EMMA: a platform for consistent storage and efficient analysis of microarray data

As a high throughput technique, microarray experiments produce large data sets, consisting of measured data, laboratory protocols, and experimental settings. We have implemented the open source platform EMMA to store and analyze these data. The system provides automated pipelines for data processing and has a modular architecture that can be easily extended. EMMA features detailed reports about spots and their corresponding measurements. In addition to routine data analysis algorithms, the system can be integrated with other components that contain additional data sources (e.g. genome annotation systems).     

GenColors: accelerated comparative analysis and annotation of prokaryotic genomes at various stages of completeness

SUMMARY: GenColors is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes, considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. The genome comparison tools determine, for example, best-bidirectional hits, gene conservation, syntenies and gene core sets. Swiss-Prot/TrEMBL hits allow annotations in an effective manner. To further support the annotation base-specific quality data can also be displayed if available. With GenColors dedicated genome browsers containing a group of related genomes can be easily set up and maintained. It has been efficiently used for Borrelia garinii and is currently applied to various ongoing genome projects. AVAILABILITY: Detailed information on GenColors is available at http://gencolors.imb-jena.de. Online usage of GenColors-based genome browsers is the preferred application mode. The system is also available upon request for local installation.     

AGMIAL: implementing an annotation strategy for prokaryote genomes as a distributed system

We have implemented a genome annotation system for prokaryotes called AGMIAL. Our approach embodies a number of key principles. First, expert manual annotators are seen as a critical component of the overall system; user interfaces were cyclically refined to satisfy their needs. Second, the overall process should be orchestrated in terms of a global annotation strategy; this facilitates coordination between a team of annotators and automatic data analysis. Third, the annotation strategy should allow progressive and incremental annotation from a time when only a few draft contigs are available, to when a final finished assembly is produced. The overall architecture employed is modular and extensible, being based on the W3 standard Web services framework. Specialized modules interact with two independent core modules that are used to annotate, respectively, genomic and protein sequences. AGMIAL is currently being used by several INRA laboratories to analyze genomes of bacteria relevant to the food-processing industry, and is distributed under an open source license.     

Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools

The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.     

The use of evolutionary biology concepts for genome annotation

The past decade has seen the completion of numerous whole-genome sequencing projects, began with bacterial genomes and continued with eukaryotic species from different phyla: fungi, plants and animals. Besides, more biological information are produced and are shared thanks to information exchange systems, and more biological concepts, as well as more bioinformatics tools, are available. In this article, we will describe how the evolutionary biology concepts, as well as computer science, are useful for a better understanding of biology in general and genome annotation in particular. The genome annotation process consists of taking the raw DNA produced, for example, by the genome sequencing projects, adding the layers of analysis and interpretation necessary to extract its biological significance and placing it in the context of our understanding of biological processes. Genome annotation is a multistep process falling into two broad categories: structural and functional annotation.     

Genome information resources - developments at Ensembl

Genome information resources such as Ensembl manage and present DNA sequence and annotation arising from genome projects. Recent developments in the Ensembl system include access to inter-species comparisons at both the genomic and protein sequence levels and improvements to the display of polymorphism data. Users can now display their own data in the context of other annotation. In addition, a fast and flexible data retrieval system, EnsMart, has been developed.     

STATegra EMS: an Experiment Management System for complex next-generation omics experiments

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures.     

RGAAT: A Reference-based Genome Assembly and Annotation Tool for New Genomes and Upgrade of Known Genomes

The rapid development of high-throughput sequencing technologies has led to a dramatic decrease in the money and time required for de novo genome sequencing or genome resequencing projects, with new genome sequences constantly released every week. Among such projects, the plethora of updated genome assemblies induces the requirement of version-dependent annotation files and other compatible public dataset for downstream analysis. To handle these tasks in an efficient manner, we developed the reference-based genome assembly and annotation tool (RGAAT), a flexible toolkit for resequencing-based consensus building and annotation update. RGAAT can detect sequence variants with comparable precision, specificity, and sensitivity to GATK and with higher precision and specificity than Freebayes and SAMtools on four DNA-seq datasets tested in this study. RGAAT can also identify sequence variants based on cross-cultivar or cross-version genomic alignments. Unlike GATK and SAMtools/BCFtools, RGAAT builds the consensus sequence by taking into account the true allele frequency. Finally, RGAAT generates a coordinate conversion file between the reference and query genomes using sequence variants and supports annotation file transfer. Compared to the rapid annotation transfer tool (RATT), RGAAT displays better performance characteristics for annotation transfer between different genome assemblies, strains, and species. In addition, RGAAT can be used for genome modification, genome comparison, and coordinate conversion. RGAAT is available at https://sourceforge.net/projects/rgaat/ and https://github.com/wushyer/RGAAT_v2 at no cost.     

Biological information: making it accessible and integrated (and trying to make sense of it)

The availability of the genome sequences of human and mouse, human sequence variation data and other large genetic data sets will lead to a revolution in understanding of the human machine and the treatment of its diseases. The success of the international genome sequencing consortiums shows what can be achieved by well coordinated large scale public domain projects and the benefits of data access to all. It is already clear that the availability of this sequence is having a huge impact on research worldwide. Complete genome sequences provide a framework to pull all biological data together such that each piece has the potential to say something about biology as a whole. Biology is too complex for any organisation to have a monopoly of ideas or data, so the collection, analysis and access to this data can be contributed to by research institutes around the world. However, although it is possible for all this data to be accessible to all through the internet, the more organisations provide data or analysis separately, the harder it becomes for anyone to collect and integrate the results. To address these problems of intergration of data, open standards for biological data exchange, such as the 'Distributed Annotation System' (DAS) are being developed and bioinformatics (Dowell et al., 2001) as a whole is now being strongly driven by the open source software (OSS) model for collaborative software development (Hubbard and Birney, 1999). The leading provider of human genome annotation, the Ensembl project (http://www.ensembl.org), is entirely an OSS project and has been widely adopted by academic and commerical organisations alike (Hubbard et al., 2002). Accurate automatic annotation of features such as genes in vertebrate genomes currently relies on supporting evidence in the form of homologies to mRNAs, ESTs or protein. However, it appears that sufficient high quality experimentally curated annotation now exists to be used as a substrate for machine learning algorithms to create effective models of biological signal sequences (Down and Hubbard, 2002). Is there hope for ab initio prediction methods after all?     

MaGe: a microbial genome annotation system supported by synteny results

Magnifying Genomes (MaGe) is a microbial genome annotation system based on a relational database containing information on bacterial genomes, as well as a web interface to achieve genome annotation projects. Our system allows one to initiate the annotation of a genome at the early stage of the finishing phase. MaGe's main features are (i) integration of annotation data from bacterial genomes enhanced by a gene coding re-annotation process using accurate gene models, (ii) integration of results obtained with a wide range of bioinformatics methods, among which exploration of gene context by searching for conserved synteny and reconstruction of metabolic pathways, (iii) an advanced web interface allowing multiple users to refine the automatic assignment of gene product functions. MaGe is also linked to numerous well-known biological databases and systems. Our system has been thoroughly tested during the annotation of complete bacterial genomes (Acinetobacter baylyi ADP1, Pseudoalteromonas haloplanktis, Frankia alni) and is currently used in the context of several new microbial genome annotation projects. In addition, MaGe allows for annotation curation and exploration of already published genomes from various genera (e.g. Yersinia, Bacillus and Neisseria). MaGe can be accessed at http://www.genoscope.cns.fr/agc/mage.     

Protozoan genomes: gene identification and annotation

The draft sequence of several complete protozoan genomes is now available and genome projects are ongoing for a number of other species. Different strategies are being implemented to identify and annotate protein coding and RNA genes in these genomes, as well as study their genomic architecture. Since the genomes vary greatly in size, GC-content, nucleotide composition, and degree of repetitiveness, genome structure is often a factor in choosing the methodology utilised for annotation. In addition, the approach taken is dictated, to a greater or lesser extent, by the particular reasons for carrying out genome-wide analyses and the level of funding available for projects. Nevertheless, these projects have provided a plethora of material that will aid in understanding the biology and evolution of these parasites, as well as identifying new targets that can be used to design urgently required drug treatments for the diseases they cause.     

Genome-tools: a flexible package for genome sequence analysis

Genome-tools is a Perl module, a set of programs, and a user interface that facilitates access to genome sequence information. The package is flexible, extensible, and designed to be accessible and useful to both nonprogrammers and programmers. Any relatively well-annotated genome available with standard GenBank genome files may be used with genome-tools. A simple Web-based front end permits searching any available genome with an intuitive interface. Flexible design choices also make it simple to handle revised versions of genome annotation files as they change. In addition, programmers can develop cross-genomic tools and analyses with minimal additional overhead by combining genome-tools modules with newly written modules. Genome-tools runs on any computer platform for which Perl is available, including Unix, Microsoft Windows, and Mac OS. By simplifying the access to large amounts of genomic data, genome-tools may be especially useful for molecular biologists looking at newly sequenced genomes, for which few informatics tools are available. The genome-tools Web interface is accessible at http://genome-tools.sourceforge.net, and the source code is available at http://sourceforge.net/projects/genome-tools.     

Development of joint application strategies for two microbial gene finders

MOTIVATION: As a starting point in annotation of bacterial genomes, gene finding programs are used for the prediction of functional elements in the DNA sequence. Due to the faster pace and increasing number of genome projects currently underway, it is becoming especially important to have performant methods for this task. RESULTS: This study describes the development of joint application strategies that combine the strengths of two microbial gene finders to improve the overall gene finding performance. Critica is very specific in the detection of similarity-supported genes as it uses a comparative sequence analysis-based approach. Glimmer employs a very sophisticated model of genomic sequence properties and is sensitive also in the detection of organism-specific genes. Based on a data set of 113 microbial genome sequences, we optimized a combined application approach using different parameters with relevance to the gene finding problem. This results in a significant improvement in specificity while there is similarity in sensitivity to Glimmer. The improvement is especially pronounced for GC rich genomes. The method is currently being applied for the annotation of several microbial genomes. AVAILABILITY: The methods described have been implemented within the gene prediction component of the GenDB genome annotation system.     

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.     

REGANOR

With >1,000 prokaryotic genome sequencing projects ongoing or already finished, comprehensive comparative analysis of the gene content of these genomes has become viable. To allow for a meaningful comparative analysis, gene prediction of the various genomes should be as accurate as possible. It is clear that improving the state of genome annotation requires automated gene identification methods to cope with the influence of artifacts, such as genomic GC content. There is currently still room for improvement in the state of annotations. We present a web server and a database of high-quality gene predictions. The web server is a resource for gene identification in prokaryote genome sequences. It implements our previously described, accurate gene finding method REGANOR. We also provide novel gene predictions for 241 complete, or almost complete, prokaryotic genomes. We demonstrate how this resource can easily be utilised to identify promising candidates for currently missing genes from genome annotations with several examples. All data sets are available online. AVAILABILITY: The gene finding server is accessible via https://www.cebitec.uni-bielefeld.de/groups/brf/software/reganor/cgi-bin/reganor_upload.cgi. The server software is available with the GenDB genome annotation system (version 2.2.1 onwards) under the GNU general public license. The software can be downloaded from https://sourceforge.net/projects/gendb/. More information on installing GenDB and REGANOR and the system requirements can be found on the GenDB project page http://www.cebitec.uni-bielefeld.de/groups/brf/software/wiki/GenDBWiki/AdministratorDocumentation/GenDBInstallation     

RNAspace.org: An integrated environment for the prediction, annotation, and analysis of ncRNA

The annotation of noncoding RNA genes remains a major bottleneck in genome sequencing projects. Most genome sequences released today still come with sets of tRNAs and rRNAs as the only annotated RNA elements, ignoring hundreds of other RNA families. We have developed a web environment that is dedicated to noncoding RNA (ncRNA) prediction, annotation, and analysis and allows users to run a variety of tools in an integrated and flexible manner. This environment offers complementary ncRNA gene finders and a set of tools for the comparison, visualization, editing, and export of ncRNA candidates. Predictions can be filtered according to a large set of characteristics. Based on this environment, we created a public website located at http://RNAspace.org. It accepts genomic sequences up to 5 Mb, which permits for an online annotation of a complete bacterial genome or a small eukaryotic chromosome. The project is hosted as a Source Forge project (http://rnaspace.sourceforge.net/).     

面向大规模人群的基因组注释系统

基因组注释是识别出基因组序列中功能组件的过程,其可以直接对序列赋予生物学意义,由此方便研究者探究和分析基因组功能.基因组注释可以帮助研究从三个层次上理解基因组,一种是在核苷酸水平的注释,主要确定DNA序列中基因、RNA、重复序列等组件的物理位置,包括转录起始,翻译起始,外显子边界等具体位置信息.同时可以注释得到变异在不...     

Ensembl 2002: accommodating comparative genomics

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.     

PhyloGena--a user-friendly system for automated phylogenetic annotation of unknown sequences

MOTIVATION: Phylogenomic approaches towards functional and evolutionary annotation of unknown sequences have been suggested to be superior to those based only on pairwise local alignments. User-friendly software tools making the advantages of phylogenetic annotation available for the ever widening range of bioinformatically uninitiated biologists involved in genome/EST annotation projects are, however, not available. We were particularly confronted with this issue in the annotation of sequences from different groups of complex algae originating from secondary endosymbioses, where the identification of the phylogenetic origin of genes is often more problematic than in taxa well represented in the databases (e.g. animals, plants or fungi). RESULTS: We present a flexible pipeline with a user-friendly, interactive graphical user interface running on desktop computers that automatically performs a basic local alignment search tool (BLAST) search of query sequences, selects a representative subset of them, then creates a multiple alignment from the selected sequences, and finally computes a phylogenetic tree. The pipeline, named PhyloGena, uses public domain software for all standard bioinformatics tasks (similarity search, multiple alignment, and phylogenetic reconstruction). As the major technological innovation, selection of a meaningful subset of BLAST hits was implemented using logic programming, mimicing the selection procedure (BLAST tables, multiple alignments and phylogenetic trees) are displayed graphically, allowing the user to interact with the pipeline and deduce the function and phylogenetic origin of the query. PhyloGena thus makes phylogenomic annotation available also for those biologists without access to large computing facilities and with little informatics background. Although phylogenetic annotation is particularly useful when working with composite genomes (e.g. from complex algae), PhyloGena can be helpful in expressed sequence tag and genome annotation also in other organisms. AVAILABILITY: PhyloGena (executables for LINUX and Windows 2000/XP as well as source code) is available by anonymous ftp from http://www.awi.de/en/phylogena.