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Results for “Genomic profiling”

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At least 1,117 records · Page 62Linked to original sources
PubMed2006

Detection of compound mode of action by computational integration of whole-genome measurements and genetic perturbations.

BACKGROUND: A key problem of drug development is to decide which compounds to evaluate further in expensive clinical trials (Phase I- III). This decision is primarily based on the primary targets and mechanisms of action of the chemical compounds under consideration. Whole-genome expression measurements have shown to be useful for this process but current approaches suffer from requiring either a large number of mutant experiments or a detailed understanding of the regulatory networks. RESULTS: We have designed an algorithm, CutTree that when applied to whole-genome expression datasets identifies the primary affected genes (PAGs) of a chemical compound by separating them from downstream, indirectly affected genes. Unlike previous methods requiring whole-genome deletion libraries or a complete map of gene network architecture, CutTree identifies PAGs from a limited set of experimental perturbations without requiring any prior information about the underlying pathways. The principle for CutTree is to iteratively filter out PAGs from other recurrently active genes (RAGs) that are not PAGs. The in silico validation predicted that CutTree should be able to identify 3-4 out of 5 known PAGs (approximately 70%). In accordance, when we applied CutTree to whole-genome expression profiles from 17 genetic perturbations in the presence of galactose in Yeast, CutTree identified four out of five known primary galactose targets (80%). Using an exhaustive search strategy to detect these PAGs would not have been feasible (>1012 combinations). CONCLUSION: In combination with genetic perturbation techniques like short interfering RNA (siRNA) followed by whole-genome expression measurements, CutTree sets the stage for compound target identification in less well-characterized but more disease-relevant mammalian cell systems.

Algorithms↗
PubMed2026

Comparative genomics and full-length transcriptome profiling of wing morphs in Tetrix grossus (Orthoptera: Tetrigidae).

Wing polymorphism represents a paradigmatic dispersal-reproduction trade-off, yet its molecular basis remains uncharacterised in the phylogenetically distant pygmy grasshoppers (Tetrigidae). Here we integrate comparative genomics across ten orthopteran species with full-length transcriptomics of long-winged (FL) and short-winged (FS) Tetrix grossus. OrthoFinder recovered 118 orthogroups specific to T. grossus. Against a backdrop of pronounced gene-family contraction (36 expansions versus 222 contractions; net -186, mirrored at the ancestral Tetrix node, +37/-140), we identified an ancestral, Tetrix-specific expansion of hormone-regulation (12 genes; fold enrichment 7.93) and lipid/carbohydrate-metabolic families organised into syntenic clusters, alongside 513 positively selected genes enriched for integrin-mediated cell adhesion (6 genes), a process relevant to epithelial and appendage morphogenesis. Full-length transcriptomics of one long-winged (FL) and one short-winged (FS) adult female detected 7530 (FL) and 7515 (FS) expressed genes, with 794 FL- and 776 FS-restricted transcriptome-derived SNP-associated genes. The FL morph was enriched for an EGFR/Ras-Rho developmental-patterning axis and neuromuscular flight genes, whereas the FS morph was enriched for insulin/peptide-hormone response and growth-regulatory loci. Overall, we present genomic resources and testable hypotheses concerning the evolution and regulation of wing morphs in Tetrigidae rather than a validated genetic architecture of wing-morph determination.

Animals↗
PubMed1998

Bisulfite genomic sequencing-derived methylation profile of the xist gene throughout early mouse development.

Differential epigenetic modification by methylation of CpG dinucleotides is a candidate mechanism that may identify the alleles of imprinted genes and result in monoallelic expression of either the maternal or the paternal allele. Determination of the allelic methylation status of imprinted genes in the gametes and during early development is constrained by the limiting quantities of genomic DNA available from these early developmental stages. To circumvent this problem we have used bisulfite genomic sequencing to determine the allelic methylation status of the minimal promoter and a 1-kb region within the Xist gene during preimplantation development. We find that the parental Xist alleles are not differentially methylated in these regions. Our findings are discussed in the context of previous conflicting data obtained using methylation-sensitive restriction enzyme digestion followed by PCR amplification to assay for methylation.

Animals↗
PubMed2001

Methods and approaches in the analysis of gene expression data.

The application of high-density DNA array technology to monitor gene transcription has been responsible for a real paradigm shift in biology. The majority of research groups now have the ability to measure the expression of a significant proportion of the human genome in a single experiment, resulting in an unprecedented volume of data being made available to the scientific community. As a consequence of this, the storage, analysis and interpretation of this information present a major challenge. In the field of immunology the analysis of gene expression profiles has opened new areas of investigation. The study of cellular responses has revealed that cells respond to an activation signal with waves of co-ordinated gene expression profiles and that the components of these responses are the key to understanding the specific mechanisms which lead to phenotypic differentiation. The discovery of 'cell type specific' gene expression signatures have also helped the interpretation of the mechanisms leading to disease progression. Here we review the principles behind the most commonly used data analysis methods and discuss the approaches that have been employed in immunological research.

Classification↗
PubMed2004

Genetic and genomic approaches to identify and study the targets of bioactive small molecules.

Natural and synthetic bioactive small molecules form the backbone of modern therapeutics. These drugs primarily exert their effect by targeting cellular host or foreign proteins that are critical for the progression of disease. Therefore, a crucial step in the process of recognizing valuable new drug leads is identification of their protein targets; this is often a time consuming and difficult task. This report is intended to provide a comprehensive review of recent developments in genetic and genomic approaches to overcome the hurdle of discovering the protein targets of bioactive small molecules.

Biological Products↗
PubMed2005

cDNA cloning and phylogenetic analysis of the sixth complement component in rainbow trout.

The sixth complement protein (C6) is an essential component of the membrane attack complex (MAC); the end product of the lytic pathway of complement activation. The MAC complex constitutes a supramolecular assembly containing the five precursor proteins C5b, C6, C7, C8, and C9. Once assembled on the target surface it forms transmembrane channels that cause membrane damage and cytolysis of complement-opsonized pathogens. Besides mediating direct pathogen elimination, exposure of cells to sublytic doses of MAC can trigger diverse cellular responses such as, cell activation, induction of apoptosis, cell cycle re-entry and proliferation in various biological settings. The terminal complement components (C6-C9) are structurally related proteins, differing in size and complexity. In order to study their evolution, we report here the cloning and molecular characterization of C6 component in rainbow trout. The deduced amino acid sequence of trout C6 exhibits 55 and 44% identity with zebra fish and human orthologs, respectively. The 'domain' architecture of trout C6 resembles that of mammalian counterparts, and the cysteine backbone is also conserved. Finally, trout C6 gene appears to exist as a single copy in the trout genome, and is expressed in a wide range of trout tissues.

Amino Acid Sequence↗
PubMed2005

A 7872 cDNA microarray and its use in bovine functional genomics.

The strategy used to create and annotate a 7872 cDNA microarray from cattle placenta and spleen cDNA sequences is described. This microarray contains approximately 6300 unique genes, as determined by BLASTN and TBLASTX similarity search against the human and mouse UniGene and draft human genome sequence databases (build 34). Sequences on the array were annotated with gene ontology (GO) terms, thereby facilitating data analysis and interpretation. A total of 3244 genes were annotated with GO terms. The array is rich in sequences encoding transcription factors, signal transducers and cell cycle regulators. Current research being conducted with this array is described, and an overview of planned improvements in our microarray platform for cattle functional genomics is presented.

Animals↗
PubMed2005

Genomics in myeloid leukemias: an array of possibilities.

Myeloid leukemias are clonal hematopoietic stem cell disorders characterized either by proliferation of one or more of the myeloid lineages (chronic myelogenous leukemia) or by clonal expansion of myeloid blasts (acute myeloid leukemia). Over the past several years our knowledge of these hematologic malignancies has increased tremendously. The result is a classification that incorporates morphologic, immunophenotypic, genetic and clinical features in an attempt to define biologically and clinically relevant entities. Nevertheless, in many tumor subtypes the pathogenic event is still unknown. Furthermore, well-defined leukemia subgroups exhibit considerable heterogeneity, arousing the suspicion that several molecularly distinct subtypes might exist within the same cytogenetic category. Therefore, an ideal classification system would ultimately be based on the underlying molecular pathogenesis, but such knowledge is not yet available. However, by surveying the expression levels of thousands of genes in parallel, DNA microarrays have recently contributed to an increasingly refined molecular taxonomy of myeloid disorders. This powerful technology is becoming well established and has been used to diagnosis cancer and predict clinical outcome, to discover novel tumor subclasses, to gain insights into pathogenesis, and to identify new therapeutic targets. While many challenges remain ahead, genomic technologies have already demonstrated tremendous potential. We expect whole genome approaches will significantly contribute to a better understanding of the pathogenesis and result in a refined molecular classification of myeloid leukemias.

Gene Expression Profiling↗
PubMed2004

Novel cell wall architecture of isoxaben-habituated Arabidopsis suspension-cultured cells: global transcript profiling and cellular analysis.

The herbicide isoxaben is a highly specific and potent inhibitor of cellulose synthesis in plants. Nevertheless, suspension-cultured cells can be habituated to grow in high concentrations of isoxaben, and apparently compensate for the disruption of cellulose synthesis by the modulation of other cell wall components. We have habituated Arabidopsis cells to isoxaben and characterized the cellular and genetic consequences. Near whole-genome transcript profiling implicated novel genes in cell wall assembly and extended our understanding of the activity of known cell wall-related genes including glycosyltransferases involved in cellulose and pectin biosynthesis. Habituation does not appear to be mediated by stress response processes, nor by functional redundancy within the cellulose synthase (AtCesA) family. Uniquely, amongst the cellulose synthase superfamily, AtCslD5 was highly upregulated and may play a role in the biosynthesis of the novel walls of habituated cells. In silico analysis of differentially expressed genes with unknown functions identified a putative glycosyltransferase and collagen-like putative cell wall protein.

Adaptation, Biological↗
PubMed2002

The cloning, genomic organization and tissue expression profile of the human DLG5 gene.

BACKGROUND: Familial atrial fibrillation, an autosomal dominant disease, was previously mapped to chromosome 10q22. One of the genes mapped to the 10q22 region is DLG5, a member of the MAGUKs (Membrane Associated Gyanylate Kinase) family which mediates intracellular signaling. Only a partial cDNA was available for DLG5. To exclude potential disease inducing mutations, it was necessary to obtain a complete cDNA and genomic sequence of the gene. METHODS: The Northern Blot analysis performed using 3' UTR of this gene indicated the transcript size to be about 7.2 KB. Using race technique and library screening the entire cDNA was cloned. This gene was evaluated by sequencing the coding region and splice functions in normal and affected family members with familial atrial fibrillation. Furthermore, haploid cell lines from affected patients were generated and analyzed for deletions that may have been missed by PCR. RESULTS: We identified two distinct alternately spliced transcripts of this gene. The genomic sequence of the DLG5 gene spanned 79 KB with 32 exons and was shown to have ubiquitous human tissue expression including placenta, heart, skeletal muscle, liver and pancreas. CONCLUSIONS: The entire cDNA of DLG5 was identified, sequenced and its genomic organization determined.

Journal Article↗
PubMed2026

DNA methylation landscape of cerebrospinal fluid cells in multiple sclerosis: an epigenome-wide association study.

BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system in which DNA methylation may link genetic and environmental risk factors. METHODS: We profiled genome-wide DNA methylation in cerebrospinal fluid (CSF) cells from people with MS (pwMS) and matched controls. Differentially methylated positions (DMPs) and regions (DMRs) were integrated with transcriptomic data, T-cell chromatin annotations, and pathway analyses. Protocadherin gamma (PCDHγ) expression was assessed in primary CD4+ T-cell subsets and confirmed by flow cytometry. FINDINGS: We identified 2710 DMPs and 4330 DMRs associating with genes that were enriched in immune signalling, adhesion and migration processes, and were accompanied by corresponding RNA changes. MS-associated methylation changes enriched in the cohesin chromatin-regulation pathway localised to T-cell regulatory regions, and this pathway included multiple protocadherin (PCDH) genes, which displayed consistent methylation and expression changes in CSF cells of pwMS compared to controls. PCDHγ cluster gene expression was detected in CD4+ T-cell subsets, and flow cytometry confirmed PCDHγ protein expression in peripheral blood T cells. Moreover, co-expression analysis suggests a role of PCDH genes in aryl hydrocarbon receptor (AHR) signalling. Protein-level validation showed fewer PCDHγ-positive CD4+ T cells in pwMS and activation-induced PCDHγ upregulation after T-cell stimulation. INTERPRETATION: DNA methylation changes in CSF resident cells reflect dysregulated T cell activation and migration in pwMS and suggest involvement of protocadherin molecules in MS pathogenesis. FUNDING: European Research Council, Swedish Research Council, Swedish Brain Foundation, Swedish MS Foundation, Knut and Alice Wallenberg Foundation, European Union and others.

Humans↗
PubMed2006

Functional genomic methodologies.

The ability to form tenable hypotheses regarding the neurobiological basis of normative functions as well as mechanisms underlying neurodegenerative and neuropsychiatric disorders is often limited by the highly complex brain circuitry and the cellular and molecular mosaics therein. The brain is an intricate structure with heterogeneous neuronal and nonneuronal cell populations dispersed throughout the central nervous system. Varied and diverse brain functions are mediated through gene expression, and ultimately protein expression, within these cell types and interconnected circuits. Large-scale high-throughput analysis of gene expression in brain regions and individual cell populations using modern functional genomics technologies has enabled the simultaneous quantitative assessment of dozens to hundreds to thousands of genes. Technical and experimental advances in the accession of tissues, RNA amplification technologies, and the refinement of downstream genetic methodologies including microarray analysis and real-time quantitative PCR have generated a wellspring of informative studies pertinent to understanding brain structure and function. In this review, we outline the advantages as well as some of the potential challenges of applying high throughput functional genomics technologies toward a better understanding of brain tissues and diseases using animal models as well as human postmortem tissues.

Animals↗
PubMed2001

Discovery of a novel murine type C retrovirus by data mining.

Analysis of genomic and expression data allows both identification and characterization of novel retroviruses. We describe a recombinant type C murine retrovirus, similar to the Mus dunni endogenous retrovirus, with VL30-like long terminal repeats and murine leukemia virus-like coding sequences. This virus is present in multiple copies in the mouse genome and expressed in a range of mouse tissues.

Amino Acid Sequence↗
PubMed2007

Experimental validation of novel genes predicted in the un-annotated regions of the Arabidopsis genome.

BACKGROUND: Several lines of evidence support the existence of novel genes and other transcribed units which have not yet been annotated in the Arabidopsis genome. Two gene prediction programs which make use of comparative genomic analysis, Twinscan and EuGene, have recently been deployed on the Arabidopsis genome. The ability of these programs to make use of sequence data from other species has allowed both Twinscan and EuGene to predict over 1000 genes that are intergenic with respect to the most recent annotation release. A high throughput RACE pipeline was utilized in an attempt to verify the structure and expression of these novel genes. RESULTS: 1,071 un-annotated loci were targeted by RACE, and full length sequence coverage was obtained for 35% of the targeted genes. We have verified the structure and expression of 378 genes that were not present within the most recent release of the Arabidopsis genome annotation. These 378 genes represent a structurally diverse set of transcripts and encode a functionally diverse set of proteins. CONCLUSION: We have investigated the accuracy of the Twinscan and EuGene gene prediction programs and found them to be reliable predictors of gene structure in Arabidopsis. Several hundred previously un-annotated genes were validated by this work. Based upon this information derived from these efforts it is likely that the Arabidopsis genome annotation continues to overlook several hundred protein coding genes.

Arabidopsis↗
PubMed2005

The agony and ecstasy of "OMIC" technologies in drug development.

Over the last decade we have witnessed a fundamental change in how biomedical research is carried out and we can now assess the impact of the Human Genome Project on drug discovery and development. Advances in "omics" technologies (genomics, transcriptomics, proteomics and metabonomics) were touted as having the potential to revolutionize our approach to disease diagnosis, prognostication and development of novel therapeutics. However, the promise of rapid advances in medicine "from the lab bench to the bedside" has not manifested as of yet. Indeed it appears that the translational applications of genomic-based research have preceded the development of both (i) a conceptual framework for disease understanding and (ii) effective tools that can exploit the vast amounts of data derived from these efforts. In reality great progress has been made, however understanding processes such as disease progression (or drug response) requires systematic insight into dynamic (and temporal) differences in gene regulation, interaction and function. This review will discuss "omic" technologies with the emphasis upon advances in our understanding of the human genome derived transcriptome (RNA), and its proteome (proteins), while focusing upon the translation of this information into the drug development paradigm.

Computational Biology↗
PubMed2026

Epigenetic profiling of circulating cell-free DNA for early detection and minimal residual disease assessment in lung cancer: a focus on DNA methylation.

Lung Cancer (LC) continues to be the biggest cause of cancer-related deaths around the world, mostly because of delayed diagnosis. Even if tissue biopsies and circulating tumor DNA (ctDNA) tests have revolutionized clinical management of LC patients, their effectiveness is restricted in settings with lower tumor burden, molecular heterogeneity, and bias in sampling approaches. In this scenario, the epigenetic profiling of cell-free DNA (cfDNA) stands out as a promising, less invasive approach, accurately detect cancer traces. Evidence from stage I-II disease and CT-detected pulmonary nodules supports the diagnostic potential of cfDNA methylation, although further validation in prospective screening cohorts remains necessary. Beyond genomic alterations, cfDNA epigenetic changes, including DNA methylation, chromatin organization, nucleosome positioning, and fragmentation patterns, reflect multi-dimensional complexity of tumor biology. These properties convey both the functional status and the origin of the circulating DNA fragments, accelerating for tumor integrating genomic analysis. Within this group, DNA methylation is the biologically robust and clinically well-established epigenetic marker, as alterations in methylation linked to cancer often occur in the early stages of tumorigenesis and are commonly found across different cancer cell types. Here, we explored the biological and clinical relevance of the epigenetic landscape of cfDNA in LC patients, particularly focusing on DNA methylation-based biomarkers and their evolving applications towards early diagnosis and post-surgical monitoring of minimal residual disease (MRD). We aimed to comprehensively overview analytical approaches for cfDNA methylation analysis, including targeted and genome-wide profiling strategies, and discuss their integration with machine learning (ML) and multi-omics frameworks in order to improve diagnostic performance and clinical applicability in LC management.

DNA methylation↗
PubMed2001

Tissue microdissection techniques in quantitative genome and gene expression analyses.

Current advances in quantitative genome and gene expression analyses allow precise molecular genetic fingerprinting of tumor tissues. A crucial factor for the reliability of the data obtained with these refined techniques is the use of morphologically well-defined cell populations. Microdissection technology has been developed to procure pure cell populations from specific areas of tissue sections under microscopic control. This review covers techniques of tissue microdissection in the context of commonly used methods of quantitative genome and gene expression analysis. The first part of the review will summarize the technical aspects of various methods developed for tissue microdissection. In the latter part, current applications of quantitative genome and gene expression analysis techniques employed in microdissected tissue samples will be described.

Animals↗