Prophage Finder: a prophage loci prediction tool for prokaryotic genome sequences

Prophage loci often remain under-annotated or even unrecognized in prokaryotic genome sequencing projects. A PHP application, Prophage Finder, has been developed and implemented to predict prophage loci, based upon clusters of phage-related gene products encoded within DNA sequences. This application provides results detailing several facets of these clusters to facilitate rapid prediction and analysis of prophage sequences. Prophage Finder was tested using previously annotated prokaryotic genomic sequences with manually curated prophage loci as benchmarks. Additional analyses from Prophage Finder searches of several draft prokaryotic genome sequences are available through the Web site (http://bioinformatics.uwp.edu/~phage/DOEResults.php) to illustrate the potential of this application.     

FITBAR: a web tool for the robust prediction of prokaryotic regulons

Background  

The binding of regulatory proteins to their specific DNA targets determines the accurate expression of the neighboring genes. The in silico prediction of new binding sites in completely sequenced genomes is a key aspect in the deeper understanding of gene regulatory networks. Several algorithms have been described to discriminate against false-positives in the prediction of new binding targets; however none of them has been implemented so far to assist the detection of binding sites at the genomic scale.     

CID-miRNA: a web server for prediction of novel miRNA precursors in human genome

microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filtering systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at http://mirna.jnu.ac.in/cidmirna/.     

PeerGAD: a peer-review-based and community-centric web application for viewing and annotating prokaryotic genome sequences

PeerGAD is a web-based database-driven application that allows community-wide peer-reviewed annotation of prokaryotic genome sequences. The application was developed to support the annotation of the Pseudomonas syringae pv. tomato strain DC3000 genome sequence and is easily portable to other genome sequence annotation projects. PeerGAD incorporates several innovative design and operation features and accepts annotations pertaining to gene naming, role classification, gene translation and annotation derivation. The annotator tool in PeerGAD is built around a genome browser that offers users the ability to search and navigate the genome sequence. Because the application encourages annotation of the genome sequence directly by researchers and relies on peer review, it circumvents the need for an annotation curator while providing added value to the annotation data. Support for the Gene Ontology vocabulary, a structured and controlled vocabulary used in classification of gene roles, is emphasized throughout the system. Here we present the underlying concepts integral to the functionality of PeerGAD.     

NotI flanking sequences: a tool for gene discovery and verification of the human genome

A set of 22 551 unique human NotI flanking sequences (16.2 Mb) was generated. More than 40% of the set had regions with significant similarity to known proteins and expressed sequences. The data demonstrate that regions flanking NotI sites are less likely to form nucleosomes efficiently and resemble promoter regions. The draft human genome sequence contained 55.7% of the NotI flanking sequences, Celera’s database contained matches to 57.2% of the clones and all public databases (including non-human and previously sequenced NotI flanks) matched 89.2% of the NotI flanking sequences (identity ≥90% over at least 50 bp, data from December 2001). The data suggest that the shotgun sequencing approach used to generate the draft human genome sequence resulted in a bias against cloning and sequencing of NotI flanks. A rough estimation (based primarily on chromosomes 21 and 22) is that the human genome contains 15 000–20 000 NotI sites, of which 6000–9000 are unmethylated in any particular cell. The results of the study suggest that the existing tools for computational determination of CpG islands fail to identify a significant fraction of functional CpG islands, and unmethylated DNA stretches with a high frequency of CpG dinucleotides can be found even in regions with low CG content.     

MPSQ: a web tool for protein-state searching

MPSQ (multi-protein-states query) is a web-based tool for the discovery of protein states (e.g. biological interactions, covalent modifications, cellular localizations). In particular, large sets of genes can be used to search for enriched state transition network maps (NMs) and features facilitating the interpretation of genomic-scale experiments such as microarrays. One NM collects all the catalogued states of a protein as well as the mutual transitions between the states. For the returned NM, graph visualization is provided for easy understanding and to guide further analysis.     

Mercator: a fast and simple web server for genome scale functional annotation of plant sequence data

Next‐generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required to make these data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan ‘BIN’ ontology, which is tailored for functional annotation of plant ‘omics’ data. The classification procedure performs parallel sequence searches against reference databases, compiles the results and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan‐to‐GO translation table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/Mercator .     

G-IMEx: A comprehensive software tool for detection of microsatellites from genome sequences

Microsatellites are ubiquitous short tandem repeats found in all known genomes and are known to play a very important role in various studies and fields including DNA fingerprinting, paternity studies, evolutionary studies, virulence and adaptation of certain bacteria and viruses etc. Due to the sequencing of several genomes and the availability of enormous amounts of sequence data during the past few years, computational studies of microsatellites are of interest for many researchers. In this context, we developed a software tool called Imperfect Microsatellite Extractor (IMEx), to extract perfect, imperfect and compound microsatellites from genome sequences along with their complete statistics. Recently we developed a user-friendly graphical-interface using JAVA for IMEx to be used as a stand-alone software named G-IMEx. G-IMEx takes a nucleotide sequence as an input and the results are produced in both html and text formats. The Linux version of G-IMEx can be downloaded for free from http://www.cdfd.org.in/imex.     

Structural proteomics: a tool for genome annotation

In any newly sequenced genome, 30% to 50% of genes encode proteins with unknown molecular or cellular function. Fortunately, structural genomics is emerging as a powerful approach of functional annotation. Because of recent developments in high-throughput technologies, ongoing structural genomics projects are generating new structures at an unprecedented rate. In the past year, structural studies have identified many new structural motifs involved in enzymatic catalysis or in binding ligands or other macromolecules (DNA, RNA, protein). The efficiency by which function is deduced from structure can be further improved by the integration of structure with bioinformatics and other experimental approaches, such as screening for enzymatic activity or ligand binding.     

Organization of simple sequences in the Drosophilia melanoga ter genome

Fragments of Drosophila melanogaster DNA that intensively hybridize with simple sequences poly[(dG-dT).(dC-dA)], poly[(dA).(dT)] and poly[(dG-dA).(dC-dT)] were cloned. The first two types of simple sequences are organized in these clones as separated stretches of moderate length, repeated many times within 12-15 kb. Each cluster contains only one type of the simple sequences and originates from a unique in the genome. In contrast, poly[(dG-dA).(dC-dT)] occurs in the genome as several isolated motifs.     

LIPPRED: A web server for accurate prediction of lipoprotein signal sequences and cleavage sites

Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Na?ve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites.     

HOCTAR database: a unique resource for microRNA target prediction

An Antarctic strain (NJ-7) of Chlorella vulgaris possesses the same 18S rRNA sequence as that of a temperate strain (UTEX259), but shows significantly higher freezing tolerance than the latter. Suppression subtractive hybridization (SSH) was performed to identify genes of intensified expression in NJ-7 relative to UTEX259. Among the genes identified, Ccor1 and Ccor2, co-organized in the same gene cluster Ccor1-Ccor2-Ccor1-Ccor2, showed much higher expression levels in NJ-7 than in UTEX259 at both 20°C and 4°C. As detected by Northern blot and Western blot analyses, the two genes were cold-inducible in NJ-7 but almost not expressed in UTEX259. Their encoded products are predicted to share 55.7% identity to each other and possess physicochemical characteristics similar to that of late embryogenesis abundant (LEA) proteins in plants. The purified recombinant Ccor1 and Ccor2 showed high heat-stability and could act as cryoprotectants to lactate dehydrogenase in vitro. Based on their expression patterns and protein characteristics, we propose that Ccor1 and Ccor2 are two novel LEA proteins and are related to the greatly enhanced freezing tolerance in the Antarctic strain.