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PubMed2005

Gene identification signature (GIS) analysis for transcriptome characterization and genome annotation.

We have developed a DNA tag sequencing and mapping strategy called gene identification signature (GIS) analysis, in which 5' and 3' signatures of full-length cDNAs are accurately extracted into paired-end ditags (PETs) that are concatenated for efficient sequencing and mapped to genome sequences to demarcate the transcription boundaries of every gene. GIS analysis is potentially 30-fold more efficient than standard cDNA sequencing approaches for transcriptome characterization. We demonstrated this approach with 116,252 PET sequences derived from mouse embryonic stem cells. Initial analysis of this dataset identified hundreds of previously uncharacterized transcripts, including alternative transcripts of known genes. We also uncovered several intergenically spliced and unusual fusion transcripts, one of which was confirmed as a trans-splicing event and was differentially expressed. The concept of paired-end ditagging described here for transcriptome analysis can also be applied to whole-genome analysis of cis-regulatory and other DNA elements and represents an important technological advance for genome annotation.

5' Flanking Region↗
PubMed2006

Saccharomyces cerevisiae S288C genome annotation: a working hypothesis.

The S. cerevisiae genome is the most well-characterized eukaryotic genome and one of the simplest in terms of identifying open reading frames (ORFs), yet its primary annotation has been updated continually in the decade since its initial release in 1996 (Goffeau et al., 1996). The Saccharomyces Genome Database (SGD; www.yeastgenome.org) (Hirschman et al., 2006), the community-designated repository for this reference genome, strives to ensure that the S. cerevisiae annotation is as accurate and useful as possible. At SGD, the S. cerevisiae genome sequence and annotation are treated as a working hypothesis, which must be repeatedly tested and refined. In this paper, in celebration of the tenth anniversary of the completion of the S. cerevisiae genome sequence, we discuss the ways in which the S. cerevisiae sequence and annotation have changed, consider the multiple sources of experimental and comparative data on which these changes are based, and describe our methods for evaluating, incorporating and documenting these new data.

Base Sequence↗
PubMed2005

Functional genome annotation through phylogenomic mapping.

Accurate determination of functional interactions among proteins at the genome level remains a challenge for genomic research. Here we introduce a genome-scale approach to functional protein annotation--phylogenomic mapping--that requires only sequence data, can be applied equally well to both finished and unfinished genomes, and can be extended beyond single genomes to annotate multiple genomes simultaneously. We have developed and applied it to more than 200 sequenced bacterial genomes. Proteins with similar evolutionary histories were grouped together, placed on a three dimensional map and visualized as a topographical landscape. The resulting phylogenomic maps display thousands of proteins clustered in mountains on the basis of coinheritance, a strong indicator of shared function. In addition to systematic computational validation, we have experimentally confirmed the ability of phylogenomic maps to predict both mutant phenotype and gene function in the delta proteobacterium Myxococcus xanthus.

Bacterial Proteins↗
PubMed2002

Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER.

We compare the annotation of three complete genomes using the ab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.

Algorithms↗
PubMed2002

Narrowing and genomic annotation of the commonly deleted region of the 5q- syndrome.

The 5q- syndrome is the most distinct of the myelodysplastic syndromes, and the molecular basis for this disorder remains unknown. We describe the narrowing of the common deleted region (CDR) of the 5q- syndrome to the approximately 1.5-megabases interval at 5q32 flanked by D5S413 and the GLRA1 gene. The Ensembl gene prediction program has been used for the complete genomic annotation of the CDR. The CDR is gene rich and contains 24 known genes and 16 novel (predicted) genes. Of 40 genes in the CDR, 33 are expressed in CD34(+) cells and, therefore, represent candidate genes since they are expressed within the hematopoietic stem/progenitor cell compartment. A number of the genes assigned to the CDR represent good candidates for the 5q- syndrome, including MEGF1, G3BP, and several of the novel gene predictions. These data now afford a comprehensive mutational/expression analysis of all candidate genes assigned to the CDR.

Antigens, CD34↗
PubMedDate not supplied

Genomic annotation and transcriptome analysis of the zebrafish (Danio rerio) hox complex with description of a novel member, hox b 13a.

The zebrafish (Danio rerio) is an important model in evolutionary developmental biology, and its study is being revolutionized by the zebrafish genome project. Sequencing is at an advanced stage, but annotation is largely the result of in silico analyses. We have performed genomic annotation, comparative genomics, and transcriptional analysis using microarrays of the hox homeobox-containing transcription factors. These genes have important roles in specifying the body plan. Candidate sequences were located in version Z v 4 of the Ensembl genome database by TBLASTN searching with Danio and other vertebrate published Hox protein sequences. Homologies were confirmed by alignment with reference sequences, and by the relative position of genes along each cluster. RT-PCR using adult Tübingen cDNA was used to confirm annotations, to check the genomic sequence and to confirm expression in vivo. Our RT-PCR and microarray data show that all 49 hox genes are expressed in adult zebrafish. Significant expression for all known hox genes could be detected in our microarray analysis. We also find significant expression of hox 8 paralogs and hox b 7 a in the anti-sense direction. A novel gene, D. rerio hox b 13 a, was identified, and a preliminary characterization by in situ hybridization showed expression at 24 hpf at the tip of the developing tail. We are currently characterizing this gene at the functional level. We argue that the oligo design for microarrays can be greatly enhanced by the availability of genomic sequences.

Animals↗
PubMed2003

MUTAGEN: multi-user tool for annotating genomes.

SUMMARY: MUTAGEN is a free prokaryotic annotation system. It offers the advantages of genome comparison, graphical sequence browsers, search facilities and open-source for user-specific adjustments. The web-interface allows several users to access the system from standard desktop computers. The Sulfolobus acidocaldarius genome, and several plasmids and viruses have so far been analysed and annotated using MUTAGEN. AVAILABILITY: MUTAGEN is released as open-source software under GPL. The code is available for download and/or contribution at http://dac.molbio.ku.dk/bioinformatics/MUTAGEN/

Database Management Systems↗
PubMed2006

Genome annotating proteomics pipelines: available tools.

Proteomics based on tandem mass spectrometry is a powerful tool for identifying novel biomarkers and drug targets. Previously, a major bottleneck in high-throughput proteomics has been that the computational techniques needed to reliably identify proteins from proteomic data lagged behind the ability to collect the immense quantity of data generated. This is no longer the case, as fully automated pipelines for peptide and protein identification exist, and these are publicly and privately accessible. Such pipelines can automatically and rapidly generate high-confidence protein identifications from large datasets in a searchable format covering multiple experimental runs. However, the main challenge for the community now is to use these resources as they are, by taking full advantage of the pooling of information, so that the next barrier in our understanding of biology may be broken. There are currently two pipelines in the public domain that provide such potential: PeptideAtlas and the Genome Annotating Proteomic Pipeline. This review will introduce their features in the context of high-throughput proteomics, and provide indicative results as to their usefulness and usability through a side-by-side comparison of results obtained when processing a set of human plasma samples.

Animals↗
PubMed2005

Dragon Plant Biology Explorer. A text-mining tool for integrating associations between genetic and biochemical entities with genome annotation and biochemical terms lists.

We introduce a tool for text mining, Dragon Plant Biology Explorer (DPBE) that integrates information on Arabidopsis (Arabidopsis thaliana) genes with their functions, based on gene ontologies and biochemical entity vocabularies, and presents the associations as interactive networks. The associations are based on (1) user-provided PubMed abstracts; (2) a list of Arabidopsis genes compiled by The Arabidopsis Information Resource; (3) user-defined combinations of four vocabulary lists based on the ones developed by the general, plant, and Arabidopsis GO consortia; and (4) three lists developed here based on metabolic pathways, enzymes, and metabolites derived from AraCyc, BRENDA, and other metabolism databases. We demonstrate how various combinations can be applied to fields of (1) gene function and gene interaction analyses, (2) plant development, (3) biochemistry and metabolism, and (4) pharmacology of bioactive compounds. Furthermore, we show the suitability of DPBE for systems approaches by integration with "omics" platform outputs. Using a list of abiotic stress-related genes identified by microarray experiments, we show how this tool can be used to rapidly build an information base on the previously reported relationships. This tool complements the existing biological resources for systems biology by identifying potentially novel associations using text analysis between cellular entities based on genome annotation terms. Thus, it allows researchers to efficiently summarize existing information for a group of genes or pathways, so as to make better informed choices for designing validation experiments. Last, DPBE can be helpful for beginning researchers and graduate students to summarize vast information in an unfamiliar area. DPBE is freely available for academic and nonprofit users at http://research.i2r.a-star.edu.sg/DRAGON/ME2/.

Arabidopsis↗
PubMed2025

Expanding kinetoplastid genome annotation through protein structure comparison.

Kinetoplastids belong to the Discoba supergroup, an early divergent eukaryotic clade. Although the amount of genomic information on these parasites has grown substantially, assigning gene functions through traditional sequence-based homology methods remains challenging. Recently, significant advancements have been made in in-silico protein structure prediction and algorithms for rapid and precise large-scale protein structure comparisons. In this work, we developed a protein structure-based homology search pipeline (ASC, Annotation by Structural Comparisons) and applied it to transfer biological information to all kinetoplastid proteins available in TriTrypDB, the reference database for this lineage. Our pipeline enabled the assignment of structural similarity to a substantial portion of kinetoplastid proteins, improving current knowledge through annotation transfer. Additionally, we identified structural homologs for representatives of 6,700 uncharacterized proteins across 33 kinetoplastid species, proteins that could not be annotated using existing sequence-based tools and databases. As a result, this approach allowed us to infer potential biological information for a considerable number of kinetoplastid proteins. Among these, we identified structural homologs to ubiquitous eukaryotic proteins that are challenging to detect in kinetoplastid genomes through standard genome annotation pipelines. The results (KASC, Kinetoplastid Annotation by Structural Comparison) are openly accessible to the community at kasc.fcien.edu.uy through a user-friendly, gene-by-gene interface that enables visual inspection of the data.

Kinetoplastida↗
PubMed2005

Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary.

MOTIVATION: High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. RESULTS: We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.

Artificial Intelligence↗
PubMed2004

Genome annotation by high-throughput 5' RNA end determination.

Complete gene identification and annotation, including alternative transcripts, remains a challenge in understanding genome organization. Such annotation can be achieved by a combination of computational analysis and experimental confirmation. Here, we describe a high-throughput technique, trans-spliced exon coupled RNA end determination (TEC-RED), that identifies 5' ends of expressed genes in nematodes. TEC-RED can distinguish coding regions from regulatory regions and identify genes as well as their alternative transcripts that have different 5' ends. Application of TEC-RED to approximately 10% of the Caenorhabditis elegans genome yielded tags 75% of which experimentally verified predicted 5'-RNA ends and 25% of which provided previously unknown information about 5'-RNA ends, including the identification of 99 previously unknown genes and 32 previously unknown operons. This technique will be applicable in any organisms that have a trans-splicing reaction from spliced leader RNA. We also describe an efficient sequential method for concatenating short sequence tags for any serial analysis of gene expression-like techniques.

Animals↗
PubMed2005

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

BACKGROUND: A large number of animal and plant genomes have been completely sequenced over the last decade and are now publicly available. Although genomes can be rapidly sequenced, identifying protein-coding genes still remains a problematic task. Availability of protein sequence data allows direct confirmation of protein-coding genes. Mass spectrometry has recently emerged as a powerful tool for proteomic studies. Protein identification using mass spectrometry is usually carried out by searching against databases of known proteins or transcripts. This approach generally does not allow identification of proteins that have not yet been predicted or whose transcripts have not been identified. RESULTS: We searched 3,967 mass spectra from 16 LC-MS/MS runs of Anopheles gambiae salivary gland homogenates against the Anopheles gambiae genome database. This allowed us to validate 23 known transcripts and 50 novel transcripts. In addition, a novel gene was identified on the basis of peptides that matched a genomic region where no gene was known and no transcript had been predicted. The amino termini of proteins encoded by two predicted transcripts were confirmed based on N-terminally acetylated peptides sequenced by tandem mass spectrometry. Finally, six sequence polymorphisms could be annotated based on experimentally obtained peptide sequences. CONCLUSION: The peptide sequences from this study were mapped onto the genomic sequence using the distributed annotation system available at Ensembl and can be visualized in the context of all other existing annotations. The strategy described in this paper can be used to correct and confirm genome annotations and permit discovery of novel proteins in a high-throughput manner by mass spectrometry.

Animals↗
PubMed2004

Visualization of multiple genome annotations and alignments with the K-BROWSER.

We introduce a novel genome browser application, the K-BROWSER, that allows intuitive visualization of biological information across an arbitrary number of multiply aligned genomes. In particular, the K-BROWSER simultaneously displays an arbitrary number of genomes both through overlaid annotations and predictions that describe their respective characteristics, and through the multiple alignment that describes their global relationship to one another. The browsing environment has been designed to allow users seamless access to information available in every genome and, furthermore, to allow easy navigation within and between genomes. As of the date of publication, the K-BROWSER has been set up on the human, mouse, and rat genomes.

Animals↗
PubMed2004

Gene trap as a tool for genome annotation and analysis of X chromosome inactivation in human embryonic stem cells.

Human embryonic stem (ES) cells were suggested to be an important tool in transplantation medicine. However, they also play a major role in human genetics. Using the gene trap strategy, we have created a bank of clones with insertion mutations in human ES cells. These insertions occurred within known, predicted and unknown genes, and thus assist us in annotating the genes in the human genome. The insertions into the genome occurred in multiple chromosomes with a preference to larger chromosomes. Utilizing a clone where the integration occurred in the X chromosome, we have studied X-chromosome inactivation in human cells. We thus show that in undifferentiated female human ES cells both X chromosomes remain active and upon differentiation one chromosome undergoes inactivation. In the differentiated embryonic cells the inactivation is random, while in the extra-embryonic cells it is non-random. In addition, using a selection methodology, we demonstrate that in a minority of the cells partial inactivation and XIST expression occur even in the undifferentiated cells. We suggest that X chromosome inactivation during human embryogenesis, which coincides with differentiation, may be separated from the differentiation process. The genetic manipulation of human ES cells now opens new ways of analyzing chromosome status and gene expression in humans.

Animals↗
PubMed2005

ECgene: genome annotation for alternative splicing.

ECgene provides annotation for gene structure, function and expression, taking alternative splicing events into consideration. The gene-modeling algorithm combines the genome-based expressed sequence tag (EST) clustering and graph-theoretic transcript assembly procedures. The website provides several viewers and applications that have many unique features useful for the analysis of the transcript structure and gene expression. The summary viewer shows the gene summary and the essence of other annotation programs. The genome browser and the transcript viewer are available for comparing the gene structure of splice variants. Changes in the functional domains by alternative splicing can be seen at a glance in the transcript viewer. We also provide two unique ways of analyzing gene expression. The SAGE tags deduced from the assembled transcripts are used to delineate quantitative expression patterns from SAGE libraries available publically. Furthermore, the cDNA libraries of EST sequences in each cluster are used to infer qualitative expression patterns. It should be noted that the ECgene website provides annotation for the whole transcriptome, not just the alternatively spliced genes. Currently, ECgene supports the human, mouse and rat genomes. The ECgene suite of tools and programs is available at http://genome.ewha.ac.kr/ECgene/.

Algorithms↗
PubMed2004

Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

Base Sequence↗