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At least 415 records · Page 23Linked to original sources

PubMed2002

Large-scale analysis of the human and mouse transcriptomes.

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Animals↗

PubMed2003

Sex- and age-dependent human transcriptome variability: implications for chronic heart failure.

Heart failure (HF) is the end result of progressive and diverse biological adaptations within the diseased myocardium. We used cDNA microarrays and quantitative PCR to examine the transcriptomes of 38 left ventricles from failing and nonfailing human myocardium. After identification of a pool of putative HF-responsive candidate genes by microarrays on seven nonfailing and eight failing hearts, we used quantitative PCR and a general linear statistical model in a larger sample set (n = 34) to validate and examine the role of contributing biological variables (age and sex). We find that most HF-candidate genes (transcription factors, Cebpb, Npat; signaling molecules, Map2k3, Map4k5; extracellular matrix proteins, Lum, Cola1; and metabolic enzymes, Mars) demonstrated significant changes in gene expression; however, the majority of differences among samples depended on variables such as sex and age, and not on HF alone. Some HF-responsive gene products also demonstrated highly significant changes in expression as a function of age and/or sex, but independent of HF (Ngp1, Cd163, and Npat). These results emphasize the need to account for biological variables (HF, sex and age interactions) to elucidate genomic correlates that trigger molecular pathways responsible for the progression of HF syndromes.

Adult↗

PubMed2003

Transcriptome dynamics of Deinococcus radiodurans recovering from ionizing radiation.

Deinococcus radiodurans R1 (DEIRA) is a bacterium best known for its extreme resistance to the lethal effects of ionizing radiation, but the molecular mechanisms underlying this phenotype remain poorly understood. To define the repertoire of DEIRA genes responding to acute irradiation (15 kGy), transcriptome dynamics were examined in cells representing early, middle, and late phases of recovery by using DNA microarrays covering approximately 94% of its predicted genes. At least at one time point during DEIRA recovery, 832 genes (28% of the genome) were induced and 451 genes (15%) were repressed 2-fold or more. The expression patterns of the majority of the induced genes resemble the previously characterized expression profile of recA after irradiation. DEIRA recA, which is central to genomic restoration after irradiation, is substantially up-regulated on DNA damage (early phase) and down-regulated before the onset of exponential growth (late phase). Many other genes were expressed later in recovery, displaying a growth-related pattern of induction. Genes induced in the early phase of recovery included those involved in DNA replication, repair, and recombination, cell wall metabolism, cellular transport, and many encoding uncharacterized proteins. Collectively, the microarray data suggest that DEIRA cells efficiently coordinate their recovery by a complex network, within which both DNA repair and metabolic functions play critical roles. Components of this network include a predicted distinct ATP-dependent DNA ligase and metabolic pathway switching that could prevent additional genomic damage elicited by metabolism-induced free radicals.

Amino Acid Sequence↗

PubMed2001

Exploring the transcriptome of the malaria sporozoite stage.

Most studies of gene expression in Plasmodium have been concerned with asexual and/or sexual erythrocytic stages. Identification and cloning of genes expressed in the preerythrocytic stages lag far behind. We have constructed a high quality cDNA library of the Plasmodium sporozoite stage by using the rodent malaria parasite P. yoelii, an important model for malaria vaccine development. The technical obstacles associated with limited amounts of RNA material were overcome by PCR-amplifying the transcriptome before cloning. Contamination with mosquito RNA was negligible. Generation of 1,972 expressed sequence tags (EST) resulted in a total of 1,547 unique sequences, allowing insight into sporozoite gene expression. The circumsporozoite protein (CS) and the sporozoite surface protein 2 (SSP2) are well represented in the data set. A BLASTX search with all tags of the nonredundant protein database gave only 161 unique significant matches (P(N) < or = 10(-4)), whereas 1,386 of the unique sequences represented novel sporozoite-expressed genes. We identified ESTs for three proteins that may be involved in host cell invasion and documented their expression in sporozoites. These data should facilitate our understanding of the preerythrocytic Plasmodium life cycle stages and the development of preerythrocytic vaccines.

Amino Acid Motifs↗

PubMed2001

The contribution of 700,000 ORF sequence tags to the definition of the human transcriptome.

Open reading frame expressed sequences tags (ORESTES) differ from conventional ESTs by providing sequence data from the central protein coding portion of transcripts. We generated a total of 696,745 ORESTES sequences from 24 human tissues and used a subset of the data that correspond to a set of 15,095 full-length mRNAs as a means of assessing the efficiency of the strategy and its potential contribution to the definition of the human transcriptome. We estimate that ORESTES sampled over 80% of all highly and moderately expressed, and between 40% and 50% of rarely expressed, human genes. In our most thoroughly sequenced tissue, the breast, the 130,000 ORESTES generated are derived from transcripts from an estimated 70% of all genes expressed in that tissue, with an equally efficient representation of both highly and poorly expressed genes. In this respect, we find that the capacity of the ORESTES strategy both for gene discovery and shotgun transcript sequence generation significantly exceeds that of conventional ESTs. The distribution of ORESTES is such that many human transcripts are now represented by a scaffold of partial sequences distributed along the length of each gene product. The experimental joining of the scaffold components, by reverse transcription-PCR, represents a direct route to transcript finishing that may represent a useful alternative to full-length cDNA cloning.

Expressed Sequence Tags↗

PubMed2002

A computational/functional genomics approach for the enrichment of the retinal transcriptome and the identification of positional candidate retinopathy genes.

Grouping genes by virtue of their sequence similarity, functional association, or spatiotemporal distribution is an important first step in investigating function. Given the recent identification of >30,000 human genes either by analyses of genomic sequence or by derivation/assembly of ESTs, automated means of discerning gene function and association with disease are critical for the efficient processing of this large volume of data. We have designed a series of computational tools to manipulate the EST sequence database (dbEST) to predict EST clusters likely representing genes expressed exclusively or preferentially in a specific tissue. We implemented this tool by extracting 40,000 human retinal ESTs and performing in silico subtraction against 1.4 million human ESTs. This process yielded 925 ESTs likely to be specifically or preferentially expressed in the retina. We mapped all retinal-specific/predominant sequences in the human genome and produced a web-based searchable map of the retina transcriptome, onto which we overlaid the positions of all mapped but uncloned retinopathy genes. This resource has provided positional candidates for 42 of 51 uncloned retinopathies and may expedite substantially the identification of disease-associated genes. More importantly, the ability to systematically group ESTs according to their predicted expression profile is likely to be an important resource for studying gene function in a wide range of tissues and physiological systems and to identify positional candidate genes for human disorders whose phenotypic manifestations are restricted to specific tissues/organs/cell types.

Databases, Nucleic Acid↗

PubMed2001

Insight into hepatocellular carcinogenesis at transcriptome level by comparing gene expression profiles of hepatocellular carcinoma with those of corresponding noncancerous liver.

Human hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. In this work, we report on a comprehensive characterization of gene expression profiles of hepatitis B virus-positive HCC through the generation of a large set of 5'-read expressed sequence tag (EST) clusters (11,065 in total) from HCC and noncancerous liver samples, which then were applied to a cDNA microarray system containing 12,393 genes/ESTs and to comparison with a public database. The commercial cDNA microarray, which contains 1,176 known genes related to oncogenesis, was used also for profiling gene expression. Integrated data from the above approaches identified 2,253 genes/ESTs as candidates with differential expression. A number of genes related to oncogenesis and hepatic function/differentiation were selected for further semiquantitative reverse transcriptase-PCR analysis in 29 paired HCC/noncancerous liver samples. Many genes involved in cell cycle regulation such as cyclins, cyclin-dependent kinases, and cell cycle negative regulators were deregulated in most patients with HCC. Aberrant expression of the Wnt-beta-catenin pathway and enzymes for DNA replication also could contribute to the pathogenesis of HCC. The alteration of transcription levels was noted in a large number of genes implicated in metabolism, whereas a profile change of others might represent a status of dedifferentiation of the malignant hepatocytes, both considered as potential markers of diagnostic value. Notably, the altered transcriptome profiles in HCC could be correlated to a number of chromosome regions with amplification or loss of heterozygosity, providing one of the underlying causes of the transcription anomaly of HCC.

Carcinoma, Hepatocellular↗

PubMed2000

Shotgun sequencing of the human transcriptome with ORF expressed sequence tags.

Theoretical considerations predict that amplification of expressed gene transcripts by reverse transcription-PCR using arbitrarily chosen primers will result in the preferential amplification of the central portion of the transcript. Systematic, high-throughput sequencing of such products would result in an expressed sequence tag (EST) database consisting of central, generally coding regions of expressed genes. Such a database would add significant value to existing public EST databases, which consist mostly of sequences derived from the extremities of cDNAs, and facilitate the construction of contigs of transcript sequences. We tested our predictions, creating a database of 10,000 sequences from human breast tumors. The data confirmed the central distribution of the sequences, the significant normalization of the sequence population, the frequent extension of contigs composed of existing human ESTs, and the identification of a series of potentially important homologues of known genes. This approach should make a significant contribution to the early identification of important human genes, the deciphering of the draft human genome sequence currently being compiled, and the shotgun sequencing of the human transcriptome.

Animals↗

PubMedDate not supplied

Transcriptomics and proteomics: tools for the identification of novel drug targets and vaccine candidates for tuberculosis.

The availability of the complete genome sequence of Mycobacterium tuberculosis has revolutionised many areas of tuberculosis research and facilitated functional genomics studies. Most notably, transcriptomics and proteomics have become important tools in gaining increased understanding of the biology of M. tuberculosis and offer the promise of being able to deliver novel drug targets and vaccine candidates.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2025

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16 000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2 > 0.6 were mapped to CL for OC, 12 588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD↗

PubMed2001

Combined transcriptome and proteome analysis as a powerful approach to study genes under glucose repression in Bacillus subtilis.

We used 2D protein gel electrophoresis and DNA microarray technologies to systematically analyze genes under glucose repression in B:acillus subtilis. In particular, we focused on genes expressed after the shift from glycolytic to gluconeogenic at the middle logarithmic phase of growth in a nutrient sporulation medium, which remained repressed by the addition of glucose. We also examined whether or not glucose repression of these genes was mediated by CcpA, the catabolite control protein of this bacterium. The wild-type and ccpA1 cells were grown with and without glucose, and their proteomes and transcriptomes were compared. 2D gel electrophoresis allowed us to identify 11 proteins, the synthesis of which was under glucose repression. Of these proteins, the synthesis of four (IolA, I, S and PckA) was under CcpA-independent control. Microarray analysis enabled us to detect 66 glucose-repressive genes, 22 of which (glmS, acoA, C, yisS, speD, gapB, pckA, yvdR, yxeF, iolA, B, C, D, E, F, G, H, I, J, R, S and yxbF ) were at least partially under CcpA-independent control. Furthermore, we found that CcpA and IolR, a repressor of the iol divergon, were involved in the glucose repression of the synthesis of inositol dehydrogenase encoded by iolG included in the above list. The CcpA-independent glucose repression of the iol genes appeared to be explained by inducer exclusion.

Amino Acid Sequence↗

PubMed2002

The Gene Resource Locator: gene locus maps for transcriptome analysis.

Since the advent of the draft human genome sequence there has been growing interest in transcriptome analysis based on genomic data. The Gene Resource Locator (GRL) assembles gene maps that include information on gene-expression patterns, cis-elements in regulatory regions and alternatively spliced transcripts. The database was constructed using customized software, and currently contains 2.2 million alignments (exon-intron structures). The alignments have been annotated and integrated into a system that encompasses approximately 90 000 EST loci sharing common exons, 8091 alternatively spliced transcript groups, 10 801 expression-profile groups, 8066 candidate regulatory regions in full-length cDNAs, and 1 million SNP loci. We have used Flash technology to build a dynamic web viewer that facilitates browsing through the millions of alignments. All of the information is available through the World Wide Web at the Gene Resource Locator web site (http://grl.gi.k.u-tokyo.ac.jp).

Alternative Splicing↗

PubMed2002

Transcriptome analysis of Escherichia coli using high-density oligonucleotide probe arrays.

Microarrays traditionally have been used to analyze the expression behavior of large numbers of coding transcripts. Here we present a comprehensive approach for high-throughput transcript discovery in Escherichia coli focused mainly on intergenic regions which, together with analysis of coding transcripts, provides us with a more complete insight into the organism's transcriptome. Using a whole genome array, we detected expression for 4052 coding transcripts and identified 1102 additional transcripts in the intergenic regions of the E.coli genome. Further classification reveals 317 novel transcripts with unknown function. Our results show that, despite sophisticated approaches to genome annotation, many cellular transcripts remain unidentified. Through the experimental identification of all RNAs expressed under a specific condition, we gain a more thorough understanding of all cellular processes.

3' Untranslated Regions↗

PubMed2002

Density of points clustering, application to transcriptomic data analysis.

With the increasing amount of data produced by high-throughput technologies in many fields of science, clustering has become an integral step in exploratory data analysis in order to group similar elements into classes. However, many clustering algorithms can only work properly if aided by human expertise. For example, one parameter which is crucial and often manually set is the number of clusters present in the analyzed set. We present a novel stopping rule to find the optimal number of clusters based on the comparison of the density of points inside the clusters and between them. The method is evaluated on synthetic as well as on real transcriptomic data and compared with two current methods. Finally, we illustrate its usefulness in the analysis of the expression profiles of promyelocytic cells before and after treatment with all-trans retinoic acid. Simultaneous clustering for gene regulation and absolute initial expression levels allowed the identification of numerous genes associated with signal transduction revealing the complexity of retinoic acid signaling.

Algorithms↗

PubMed2003

MtDB: a database for personalized data mining of the model legume Medicago truncatula transcriptome.

In order to identify the genes and gene functions that underlie key aspects of legume biology, researchers have selected the cool season legume Medicago truncatula (Mt) as a model system for legume research. A set of >170 000 Mt ESTs has been assembled based on in-depth sampling from various developmental stages and pathogen-challenged tissues. MtDB is a relational database that integrates Mt transcriptome data and provides a wide range of user-defined data mining options. The database is interrogated through a series of interfaces with 58 options grouped into two filters. In addition, the user can select and compare unigene sets generated by different assemblers: Phrap, Cap3 and Cap4. Sequence identifiers from all public Mt sites (e.g. IDs from GenBank, CCGB, TIGR, NCGR, INRA) are fully cross-referenced to facilitate comparisons between different sites, and hypertext links to the appropriate database records are provided for all queries' results. MtDB's goal is to provide researchers with the means to quickly and independently identify sequences that match specific research interests based on user-defined criteria. The underlying database and query software have been designed for ease of updates and portability to other model organisms. Public access to the database is at http://www.medicago.org/MtDB.

Chromosome Mapping↗

PubMed2003

Small amplified RNA-SAGE: an alternative approach to study transcriptome from limiting amount of mRNA.

Serial analysis of gene expression (SAGE) is a widely used and powerful technique to characterize and compare transcriptomes. Although several modifications have been proposed to the initial protocol with the aim of reducing the amount of starting material, unless additional PCR steps are added, the technique is still limited by the need for at least 1 micro g of total RNA. As extra PCR amplification might introduce representation biases, current SAGE protocols are not fully suitable for the study of small, microdissected tissue samples. We propose here an alternative method involving the linear amplification of small mRNA fragments containing the SAGE tags. The procedure allows preparation of libraries of over 100 000 tags from as few as 2500 cells. A satisfactory correlation was observed between a microSAGE library made from 5 microg of total thyroid RNA, and a library prepared from 50 ng of the same RNA preparation according to the present protocol.

Animals↗

PubMed2026

Genomic and Transcriptomic Correlates of Deep PSA Response in Patients with Metastatic Androgen Pathway Modulation-Sensitive Prostate Cancer.

BACKGROUND: Despite advances in metastatic androgen pathway modulation-sensitive prostate cancer (mAPMS) treatment, outcomes remain heterogeneous. Achieving a post-treatment undetectable prostate specific antigen (PSA) is a strong prognostic marker. We aimed to identify genomic and transcriptomic determinants of PSA response in a real-world clinical-genomic cohort. PATIENTS AND METHODS: Patients with mAPMS who underwent DNA (Tempus xT) and, in a subset, RNA (Tempus xR) sequencing were identified from the Tempus Lens database. Inclusion required stage IV disease within 90 days of sample collection and samples obtained within 12 months before or 3 months after treatment initiation. Patients with PSA at 6 months (n = 525) were classified as PSA-low (<0.1 ng/mL, n = 240) or PSA-high (≥0.1 ng/mL, n = 285). Overall survival (OS) was assessed by 6-month landmark analysis with delayed-entry adjustment. Logistic and Cox models were adjusted for clinical variables. Sensitivity analyses used a relative definition of > 95% PSA decline from baseline. RESULTS: Baseline PSA was lower in PSA-low versus PSA-high patients (24 vs 36 ng/mL, p = 0.01). SPOP (17% vs 11%) and ZFHX3 (2.5% vs 6%) alterations differed between groups, but neither persisted after adjustment. Using the relative definition, ZMYM3 and JAK1 alterations were independently associated with failure to achieve a deep PSA response. Expression of PSMA, TROP2, B7-H3, and STEAP1 did not differ between groups. PSA-low status was independently associated with improved OS, as was deep relative response. CONCLUSION: Deep PSA response at 6 months correlates with improved OS in mAPMS. Integrating molecular markers with PSA response may inform treatment intensification or de-escalation strategies.

Biomarkers↗

PubMed2003

Transcriptome profiling and the pathogenesis of diabetic complications.

Diabetes is an escalating problem worldwide and a major cause of vascular disease, renal failure, and blindness, among other complications. The cellular mediators of high glucose-induced injury include activation of protein kinase C, accumulation of cell sorbitol from increased flux through the aldose reductase pathway, and generation of advanced glycosylation end products and reactive oxygen species, among others. Current strategies for preventing and slowing the progression of the macrovascular and microvascular complications of diabetes include optimization of glycemic control and BP, angiotensin-converting enzyme inhibitors and angiotensin II blockers, and HMG CoA reductase inhibitors. However, there is an urgent need to develop new therapeutic strategies, as these interventions, although they may slow, rarely halt the progression of diabetic complications. Central to this process is the elucidation of the molecular events that drive this complex disease and that are potential therapeutic targets. This review discusses the promise offered in this regard by global monitoring of cellular or tissue mRNA expression (so-called transcriptomics) and illustrates the potential of this approach by focusing on recent studies on the pathogenesis of diabetic nephropathy.

Actins↗