Showing papers in "Nucleic Acids Research in 2010"
TL;DR: The ANNOVAR tool to annotate single nucleotide variants and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP is developed.
Abstract: High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a 'variants reduction' protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/.
10,461 citations
TL;DR: The key purpose of interactive analysis is to check whether conserved residues line up in multiple structural alignments and how Conserved residues and ligands cluster together in multiple structure superimpositions.
Abstract: Our web site (http://ekhidna.biocenter.helsinki.fi/dali_server) runs the Dali program for protein structure comparison. The web site consists of three parts: (i) the Dali server compares newly solved structures against structures in the Protein Data Bank (PDB), (ii) the Dali database allows browsing precomputed structural neighbourhoods and (iii) the pairwise comparison generates suboptimal alignments for a pair of structures. Each part has its own query form and a common format for the results page. The inputs are either PDB identifiers or novel structures uploaded by the user. The results pages are hyperlinked to aid interactive analysis. The web interface is simple and easy to use. The key purpose of interactive analysis is to check whether conserved residues line up in multiple structural alignments and how conserved residues and ligands cluster together in multiple structure superimpositions. In favourable cases, protein structure comparison can lead to evolutionary discoveries not detected by sequence analysis.
3,573 citations
TL;DR: The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make Gene MANIA a useful tool for any biologist.
Abstract: GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
3,211 citations
TL;DR: AgriGO as discussed by the authors is an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of EasyGO, to meet analysis demands from new technologies and research objectives.
Abstract: Gene Ontology (GO), the de facto standard in gene functionality description, is used widely in functional annotation and enrichment analysis. Here, we introduce agriGO, an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of our previous GO enrichment tool (EasyGO), to meet analysis demands from new technologies and research objectives. EasyGO is valuable for its proficiency, and has proved useful in uncovering biological knowledge in massive data sets from high-throughput experiments. For agriGO, the system architecture and website interface were redesigned to improve performance and accessibility. The supported organisms and gene identifiers were substantially expanded (including 38 agricultural species composed of 274 data types). The requirement on user input is more flexible, in that user-defined reference and annotation are accepted. Moreover, a new analysis approach using Gene Set Enrichment Analysis strategy and customizable features is provided. Four tools, SEA (Singular enrichment analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA), are integrated as a toolkit to meet different demands. We also provide a cross-comparison service so that different data sets can be compared and explored in a visualized way. Lastly, agriGO functions as a GO data repository with search and download functions; agriGO is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/.
2,274 citations
TL;DR: The new disease/drug information resource named KEGG MEDICUS can be used as a reference knowledge base for computational analysis of molecular networks, especially, by integrating large-scale experimental datasets.
Abstract: Most human diseases are complex multi-factorial diseases resulting from the combination of various genetic and environmental factors. In the KEGG database resource (http://www.genome.jp/kegg/), diseases are viewed as perturbed states of the molecular system, and drugs as perturbants to the molecular system. Disease information is computerized in two forms: pathway maps and gene/ molecule lists. The KEGG PATHWAY database contains pathway maps for the molecular systems in both normal and perturbed states. In the KEGG DISEASE database, each disease is represented by a list of known disease genes, any known environmental factors at the molecular level, diagnostic markers and therapeutic drugs, which may reflect the underlying molecular system. The KEGG DRUG database contains chemical structures and/or chemical components of all drugs in Japan, including crude drugs and TCM (Traditional Chinese Medicine) formulas, and drugs in the USA and Europe. This database also captures knowledge about two types of molecular networks: the interaction network with target molecules, metabolizing enzymes, other drugs, etc. and the chemical structure transformation network in the history of drug development. The new disease/drug information resource named KEGG MEDICUS can be used as a reference knowledge base for computational analysis of molecular networks, especially, by integrating large-scale experimental datasets.
2,181 citations
TL;DR: A new framework aimed at both novice as well as expert users that exposes novel methods of obtaining annotations and visualizing sequence analysis results through one uniform and consistent interface is presented.
Abstract: The EMBL-EBI provides access to various mainstream sequence analysis applications. These include sequence similarity search services such as BLAST, FASTA, InterProScan and multiple sequence alignment tools such as ClustalW, T-Coffee and MUSCLE. Through the sequence similarity search services, the users can search mainstream sequence databases such as EMBL-Bank and UniProt, and more than 2000 completed genomes and proteomes. We present here a new framework aimed at both novice as well as expert users that exposes novel methods of obtaining annotations and visualizing sequence analysis results through one uniform and consistent interface. These services are available over the web and via Web Services interfaces for users who require systematic access or want to interface with customized pipe-lines and workflows using common programming languages. The framework features novel result visualizations and integration of domain and functional predictions for protein database searches. It is available at http://www.ebi.ac.uk/Tools/sss for sequence similarity searches and at http://www.ebi.ac.uk/Tools/msa for multiple sequence alignments.
1,768 citations
TL;DR: The new version of the ConSurf web server is presented, providing an easier and more intuitive step-by-step interface, while offering the user more flexibility during the process, and calculates the evolutionary rates for nucleic acid sequences.
Abstract: It is informative to detect highly conserved positions in proteins and nucleic acid sequence/structure since they are often indicative of structural and/or functional importance. ConSurf (http://consurf.tau.ac.il) and ConSeq (http://conseq.tau.ac.il) are two well-established web servers for calculating the evolutionary conservation of amino acid positions in proteins using an empirical Bayesian inference, starting from protein structure and sequence, respectively. Here, we present the new version of the ConSurf web server that combines the two independent servers, providing an easier and more intuitive step-by-step interface, while offering the user more flexibility during the process. In addition, the new version of ConSurf calculates the evolutionary rates for nucleic acid sequences. The new version is freely available at: http://consurf.tau.ac.il/.
1,665 citations
TL;DR: The FASTQ format is defined, covering the original Sanger standard, the Solexa/Illumina variants and conversion between them, based on publicly available information such as the MAQ documentation and conventions recently agreed by the Open Bioinformatics Foundation projects Biopython, BioPerl, BioRuby, BioJava and EMBOSS.
Abstract: FASTQ has emerged as a common file format for sharing sequencing read data combining both the sequence and an associated per base quality score, despite lacking any formal definition to date, and existing in at least three incompatible variants. This article defines the FASTQ format, covering the original Sanger standard, the Solexa/Illumina variants and conversion between them, based on publicly available information such as the MAQ documentation and conventions recently agreed by the Open Bioinformatics Foundation projects Biopython, BioPerl, BioRuby, BioJava and EMBOSS. Being an open access publication, it is hoped that this description, with the example files provided as Supplementary Data, will serve in future as a reference for this important file format.
1,289 citations
TL;DR: The University of California, Santa Cruz Genome Browser website provides a large database of publicly available sequence and annotation data along with an integrated tool set for examining and comparing the genomes of organisms, aligning sequence to genomes, and displaying and sharing users’ own annotation data.
Abstract: The University of California, Santa Cruz (UCSC) Genome Browser website (http://genome.ucsc.edu/) provides a large database of publicly available sequence and annotation data along with an integrated tool set for examining and comparing the genomes of organisms, aligning sequence to genomes, and displaying and sharing users' own annotation data. As of September 2009, genomic sequence and a basic set of annotation 'tracks' are provided for 47 organisms, including 14 mammals, 10 non-mammal vertebrates, 3 invertebrate deuterostomes, 13 insects, 6 worms and a yeast. New data highlights this year include an updated human genome browser, a 44-species multiple sequence alignment track, improved variation and phenotype tracks and 16 new genome-wide ENCODE tracks. New features include drag-and-zoom navigation, a Wiki track for user-added annotations, new custom track formats for large datasets (bigBed and bigWig), a new multiple alignment output tool, links to variation and protein structure tools, in silico PCR utility enhancements, and improved track configuration tools.
1,226 citations
TL;DR: TranslatorX is presented, a web server designed to align protein-coding nucleotide sequences based on their corresponding amino acid translations, with a rich output, including Jalview-powered graphical visualization of the alignments, codon-based alignments coloured according to the corresponding amino acids, measures of compositional bias and first, second and third codon position specific alignments.
Abstract: We present TranslatorX, a web server designed to align protein-coding nucleotide sequences based on their corresponding amino acid translations. Many comparisons between biological sequences (nucleic acids and proteins) involve the construction of multiple alignments. Alignments represent a statement regarding the homology between individual nucleotides or amino acids within homologous genes. As protein-coding DNA sequences evolve as triplets of nucleotides (codons) and it is known that sequence similarity degrades more rapidly at the DNA than at the amino acid level, alignments are generally more accurate when based on amino acids than on their corresponding nucleotides. TranslatorX novelties include: (i) use of all documented genetic codes and the possibility of assigning different genetic codes for each sequence; (ii) a battery of different multiple alignment programs; (iii) translation of ambiguous codons when possible; (iv) an innovative criterion to clean nucleotide alignments with GBlocks based on protein information; and (v) a rich output, including Jalview-powered graphical visualization of the alignments, codon-based alignments coloured according to the corresponding amino acids, measures of compositional bias and first, second and third codon position specific alignments. The TranslatorX server is freely available at http://translatorx.co.uk.
1,186 citations
TL;DR: An algorithm for gene identification in DNA sequences derived from shotgun sequencing of microbial communities and its accuracy is described and several thousands of new genes could be added to existing annotations of several human and mouse gut metagenomes.
Abstract: We describe an algorithm for gene identification in DNA sequences derived from shotgun sequencing of microbial communities. Accurate ab initio gene prediction in a short nucleotide sequence of anonymous origin is hampered by uncertainty in model parameters. While several machine learning approaches could be proposed to bypass this difficulty, one effective method is to estimate parameters from dependencies, formed in evolution, between frequencies of oligonucleotides in protein-coding regions and genome nucleotide composition. Original version of the method was proposed in 1999 and has been used since for (i) reconstructing codon frequency vector needed for gene finding in viral genomes and (ii) initializing parameters of self-training gene finding algorithms. With advent of new prokaryotic genomes en masse it became possible to enhance the original approach by using direct polynomial and logistic approximations of oligonucleotide frequencies, as well as by separating models for bacteria and archaea. These advances have increased the accuracy of model reconstruction and, subsequently, gene prediction. We describe the refined method and assess its accuracy on known prokaryotic genomes split into short sequences. Also, we show that as a result of application of the new method, several thousands of new genes could be added to existing annotations of several human and mouse gut metagenomes.
TL;DR: A second generation splice detection algorithm, MapSplice, whose focus is high sensitivity and specificity in the detection of splices as well as CPU and memory efficiency is introduced, which indicates that Map Splice is a highly accurate algorithm for the alignment of RNA-seq reads to splice junctions.
Abstract: The accurate mapping of reads that span splice junctions is a critical component of all analytic techniques that work with RNA-seq data. We introduce a second generation splice detection algorithm, MapSplice, whose focus is high sensitivity and specificity in the detection of splices as well as CPU and memory efficiency. MapSplice can be applied to both short (<75 bp) and long reads (≥ 75 bp). MapSplice is not dependent on splice site features or intron length, consequently it can detect novel canonical as well as non-canonical splices. MapSplice leverages the quality and diversity of read alignments of a given splice to increase accuracy. We demonstrate that MapSplice achieves higher sensitivity and specificity than TopHat and SpliceMap on a set of simulated RNA-seq data. Experimental studies also support the accuracy of the algorithm. Splice junctions derived from eight breast cancer RNA-seq datasets recapitulated the extensiveness of alternative splicing on a global level as well as the differences between molecular subtypes of breast cancer. These combined results indicate that MapSplice is a highly accurate algorithm for the alignment of RNA-seq reads to splice junctions. Software download URL: http://www.netlab.uky.edu/p/bioinfo/MapSplice.
TL;DR: REBASE is a comprehensive and fully curated database of information about the components of restriction-modification (RM) systems that contains fully referenced information about recognition and cleavage sites for both restriction enzymes and methyltransferases as well as commercial availability, methylation sensitivity, crystal and sequence data.
Abstract: REBASE is a comprehensive and fully curated database of information about the components of restriction-modification (RM) systems. It contains fully referenced information about recognition and cleavage sites for both restriction enzymes and methyltransferases as well as commercial availability, methylation sensitivity, crystal and sequence data. All genomes that are completely sequenced are analyzed for RM system components, and with the advent of PacBio sequencing, the recognition sequences of DNA methyltransferases (MTases) are appearing rapidly. Thus, Type I and Type III systems can now be characterized in terms of recognition specificity merely by DNA sequencing. The contents of REBASE may be browsed from the web http://rebase.neb.com and selected compilations can be downloaded by FTP (ftp.neb.com). Monthly updates are also available via email.
TL;DR: AMSA, an annotated multiple sequence alignment format used to build a new generation of generalized profiles, the migration of ScanProsite to Vital-IT, a cluster of 633 CPUs, and the adoption of the Distributed Annotation System (DAS) to facilitate PROSITE data integration and interchange with other sources are described.
Abstract: PROSITE consists of documentation entries describing protein domains, families and functional sites, as well as associated patterns and profiles to identify them. It is complemented by ProRule, a collection of rules based on profiles and patterns, which increases the discriminatory power of these profiles and patterns by providing additional information about functionally and/or structurally critical amino acids. PROSITE is largely used for the annotation of domain features of UniProtKB/Swiss-Prot entries. Among the 983 (DNA-binding) domains, repeats and zinc fingers present in Swiss-Prot (release 57.8 of 22 September 2009), 696 ( approximately 70%) are annotated with PROSITE descriptors using information from ProRule. In order to allow better functional characterization of domains, PROSITE developments focus on subfamily specific profiles and a new profile building method giving more weight to functionally important residues. Here, we describe AMSA, an annotated multiple sequence alignment format used to build a new generation of generalized profiles, the migration of ScanProsite to Vital-IT, a cluster of 633 CPUs, and the adoption of the Distributed Annotation System (DAS) to facilitate PROSITE data integration and interchange with other sources. The latest version of PROSITE (release 20.54, of 22 September 2009) contains 1308 patterns, 863 profiles and 869 ProRules. PROSITE is accessible at: http://www.expasy.org/prosite/.
TL;DR: The results point to a hitherto unrecognized and uncharacterized miRNA trafficking system in mammalian cells that is consistent with the cell–cell communication hypothesis.
Abstract: The discovery of microRNAs (miRNAs) as a new class of regulators of gene expression has triggered an explosion of research activities, but has left many unanswered questions about how this regulation functions and how it is integrated with other regulatory mechanisms. A number of miRNAs have been found to be present in plasma and other body fluids of humans and mice in surprisingly high concentrations. This observation was unexpected in two respects: first, the fact that these molecules are present at all outside the cell at significant concentrations and second, that these molecules appear to be stable outside of the cell. In light of this it has been suggested that the biological function of miRNAs may also extend outside of the cell and mediate cell–cell communication. We report here that after serum deprivation several human cell lines tested promptly export a substantial amount of miRNAs into the culture medium and the export process is largely energy dependent. The exported miRNAs are found both within and outside of the 16.5 and 120 K centrifugation pellets which contain most of the known cell-derived vesicles, the microvesicles and exosomes. We have identified some candidate proteins involved in this system, and one of these proteins may also play a role in protecting extracellular miRNAs from degradation. Our results point to a hitherto unrecognized and uncharacterized miRNA trafficking system in mammalian cells that is consistent with the cell–cell communication hypothesis.
TL;DR: The database characteristics and implementation are described, the use of the use is demonstrated, its use is discussed, and future directions for its development are discussed.
Abstract: BioNumbers (http://www.bionumbers.hms.harvard.edu) is a database of key numbers in molecular and cell biology—the quantitative properties of biological systems of interest to computational, systems and molecular cell biologists. Contents of the database range from cell sizes to metabolite concentrations, from reaction rates to generation times, from genome sizes to the number of mitochondria in a cell. While always of importance to biologists, having numbers in hand is becoming increasingly critical for experimenting, modeling, and analyzing biological systems. BioNumbers was motivated by an appreciation of how long it can take to find even the simplest number in the vast biological literature. All numbers are taken directly from a literature source and that reference is provided with the number. BioNumbers is designed to be highly searchable and queries can be performed by keywords or browsed by menus. BioNumbers is a collaborative community platform where registered users can add content and make comments on existing data. All new entries and commentary are curated to maintain high quality. Here we describe the database characteristics and implementation, demonstrate its use, and discuss future directions for its development.
TL;DR: The study elucidates that fine tuning of HULC expression is part of an auto-regulatory loop in which it’s inhibitory to expression and activity of miR-372 allows lncRNA up-regulated expression in liver cancer.
Abstract: Long non-coding RNA (lncRNA), highly up-regulated in liver cancer (HULC) plays an important role in tumorigenesis. Depletion of HULC resulted in a significant deregulation of several genes involved in liver cancer. Although up-regulation of HULC expression in hepatocellular carcinoma has been reported, the molecular mechanisms remain unknown. In this study, we used in vivo and in vitro approaches to characterize cancer-dependent alterations in the chromatin organization and find a CREB binding site (encompassing from −67 to −53 nt) in the core promoter. Besides, we also provided evidence that PKA pathway may involved in up-regulation of HULC. Furthermore, we demonstrated HULC may act as an endogenous ‘sponge’, which down-regulates a series of microRNAs (miRNAs) activities, including miR-372. Inhibition of miR-372 leads to reducing translational repression of its target gene, PRKACB, which in turn induces phosphorylation of CREB. Over-expression of miR-372 decreases the association of CREB with the proximal promoter, followed by the dissociation of P300, resulting in a change of the histone ‘code’, such as in deacetylation and methylation. The study elucidates that fine tuning of HULC expression is part of an auto-regulatory loop in which it’s inhibitory to expression and activity of miR-372 allows lncRNA up-regulated expression in liver cancer.
TL;DR: The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other, but the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates.
Abstract: High-throughput molecular technologies can profile microbial communities at high resolution even in complex environments like the intestinal microbiota. Recent improvements in next-generation sequencing technologies allow for even finer resolution. We compared phylogenetic profiling of both longer (454 Titanium) sequence reads with shorter, but more numerous, paired-end reads (Illumina). For both approaches, we targeted six tandem combinations of 16S rRNA gene variable regions, in microbial DNA extracted from a human faecal sample, in order to investigate their limitations and potentials. In silico evaluations predicted that the V3/V4 and V4/V5 regions would provide the highest classification accuracies for both technologies. However, experimental sequencing of the V3/V4 region revealed significant amplification bias compared to the other regions, emphasising the necessity for experimental validation of primer pairs. The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other. However, the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates beyond 60 nt. Nonetheless, with improved quality and longer reads, the far greater coverage of Illumina promises unparalleled insights into highly diverse and complex environments such as the human gut.
TL;DR: TriTrypDB is an integrated database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs, utilizing a sophisticated search strategy system.
Abstract: TriTrypDB (http://tritrypdb.org) is an integrated database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. TriTrypDB is a collaborative project, utilizing the GUS/WDK computational infrastructure developed by the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org) to integrate genome annotation and analyses from GeneDB and elsewhere with a wide variety of functional genomics datasets made available by members of the global research community, often pre-publication. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. 'User Comments' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate.
TL;DR: The NCBI BioSystems database centralizes and cross-links existing biological systems databases and allows users of NCBI’s Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type.
Abstract: The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI's Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.
TL;DR: A total of 306 800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as Tm, location on the transcript and amplicon size.
Abstract: PrimerBank (http://pga.mgh.harvard.edu/primerbank/) is a public resource for the retrieval of human and mouse primer pairs for gene expression analysis by PCR and Quantitative PCR (QPCR). A total of 306 800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as Tm, location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. There are several ways to search for primers for the gene(s) of interest, such as by: GenBank accession number, NCBI protein accession number, NCBI gene ID, PrimerBank ID, NCBI gene symbol or gene description (keyword). In all, 26 855 primer pairs covering most known mouse genes have been experimentally validated by QPCR, agarose gel analysis, sequencing and BLAST, and all validation data can be freely accessed from the PrimerBank web site.
TL;DR: A novel gene prediction method FragGeneScan is developed, which combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads, which consistently outperformed MetaGene for short reads.
Abstract: The advances of next-generation sequencing technology have facilitated metagenomics research that attempts to determine directly the whole collection of genetic material within an environmental sample (i.e. the metagenome). Identification of genes directly from short reads has become an important yet challenging problem in annotating metagenomes, since the assembly of metagenomes is often not available. Gene predictors developed for whole genomes (e.g. Glimmer) and recently developed for metagenomic sequences (e.g. MetaGene) show a significant decrease in performance as the sequencing error rates increase, or as reads get shorter. We have developed a novel gene prediction method FragGeneScan, which combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads. The performance of FragGeneScan was comparable to Glimmer and MetaGene for complete genomes. But for short reads, FragGeneScan consistently outperformed MetaGene (accuracy improved ~62% for reads of 400 bases with 1% sequencing errors, and ~18% for short reads of 100 bases that are error free). When applied to metagenomes, FragGeneScan recovered substantially more genes than MetaGene predicted (>90% of the genes identified by homology search), and many novel genes with no homologs in current protein sequence database.
TL;DR: A read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias in nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer.
Abstract: Generation of cDNA using random hexamer priming induces biases in the nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer. The bias is independent of organism and laboratory and impacts the uniformity of the reads along the transcriptome. We provide a read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias.
TL;DR: This study reveals global circuitry of the NRF2 stress response emphasizing Nrf2 as a central node in cell survival response and modulated pathways in stress response and cell proliferation distinguish the inducible and basal programs.
Abstract: The Nrf2 (nuclear factor E2 p45-related factor 2) transcription factor responds to diverse oxidative and electrophilic environmental stresses by circumventing repression by Keap1, translocating to the nucleus, and activating cytoprotective genes. Nrf2 responses provide protection against chemical carcinogenesis, chronic inflammation, neurodegeneration, emphysema, asthma and sepsis in murine models. Nrf2 regulates the expression of a plethora of genes that detoxify oxidants and electrophiles and repair or remove damaged macromolecules, such as through proteasomal processing. However, many direct targets of Nrf2 remain undefined. Here, mouse embryonic fibroblasts (MEF) with either constitutive nuclear accumulation (Keap1−/−) or depletion (Nrf2−/−) of Nrf2 were utilized to perform chromatin-immunoprecipitation with parallel sequencing (ChIP-Seq) and global transcription profiling. This unique Nrf2 ChIP-Seq dataset is highly enriched for Nrf2-binding motifs. Integrating ChIP-Seq and microarray analyses, we identified 645 basal and 654 inducible direct targets of Nrf2, with 244 genes at the intersection. Modulated pathways in stress response and cell proliferation distinguish the inducible and basal programs. Results were confirmed in an in vivo stress model of cigarette smoke-exposed mice. This study reveals global circuitry of the Nrf2 stress response emphasizing Nrf2 as a central node in cell survival response.
TL;DR: The Immune Epitope Database (IEDB), which provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments, was completely redesigned for the IEDB 2.0 release.
Abstract: The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180,978 experiments were curated manually from the literature, which covers approximately 99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129,186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009.
TL;DR: A two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows in homology assignment.
Abstract: The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters.
TL;DR: The main changes include a more precise definition of the curation policy and the development of an enhanced and user-friendly interface to facilitate the analysis of the ever-growing interaction dataset.
Abstract: MINT (http://mint.bio.uniroma2.it/mint) is a public repository for molecular interactions reported in peer-reviewed journals. Since its last report, MINT has grown considerably in size and evolved in scope to meet the requirements of its users. The main changes include a more precise definition of the curation policy and the development of an enhanced and user-friendly interface to facilitate the analysis of the ever-growing interaction dataset. MINT has adopted the PSI-MI standards for the annotation and for the representation of molecular interactions and is a member of the IMEx consortium.
TL;DR: The JASPAR database now uses versioning of matrices, and classification of TF families has been improved by adopting a new DNA-binding domain nomenclature, and three new special collections provide matrix profile data produced by recent alternative high-throughput approaches.
Abstract: JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches.
TL;DR: The Plant Transcription Factor Database (PlnTFDB) is an integrative database that provides putatively complete sets of transcription factors and other transcriptional regulators in plant species whose genomes have been completely sequenced and annotated.
Abstract: The Plant Transcription Factor Database (PlnTFDB; http://plntfdb.bio.uni-potsdam.de/v3.0/) is an integrative database that provides putatively complete sets of transcription factors (TFs) and other transcriptional regulators (TRs) in plant species (sensu lato) whose genomes have been completely sequenced and annotated. The complete sets of 84 families of TFs and TRs from 19 species ranging from unicellular red and green algae to angiosperms are included in PlnTFDB, representing >1.6 billion years of evolution of gene regulatory networks. For each gene family, a basic description is provided that is complemented by literature references, and multiple sequence alignments of protein domains. TF or TR gene entries include information of expressed sequence tags, 3D protein structures of homologous proteins, domain architecture and cross-links to other computational resources online. Moreover, the different species in PlnTFDB are linked to each other by means of orthologous genes facilitating cross-species comparisons.
TL;DR: 3DLigandSite is a web server for the prediction of ligand-binding sites based upon successful manual methods used in the eighth round of the Critical Assessment of techniques for protein Structure Prediction (CASP8), which utilizes protein-structure prediction to provide structural models for proteins that have not been solved.
Abstract: 3DLigandSite is a web server for the prediction of ligand-binding sites. It is based upon successful manual methods used in the eighth round of the Critical Assessment of techniques for protein Structure Prediction (CASP8). 3DLigandSite utilizes protein-structure prediction to provide structural models for proteins that have not been solved. Ligands bound to structures similar to the query are superimposed onto the model and used to predict the binding site. In benchmarking against the CASP8 targets 3DLigandSite obtains a Matthew's correlation co-efficient (MCC) of 0.64, and coverage and accuracy of 71 and 60%, respectively, similar results to our manual performance in CASP8. In further benchmarking using a large set of protein structures, 3DLigandSite obtains an MCC of 0.68. The web server enables users to submit either a query sequence or structure. Predictions are visually displayed via an interactive Jmol applet. 3DLigandSite is available for use at http://www.sbg.bio.ic.ac.uk/3dligandsite.