issues in bioinformatics. To rapidly construct a reasonable MSA, we developed the initial version of the MAFFT program in 2002. MSA software is now facing greater challenges in both scalability and accuracy than those of 5 years ago. As increasing amounts of sequence data are being generated by large-scale sequencing projects, scalability is now critical in many situations. The requirement of accuracy has also entered a new stage since the discovery of functional noncoding RNAs (ncRNAs); the secondary structure should be considered for constructing a high-quality alignment of distantly related ncRNAs. To deal with these problems, in 2007, we updated MAFFT to Version 6 with two new techniques: the PartTree algorithm and the Four-way consistency objective function. The former improved the scalability of progressive alignment and the latter improved the accuracy of ncRNA alignment. We review these and other techniques that MAFFT uses and suggest possible future directions of MSA software as a basis of comparative analyses. MAFFT is available at http://align.bmr.kyushu-u.ac.jp/mafft/software/.     

On the role of structural information in remote homology detection and sequence alignment: new methods using hybrid sequence profiles

Structural alignments often reveal relationships between proteins that cannot be detected using sequence alignment alone. However, profile search methods based entirely on structural alignments alone have not been found to be effective in finding remote homologs. Here, we explore the role of structural information in remote homolog detection and sequence alignment. To this end, we develop a series of hybrid multidimensional alignment profiles that combine sequence, secondary and tertiary structure information into hybrid profiles. Sequence-based profiles are profiles whose position-specific scoring matrix is derived from sequence alignment alone; structure-based profiles are those derived from multiple structure alignments. We compare pure sequence-based profiles to pure structure-based profiles, as well as to hybrid profiles that use combined sequence-and-structure-based profiles, where sequence-based profiles are used in loop/motif regions and structural information is used in core structural regions. All of the hybrid methods offer significant improvement over simple profile-to-profile alignment. We demonstrate that both sequence-based and structure-based profiles contribute to remote homology detection and alignment accuracy, and that each contains some unique information. We discuss the implications of these results for further improvements in amino acid sequence and structural analysis.     

Pattern-induced multi-sequence alignment (PIMA) algorithm employing secondary structure-dependent gap penalties for use in comparative protein modelling.

A multiple sequence alignment algorithm is described that uses a dynamic programming-based pattern construction method to align a set of homologous sequences based on their common pattern of conserved sequence elements. This pattern-induced multi-sequence alignment (PIMA) algorithm can employ secondary-structure dependent gap penalties for use in comparative modelling of new sequences when the three-dimensional structure of one or more members of the same family is known. We show that the use of secondary structure information can significantly improve the accuracy of aligning structure boundaries in a set of homologous sequences even when the structure of only one member of the family is known.     

PROMALS: towards accurate multiple sequence alignments of distantly related proteins

MOTIVATION: Accurate multiple sequence alignments are essential in protein structure modeling, functional prediction and efficient planning of experiments. Although the alignment problem has attracted considerable attention, preparation of high-quality alignments for distantly related sequences remains a difficult task. RESULTS: We developed PROMALS, a multiple alignment method that shows promising results for protein homologs with sequence identity below 10%, aligning close to half of the amino acid residues correctly on average. This is about three times more accurate than traditional pairwise sequence alignment methods. PROMALS algorithm derives its strength from several sources: (i) sequence database searches to retrieve additional homologs; (ii) accurate secondary structure prediction; (iii) a hidden Markov model that uses a novel combined scoring of amino acids and secondary structures; (iv) probabilistic consistency-based scoring applied to progressive alignment of profiles. Compared to the best alignment methods that do not use secondary structure prediction and database searches (e.g. MUMMALS, ProbCons and MAFFT), PROMALS is up to 30% more accurate, with improvement being most prominent for highly divergent homologs. Compared to SPEM and HHalign, which also employ database searches and secondary structure prediction, PROMALS shows an accuracy improvement of several percent. AVAILABILITY: The PROMALS web server is available at: http://prodata.swmed.edu/promals/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Template-based protein structure modeling using the RaptorX web server

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.     

Exploring genome architecture through GOV: a WWW-based gene order visualizer

MOTIVATION: The past decade has seen extension in the methods of sequence analysis from single gene based to analyzing multiple genes and proteins simultaneously. Consequently, there is a need for software tools that will allow mining of these enormous datasets at genome level effectively. A key challenge is to make them user-friendly, available to a larger community and integrate with public domain software without much hassle. RESULTS: A web-based interactive computational tool is described for visualization and comparison of gene order from prokaryotic and selected viral genome data. Many intriguing similarities and differences in gene order of multiple genomes can be compared and revealed. The interface facilitates easy extraction of the nucleotide sequence of the gene of interest and BLAST analysis against GenBank at NCBI to provide insights into gene functions and orthologs of the gene in other species.     

EnteriX 2003: Visualization tools for genome alignments of Enterobacteriaceae

We describe EnteriX, a suite of three web-based visualization tools for graphically portraying alignment information from comparisons among several fixed and user-supplied sequences from related enterobacterial species, anchored on a reference genome (http://bio.cse.psu.edu/). The first visualization, Enteric, displays stacked pairwise alignments between a reference genome and each of the related bacteria, represented schematically as PIPs (Percent Identity Plots). Encoded in the views are large-scale genomic rearrangement events and functional landmarks. The second visualization, Menteric, computes and displays 1 Kb views of nucleotide-level multiple alignments of the sequences, together with annotations of genes, regulatory sites and conserved regions. The third, a Java-based tool named Maj, displays alignment information in two formats, corresponding roughly to the Enteric and Menteric views, and adds zoom-in capabilities. The uses of such tools are diverse, from examining the multiple sequence alignment to infer conserved sites with potential regulatory roles, to scrutinizing the commonalities and differences between the genomes for pathogenicity or phylogenetic studies. The EnteriX suite currently includes >15 enterobacterial genomes, generates views centered on four different anchor genomes and provides support for including user sequences in the alignments.