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PubMed2003

Transcript mapping and genome annotation of ascidian mtDNA using EST data.

Mitochondrial transcripts of two ascidian species were reconstructed through sequence assembly of publicly available ESTs resembling mitochondrial DNA sequences (mt-ESTs). This strategy allowed us to analyze processing and mapping of the mitochondrial transcripts and to investigate the gene organization of a previously uncharacterized mitochondrial genome (mtDNA). This new strategy would greatly facilitate the sequencing and annotation of mtDNAs. In Ciona intestinalis, the assembled mt-ESTs covered 22 mitochondrial genes ( approximately 12,000 bp) and provided the partial sequence of the mtDNA and the prediction of its gene organization. Such sequences were confirmed by amplification and sequencing of the entire Ciona mtDNA. For Halocynthia roretzi, for which the mtDNA sequence was already available, the inferred mt transcripts allowed better definition of gene boundaries (16S rRNA, ND1, ATP6, and tRNA-Ser genes) and the identification of a new gene (an additional Phe-tRNA). In both species, polycistronic and immature transcripts, creation of stop codons by polyadenylation, tRNA signal processing, and rRNA transcript termination signals were identified, thus suggesting that the main features of mitochondrial transcripts are conserved in Chordata.

Animals↗

PubMed2026

The effect of sex and endurance exercise training on the incretin signaling pathway in 17 rat tissues.

Incretin-based pharmacotherapies, particularly glucagon-like peptide-1 (GLP-1) receptor agonists, have transformed the treatment of type 2 diabetes, with demonstrated benefits across multiple organ systems. Their success has driven the investigation of related gut-derived hormones, most prominently dual GLP-1/glucose-dependent insulinotropic polypeptide (GIP) receptor agonists, but extend to other targets with similar metabolic functions. For this class of drugs, the extent to which organ health improvements are secondary to improved systemic glycemic control versus direct tissue signaling remains unclear, partly because receptor availability across tissues is poorly annotated. We leveraged data from the Molecular Transducers of Physical Activity Consortium to annotate incretin receptor expression across 17 tissues in Fischer 344 rats and the Genotype-Tissue Expression Portal for human-level receptor expression. Furthermore, given the role of exercise in the preservation of muscle mass during weight loss, we analyzed the effects of 1, 2, 4, or 8 wk of treadmill exercise training on incretin-related signaling at the epigenetic, transcript, and protein levels. Endurance training elicited sex- and tissue-specific changes in incretin receptor expression, including downregulation of Gcgr across brown adipose, adrenal glands, and white adipose tissue (WAT). Training-induced Gipr regulation occurred in the adrenal glands, brain cortex, and hippocampus. Collectively, these findings contribute to the map of incretin receptor biology and identify exercise-responsive regulatory axes that may underlie synergistic effects of exercise and incretin-based therapies on weight management and metabolic health.NEW & NOTEWORTHY This study provides the first multiomic, multitissue description of incretin signaling receptor expression and regulation in response to endurance exercise training. We identify time point and sex-specific changes in incretin signaling across tissues, highlighting training effects on Gcgr, Gipr, and Sctr regulation in the adrenals, WAT, and brain. These findings help establish an exercise-responsive incretin signaling axis that may identify interactions from incretin-based therapies and exercise-based lifestyle interventions.

Animals↗

PubMed2004

Biosphere: the interoperation of web services in microarray cluster analysis.

UNLABELLED: The growing use of DNA microarrays in biomedical research has led to the proliferation of analysis tools. These software programs address different aspects of analysis (e.g. normalisation and clustering within and across individual arrays) as well as extended analysis methods (e.g. clustering, annotation and mining of multiple datasets). Therefore, microarray data analysis typically requires the interoperability of multiple software programs involving different analysis types and methods. Such interoperation is often hampered by the heterogeneity inherent in the software tools (which may function by implementing different interfaces and using different programming languages). To address this problem, we employed the simple object access protocol (SOAP)-based web service approach that provides a uniform programmatic interface to these heterogeneous software components. To demonstrate this approach in the microarray context, we created a web server application, Biosphere, which interoperates a number of web services that are geographically widely distributed. These web services include a clustering web service, which is a suite of different clustering algorithms for analysing microarray data; XEMBL, developed at the European Bioinformatics Institute (EBI) for retrieving EMBL Nucleotide Sequence Database sequence data; and three gene annotation web services: GetGO, GetHAPI and GetUMLS. GetGO allows retrieval of Gene Ontology (GO) annotation, and the other two web services retrieve annotation from the biomedical literature that is indexed based on the Medical Subject Headings (MeSH) terms. With these web services, Biosphere allows the users to do the following: (i) cluster gene expression data using seven different algorithms; (ii) visualise the clustering results that are grouped statistically in colour; and (iii) retrieve sequence, annotation and citation data for the genes of interest. AVAILABILITY: Biosphere and its web services described in Web Service Description Language (WSDL) can be accessed at http://rook.cecid.hku.hk:8280/BiosphereServer.

Cluster Analysis↗

PubMed2005

Refined repetitive sequence searches utilizing a fast hash function and cross species information retrievals.

BACKGROUND: Searching for small tandem/disperse repetitive DNA sequences streamlines many biomedical research processes. For instance, whole genomic array analysis in yeast has revealed 22 PHO-regulated genes. The promoter regions of all but one of them contain at least one of the two core Pho4p binding sites, CACGTG and CACGTT. In humans, microsatellites play a role in a number of rare neurodegenerative diseases such as spinocerebellar ataxia type 1 (SCA1). SCA1 is a hereditary neurodegenerative disease caused by an expanded CAG repeat in the coding sequence of the gene. In bacterial pathogens, microsatellites are proposed to regulate expression of some virulence factors. For example, bacteria commonly generate intra-strain diversity through phase variation which is strongly associated with virulence determinants. A recent analysis of the complete sequences of the Helicobacter pylori strains 26695 and J99 has identified 46 putative phase-variable genes among the two genomes through their association with homopolymeric tracts and dinucleotide repeats. Life scientists are increasingly interested in studying the function of small sequences of DNA. However, current search algorithms often generate thousands of matches -- most of which are irrelevant to the researcher. RESULTS: We present our hash function as well as our search algorithm to locate small sequences of DNA within multiple genomes. Our system applies information retrieval algorithms to discover knowledge of cross-species conservation of repeat sequences. We discuss our incorporation of the Gene Ontology (GO) database into these algorithms. We conduct an exhaustive time analysis of our system for various repetitive sequence lengths. For instance, a search for eight bases of sequence within 3.224 GBases on 49 different chromosomes takes 1.147 seconds on average. To illustrate the relevance of the search results, we conduct a search with and without added annotation terms for the yeast Pho4p binding sites, CACGTG and CACGTT. Also, a cross-species search is presented to illustrate how potential hidden correlations in genomic data can be quickly discerned. The findings in one species are used as a catalyst to discover something new in another species. These experiments also demonstrate that our system performs well while searching multiple genomes -- without the main memory constraints present in other systems. CONCLUSION: We present a time-efficient algorithm to locate small segments of DNA and concurrently to search the annotation data accompanying the sequence. Genome-wide searches for short sequences often return hundreds of hits. Our experiments show that subsequently searching the annotation data can refine and focus the results for the user. Our algorithms are also space-efficient in terms of main memory requirements. Source code is available upon request.

Algorithms↗

PubMed2025

Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.

Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations. We investigated the potential of increasing prediction ability by combining genomic and transcriptomic datasets, adding whole-genome sequencing (WGS) SNP data, functional annotation-based filtering, and empirical quality filtering. Our RNA-Seq data were generated cost-efficiently using small-footprint plant cultivation, high-throughput RNA extraction, and Library preparation miniaturization. We also examined sequencing depth reduction as an additional cost-saving measure. We used fivefold cross-validation to evaluate the prediction ability of the gene expression dataset, the RNA-Seq SNP dataset, and the consensus SNP dataset between the RNA-Seq and parental WGS data, resulting in prediction abilities between 0.73 and 0.78. The consensus SNP dataset performed best, with five out of eight traits performing significantly better compared to a 50K SNP array, which served as a benchmark. The advantage of the consensus SNP dataset was most prominent in the inter-population predictions, in which the training and validation sets originated from different RIL sub-populations. We were therefore able to not only show that RNA-Seq data alone are able to predict various complex traits in barley using RILs, but also that the performance can be further increased with WGS data for which the public availability will steadily increase.

Hordeum↗

PubMed2005

A comprehensive update of the sequence and structure classification of kinases.

BACKGROUND: A comprehensive update of the classification of all available kinases was carried out. This survey presents a complete global picture of this large functional class of proteins and confirms the soundness of our initial kinase classification scheme. RESULTS: The new survey found the total number of kinase sequences in the protein database has increased more than three-fold (from 17,310 to 59,402), and the number of determined kinase structures increased two-fold (from 359 to 702) in the past three years. However, the framework of the original two-tier classification scheme (in families and fold groups) remains sufficient to describe all available kinases. Overall, the kinase sequences were classified into 25 families of homologous proteins, wherein 22 families (approximately 98.8% of all sequences) for which three-dimensional structures are known fall into 10 fold groups. These fold groups not only include some of the most widely spread proteins folds, such as the Rossmann-like fold, ferredoxin-like fold, TIM-barrel fold, and antiparallel beta-barrel fold, but also all major classes (all alpha, all beta, alpha+beta, alpha/beta) of protein structures. Fold predictions are made for remaining kinase families without a close homolog with solved structure. We also highlight two novel kinase structural folds, riboflavin kinase and dihydroxyacetone kinase, which have recently been characterized. Two protein families previously annotated as kinases are removed from the classification based on new experimental data. CONCLUSION: Structural annotations of all kinase families are now revealed, including fold descriptions for all globular kinases, making this the first large functional class of proteins with a comprehensive structural annotation. Potential uses for this classification include deduction of protein function, structural fold, or enzymatic mechanism of poorly studied or newly discovered kinases based on proteins in the same family.

Algorithms↗

PubMed2006

GeneTools--application for functional annotation and statistical hypothesis testing.

BACKGROUND: Modern biology has shifted from "one gene" approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in "batch" mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for "integrated" solutions. RESULTS: GeneTools is a web-service providing access to a database that brings together information from a broad range of resources. The annotation data are updated weekly, guaranteeing that users get data most recently available. Data submitted by the user are stored in the database, where it can easily be updated, shared between users and exported in various formats. GeneTools provides three different tools: i) NMC Annotation Tool, which offers annotations from several databases like UniGene, Entrez Gene, SwissProt and GeneOntology, in both single- and batch search mode. ii) GO Annotator Tool, where users can add new gene ontology (GO) annotations to genes of interest. These user defined GO annotations can be used in further analysis or exported for public distribution. iii) eGOn, a tool for visualization and statistical hypothesis testing of GO category representation. As the first GO tool, eGOn supports hypothesis testing for three different situations (master-target situation, mutually exclusive target-target situation and intersecting target-target situation). An important additional function is an evidence-code filter that allows users, to select the GO annotations for the analysis. CONCLUSION: GeneTools is the first "all in one" annotation tool, providing users with a rapid extraction of highly relevant gene annotation data for e.g. thousands of genes or clones at once. It allows a user to define and archive new GO annotations and it supports hypothesis testing related to GO category representations. GeneTools is freely available through www.genetools.no

Algorithms↗

PubMed2003

An exhaustive DNA micro-satellite map of the human genome using high performance computing.

The current pace of the generation of sequence data requires the development of software tools that can rapidly provide full annotation of the data. We have developed a new method for rapid sequence comparison using the exact match algorithm without repeat masking. As a demonstration, we have identified all perfect simple tandem repeats (STR) within the draft sequence of the human genome. The STR elements (chromosome, position, length and repeat subunit) have been placed into a relational database. Repeat flanking sequence is also publicly accessible at http://grid.abcc.ncifcrf.gov. To illustrate the utility of this complete set of STR elements, we documented the increased density of potentially polymorphic markers throughout the genome. The new STR markers may be useful in disease association studies because so many STR elements manifest multiallelic polymorphism. Also, because triplet repeat expansions are important for human disease etiology, we identified trinucleotide repeats that exist within exons of known genes. This resulted in a list that includes all 14 genes known to undergo polynucleotide expansion, and 48 additional candidates. Several of these are non-polyglutamine triplet repeats. Other examinations of the STR database demonstrated repeats spanning splice junctions and identified SNPs within repeat elements.

Alleles↗

PubMed2006

Creation and implications of a phenome-genome network.

Although gene and protein measurements are increasing in quantity and comprehensiveness, they do not characterize a sample's entire phenotype in an environmental or experimental context. Here we comprehensively consider associations between components of phenotype, genotype and environment to identify genes that may govern phenotype and responses to the environment. Context from the annotations of gene expression data sets in the Gene Expression Omnibus is represented using the Unified Medical Language System, a compendium of biomedical vocabularies with nearly 1-million concepts. After showing how data sets can be clustered by annotative concepts, we find a network of relations between phenotypic, disease, environmental and experimental contexts as well as genes with differential expression associated with these concepts. We identify novel genes related to concepts such as aging. Comprehensively identifying genes related to phenotype and environment is a step toward the Human Phenome Project.

Aging↗

PubMed2004

The otter annotation system.

With the completion of the human genome sequence and genome sequence available for other vertebrate genomes, the task of manual annotation at the large genome scale has become a priority. Possibly even more important, is the requirement to curate and improve this annotation in the light of future data. For this to be possible, there is a need for tools to access and manage the annotation. Ensembl provides an excellent means for storing gene structures, genome features, and sequence, but it does not support the extra textual data necessary for manual annotation. We have extended Ensembl to create the Otter manual annotation system. This comprises a relational database schema for storing the manual annotation data, an application-programming interface (API) to access it, an extensible markup language (XML) format to allow transfer of the data, and a server to allow multiuser/multimachine access to the data. We have also written a data-adaptor plugin for the Apollo Browser/Editor to enable it to utilize an Otter server. The otter database is currently used by the Vertebrate Genome Annotation (VEGA) site (http://vega.sanger.ac.uk), which provides access to manually curated human chromosomes. Support is also being developed for using the AceDB annotation editor, FMap, via a perl wrapper called Lace. The Human and Vertebrate Annotation (HAVANA) group annotators at the Sanger center are using this to annotate human chromosomes 1 and 20.

Computational Biology↗

PubMed2026

Genome-wide detection of human 5' UTR variants that impact protein translation.

The 5' untranslated region (5' UTR) of messenger RNAs (mRNAs) plays a central role in regulating protein synthesis initiation, particularly through the Kozak sequence and upstream open reading frames (uORFs). Genetic variants within these regulatory elements could affect translation, altering gene expression and contributing to clinical phenotypes in humans. We developed a computational method called 5ULTRA (5' Untranslated Region Annotation) for analysis of whole-exome sequencing and whole-genome sequencing data to detect, annotate, and prioritize 5' UTR variants with potential translation impact. 5ULTRA identifies single-nucleotide variants, indels, and splicing variants that affect uORFs by creating or disrupting start/stop codons and that alter Kozak sequence strength of either the uORFs or the main coding sequence. 5ULTRA incorporates recent uORF databases and provides comprehensive annotations. 5ULTRA implements a machine-learning score to prioritize candidate variants with predicted effects on translation and also provides specific mechanistic predictions. The score correlates strongly with experimentally measured protein-level effects of 5' UTR variants. We applied 5ULTRA to multiple genetics datasets across diverse disease contexts, identifying candidate variants including potential cancer-driving somatic mutations predicted to decrease ABI1 level or increase NRAS abundance; common variants associated with traits such as multiple sclerosis, lung function, and cardiovascular function, by altering protein levels of TAGAP, VRTN, and SPAAR, respectively; and rare germline variants in our cohort, including a splicing variant of RPSA leading to 5' UTR sequence alteration that causes congenital asplenia and a variant of TNF that could predispose to tuberculosis.

Humans↗

PubMed2003

Computational methods and evaluation of RNA stabilization reagents for genome-wide expression studies.

Gene expression studies require high quality messenger RNA (mRNA) in addition to other factors such as efficient primers and labeling reagents. To prevent RNA degradation and to improve the quality of gene array expression data, several commercial reagents have become available. We examined a conventional hot-phenol lysis method and RNA stabilization reagents, and generated comparative gene expression profiles from Escherichia coli cells grown on minimal medium. Our data indicate that certain RNA stabilization reagents induce stress responses and proper caution must be exercised during their use. We observed that the laboratory reagent (phenol/EtOH, 5:95, v/v) worked efficiently in isolating high quality mRNA and reproducibility was such that reliable gene expression profiles were generated. To assist in the analysis of gene expression data, we wrote a number of macros that use the most recent gene annotation and process data in accordance with gene function. Scripts were also written to examine the occurrence of artifacts, based on GC content, length of the individual open reading frame (ORF), its distribution on plus and minus DNA strands, and the distance from the replication origin.

Base Composition↗

PubMed2006

DDBJ working on evaluation and classification of bacterial genes in INSDC.

DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) newly collected and released 12,927,184 entries or 13,787,688,598 bases in the period from July 2005 to June 2006. The released data contain honeybee expressed sequence tags (ESTs), re-examined and re-annotated complete genome data of Escherichia coli K-12 W3110, medaka WGS and human MGA. We also systematically evaluated and classified the genes in the complete bacterial genomes submitted to the International Nucleotide Sequence Database Collaboration (INSDC, http://insdc.org) that is composed of DDBJ, EMBL Bank and GenBank. The examination and classification selected 557,000 genes as reliable ones among all the bacterial genes predicted by us.

Animals↗

PubMed2001

DIAN: a novel algorithm for genome ontological classification.

Faced with the determination of many completely sequenced genomes, computational biology is now faced with the challenge of interpreting the significance of these data sets. A multiplicity of data-related problems impedes this goal: Biological annotations associated with raw data are often not normalized, and the data themselves are often poorly interrelated and their interpretation unclear. All of these problems make interpretation of genomic databases increasingly difficult. With the current explosion of sequences now available from the human genome as well as from model organisms, the importance of sorting this vast amount of conceptually unstructured source data into a limited universe of genes, proteins, functions, structures, and pathways has become a bottleneck for the field. To address this problem, we have developed a method of interrelating data sources by applying a novel method of associating biological objects to ontologies. We have developed an intelligent knowledge-based algorithm, to support biological knowledge mapping, and, in particular, to facilitate the interpretation of genomic data. In this respect, the method makes it possible to inventory genomes by collapsing multiple types of annotations and normalizing them to various ontologies. By relying on a conceptual view of the genome, researchers can now easily navigate the human genome in a biologically intuitive, scientifically accurate manner.

Algorithms↗

PubMed2002

The Protein Information Resource: an integrated public resource of functional annotation of proteins.

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).

Amino Acid Sequence↗

PubMed2005

Automating genomic data mining via a sequence-based matrix format and associative rule set.

There is an enormous amount of information encoded in each genome--enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands.

Base Sequence↗

PubMed2006

MIAME/Plant - adding value to plant microarrray experiments.

Appropriate biological interpretation of microarray data calls for relevant experimental annotation. The widely accepted MIAME guidelines provide a generic, organism-independant standard for minimal information about microarray experiments. In its overall structure, MIAME is very general and specifications cover mostly technical aspects, while relevant organism-specific information useful to understand the underlying experiments is largely missing. If plant biologists want to use results from published microarray experiments, they need detailed information about biological aspects, such as growth conditions, harvesting time or harvested organ(s). Here, we propose MIAME/Plant, a standard describing which biological details to be captured for describing microarray experiments involving plants. We expect that a more detailed and more systematic annotation of microarray experiments will greatly increase the use of transcriptome data sets for the scientific community. The power and value of systematic annotation of microarray data is convincingly demonstrated by data warehouses such as Genevestigator(R) or NASCArrays, and better experimental annotation will make these applications even more powerful.

Editorial↗

PubMed2007

DroSpeGe: rapid access database for new Drosophila species genomes.

The Drosophila species comparative genome database DroSpeGe (http://insects.eugenes.org/DroSpeGe/) provides genome researchers with rapid, usable access to 12 new and old Drosophila genomes, since its inception in 2004. Scientists can use, with minimal computing expertise, the wealth of new genome information for developing new insights into insect evolution. New genome assemblies provided by several sequencing centers have been annotated with known model organism gene homologies and gene predictions to provided basic comparative data. TeraGrid supplies the shared cyberinfrastructure for the primary computations. This genome database includes homologies to Drosophila melanogaster and eight other eukaryote model genomes, and gene predictions from several groups. BLAST searches of the newest assemblies are integrated with genome maps. GBrowse maps provide detailed views of cross-species aligned genomes. BioMart provides for data mining of annotations and sequences. Common chromosome maps identify major synteny among species. Potential gain and loss of genes is suggested by Gene Ontology groupings for genes of the new species. Summaries of essential genome statistics include sizes, genes found and predicted, homology among genomes, phylogenetic trees of species and comparisons of several gene predictions for sensitivity and specificity in finding new and known genes.

Animals↗