The Ensembl automatic gene annotation system

As more genomes are sequenced, there is an increasing need for automated first-pass annotation which allows timely access to important genomic information. The Ensembl gene-building system enables fast automated annotation of eukaryotic genomes. It annotates genes based on evidence derived from known protein, cDNA, and EST sequences. The gene-building system rests on top of the core Ensembl (MySQL) database schema and Perl Application Programming Interface (API), and the data generated are accessible through the Ensembl genome browser (http://www.ensembl.org). To date, the Ensembl predicted gene sets are available for the A. gambiae, C. briggsae, zebrafish, mouse, rat, and human genomes and have been heavily relied upon in the publication of the human, mouse, rat, and A. gambiae genome sequence analysis. Here we describe in detail the gene-building system and the algorithms involved. All code and data are freely available from http://www.ensembl.org.     

EAnnot: a genome annotation tool using experimental evidence

The sequence of any genome becomes most useful for biological experimentation when a complete and accurate gene set is available. Gene prediction programs offer an efficient way to generate an automated gene set. Manual annotation, when performed by experienced annotators, is more accurate and complete than automated annotation. However, it is a laborious and expensive process, and by its nature, introduces a degree of variability not found with automated annotation. EAnnot (Electronic Annotation) is a program originally developed for manually annotating the human genome. It combines the latest bioinformatics tools to extract and analyze a wide range of publicly available data in order to achieve fast and reliable automatic gene prediction and annotation. EAnnot builds gene models based on mRNA, EST, and protein alignments to genomic sequence, attaches supporting evidence to the corresponding genes, identifies pseudogenes, and locates poly(A) sites and signals. Here, we compare manual annotation of human chromosome 6 with annotation performed by EAnnot in order to assess the latter's accuracy. EAnnot can readily be applied to manual annotation of other eukaryotic genomes and can be used to rapidly obtain an automated gene set.     

AnoEST: toward A. gambiae functional genomics

Here, we present an analysis of 215,634 EST and cDNA sequences of a major vector of human malaria Anopheles gambiae structured into the AnoEST database. The expressed sequences are grouped into clusters using genomic sequence as template and associated with inferred functional annotation, including the following: corresponding Ensembl gene prediction, putative orthologous genes in other species, homology to known proteins, protein domains, associated Gene Ontology terms, and corresponding classification into broad GO-slim functional groups. AnoEST is a vital resource for interpretation of expression profiles derived using recently developed A. gambiae cDNA microarrays. Using these cDNA microarrays, we have experimentally confirmed the expression of 7961 clusters during mosquito development. Of these, 3100 are not associated with currently predicted genes. Moreover, we found that clusters with confirmed expression are nonbiased with respect to the current gene annotation or homology to known proteins. Consequently, we expect that many as yet unconfirmed clusters are likely to be actual A. gambiae genes. [AnoEST is publicly available at http://komar.embl.de, and is also accessible as a Distributed Annotation Service (DAS).].     

GANESH: software for customized annotation of genome regions

GANESH is a software package designed to support the genetic analysis of regions of human and other genomes. It provides a set of components that may be assembled to construct a self-updating database of DNA sequence, mapping data, and annotations of possible genome features. Once one or more remote sources of data for the target region have been identified, all sequences for that region are downloaded, assimilated, and subjected to a (configurable) set of standard database-searching and genome-analysis packages. The results are stored in compressed form in a relational database, and are updated automatically on a regular schedule so that they are always immediately available in their most up-to-date versions. A Java front-end, executed as a stand alone application or web applet, provides a graphical interface for navigating the database and for viewing the annotations. There are facilities for importing and exporting data in the format of the Distributed Annotation System (DAS), enabling a GANESH database to be used as a component of a DAS configuration. The system has been used to construct databases for about a dozen regions of human chromosomes and for three regions of mouse chromosomes.     

An overview of Ensembl

Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to "widen" this biological integration to include other model organisms relevant to understanding human biology as they become available; to "deepen" this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive.     

HUMA: A platform for the analysis of genetic variation in humans

The completion of the human genome project at the beginning of the 21st century, along with the rapid advancement of sequencing technologies thereafter, has resulted in exponential growth of biological data. In genetics, this has given rise to numerous variation databases, created to store and annotate the ever‐expanding dataset of known mutations. Usually, these databases focus on variation at the sequence level. Few databases focus on the analysis of variation at the 3D level, that is, mapping, visualizing, and determining the effects of variation in protein structures. Additionally, these Web servers seldom incorporate tools to help analyze these data. Here, we present the Human Mutation Analysis (HUMA) Web server and database. HUMA integrates sequence, structure, variation, and disease data into a single, connected database. A user‐friendly interface provides click‐based data access and visualization, whereas a RESTful Web API provides programmatic access to the data. Tools have been integrated into HUMA to allow initial analyses to be carried out on the server. Furthermore, users can upload their private variation datasets, which are automatically mapped to public data and can be analyzed using the integrated tools. HUMA is freely accessible at https://huma.rubi.ru.ac.za .     

The Ensembl analysis pipeline

The Ensembl pipeline is an extension to the Ensembl system which allows automated annotation of genomic sequence. The software comprises two parts. First, there is a set of Perl modules ("Runnables" and "RunnableDBs") which are 'wrappers' for a variety of commonly used analysis tools. These retrieve sequence data from a relational database, run the analysis, and write the results back to the database. They inherit from a common interface, which simplifies the writing of new wrapper modules. On top of this sits a job submission system (the "RuleManager") which allows efficient and reliable submission of large numbers of jobs to a compute farm. Here we describe the fundamental software components of the pipeline, and we also highlight some features of the Sanger installation which were necessary to enable the pipeline to scale to whole-genome analysis.     

A status report on the sequencing and annotation of the P. falciparum genome.

Almost 5 years ago, an international consortium of sequencing centers and funding agencies was formed to sequence the genome of the human malaria parasite Plasmodium falciparum. A novel chromosome by chromosome shotgun strategy was devised to sequence this very AT-rich genome. Two of the 14 chromosomes have been completed and the remaining chromosomes are in the final stages of gap closure. The consortium recently developed plans for the annotation and analysis of the complete genome sequence and its publication in 2002.     

Sockeye: a 3D environment for comparative genomics

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.     

MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes

We have developed a portable and easily configurable genome annotation pipeline called MAKER. Its purpose is to allow investigators to independently annotate eukaryotic genomes and create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab initio gene predictions, and automatically synthesizes these data into gene annotations having evidence-based quality indices. MAKER is also easily trainable: Outputs of preliminary runs are used to automatically retrain its gene-prediction algorithm, producing higher-quality gene-models on subsequent runs. MAKER's inputs are minimal, and its outputs can be used to create a GMOD database. Its outputs can also be viewed in the Apollo Genome browser; this feature of MAKER provides an easy means to annotate, view, and edit individual contigs and BACs without the overhead of a database. As proof of principle, we have used MAKER to annotate the genome of the planarian Schmidtea mediterranea and to create a new genome database, SmedGD. We have also compared MAKER's performance to other published annotation pipelines. Our results demonstrate that MAKER provides a simple and effective means to convert a genome sequence into a community-accessible genome database. MAKER should prove especially useful for emerging model organism genome projects for which extensive bioinformatics resources may not be readily available.     

Community annotation: procedures, protocols, and supporting tools

Investigators at the Baylor College of Medicine Human Genome Sequencing Center (BCM-HGSC) and BeeBase organized a community-wide effort to manually annotate the honey bee (Apis mellifera) genome. Although various strategies for manual annotation have been used in the past, the value of dispersed community annotation has not yet been demonstrated. Here we make a case for the merit of dispersed community annotation. We present annotation procedures, standard protocols, and tools used for sequence analysis, data submission, and data management. We also report lessons learned from this dispersed community annotation effort for a metazoan genome.     

UniProt genomic mapping for deciphering functional effects of missense variants

Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations, such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease‐related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated single nucleotide polymorphism (SNP) data show that 32% of UniProtKB variants colocate with 8% of ClinVar SNPs. The majority of colocated UniProtKB disease‐associated variants (86%) map to 'pathogenic' ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein, and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.     

Comparing Vertebrate Whole-Genome Shotgun Reads to the Human Genome

Multi-species sequence comparisons are a very efficient way to reveal conserved genes. Because sequence finishing is expensive and time consuming, many genome sequences are likely to stay incomplete. A challenge is to use these fragmented data for understanding the human genome. Methods for using cross-species whole-genome shotgun sequence (WGS) for genome annotation are described in this paper. About one-half million high-quality rat WGS reads (covering 7.5% of the rat genome) generated at the Baylor College of Medicine Human Genome Sequencing Center were compared with the human genome. Using computer-generated random reads as a negative control, a set of parameters was determined for reliable interpretation of BLAST search results. About 10% of the rat reads contain regions that are conserved in the human genomic sequence and about one-third of these include known gene-coding regions. Mapping the conserved regions to human chromosomes showed a 23-fold enrichment for coding regions compared with noncoding regions. This approach can also be applied to other mammalian genomes for gene finding. These data predicted approximately 42,500 genes in the human, slightly more than reported previously.     

A new platform linking chromosomal and sequence information

We have tested whether a direct correlation of sequence information and staining properties of chromosomes is possible and whether this combined information can be used to precisely map any position on the chromosome. Despite huge differences of compaction between the naked DNA and the DNA packed in chromosomes we found a striking correlation when visualizing the GGCC density on both levels. Software was developed that allows one to superimpose chromosomal fluorescence intensity profiles generated by chromolysin A3 (CMA3) staining with GGCC density extracted from the Ensembl database. Thus, any position along the chromosome can be defined in megabase pairs (Mb) besides the cytoband information, enabling direct alignment of chromosomal information with the sequence data. The mapping tool was validated using 13 different BAC clones, resulting in a mean difference from Ensembl data of 2 Mb (ranging from 0.79 to 3.57 Mb). Our results indicate that the sequence density information and information gained with sequence-specific fluorochromes are superimposable. Thus, the visualized GGCC motif density along the chromosome (sequence bands) provides a unique platform for comparing different types of genomic information. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The human genome browser at UCSC

As vertebrate genome sequences near completion and research refocuses to their analysis, the issue of effective genome annotation display becomes critical. A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu. This browser displays assembly contigs and gaps, mRNA and expressed sequence tag alignments, multiple gene predictions, cross-species homologies, single nucleotide polymorphisms, sequence-tagged sites, radiation hybrid data, transposon repeats, and more as a stack of coregistered tracks. Text and sequence-based searches provide quick and precise access to any region of specific interest. Secondary links from individual features lead to sequence details and supplementary off-site databases. One-half of the annotation tracks are computed at the University of California, Santa Cruz from publicly available sequence data; collaborators worldwide provide the rest. Users can stably add their own custom tracks to the browser for educational or research purposes. The conceptual and technical framework of the browser, its underlying MYSQL database, and overall use are described. The web site currently serves over 50,000 pages per day to over 3000 different users.     

Annotation of functional variation in personal genomes using RegulomeDB

As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.