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At least 1,405 records · Page 78Linked to original sources
PubMed2005

A DNA microarray survey of gene expression in normal human tissues.

BACKGROUND: Numerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes. RESULTS: Here we describe a systematic survey of gene expression in 115 human tissue samples representing 35 different tissue types, using cDNA microarrays representing approximately 26,000 different human genes. Unsupervised hierarchical cluster analysis of the gene-expression patterns in these tissues identified clusters of genes with related biological functions and grouped the tissue specimens in a pattern that reflected their anatomic locations, cellular compositions or physiologic functions. In unsupervised and supervised analyses, tissue-specific patterns of gene expression were readily discernable. By comparative hybridization to normal genomic DNA, we were also able to estimate transcript abundances for expressed genes. CONCLUSIONS: Our dataset provides a baseline for comparison to diseased tissues, and will aid in the identification of tissue-specific functions. In addition, our analysis identifies potential molecular markers for detection of injury to specific organs and tissues, and provides a foundation for selection of potential targets for selective anticancer therapy.

Cluster Analysis↗
PubMed2007

Ribozyme technology for cancer gene target identification and validation.

Ribozymes are naturally occurring RNAs with catalytic activities including cis- or trans- cleavage of RNA at predefined sequence sites. This activity has been exploited for specific gene inactivation in cells during the last two decades, and ribozymes have been important functional genomics tools, especially in the pre-RNAi era. It has also been broadly applied in drug target identification and validation in pharmaceutical R&D. This chapter covers many application principles and case studies of ribozyme technology in the areas of cancer research. We also described RNAi applications in some of the same studies for comparison. Although RNAi may be more effective than ribozymes in many respects, they are nonetheless built on many of the same principles.

Animals↗
PubMed2006

A global assembly of cotton ESTs.

Approximately 185,000 Gossypium EST sequences comprising >94,800,000 nucleotides were amassed from 30 cDNA libraries constructed from a variety of tissues and organs under a range of conditions, including drought stress and pathogen challenges. These libraries were derived from allopolyploid cotton (Gossypium hirsutum; A(T) and D(T) genomes) as well as its two diploid progenitors, Gossypium arboreum (A genome) and Gossypium raimondii (D genome). ESTs were assembled using the Program for Assembling and Viewing ESTs (PAVE), resulting in 22,030 contigs and 29,077 singletons (51,107 unigenes). Further comparisons among the singletons and contigs led to recognition of 33,665 exemplar sequences that represent a nonredundant set of putative Gossypium genes containing partial or full-length coding regions and usually one or two UTRs. The assembly, along with their UniProt BLASTX hits, GO annotation, and Pfam analysis results, are freely accessible as a public resource for cotton genomics. Because ESTs from diploid and allotetraploid Gossypium were combined in a single assembly, we were in many cases able to bioinformatically distinguish duplicated genes in allotetraploid cotton and assign them to either the A or D genome. The assembly and associated information provide a framework for future investigation of cotton functional and evolutionary genomics.

DNA, Complementary↗
PubMedDate not supplied

Molecular basis of RhD-positive/D-negative chimerism in two patients.

This study investigated two patients with Rh chimerism: patient A, a healthy individual, and patient B with myelofibrosis. Flow cytometry studies showed two red blood cell populations of Rh phenotypes R1r and rr at percentages of about 25% and 75% respectively. Normal RhD transcript sequences were found following RT-PCR. Genomic DNA (gDNA) showed normal exon, intron, GATA regions and exon/intron boundary sequences except for a single base change in intron 7 (C --> A) of exon 7 in patient A. The major change found in both patients was the absence of RHD exon 9 DNA in gDNA isolated from peripheral blood. These findings suggest a somatic mutation, probably in a stem cell common to the myeloid lineage of both patients, and indicate that patient A may undergo malignant transformation in the future.

Adult↗
PubMed2006

The genome and transcriptomes of the anti-tumor agent Clostridium novyi-NT.

Bacteriolytic anti-cancer therapies employ attenuated bacterial strains that selectively proliferate within tumors. Clostridium novyi-NT spores represent one of the most promising of these agents, as they generate potent anti-tumor effects in experimental animals. We have determined the 2.55-Mb genomic sequence of C. novyi-NT, identifying a new type of transposition and 139 genes that do not have homologs in other bacteria. The genomic sequence was used to facilitate the detection of transcripts expressed at various stages of the life cycle of this bacterium in vitro as well as in infections of tumors in vivo. Through this analysis, we found that C. novyi-NT spores contained mRNA and that the spore transcripts were distinct from those in vegetative forms of the bacterium.

Animals↗
PubMed2003

The complete Corynebacterium glutamicum ATCC 13032 genome sequence and its impact on the production of L-aspartate-derived amino acids and vitamins.

The complete genomic sequence of Corynebacterium glutamicum ATCC 13032, well-known in industry for the production of amino acids, e.g. of L-glutamate and L-lysine was determined. The C. glutamicum genome was found to consist of a single circular chromosome comprising 3282708 base pairs. Several DNA regions of unusual composition were identified that were potentially acquired by horizontal gene transfer, e.g. a segment of DNA from C. diphtheriae and a prophage-containing region. After automated and manual annotation, 3002 protein-coding genes have been identified, and to 2489 of these, functions were assigned by homologies to known proteins. These analyses confirm the taxonomic position of C. glutamicum as related to Mycobacteria and show a broad metabolic diversity as expected for a bacterium living in the soil. As an example for biotechnological application the complete genome sequence was used to reconstruct the metabolic flow of carbon into a number of industrially important products derived from the amino acid L-aspartate.

Amino Acid Sequence↗
PubMed2006

Horizontal transfer of a virulence operon to the ancestor of Mycobacterium tuberculosis.

The contribution of interspecies horizontal gene transfer (HGT) to the evolution and virulence of Mycobacterium tuberculosis, the agent of tuberculosis in humans, has been barely investigated. Here we have studied the evolutionary history of the M. tuberculosis Rv0986-8 virulence operon recently identified, through functional genomics approaches, as playing an important role in parasitism of host phagocytic cells. We showed that among actinobacteria, this operon is specific to the M. tuberculosis complex and to ancestral Mycobacterium prototuberculosis species. These data, together with phylogenetic reconstruction and other in silico analyses, provided strong evidence that this operon has been acquired horizontally by the ancestor of M. tuberculosis, before the recent evolutionary bottleneck that preceded the clonal-like evolution of the M. tuberculosis complex. Genomic signature profiling further suggested that the transfer was plasmid mediated and that the operon originated from a gamma-proteobacterium donor species. Our study points out for the first time the contribution of HGT to the emergence of M. tuberculosis and close relatives as major pathogens. In addition, our data underline the importance of deciphering gene transfer networks in M. tuberculosis in order to better understand the evolutionary mechanisms involved in mycobacterial virulence.

Agrobacterium tumefaciens↗
PubMed2006

Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome.

Genomic tiling microarrays have become a popular tool for interrogating the transcriptional activity of large regions of the genome in an unbiased fashion. There are several key parameters associated with each tiling experiment (e.g., experimental protocols and genomic tiling density). Here, we assess the role of these parameters as they are manifest in different tiling-array platforms used for transcription mapping. First, we analyze how a number of published tiling-array experiments agree with established gene annotation on human chromosome 22. We observe that the transcription detected from high-density arrays correlates substantially better with annotation than that from other array types. Next, we analyze the transcription-mapping performance of the two main high-density oligonucleotide array platforms in the ENCODE regions of the human genome. We hybridize identical biological samples and develop several ways of scoring the arrays and segmenting the genome into transcribed and nontranscribed regions, with the aim of making the platforms most comparable to each other. Finally, we develop a platform comparison approach based on agreement with known annotation. Overall, we find that the performance improves with more data points per locus, coupled with statistical scoring approaches that properly take advantage of this, where this larger number of data points arises from higher genomic tiling density and the use of replicate arrays and mismatches. While we do find significant differences in the performance of the two high-density platforms, we also find that they complement each other to some extent. Finally, our experiments reveal a significant amount of novel transcription outside of known genes, and an appreciable sample of this was validated by independent experiments.

Cell Line↗
PubMed2004

Mycobacterium tuberculosis gene expression during adaptation to stationary phase and low-oxygen dormancy.

The innate mechanisms used by Mycobacterium tuberculosis to persist during periods of non-proliferation are central to understanding the physiology of the bacilli during latent disease. We have used whole genome expression profiling to expose adaptive mechanisms initiated by M. tuberculosis in two common models of M. tuberculosis non-proliferation. The first of these models was a standard growth curve in which gene expression changes were followed from exponential growth through the transition to stationary phase. In the second model, we followed the adaptive process of M. tuberculosis during transition from aerobic growth to a state of anaerobic non-replicating persistence. The most striking finding from these experiments was the strong induction of the entire DosR "dormancy" regulon over approximately 20 days during the long transition to an anaerobic state. This is contrasted by the muted overall response to aerated stationary phase with only a partial dormancy regulon response. From the results presented here we conclude that the respiration-limited environment of the oxygen-depleted NRP model recreates at least one fundamental factor for which the genome of M. tuberculosis encodes a decisive adaptive program.

Adaptation, Physiological↗
PubMed2001

Database resources of the National Center for Biotechnology Information.

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI's Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap'99, Human-Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri-tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih. gov.

Animals↗
PubMed2006

Post-genomic approaches to understanding the mechanisms of environmentally induced phenotypic plasticity.

Post-genomic techniques offer new and detailed insights into the mechanisms underpinning all biological processes, including phenotypic plasticity and environmentally relevant phenotypes. Although they require access to genomic resources it is now possible to create these for species of comparative or environmental interest even within a modest research project. Here we describe an open transcript screen for genes responding to environmental cold that might account for the acquired cold-specific phenotype in all its complex manifestations. Construction of a cDNA microarray led to a survey of transcript expression levels in seven tissues of carp, as a function of time, and three different extents of cooling. The resulting data delineated a common stress response found in all tissues that comprises genes involved in cellular homeostasis, including energy charge, ATP turnover, protein turnover and stress protein production. These genes respond to kinds of perturbation other than cold and probably form part of a more general stress response common to other species. We also defined tissue-specific response patterns of transcript regulation whose main characteristics were investigated by a profiling technique based on categorisation of gene function. These genes underpin the highly tissue-specific pattern of physiological adaptations observed in the cold-acclimated fish. As a result we have identified a large number of candidate gene targets with which to investigate adaptive responses to environmental challenge.

Adaptation, Physiological↗
PubMed2003

Progress in functional genomics approaches to antifungal drug target discovery.

Antifungal drug discovery is starting to benefit from the enormous advances in the genomics field, which have occurred in the past decade. As traditional drug screening on existing targets is not delivering the long-awaited potent antifungals, efforts to use novel genetics and genomics-based strategies to aid in the discovery of novel drug targets are gaining increased importance. The current paradigm in antifungal drug target discovery focuses on basically two main classes of targets to evaluate: genes essential for viability and virulence or pathogenicity factors. Here we report on recent advances in genetics and genomics-based technologies that will allow us not only to identify and validate novel fungal drug targets, but hopefully in the longer run also to discover potent novel therapeutic agents. Fungal pathogens have typically presented significant obstacles when subjected to genetics, but the creativity of scientists in the anti-infectives field and the cross-talk with scientists in other areas is now yielding exciting new tools and technologies to tackle the problem of finding potent, specific and non-toxic antifungal therapeutics.

Animals↗
PubMed2001

In silico research in drug discovery.

Target and lead discovery constitute the main components of today's early pharmaceutical research. The aim of target discovery is the identification and validation of suitable drug targets for therapeutic intervention, whereas lead discovery identifies novel chemical molecules that act on those targets. With the near completion of the human genome sequencing, bioinformatics has established itself as an essential tool in target discovery and the in silico analysis of gene expression and gene function are now an integral part of it, facilitating the selection of the most relevant targets for a disease under study. In lead discovery, advances in chemoinformatics have led to the design of compound libraries in silico that can be screened virtually. Moreover, computational methods are being developed to predict the drug-likeness of compounds. Thus, drug discovery is already on the road towards electronic R&D.

Computational Biology↗
PubMed2026

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans↗
PubMed2006

Application of genomic technologies to human prostate cancer.

Prostate cancer is the most commonly diagnosed non-cutaneous malignancy in U.S. males and has a broad spectrum of clinical behavior ranging from indolent to lethal. Microarray technology has provided unprecedented opportunity to explore the genetic processes underlying prostate cancer by providing a comprehensive survey of a cell's transcriptional landscape. Prostate cancer, however, has posed significant challenges that have contributed to inconsistent results between studies and difficulty replicating findings. Despite these challenges, several important insights have been gained along with new clinical biomarkers of diagnosis and prognosis. Continued improvements in methods of tissue preparation, microarray technology and data analysis will overcome existing challenges and fuel future discoveries.

Gene Expression Profiling↗
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↗
PubMed2003

GoMiner: a resource for biological interpretation of genomic and proteomic data.

We have developed GoMiner, a program package that organizes lists of 'interesting' genes (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. GoMiner provides quantitative and statistical output files and two useful visualizations. The first is a tree-like structure analogous to that in the AmiGO browser and the second is a compact, dynamically interactive 'directed acyclic graph'. Genes displayed in GoMiner are linked to major public bioinformatics resources.

Computer Graphics↗
PubMed2025

Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis.

BACKGROUND: Palmitoylation, a post-translational lipid modification, has garnered increasing attention for its role in inflammatory processes and tumorigenesis. Emerging evidence suggests a potential association between palmitoylation and inflammatory responses in the pathogenesis of endometriosis. However, the precise mechanistic interplay remains elusive, necessitating further investigation. METHODS: This study integrated transcriptomic analysis and Mendelian randomization (MR) to identify a causal gene set implicated in endometriosis. Differentially expressed genes (DEGs) were first identified in the training dataset using the limma package in R. Weighted gene co-expression network analysis (WGCNA) was subsequently performed, leveraging Single Sample Gene Set Enrichment Analysis (ssGSEA)-derived scores of palmitoylation-related genes (PRGs) as phenotypic traits to identify key modular genes. The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. RESULTS: Through a rigorous screening process, VRK1, GALNT12, and RMI1 emerged as key genes associated with palmitoylation, exhibiting significant downregulation in endometriosis samples (P <&#x2009;0.05), indicative of a potential protective role. Immune infiltration analysis further revealed strong correlations between these genes and M2 macrophages as well as resting Natural Killer (NK) cells. Additionally, investigations into the targeted RNA network and drug association profiling provided novel insights, laying the groundwork for future high-quality validation studies. CONCLUSIONS: This study employed a comprehensive analytical framework to identify palmitoylation-associated key genes in endometriosis. The integration of immunoinfiltration analysis, RNA network construction, and drug association profiling offers valuable insights for advancing clinical diagnostics, disease monitoring, and therapeutic development in endometriosis.

Humans↗