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Results for “Gene functional annotation”

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At least 73 records · Page 4Linked to original sources
PubMed2003

Identification of temporal patterns of gene expression in the uteri of immature, ovariectomized mice following exposure to ethynylestradiol.

Estrogen induction of uterine wet weight provides an excellent model to investigate relationships between changes in global gene expression and well-characterized physiological responses. In this study, time course microarray GeneChip data were analyzed using a novel approach to identify temporal changes in uterine gene expression following treatment of immature ovariectomized C57BL/6 mice with 0.1 mg/kg 17alpha-ethynylestradiol. Functional gene annotation information from public databases facilitated the association of changes in gene expression with physiological outcomes, which allowed detailed mechanistic inferences to be drawn regarding cell cycle control and proliferation, transcription and translation, structural tissue remodeling, and immunologic responses. These systematic approaches confirm previously established responses, identify novel estrogen-regulated transcriptional effects, and disclose the coordinated activation of multiple modes of action that support the uterotrophic response elicited by estrogen. In particular, it was possible to elucidate the physiological significance of the dramatic induction of arginase, a classic estrogenic response, by elucidating its mechanistic relevance and delineating the role of arginine and ornithine utilization in the estrogen-stimulated induction of uterine wet weight.

Animals↗
PubMed2004

A fast algorithm for determining the best combination of local alignments to a query sequence.

BACKGROUND: Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or amino acids are in the same order in both sequences. Recombination perturbs this order. An algorithm that can reconstruct sequence similarity despite rearrangement would be helpful for reconstructing the evolutionary history of recombined sequences. RESULTS: We propose a graph-based algorithm for combining multiple local alignments to a query sequence into the single combination of alignments that either covers the maximal portion of the query or results in the single highest alignment score to the query. This algorithm can help study the process of genome rearrangement, improve functional gene annotation, and reconstruct the evolutionary history of recombined proteins. The algorithm takes O(n2) time, where n is the number of local alignments considered. CONCLUSIONS: We discuss two example applications of the algorithm. The algorithm is able to provide useful reconstructions of the metazoan mitochondrial genome. It is also able to increase the percentage of a query sequence's amino acid residues for which similar stretches of amino acids can be found in sequence databases.

Algorithms↗
PubMed2005

stam--a Bioconductor compliant R package for structured analysis of microarray data.

BACKGROUND: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles. The definition of novel subclasses based on gene expression is a difficult problem not addressed systematically by currently available software tools. RESULTS: We present a computational tool for semi-supervised molecular disease entity detection. It automatically discovers molecular heterogeneities in phenotypically defined disease entities and suggests alternative molecular sub-entities of clinical phenotypes. This is done using both gene expression data and functional gene annotations. We provide stam, a Bioconductor compliant software package for the statistical programming environment R. We demonstrate that our tool detects gene expression patterns, which are characteristic for only a subset of patients from an established disease entity. We call such expression patterns molecular symptoms. Furthermore, stam finds novel sub-group stratifications of patients according to the absence or presence of molecular symptoms. CONCLUSION: Our software is easy to install and can be applied to a wide range of datasets. It provides the potential to reveal so far indistinguishable patient sub-groups of clinical relevance.

Calibration↗
PubMed2006

In vivo-in vitro toxicogenomic comparison of TCDD-elicited gene expression in Hepa1c1c7 mouse hepatoma cells and C57BL/6 hepatic tissue.

BACKGROUND: In vitro systems have inherent limitations in their ability to model whole organism gene responses, which must be identified and appropriately considered when developing predictive biomarkers of in vivo toxicity. Systematic comparison of in vitro and in vivo temporal gene expression profiles were conducted to assess the ability of Hepa1c1c7 mouse hepatoma cells to model hepatic responses in C57BL/6 mice following treatment with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). RESULTS: Gene expression analysis and functional gene annotation indicate that Hepa1c1c7 cells appropriately modeled the induction of xenobiotic metabolism genes in vivo. However, responses associated with cell cycle progression and proliferation were unique to Hepa1c1c7 cells, consistent with the cell cycle arrest effects of TCDD on rapidly dividing cells. In contrast, lipid metabolism and immune responses, representative of whole organism effects in vivo, were not replicated in Hepa1c1c7 cells. CONCLUSION: These results identified inherent differences in TCDD-mediated gene expression responses between these models and highlighted the limitations of in vitro systems in modeling whole organism responses, and additionally identified potential predictive biomarkers of toxicity.

Animals↗
PubMed2006

High-throughput isolation of ultra-pure plasmid DNA by a robotic system.

BACKGROUND: With the availability of complete genomes, a systematic inventory of cellular processes becomes achievable. This requires assessing the function of all individual genes. Transfection of plasmid DNA into cell culture cells is an essential technique for this aim as it allows functional overexpression or downregulation of genes. While many robotic systems isolate plasmids for sequencing purposes, for more demanding applications such as transfections there is a shortage of robots for the high-throughput isolation of plasmid DNA. RESULTS: Here we describe a custom-made, automated device, which uses a special protocol to isolate plasmid DNAs with a purity sufficient for efficient transfections into mammalian cells. Approximately 1,600 ultra pure plasmids can be isolated in a 96-well plate format within 12 hours. As a unique feature the robot comprises the integration of a centrifuge instead of expensive columns, the use of a custom-made pipetting head with a movable gripper, especially designed shaking platforms and an acetone wash facility. CONCLUSION: Using this robot we demonstrate how centrifugation steps with multiple precipitations, most notably through a precipitation step of SDS in isopropanol, lead to high purity plasmid DNA and make possible high-throughput transfections into mammalian cells for functional gene annotations.

Chemical Fractionation↗
PubMed2004

Cross-species comparison of genome-wide expression patterns.

The rapid accumulation of microarray data from multiple species provides unprecedented opportunities to study the evolution of biological systems. Recent studies have used cross-species comparisons of expression profiles to annotate gene functions, to draw evolutionary inferences concerning specific biological processes and to study the global properties of expression networks.

Animals↗
PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗
PubMed2006

Isoflurane modulates genomic expression in rat amygdala.

General anesthesia, at a minimum, provides amnesia and unresponsiveness. Although anesthetics have many modulatory effects on neuronal ionophore protein complexes, it is not clear that the resulting electrophysiologic changes are the sole mechanisms of clinical anesthetic action. Cells respond to environmental changes in several ways, including alterations in DNA transcription leading to changes in the cell's proteins. We sought to expose the changes in global genomic expression, seeking potential targets involved in the processes of anesthetic-induced amnesia, and persistent long-term side effects of general anesthesia, including nausea and postoperative cognitive decline. Using Affymetrix GeneChips, we surveyed changes in expression across the entire expressed genome of Sprague-Dawley rat (n = 10 baseline, n = 6 isoflurane) basolateral amygdala 6 h after exposure to 15 min of 2% (1.4 MAC) isoflurane. Isoflurane administration was associated with altered expression in 269 unique genes possessing functional annotation. Affected genes were related to DNA transcription, protein synthesis, metabolism, signaling cascades, cytoskeletal structural proteins, and neural-specific proteins, among others. Even brief exposure to isoflurane leads to widespread changes in the genetic control in the amygdala 6 h after exposure. Gene expression is a dynamic process that may explain some long-term effects of anesthesia and that has the potential to modulate some of those effects using specific molecular therapeutics.

Amygdala↗
PubMed2003

Similarities and differences in genome-wide expression data of six organisms.

Comparing genomic properties of different organisms is of fundamental importance in the study of biological and evolutionary principles. Although differences among organisms are often attributed to differential gene expression, genome-wide comparative analysis thus far has been based primarily on genomic sequence information. We present a comparative study of large datasets of expression profiles from six evolutionarily distant organisms: S. cerevisiae, C. elegans, E. coli, A. thaliana, D. melanogaster, and H. sapiens. We use genomic sequence information to connect these data and compare global and modular properties of the transcription programs. Linking genes whose expression profiles are similar, we find that for all organisms the connectivity distribution follows a power-law, highly connected genes tend to be essential and conserved, and the expression program is highly modular. We reveal the modular structure by decomposing each set of expression data into coexpressed modules. Functionally related sets of genes are frequently coexpressed in multiple organisms. Yet their relative importance to the transcription program and their regulatory relationships vary among organisms. Our results demonstrate the potential of combining sequence and expression data for improving functional gene annotation and expanding our understanding of how gene expression and diversity evolved.

Animals↗
PubMed2005

Co-evolution analysis on endocrine research: a methodological approach.

The rapid growth of different kinds of biological information allows a good opportunity to analyze the co-evolutionary characteristics in endocrine regulatory pathways. Data ranging from kinds of species' genome, gene sequence, protein structure, and expression profile of different organisms can reveal the inner co-evolutionary relationship of ligands, receptors, and other related molecules. In return, these co-evolutionary characteristics can help us determine uncharacterized ligands and receptors, annotate gene functions, highlight amino acid residues with biochemical significance, and identify regulated genes in the endocrine process. Encouraging examples in this field, although at their starting stage, have emerged. Here we focus on recent progress in endocrine-related co-evolution research from a methodological approach.

Endocrine System↗
PubMed2005

Phydbac "Gene Function Predictor": a gene annotation tool based on genomic context analysis.

BACKGROUND: The large amount of completely sequenced genomes allows genomic context analysis to predict reliable functional associations between prokaryotic proteins. Major methods rely on the fact that genes encoding physically interacting partners or members of shared metabolic pathways tend to be proximate on the genome, to evolve in a correlated manner and to be fused as a single sequence in another organism. RESULTS: The new "Gene Function Predictor", linked to the web server Phydbac proposes putative associations between Escherichia coli K-12 proteins derived from a combination of these methods. We show that associations made by this tool are more accurate than linkages found in the other established databases. Predicted assignments to GO categories, based on pre-existing functional annotations of associated proteins are also available. This new database currently holds 9,379 pairwise links at an expected success rate of at least 80%, the 6,466 functional predictions to GO terms derived from these links having a level of accuracy higher than 70%. CONCLUSION: The "Gene Function Predictor" is an automatic tool that aims to help biologists by providing them hypothetical functional predictions out of genomic context characteristics. The "Gene Function predictor" is available at http://www.igs.cnrs-mrs.fr/phydbac/indexPS.html.

Algorithms↗
PubMed2004

GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes.

BACKGROUND: The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for predicting gene product function by annotation with Gene Ontology (GO) terms. GOtcha predicts GO term associations with term-specific probability (P-score) measures of confidence. Term-specific probabilities are a novel feature of GOtcha and allow the identification of conflicts or uncertainty in annotation. RESULTS: The GOtcha method was applied to the recently sequenced genome for Plasmodium falciparum and six other genomes. GOtcha was compared quantitatively for retrieval of assigned GO terms against direct transitive assignment from the highest scoring annotated BLAST search hit (TOPBLAST). GOtcha exploits information deep into the 'twilight zone' of similarity search matches, making use of much information that is otherwise discarded by more simplistic approaches. At a P-score cutoff of 50%, GOtcha provided 60% better recovery of annotation terms and 20% higher selectivity than annotation with TOPBLAST at an E-value cutoff of 10(-4). CONCLUSIONS: The GOtcha method is a useful tool for genome annotators. It has identified both errors and omissions in the original Plasmodium falciparum annotation and is being adopted by many other genome sequencing projects.

Animals↗
PubMed2003

Predicting pathway perturbations in Down syndrome.

Comparative annotation of human chromosome 21 genomic sequence with homologous regions of mouse chromosomes 16, 17 and 10 has identified 170 orthologous gene pairs. Functional annotation of these genes, based on literature reports and computationally-derived predictions, shows that a broad range of cellular processes are represented. A goal of Down syndrome research is to determine which of these processes are perturbed by overexpression of chromosome 21 genes, and which may, therefore, contribute to the cognitive deficits that characterize Down syndrome. Eleven chromosome 21 genes are annotated to interact with or be affected by components of the MAP Kinase pathway and eight are involved in Ca2+/calcineurin signaling. Both pathways are critical for normal neurological function, and consequently their perturbations are proposed as candidates for phenotypic relevance. We present evidence suggesting that the MAP Kinase pathway is perturbed in the Ts65Dn mouse model of Down syndrome at 4-6 months of age. Analysis is complicated by the observation that overexpression of chromosome 21 genes in trisomy may be affected by method of detection, organism, tissue or brain region, and/or developmental age.

Animals↗
PubMed2000

High-throughput functional annotation of novel gene products using document clustering.

Gene products differentially expressed in healthy vs. diseased tissues may be considered drug targets since the change in their expression level can be related to the cause and progression of the disease studied. A significant portion of the proteins produced by these genes will be unknown and consequently their function must be characterised. The experimental elucidation of biochemical function must be supported by computational tools which can help predicting the possible function of a given protein from its amino acid sequence. We have designed a high-throughput system which automatically analyses amino acid sequences deduced from differentially represented cDNA clones. The system attempts to assign a biological function to protein sequences by carrying out searches in sequence databanks and by locating functionally relevant motifs in the query sequences. The results delivered by the various prediction methods consist of the annotations of matching sequences and/or motifs, which are free-format texts written by humans and therefore may describe the same concept with synonymous words. It is desirable to present the results in such a way that the annotations describing the same biological function are grouped together. To this end we devised an algorithm that enables the hierarchical clustering of free-format documents based on their contents. The system is capable of detecting and flagging conflicting annotations, and will speed up the interpretation of the function prediction results.

Algorithms↗
PubMed2026

Unravelling the genomic potential of sponge-associated Streptomyces sp. BLC 17-3 from Indonesia for mannooligosaccharide production.

This research aims to show the promising capacity of Streptomyces sp. BLC 17-3 to produce high β-mannanase enzymes and generate mannooligosaccharide (MOS) such as mannobiose, mannotriose, mannotetraose and mannopentaose when exposed to mannan polymers. Streptomyces sp. BLC 17-3 was isolated from the sponge (Rhabdastrella globostellata) Put4 obtained from the marine waters of Putus Island in Bitung, North Sulawesi, Indonesia. The characterization results showed that the peak enzyme activity was achieved at 50 mM sodium acetate, 6.0 pH, and 60 °C temperature on the seventh day of production with a value of 155.77 ± 3.21 U/mL. The SDS-PAGE and zymograms also showed that the size of the enzyme molecule was approximately ±34.8-49.1 kDa. Moreover, whole-genome sequencing was conducted to identify the genetic basis of MOS-synthesizing capabilities in the selected strain, followed by functional annotation of genes encoding mannan degradation and associated functions. The results showed an 8,248,862 Mb complete draft genome of the strain which comprised 111 predicted gene models. Gene annotation also provided important information about the location and function of protein-encoding genes. A total of 6 mannan degradation-related genes encoding mannanase-related metabolism were identified and the three-dimensional structures were predicted using AlphaFold 3. This characterization and modeling further enhanced the bioprospecting and development of this strain which exhibited efficient mannose metabolism. The results showed Streptomyces sp. BLC 17-3 as a promising microorganism for the future bioproduction of MOS which were discovered to have the capability of serving as a potential prebiotic substance to enhance digestion and promote health.

Bioprospecting↗
PubMed2004

TEAM: a tool for the integration of expression, and linkage and association maps.

The identification of genes primarily responsible for complex genetic disorders is a daunting task. Despite the assignment of many susceptibility loci, there has only been limited success in identifying disease genes based solely on positional information from genome-wide screens. The incorporation of several complementary strategies in a single integrated approach should facilitate and further enhance the efficacy of this search for genes. To permit the integration of linkage, association and expression data, together with functional annotations, we have developed a Java-based software tool: TEAM (tool for the integration of expression, and linkage and association maps). TEAM includes a genome viewer, capable of overlaying karyobands, genes, markers, linkage graphs, association data, gene expression levels and functional annotations in one composite view. Data management, analysis and filtering functionality was implemented and extended with links to the Ensembl, Unigene and Gene Ontology databases to facilitate gene annotation. Filtering functionality can help prevent the exclusion of poorly annotated, but differentially expressed, genes that reside in candidate regions that show linkage or association. Here we demonstrate the program's functionality in our study on coeliac disease (OMIM 212750), a multifactorial gluten-sensitive enteropathy. We performed a combined data analysis of a genome-wide linkage screen in 82 Dutch families with affected siblings and the microarray expression profiles of 18,110 cDNAs in 22 intestinal biopsies.

Celiac Disease↗
PubMed2026

Large-scale benchmarking of prokaryotic annotation tools across thousands of species.

BACKGROUND: Genome annotation is an important step in deriving functional meaning from prokaryotic sequencing data, yet systematic evaluations guiding tool selection are lacking. We present the first large-scale investigation of four prominent open-source annotation tools (Prokka, Bakta, EggNOG-mapper, and PGAP) across 156,033 diverse genomes. This includes Escherichia coli strains for baseline performance, thousands of archaea and bacteria genomes, as well as frameshifted and metagenome-assembled genomes. RESULTS: Bakta excels in annotating high-quality bacterial genomes, while PGAP was better for archaeal genomes and challenging bacterial assemblies, including metagenome-assembled, fragmented, or contaminated samples. For Gene Ontology annotation, PGAP consistently provides broader term coverage, whereas EggNOG-mapper offers more terms per feature. CONCLUSIONS: Our findings highlight tool-specific strengths crucial for selecting optimal solutions based on genome quality, taxonomy, and origin (e.g. MAGs). This study provides an evidence-based guide for users and informs future tool development.

Molecular Sequence Annotation↗
PubMed2005

Molecular processes during fat cell development revealed by gene expression profiling and functional annotation.

BACKGROUND: Large-scale transcription profiling of cell models and model organisms can identify novel molecular components involved in fat cell development. Detailed characterization of the sequences of identified gene products has not been done and global mechanisms have not been investigated. We evaluated the extent to which molecular processes can be revealed by expression profiling and functional annotation of genes that are differentially expressed during fat cell development. RESULTS: Mouse microarrays with more than 27,000 elements were developed, and transcriptional profiles of 3T3-L1 cells (pre-adipocyte cells) were monitored during differentiation. In total, 780 differentially expressed expressed sequence tags (ESTs) were subjected to in-depth bioinformatics analyses. The analysis of 3'-untranslated region sequences from 395 ESTs showed that 71% of the differentially expressed genes could be regulated by microRNAs. A molecular atlas of fat cell development was then constructed by de novo functional annotation on a sequence segment/domain-wise basis of 659 protein sequences, and subsequent mapping onto known pathways, possible cellular roles, and subcellular localizations. Key enzymes in 27 out of 36 investigated metabolic pathways were regulated at the transcriptional level, typically at the rate-limiting steps in these pathways. Also, coexpressed genes rarely shared consensus transcription-factor binding sites, and were typically not clustered in adjacent chromosomal regions, but were instead widely dispersed throughout the genome. CONCLUSIONS: Large-scale transcription profiling in conjunction with sophisticated bioinformatics analyses can provide not only a list of novel players in a particular setting but also a global view on biological processes and molecular networks.

3T3-L1 Cells↗