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Results for “Functional Genomics”

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At least 217 records · Page 12Linked to original sources
PubMed2005

High throughput functional genomics: identification of novel genes with tumor suppressor phenotypes.

We have used a combination of high throughput functional genomics, computerized database mining and expression analyses to discover novel human tumor suppressor genes (TSGs). A genome-wide high throughput cDNA phenotype screen was established to identify genes that induce apoptosis or reduce cell viability. TSGs are expressed in normal tissue and frequently act by reduction of growth of transformed cells or induce apoptosis. In agreement with that and thus serving as platform validation, our pro-apoptotic hits included genes for which tumor suppressing activities were known, such as kangai1 and CD81 antigen. Additional genes that so far have been claimed as putative TSGs or associated with tumor inhibitory activities (prostate differentiation factor, hRAS-like suppressor 3, DPH2L1-like and the metastasis inhibitor Kiss1) were confirmed in their proposed TSG-like phenotype by functionally defining their growth inhibitory or pro-apoptotic function towards cancer cells. Finally, novel genes were identified for which neither association with cell growth nor with apoptosis were previously described. A subset of these genes show characteristics of TSGs because they (i) reduce the growth or induce apoptosis in tumor cells; (ii) show reduced expression in tumor vs. normal tissue; and (iii) are located on chromosomal (LOH-) loci for which cancer-associated deletions are described. The pro-apoptotic phenotype and differential expression of these genes in normal and malignant tissue make them promising target candidates for the diagnosis and therapy of various tumors.

Apoptosis↗
PubMed2003

Plant metabolomics: large-scale phytochemistry in the functional genomics era.

Metabolomics or the large-scale phytochemical analysis of plants is reviewed in relation to functional genomics and systems biology. A historical account of the introduction and evolution of metabolite profiling into today's modern comprehensive metabolomics approach is provided. Many of the technologies used in metabolomics, including optical spectroscopy, nuclear magnetic resonance, and mass spectrometry are surveyed. The critical role of bioinformatics and various methods of data visualization are summarized and the future role of metabolomics in plant science assessed.

Computational Biology↗
PubMed2006

Identification of putative oncogenes in lung adenocarcinoma by a comprehensive functional genomic approach.

Amplification and overexpression of putative oncogenes confer growth advantages for tumor development. We used a functional genomic approach that integrated simultaneous genomic and transcript microarray, proteomics, and tissue microarray analyses to directly identify putative oncogenes in lung adenocarcinoma. We first identified 183 genes with increases in both genomic copy number and transcript in six lung adenocarcinoma cell lines. Next, we used two-dimensional polyacrylamide gel electrophoresis and mass spectrometry to identify 42 proteins that were overexpressed in the cancer cells relative to normal cells. Comparing the 183 genes with the 42 proteins, we identified four genes - PRDX1, EEF1A2, CALR, and KCIP-1 - in which elevated protein expression correlated with both increased DNA copy number and increased transcript levels (all r > 0.84, two-sided P < 0.05). These findings were validated by Southern, Northern, and Western blotting. Specific inhibition of EEF1A2 and KCIP-1 expression with siRNA in the four cell lines tested suppressed proliferation and induced apoptosis. Parallel fluorescence in situ hybridization and immunohistochemical analyses of EEF1A2 and KCIP-1 in tissue microarrays from patients with lung adenocarcinoma showed that gene amplification was associated with high protein expression for both genes and that protein overexpression was related to tumor grade, disease stage, Ki-67 expression, and a shorter survival of patients. The amplification of EEF1A2 and KCIP-1 and the presence of overexpressed protein in tumor samples strongly suggest that these genes could be oncogenes and hence potential targets for diagnosis and therapy in lung adenocarcinoma.

Adenocarcinoma↗
PubMed2002

Designed transcription factors as tools for therapeutics and functional genomics.

The paucity of tools that control expression of specific genes in vivo represents a major limitation of functional genomics in mammals; most available small-molecule regulators of transcription-e.g. histone deacetylase inhibitors-exert pan-genomic effects. Recent developments in understanding the role of chromatin in regulating the genome, and of protein-DNA interactions have allowed the development of designed transcription factors that regulate specific genes in vivo (Reik et al., Curr Opin Genet Dev 2002;12:233). These proteins contain two modules: (i) a zinc finger protein (ZFP)-based DNA-binding domain (DBD) designed to recognize a specific sequence (for example, a motif in the promoter of a certain gene); (ii) a functional module (for example, a transcriptional activation or repression domain). Recent data describe the use of such designed transcription factors to regulate a variety of clinically relevant gene targets in human cells: these include MDR1, erythropoietin, erbB-2 and erbB-3, VEGF, and PPARgamma. In the case of VEGF (Liu et al., J Biol Chem 2001;276:11323), proportional upregulation by the designed transcription factor of all three distinct splice isoforms generated by this locus was observed, illuminating the utility of endogenous gene control in therapeutic settings (proper isoform ratio is essential for the proangiogenic function of VEGF). In the case of PPARgamma, use of a transcriptional repressor designed to downregulate the expression of two PPARgamma isoforms allowed "mutation-free reverse genetics" analysis that illuminated a unique role for the PPARgamma2 isoform in adipogenesis (Ren et al., Genes Dev 2002;16:27). The ability to selectively activate or repress specific mammalian genes in vivo using designed transcription factors thus has considerable promise in clinical and in basic science settings.

Drug Design↗
PubMed2000

Morphants: a new systematic vertebrate functional genomics approach.

The vertebrate genome contains a predicted 50 000-100 000 genes, many of unknown function. The recent development of morpholino-based gene knock-down technology in zebrafish has opened the door to the genome-wide assignment of function based on sequence in a model vertebrate. This review describes technical aspects of morpholino use for functional genomics applications, including the potential for multigene targeting and known methodological limitations. The result of successful gene inactivation by this agent is proposed to yield embryos with a 'morphant' phenotypic designation. The establishment of a morphant database opens the door to true functional genomics using the vertebrate, Danio rerio.

Animals↗
PubMed2005

Functional genomics using high-throughput RNA interference.

RNA interference (RNAi) describes the post-transcriptional silencing of gene expression that occurs in response to the introduction of double-stranded RNA into cells. Application of RNAi in experimental systems has provided a great leap forward in the elucidation of gene function. To facilitate large-scale functional genomics studies using RNAi, several high throughput approaches have been developed based on microarray or microwell assays. Recent establishment of large libraries of RNAi reagents combined with a variety of detection assays further opens the door for genome-wide screens of gene function in mammalian cells.

Animals↗
PubMed1999

From fold predictions to function predictions: automation of functional site conservation analysis for functional genome predictions.

A database of functional sites for proteins with known structures, SITE, is constructed and used in conjunction with a simple pattern matching program SiteMatch to evaluate possible function conservation in a recently constructed database of fold predictions for Escherichia coli proteins (Rychlewski L et al., 1999, Protein Sci 8:614-624). In this and other prediction databases, fold predictions are based on algorithms that can recognize weak sequence similarities and putatively assign new proteins into already characterized protein families. It is not clear whether such sequence similarities arise from distant homologies or general similarity of physicochemical features along the sequence. Leaving aside the important question of nature of relations within fold superfamilies, it is possible to assess possible function conservation by looking at the pattern of conservation of crucial functional residues. SITE consists of a multilevel function description based on structure annotations and structure analyses. In particular, active site residues, ligand binding residues, and patterns of hydrophobic residues on the protein surface are used to describe different functional features. SiteMatch, a simple pattern matching program, is designed to check the conservation of residues involved in protein activity in alignments generated by any alignment method. Here, this procedure is used to study conservation of functional features in alignments between protein sequences from the E. coli genome and their optimal structural templates. The optimal templates were identified and alignments taken from the database of genomic structural predictions was described in a previous publication (Rychlewski L et al., 1999, Protein Sci 8:614-624). An automated assessment of function conservation is used to analyze the relation between fold and function similarity for a large number of fold predictions. For instance, it is shown that identifying low significance predictions with a high level of functional residue conservations can be used to extend the prediction sensitivity for fold prediction methods. Over 100 new fold/function predictions in this class were obtained in the E. coli genome. At the same time, about 30% of our previous fold predictions are not confirmed as function predictions, further highlighting the problem of function divergence in fold superfamilies.

Algorithms↗
PubMed2005

Biological master games: using biologists' reasoning to guide algorithm development for integrated functional genomics.

We review some powerful new algorithms that build on the intuitive biological interpretation techniques for statistical analysis of functional genomics experiments. Although they were originally designed for transcriptomics, we argue that these algorithms are applicable to any type of -omics study (transcriptomics, proteomics, metabolomics). Rank Products (RP), a strictly non-parametric test statistic to detect differentially regulated elements (genes, proteins, metabolites) in genome-wide screens. RP is particularly powerful for noisy data and low numbers of replicates and makes full use of the availability of a large number of parallel measurements that is typical of modern large-scale experiments. Iterative Group Analysis (iGA), a statistical method that makes the transition from regulated single elements to significant classes of elements, and thus provides an automatic functional annotation of an experiment. Graph-based iGA (GiGA), an extension of iGA that combines experimental data with a broad variety of biological annotations to highlight physiologically relevant regions in a given "evidence graph" (e.g., metabolic networks, signaling pathway diagrams, protein interaction maps). The sequential application of these techniques yields an increasingly abstract interpretation of experimental data that is at the same time quantitative, statistically rigorous, and biologically significant. The results can be used either as helpful tools to guide data visualization and exploration, or as the input for downstream computational applications in a systems biology framework.

Algorithms↗
PubMed2003

One step further towards real high-throughput functional genomics.

In a recent paper by Michiels et al. an important step was made towards genuine high throughput functional genomics. The authors produced an arrayed adenoviral library containing >120000 cDNAs isolated from human placenta. This library can be used for arrayed transduction of cell lines in phenotypic assays and to screen for genes involved in the induction of any phenotype for which a robust high-throughput assay can be designed.

Adenoviridae↗
PubMed2006

RNA interference-based gene silencing as an efficient tool for functional genomics in hexaploid bread wheat.

Insertional mutagenesis and gene silencing are efficient tools for the determination of gene function. In contrast to gain- or loss-of-function approaches, RNA interference (RNAi)-induced gene silencing can possibly silence multigene families and homoeologous genes in polyploids. This is of great importance for functional studies in hexaploid wheat (Triticum aestivum), where most of the genes are present in at least three homoeologous copies and conventional insertional mutagenesis is not effective. We have introduced into bread wheat double-stranded RNA-expressing constructs containing fragments of genes encoding Phytoene Desaturase (PDS) or the signal transducer of ethylene, Ethylene Insensitive 2 (EIN2). Transformed plants showed phenotypic changes that were stably inherited over at least two generations. These changes were very similar to mutant phenotypes of the two genes in diploid model plants. Quantitative real-time polymerase chain reaction revealed a good correlation between decreasing mRNA levels and increasingly severe phenotypes. RNAi silencing had the same quantitative effect on all three homoeologous genes. The most severe phenotypes were observed in homozygous plants that showed the strongest mRNA reduction and, interestingly, produced around 2-fold the amount of small RNAs compared to heterozygous plants. This suggests that the effect of RNAi in hexaploid wheat is gene-dosage dependent. Wheat seedlings with low mRNA levels for EIN2 were ethylene insensitive. Thus, EIN2 is a positive regulator of the ethylene-signaling pathway in wheat, very similar to its homologs in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Our data show that RNAi results in stably inherited phenotypes and therefore represents an efficient tool for functional genomic studies in polyploid wheat.

Carotenoids↗
PubMed2006

A functional genomics approach to the mode of action of apratoxin A.

The cyanobacterial metabolite apratoxin A (1) demonstrates potent cytotoxicity against tumor cell lines by a hitherto unknown mechanism. We have used functional genomics to elucidate the molecular basis for this activity. Gene expression profiling and DNA content analysis showed that apratoxin A induces G1-phase cell cycle arrest and apoptosis. Cell-based functional assays with a genome-wide collection of expression cDNAs showed that ectopic induction of fibroblast growth factor receptor (FGFR) signaling attenuates the apoptotic activity of apratoxin A. This natural product inhibited phosphorylation and activation of STAT3, a downstream effector of FGFR signaling. It also caused defects in FGF-dependent processes during zebrafish development, with concomitant reductions in expression levels of the FGF target gene mkp3. We conclude that apratoxin A mediates its antiproliferative activity through the induction of G1 cell cycle arrest and an apoptotic cascade, which is at least partially initiated through antagonism of FGF signaling via STAT3.

Animals↗
PubMed2001

PlantsP: a functional genomics database for plant phosphorylation.

The PlantsP database is a curated database that combines information derived from sequences with experimental functional genomics information. PlantsP focuses on plant protein kinases and protein phosphatases. The database will specifically provide a resource for information on a collection of T-DNA insertion mutants (knockouts) in each protein kinase and phosphatase in Arabidopsis thaliana. PlantsP also provides a curated view of each protein that includes a comprehensive annotation of functionally related sequence motifs, sequence family definitions, alignments and phylogenetic trees, and descriptive information drawn directly from the literature. PlantsP is available at http://PlantsP.sdsc.edu.

Arabidopsis↗
PubMed2001

Recombineering: a powerful new tool for mouse functional genomics.

Highly efficient phage-based Escherichia coli homologous recombination systems have recently been developed that enable genomic DNA in bacterial artificial chromosomes to be modified and subcloned, without the need for restriction enzymes or DNA ligases. This new form of chromosome engineering, termed recombinogenic engineering or recombineering, is efficient and greatly decreases the time it takes to create transgenic mouse models by traditional means. Recombineering also facilitates many kinds of genomic experiment that have otherwise been difficult to carry out, and should enhance functional genomic studies by providing better mouse models and a more refined genetic analysis of the mouse genome.

Animals↗
PubMed2004

Caenorhabditis elegans functional genomics: omic resonance.

The nematode Caenorhabditis elegans is widely used as a model organism for studying many fundamental aspects of development and cell biology, including processes underlying human disease. The genome of C. elegans encodes over 19,000 protein-coding genes and hundreds of non-coding RNAs. The availability of whole genome sequence has facilitated the development of high throughput techniques for elucidating the function of individual genes and gene products. Furthermore, attempts can now be made to integrate these substantial functional genomics data collections and to understand at a global level how the flow of genomic information that is at the core of the central dogma leads to the development of a multicellular organism.

Animals↗
PubMed2003

Exploring the potential of plant RNase P as a functional genomics tool.

As we trek into the uncharted territories of the genomic era, there is an urgency for the development of approaches for assigning functions to the multitude of uncharacterized genes. Although currently available knock-out methodologies could be used for uncovering the function of newly discovered genes, the mixed outcomes in terms of the success of these approaches in down-regulating gene expression necessitate the development of new functional genomics tools. This chapter describes in detail the experimental method for targeted mRNA degradation inside plant cells by enticing the endogenous and ubiquitous RNase P into recognition of specific mRNAs as non-natural substrates.

Base Sequence↗
PubMed2002

Using CAVE technology for functional genomics studies.

We have established the first Java 3D-enabled CAVE (CAVE automated virtual environment). The Java application programming interface allows the complete separation of the program development from the program execution, opening new application domains for the CAVE technology. Programs can be developed on any Java-enabled computer platform, including Windows, Macintosh, and Linux workstations, and executed in the CAVE without modification. The introduction of Java, one of the major programming environments for bioinformatics, into the CAVE environment allows the rapid development applications for genome research, especially for the analysis of the spatial and temporal data that are being produced by functional genomics experiments. The CAVE technology will play a major role in the modeling of biological systems that is necessary to understand how these systems are organized and how they function.

Automation↗
PubMed2005

Functional Genomics meets neurodegenerative disorders. Part II: application and data integration.

The transcriptomic and proteomic techniques presented in part I (Functional Genomics meets neurodegenerative disorders. Part I: transcriptomic and proteomic technology) of this back-to-back review have been applied to a range of neurodegenerative disorders, including Huntington's disease (HD), Prion diseases (PrD), Creutzfeldt-Jakob disease, amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), frontotemporal dementia (FTD) and Parkinson's disease (PD). Samples have been derived either from human brain and cerebrospinal fluid, tissue culture cells or brains and spinal cord of experimental animal models. With the availability of huge data sets it will firstly be a major challenge to extract meaningful information and secondly, not to obtain contradicting results when data are collected in parallel from the same source of biological specimen using different techniques. Reliability of the data highly depends on proper normalization and validation both of which are discussed together with an outlook on developments that can be anticipated in the future and are expected to fuel the field. The new insight undoubtedly will lead to a redefinition and subdivision of disease entities based on biochemical criteria rather than the clinical presentation. This will have important implications for treatment strategies.

Animals↗