Viewing and annotating sequence data with Artemis

Artemis is a widely used software tool for annotating and viewing sequence data. No database is required to use Artemis. Instead, individual sequence data files can be analysed with little or no formatting, making it particularly suited to the study of small genomes and chromosomes, and straightforward for a novice user to get started. Since its release in 1999, Artemis has been used to annotate a diverse collection of prokaryotic and eukaryotic genomes, ranging from Streptomyces coelicolor to, more recently, a large proportion of the Plasmodium falciparum genome. Artemis allows annotated genomes to be easily browsed and makes it simple to add useful biological information to raw sequence data. This paper gives an overview of some of the features of Artemis and includes how it facilitates manual gene prediction and can provide an overview of entire chromosomes or small compact genomes--useful for uncovering unusual features such as pathogenicity islands.     

WebACT--an online companion for the Artemis Comparison Tool

SUMMARY: WebACT is an online resource which enables the rapid provision of simultaneous BLAST comparisons between up to five genomic sequences in a format amenable for visualization with the well-known Artemis Comparison Tool (ACT). Comparisons can be generated on-the-fly using sequences directly retrieved via EMBL database queries, or by entering or uploading user sequences. Furthermore, pre-computed comparisons are available between all publicly available, completed prokaryotic genomes and plasmids currently contained within the Genome Reviews database (372 sequences, representing 175 different species). The system is designed to minimize the volume of downloaded data and maximize performance. Genome sequences, annotation and pre-computed comparisons are stored in a relational database allowing flexible querying based on user-defined sequence regions, from whole genome to a defined region flanking a specified gene. Comparison and sequence files, whether computed online or retrieved from the database of pre-computed genome comparisons, can be viewed online using ACT and are available for download. AVAILABILITY: Freely accessible at http://www.webact.org. SUPPLEMENTARY INFORMATION: User guide and worked examples are available at http://www.webact.org/WebACT/docs.     

DNannotator: Annotation software tool kit for regional genomic sequences

Sequence annotation is essential for genomics-based research. Investigators of a specific genomic region who have developed abundant local discoveries such as genes and genetic markers, or have collected annotations from multiple resources, can be overwhelmed by the difficulty in creating local annotation and the complexity of integrating all the annotations. Presenting such integrated data in a form suitable for data mining and high-throughput experimental design is even more daunting. DNannotator, a web application, was designed to perform batch annotation on a sizeable genomic region. It takes annotation source data, such as SNPs, genes, primers, and so on, prepared by the end-user and/or a specified target of genomic DNA, and performs de novo annotation. DNannotator can also robustly migrate existing annotations in GenBank format from one sequence to another. Annotation results are provided in GenBank format and in tab-delimited text, which can be imported and managed in a database or spreadsheet and combined with existing annotation as desired. Graphic viewers, such as Genome Browser or Artemis, can display the annotation results. Reference data (reports on the process) facilitating the user's evaluation of annotation quality are optionally provided. DNannotator can be accessed at http://sky.bsd.uchicago.edu/DNannotator.htm.     

DNAPlotter: circular and linear interactive genome visualization

Summary: DNAPlotter is an interactive Java application for generatingcircular and linear representations of genomes. Making use ofthe Artemis libraries to provide a user-friendly method of loadingin sequence files (EMBL, GenBank, GFF) as well as data fromrelational databases, it filters features of interest to displayon separate user-definable tracks. It can be used to producepublication quality images for papers or web pages. Availability: DNAPlotter is freely available (under a GPL licence)for download (for MacOSX, UNIX and Windows) at the WellcomeTrust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/circular/ Contact: artemis{at}sanger.ac.uk Associate Editor: John Quackenbush     

MIPS bacterial genomes functional annotation benchmark dataset

MOTIVATION: Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. RESULTS: The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. AVAILABILITY: BFAB is available at http://mips.gsf.de/proj/bfab     

<Emphasis Type="Italic">In silico</Emphasis> Identification and Analysis of New Artemis/Artemis-like Sequences from Fungal and Metazoan Species

The Artemis Group comprises mammalian proteins with important functions in the repair of ionizing radiation-induced DNA double-strand breaks and in the cleavage of DNA hairpin extremities generated during V(D)J recombination. Little is known about the presence of Artemis/Artemis-like proteins in non-mammalian species. We have characterized new Artemis/Artemis-like sequences from the genomes of some fungi and from non-mammalian metazoan species. An in-depth phylogenetic analysis of these new Artemis/Artemis-like sequences showed that they form a distinct clade within the Pso2p/Snm1p A and B Groups. Hydrophobic cluster analysis and three-dimensional modeling allowed to map and to compare conserved regions in these Artemis/Artemis-like proteins. The results indicate that Artemis probably belongs to an ancient DNA recombination mechanism that diversified with the evolution of multi-cellular eukaryotic lineage.     

A hybrid gene team model and its application to genome analysis

It is well-known that functionally related genes occur in a physically clustered form, especially operons in bacteria. By leveraging on this fact, there has recently been an interesting problem formulation known as gene team model, which searches for a set of genes that co-occur in a pair of closely related genomes. However, many gene teams, even experimentally verified operons, frequently scatter within other genomes. Thus, the gene team model should be refined to reflect this observation. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraints. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. We also compared the result from our hybrid model to those from the traditional gene team model. We also show that predicted gene teams can be used for various genome analysis: operon prediction, phylogenetic analysis of organisms, contextual sequence analysis and genome annotation. Our program is fast enough to provide a service on the web at http://platcom.informatics.indiana.edu/platcom/. Users can select any combination of 97 genomes to predict gene teams.     

Gene finding with a hidden Markov model of genome structure and evolution

Motivation: A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement. Results: A probabilistic model of both genome structure and evolution is designed. This type of model is called an Evolutionary Hidden Markov Model (EHMM), being composed of an HMM and a set of region-specific evolutionary models based on a phylogenetic tree. All parameters can be estimated by maximum likelihood, including the phylogenetic tree. It can handle any number of aligned genomes, using their phylogenetic tree to model the evolutionary correlations. The time complexity of all algorithms used for handling the model are linear in alignment length and genome number. The model is applied to the problem of gene finding. The benefit of modelling sequence evolution is demonstrated both in a range of simulations and on a set of orthologous human/mouse gene pairs. AVAILABILITY: Free availability over the Internet on www server: http://www.birc.dk/Software/evogene.     

Sources of systematic error in functional annotation of genomes: domain rearrangement, non-orthologous gene displacement and operon disruption

Functional annotation of proteins encoded in newly sequenced genomes can be expected to meet two conflicting objectives: (i) provide as much information as possible, and (ii) avoid erroneous functional assignments and over-predictions. The continuing exponential growth of the number of sequenced genomes makes the quality of sequence annotation a critical factor in the efforts to utilize this new information. When dubious functional assignments are used as a basis for subsequent predictions, they tend to proliferate, leading to "database explosion". It is therefore important to identify the common factors that hamper functional annotation. As a first step towards that goal, we have compared the annotations of the Mycoplasma genitalium and Methanococcus jannaschii genomes produced in several independent studies. The most common causes of questionable predictions appear to be: i) non-critical use of annotations from existing database entries; ii) taking into account only the annotation of the best database hit; iii) insufficient masking of low complexity regions (e.g. non-globular domains) in protein sequences, resulting in spurious database hits obscuring relevant ones; iv) ignoring multi-domain organization of the query proteins and/or the database hits; v) non-critical functional inferences on the basis of the functions of neighboring genes in an operon; vi) non-orthologous gene displacement, i.e. involvement of structurally unrelated proteins in the same function. These observations suggest that case by case validation of functional annotation by expert biologists remains crucial for productive genome analysis.     

MuGeN: simultaneous exploration of multiple genomes and computer analysis results

MOTIVATION: The availability of increasing amounts of sequence data about completely sequenced genomes spurs the development of new methods in the fields of automated annotation, and of comparative genomics. Tools allowing the visualization of results produced by analysis methods, superimposed on possibly annotated sequence data, and enabling synchronized navigation in multiple genomes, provide new means for interactive genome exploration. This kind of visual inspection can be used as a basis to assess the quality of new analysis algorithms, or to discover genome portions to be subjected to in-depth studies. RESULTS: We propose a software package, MuGeN, built for navigating through multiple annotated genomes. It is capable of retrieving annotated sequences in several formats, stored in local files, or available in databases over the network. From these, it then generates an interactive display, or an image file, in most common formats suitable for printing, further editing or integrating in Web pages. Genome maps may be mixed with computer analysis results loaded from XML files, whose format is generic enough to be adapted to a majority of sequence oriented analysis methods. AVAILABILITY: MuGeN is available at http://www-mig.jouy.inra.fr/bdsi/MuGeN.     

GAMOLA: a new local solution for sequence annotation and analyzing draft and finished prokaryotic genomes

Laboratories working with draft phase genomes have specific software needs, such as the unattended processing of hundreds of single scaffolds and subsequent sequence annotation. In addition, it is critical to follow the "movement" and the manual annotation of single open reading frames (ORFs) within the successive sequence updates. Even with finished genomes, regular database updates can lead to significant changes in the annotation of single ORFs. In functional genomics it is important to mine data and identify new genetic targets rapidly and easily. Often there is no need for sophisticated relational databases (RDB) that greatly reduce the system-independent access of the results. Another aspect is the internet dependency of most software packages. If users are working with confidential data, this dependency poses a security issue. GAMOLA was designed to handle the numerous scaffolds and changing contents of draft phase genomes in an automated process and stores the results for each predicted ORF in flatfile databases. In addition, annotation transfers, ORF designation tracking, Blast comparisons, and primer design for whole genome microarrays have been implemented. The software is available under the license of North Carolina State University. A website and a downloadable example are accessible under (http://fsweb2.schaub. ncsu.edu/TRKwebsite/index.htm).     

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.     

GFam: a platform for automatic annotation of gene families

We have developed GFam, a platform for automatic annotation of gene/protein families. GFam provides a framework for genome initiatives and model organism resources to build domain-based families, derive meaningful functional labels and offers a seamless approach to propagate functional annotation across periodic genome updates. GFam is a hybrid approach that uses a greedy algorithm to chain component domains from InterPro annotation provided by its 12 member resources followed by a sequence-based connected component analysis of un-annotated sequence regions to derive consensus domain architecture for each sequence and subsequently generate families based on common architectures. Our integrated approach increases sequence coverage by 7.2 percentage points and residue coverage by 14.6 percentage points higher than the coverage relative to the best single-constituent database within InterPro for the proteome of Arabidopsis. The true power of GFam lies in maximizing annotation provided by the different InterPro data sources that offer resource-specific coverage for different regions of a sequence. GFam’s capability to capture higher sequence and residue coverage can be useful for genome annotation, comparative genomics and functional studies. GFam is a general-purpose software and can be used for any collection of protein sequences. The software is open source and can be obtained from http://www.paccanarolab.org/software/gfam/.     

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.     

The DOE-JGI Standard Operating Procedure for the Annotations of Microbial Genomes

The DOE-JGI Microbial Annotation Pipeline (DOE-JGI MAP) supports gene prediction and/or functional annotation of microbial genomes towards comparative analysis with the Integrated Microbial Genome (IMG) system. DOE-JGI MAP annotation is applied on nucleotide sequence datasets included in the IMG-ER (Expert Review) version of IMG via the IMG ER submission site. Users can submit the sequence datasets consisting of one or more contigs in a multi-fasta file. DOE-JGI MAP annotation includes prediction of protein coding and RNA genes, as well as repeats and assignment of product names to these genes.     

Multi-species comparative mapping in silico using the COMPASS strategy

MOTIVATION: The completion of human and mouse genome sequences provides a valuable resource for decoding other mammalian genomes. The comparative mapping by annotation and sequence similarity (COMPASS) strategy takes advantage of the resource and has been used in several genome-mapping projects. It uses existing comparative genome maps based on conserved regions to predict map locations of a sequence. An automated multiple-species COMPASS tool can facilitate in the genome sequencing effort and comparative genomics study of other mammalian species. RESULTS: The prerequisite of COMPASS is a comparative map table between the reference genome and the predicting genome. We have built and collected comparative maps among five species including human, cattle, pig, mouse and rat. Cattle-human and pig-human comparative maps were built based on the positions of orthologous markers and the conserved synteny groups between human and cattle and human and pig genomes, respectively. Mouse-human and rat-human comparative maps were based on the conserved sequence segments between the two genomes. With a match to human genome sequences, the approximate location of a query sequence can be predicted in cattle, pig, mouse and rat genomes based on the position of the match relatively to the orthologous markers or the conserved segments. AVAILABILITY: The COMPASS-tool and databases are available at http://titan.biotec.uiuc.edu/COMPASS/     

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.