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The most important advances in the field of genome annotation over the past two years involve the use of cDNA sequences, protein structures and gene expression data to predict genes. These types of information not only improve gene identification, but they also give insights into variation in gene structure and function.
While a massive amount of biomolecular information is increasingly accumulating in different databanks, on the other hand high-throughput technologies are generating a great quantity of data that need to be annotated with the genomic information available, and interpreted. To this aim, the use of specific ontologies can greatly help either in integrating different information stored within heterogeneous databanks, or in identifying and clustering sequence data sharing common characteristics. In the molecular biology domain, the Gene Ontology (GO) is the most developed and widely used ontology. To demonstrate its great utility in the annotation and biological interpretation of gene sets obtained by means of high-throughput experiments, we implemented the web application here described. It enables functional annotations of a given gene set on a genomic scale and across different species. Within our application the annotations provided by the GO vocabulary allow either to easily bind several information from different resources, or to cluster annotated genes according to their biological characteristics. Through the GO structure it is also possible to represent biological concepts with different specificity levels, from very general to very precise concepts. Furthermore, the statistical evaluation of the categorizations provided by the GO annotations enables to highlight the most significant biological characteristics of a gene set, and therefore to mine knowledge from data. Our created tool meets the need to manage a vast quantity of biological data with a simple user interface adapt also for users with limited informatics knowledge, leading them to evaluate the functional significance of experiment's results with graphical views and statistical indexes in a well-known web browser user interface.
SwissRegulon (http://www.swissregulon.unibas.ch) is a database containing genome-wide annotations of regulatory sites in the intergenic regions of genomes. The regulatory site annotations are produced using a number of recently developed algorithms that operate on multiple alignments of orthologous intergenic regions from related genomes in combination with, whenever available, known sites from the literature, and ChIP-on-chip binding data. Currently SwissRegulon contains annotations for yeast and 17 prokaryotic genomes. The database provides information about the sequence, location, orientation, posterior probability and, whenever available, binding factor of each annotated site. To enable easy viewing of the regulatory site annotations in the context of other features annotated on the genomes, the sites are displayed using the GBrowse genome browser interface and can be queried based on any annotated genomic feature. The database can also be queried for regulons, i.e. sites bound by a common factor.
ASAP is a comprehensive web-based system for community genome annotation and analysis. ASAP is being used for a large-scale effort to augment and curate annotations for genomes of enterobacterial pathogens and for additional genome sequences. New tools, such as the genome alignment program Mauve, have been incorporated into ASAP in order to improve display and analysis of related genomes. Recent improvements to the database and challenges for future development of the system are discussed. ASAP is available on the web at https://asap.ahabs.wisc.edu/asap/logon.php.
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Processed pseudogenes result from reverse transcribed mRNAs. In general, because processed pseudogenes lack promoters, they are no longer functional from the moment they are inserted into the genome. Subsequently, they freely accumulate substitutions, insertions and deletions. Moreover, the ancestral structure of processed pseudogenes could be easily inferred using the sequence of their functional homologous genes. Owing to these characteristics, processed pseudogenes represent good neutral markers for studying genome evolution. Recently, there is an increasing interest for these markers, particularly to help gene prediction in the field of genome annotation, functional genomics and genome evolution analysis (patterns of substitution). For these reasons, we have developed a method to annotate processed pseudogenes in complete genomes. To make them useful to different fields of research, we stored them in a nucleic acid database after having annotated them. In this work, we screened both mouse and human complete genomes from ENSEMBL to find processed pseudogenes generated from functional genes with introns. We used a conservative method to detect processed pseudogenes in order to minimize the rate of false positive sequences. Within processed pseudogenes, some are still having a conserved open reading frame and some have overlapping gene locations. We designated as retroelements all reverse transcribed sequences and more strictly, we designated as processed pseudogenes, all retroelements not falling in the two former categories (having a conserved open reading or overlapping gene locations). We annotated 5823 retroelements (5206 processed pseudogenes) in the human genome and 3934 (3428 processed pseudogenes) in the mouse genome. Compared to previous estimations, the total number of processed pseudogenes was underestimated but the aim of this procedure was to generate a high-quality dataset. To facilitate the use of processed pseudogenes in studying genome structure and evolution, DNA sequences from processed pseudogenes, and their functional reverse transcribed homologs, are now stored in a nucleic acid database, HOPPSIGEN. HOPPSIGEN can be browsed on the PBIL (Pole Bioinformatique Lyonnais) World Wide Web server (http://pbil.univ-lyon1.fr/) or fully downloaded for local installation.
SUMMARY: We have developed a resource, MutDB (http://mutdb.org/), to aid in determining which single nucleotide polymorphisms (SNPs) are likely to alter the function of their associated protein product. MutDB contains protein structure annotations and comparative genomic annotations for 8000 disease-associated mutations and SNPs found in the UCSC Annotated Genome and the human RefSeq gene set. MutDB provides interactive mutation maps at the gene and protein levels, and allows for ranking of their predicted functional consequences based on conservation in multiple sequence alignments. AVAILABILITY: http://mutdb.org/ SUPPLEMENTARY INFORMATION: http://mutdb.org/about/about.html
We have developed a tool for rapidly determining the number of exact matches of any word within large, internally repetitive genomes or sets of genomes. Thus we can readily annotate any sequence, including the entire human genome, with the counts of its constituent words. We create a Burrows-Wheeler transform of the genome, which together with auxiliary data structures facilitating counting, can reside in about one gigabyte of RAM. Our original interest was motivated by oligonucleotide probe design, and we describe a general protocol for defining unique hybridization probes. But our method also has applications for the analysis of genome structure and assembly. We demonstrate the identification of chromosome-specific repeats, and outline a general procedure for finding undiscovered repeats. We also illustrate the changing contents of the human genome assemblies by comparing the annotations built from different genome freezes.
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
As increasing amounts of genomic sequence from many organisms become available, and as DNA sequences become a primary reagent in biologic investigations, the role of annotation as a prospective guide for laboratory experiments will expand rapidly. Here we describe a process of high-throughput, reliable annotation, called framework annotation, which is designed to provide a foundation for initial biologic characterization of previously unexamined sequence. To examine this concept in practice, we have constructed Genome Annotation and Information Analysis (GAIA), a prototype software architecture that implements several elements important for framework annotation. The center of GAIA consists of an annotation database and the associated data management subsystem that forms the software bus along which other components communicate. The schema for this database defines three principal concepts: (1) Entries, consisting of sequence and associated historical data; (2) Features, comprising information of biologic interest; and (3) Experiments, describing the evidence that supports Features. The database permits tracking of annotation results over time, as well as assessment of the reliability of particular results. New framework annotation is produced by CARTA, a set of autonomous sensors that perform automatic analyses and assert results into the annotation database. These results are available via a Web-based query interface that uses graphical Java applets as well as text-based HTML pages to display data at different levels of resolution and permit interactive exploration of annotation. We present results for initial application of framework annotation to a set of test sequences, demonstrating its effectiveness in providing a starting point for biologic investigation, and discuss ways in which the current prototype can be improved. The prototype is available for public use and comment at http://www.cbil.upenn.edu/gaia.
A simple and general homology-based method for gene finding was applied to the 2.9-Mb Drosophila melanogaster Adh region, the target sequence of the Genome Annotation Assessment Project (GASP). Each strand of the entire sequence was used as query of the BLOCKS+ database of conserved regions of proteins. This led to functional assignments for more than one-third of the genes and two-thirds of the transposons. Considering the enormous size of the query, the fact that only two false-positive matches were reported emphasizes the high selectivity of protein family-based methods for gene finding. We used the search results to improve BLOCKS+ by identifying compositionally biased blocks. Our results confirm that protein family databases can be used effectively in automated sequence annotation efforts.
Prediction of protein-coding regions and other features of primary DNA sequence have greatly contributed to experimental biology. Significant challenges remain in genome annotation methods, including the identification of small or overlapping genes and the assessment of mRNA splicing or unconventional translation signals in expression. We have employed a combined analysis of compositional biases and conservation together with frame-specific G+C representation to reevaluate and annotate the genome sequences of mouse and rat cytomegaloviruses. Our analysis predicts that there are at least 34 protein-coding regions in these genomes that were not apparent in earlier annotation efforts. These include 17 single-exon genes, three new exons of previously identified genes, a newly identified four-exon gene for a lectin-like protein (in rat cytomegalovirus), and 10 probable frameshift extensions of previously annotated genes. This expanded set of candidate genes provides an additional basis for investigation in cytomegalovirus biology and pathogenesis.
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.
Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.
Over the last decade, there have been huge increases in the numbers of protein sequences and structures determined. In parallel, many methods have been developed for recognising similarities between these proteins, arising from their common evolutionary background, and for clustering such relatives into protein families. Here we review some of the protein family resources available to the biologist and describe how these can be used to provide structural and functional annotations for newly determined sequences. In particular we describe recent developments to the CATH domain database of protein structural families which have facilitated genome annotation and which have also revealed important caveats that must be considered when transferring functional data between homologous proteins.
Our challenge in annotating the 2.91-Mb Adh region of the Drosophila melanogaster genome was to identify genetic and genomic features automatically, completely, and precisely within a 6-week period. To do so, we augmented the MAGPIE microbial genome annotation system to handle eukaryotic genomic sequence data. The new configuration required the integration of eukaryotic gene-finding tools and DNA repeat tools into the automatic data collection module. It also required us to define in MAGPIE new strategies to combine data about eukaryotic exon predictions with functional data to refine the exon predictions. At the heart of the resulting new eukaryotic genome annotation system is a reverse comparison of public protein and complementary DNA sequences against the input genome to identify missing exons and to refine exon boundaries. The software modules that add eukaryotic genome annotation capability to MAGPIE are available as EGRET (Eukaryotic Genome Rapid Evaluation Tool).
Computational methods for automated genome annotation are critical to understanding and interpreting the bewildering mass of genomic sequence data presently being generated and released. A neural network model of the structural and compositional properties of a eukaryotic core promoter region has been developed and its application for analysis of the Drosophila melanogaster genome is presented. The model uses a time-delay architecture, a special case of a feed-forward neural network. The structure of this model allows for variable spacing between functional binding sites, which is known to play a key role in the transcription initiation process. Application of this model to a test set of core promoters not only gave better discrimination of potential promoter sites than previous statistical or neural network models, but also revealed indirectly subtle properties of the transcription initiation signal. When tested in the Adh region of 2.9 Mbases of the Drosophila genome, the neural network for promoter prediction (NNPP) program that incorporates the time-delay neural network model gives a recognition rate of 75% (69/92) with a false positive rate of 1/547 bases. The present work can be regarded as one of the first intensive studies that applies novel gene regulation technologies to the identification of the complex gene regulation sites in the genome of Drosophila melanogaster.
BACKGROUND: Chemokines and their receptors play important roles in host defense, organogenesis, hematopoiesis, and neuronal communication. Forty-two chemokines and 19 cognate receptors have been found in the human genome. Prior to this report, only 11 chicken chemokines and 7 receptors had been reported. The objectives of this study were to systematically identify chicken chemokines and their cognate receptor genes in the chicken genome and to annotate these genes and ligand-receptor binding by a comparative genomics approach. RESULTS: Twenty-three chemokine and 14 chemokine receptor genes were identified in the chicken genome. All of the chicken chemokines contained a conserved CC, CXC, CX3C, or XC motif, whereas all the chemokine receptors had seven conserved transmembrane helices, four extracellular domains with a conserved cysteine, and a conserved DRYLAIV sequence in the second intracellular domain. The number of coding exons in these genes and the syntenies are highly conserved between human, mouse, and chicken although the amino acid sequence homologies are generally low between mammalian and chicken chemokines. Chicken genes were named with the systematic nomenclature used in humans and mice based on phylogeny, synteny, and sequence homology. CONCLUSION: The independent nomenclature of chicken chemokines and chemokine receptors suggests that the chicken may have ligand-receptor pairings similar to mammals. All identified chicken chemokines and their cognate receptors were identified in the chicken genome except CCR9, whose ligand was not identified in this study. The organization of these genes suggests that there were a substantial number of these genes present before divergence between aves and mammals and more gene duplications of CC, CXC, CCR, and CXCR subfamilies in mammals than in aves after the divergence.