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Results for “Functional Genomics”

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PubMed2005

A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics.

Inferring large-scale covariance matrices from sparse genomic data is an ubiquitous problem in bioinformatics. Clearly, the widely used standard covariance and correlation estimators are ill-suited for this purpose. As statistically efficient and computationally fast alternative we propose a novel shrinkage covariance estimator that exploits the Ledoit-Wolf (2003) lemma for analytic calculation of the optimal shrinkage intensity. Subsequently, we apply this improved covariance estimator (which has guaranteed minimum mean squared error, is well-conditioned, and is always positive definite even for small sample sizes) to the problem of inferring large-scale gene association networks. We show that it performs very favorably compared to competing approaches both in simulations as well as in application to real expression data.

Journal Article↗
PubMed2006

Metabolomics as a functional genomic tool for understanding lipid dysfunction in diabetes, obesity and related disorders.

With the rise of systems biology, a number of approaches have been developed to globally profile a tier of organization in a cell, tissue or organism. Metabolomics is an approach that attempts to profile all the metabolites in a biological matrix. One of the major challenges of this approach, as with other 'omic' technologies, is that the metabolome is context-dependent and will vary with pathology, developmental stage and environmental factors. Thus, the possibility of globally profiling the metabolome of an organism is a genuine analytical challenge, as by definition this must also take into consideration all relevant factors that influence metabolism. Despite these challenges, the approach has already been applied to understand the metabolism in a range of animal models, and has more recently started to be projected into the clinical situation. In this review, the technologies currently being used in metabolomics will be assessed prior to examining their use to study diseases related to the metabolic syndrome, including Type II diabetes, obesity, cardiovascular disease and fatty liver disease.

Animals↗
PubMed2002

Functional genomics of the endocrine pancreas: the pancreas clone set and PancChip, new resources for diabetes research.

Over the past 5 years, microarrays have greatly facilitated large-scale analysis of gene expression levels. Although these arrays were not specifically geared to represent tissues and pathways known to be affected by diabetes, they have been used in both type 1 and type 2 diabetes research. To prepare a tool that is particularly useful in the study of type 1 diabetes, we have assembled a nonredundant set of 3,400 clones representing genes expressed in the mouse pancreas or pathways known to be affected by diabetes. We have demonstrated the usefulness of this clone set by preparing a cDNA glass microarray, the PancChip, and using it to analyze pancreatic gene expression from embryonic day 14.5 through adulthood in mice. The clone set and corresponding array are useful resources for diabetes research.

Adult↗
PubMed2004

Chronic effects of fatty acids on pancreatic beta-cell function: new insights from functional genomics.

Type 2 diabetes can be viewed as a failure of the pancreatic beta-cell to compensate for peripheral insulin resistance with enhanced insulin secretion. This failure is explained by both a relative loss of beta-cell mass as well as secretory defects that include enhanced basal secretion and a selective loss of sensitivity to glucose. These features are reproduced by chronic exposure of beta-cells to fatty acids (FAs), suggesting that hyperlipidemia might contribute to decompensation. Using MIN6 cells pretreated for 48 h with oleate or palmitate, we have previously defined alterations in global gene expression by transcript profiling and described additional secretory changes to those already established (Busch A-K, Cordery D, Denyer G, Biden TJ: Diabetes 51:977-987, 2002). In contrast to a modest decoupling of glucose-stimulated insulin secretion, FA pretreatment markedly enhanced the secretory response to an acute subsequent challenge with FAs. We propose that this apparent switch in sensitivity from glucose to FAs would be an appropriate response to hyperlipidemia in vivo and thus plays a positive role in beta-cell compensation for insulin resistance. Altered expression of dozens of genes could contribute to this switch, and allelic variations in any of these genes could (to varying degrees) impair beta-cell compensation and thus contribute to conditions ranging from impaired glucose tolerance to frank diabetes.

Animals↗
PubMed2001

Functional genomics in sarcoidosis--reduced or increased apoptosis?

BACKGROUND: A variety of studies have stressed the importance of the control of inflammatory cell longevity and the balance of pro-survival and pro-apoptotic signaling pathways. The aim of the study was to investigate the systemic activation of apoptosis pathways using cDNA array technology in patients with acute onset sarcoidosis. METHOD: We have performed a comprehensive genomic analysis, applying high-density human GeneChip probe arrays (HGU95A, Affymetrix) for RNA expression profiling from peripheral blood mononuclear cells from patients with acute pulmonary sarcoidosis and matched healthy controls. Twelve patients and 12 controls were assessed, mean age 36 +/- 12 and 33 +/- 10 years respectively. Results focus on apoptosis-related gene products. Group differences were assessed with the Mann-Whitney U-test. RESULTS: Seven patients had self-limited disease (all type I sarcoidosis) and 5 progressive disease requiring immunosuppression (all type II or III sarcoidosis). We found 53 of 112 (47%) apoptosis-related gene products dysregulated in sarcoidosis compared to controls. Particular growth factors, especially heparin-binding EGF-like GF, EGF, PDEGF, SISPDGF2 and VEGF, were upregulated in patients consistent with a pro-survival profile. The Bcl-2 family of genes also showed a net pro-survival profile in sarcoidosis patients. In contrast, alterations in the TNF-pathway were compatible with increased apoptosis signals in both, type I and type II/III sarcoidosis patients. Other cell death receptors were equally expressed, as were caspases and p53-associated genes. In contrast to patients with type I-sarcoidosis, patients with progressive type II or III disease showed an upregulation of NFKB and a leak of downregulation of inhibitor of apoptosis 1. CONCLUSION: Significant differences in the expression of apoptosis-related genes were found in peripheral blood of patients with acute onset sarcoidosis. Gene expression did not show a definite pattern that was suggestive of pro-survival or proapoptosis. However, the number of genes whose altered expression would be predicted to favour increased survival exceeded that of genes likely to reduce survival. Protein-based confirmation of the differences in the activity of apoptosis-pathways needs to be done in further studies.

Acute Disease↗
PubMed2003

Functional genomics and gene microarrays--the use in research and clinical medicine.

In the year 2000, the Human Genome Project Consortium presented the first complete draft of the human genome together with Celera Genetics. Since then, the so-called "post-genome era" has started. Microarrays are capable of profiling gene expression patterns of tens of thousands of genes in a single experiment and thus allow a systematic analysis of DNA and RNA variation. They seem likely to become a standard tool of both molecular biology research and clinical diagnostics. These prospects have attracted great interest and investment from both the public and private sectors. This review introduces the principle of microarray technology and gives an overview of its current and future potential in clinical medicine.

Animals↗
PubMed2004

From the sequence to cell modeling: comprehensive functional genomics in Escherichia coli.

As a result of the enormous amount of information that has been collected with E. coli over the past half century (e.g. genome sequence, mutant phenotypes, metabolic and regulatory networks, etc.), we now have detailed knowledge about gene regulation, protein activity, several hundred enzyme reactions, metabolic pathways, macromolecular machines, and regulatory interactions for this model organism. However, understanding how all these processes interact to form a living cell will require further characterization, quantification, data integration, and mathematical modeling, systems biology. No organism can rival E. coli with respect to the amount of available basic information and experimental tractability for the technologies needed for this undertaking. A focused, systematic effort to understand the E. coli cell will accelerate the development of new post-genomic technologies, including both experimental and computational tools. It will also lead to new technologies that will be applicable to other organisms, from microbes to plants, animals, and humans. E. coli is not only the best studied free-living model organism, but is also an extensively used microbe for industrial applications, especially for the production of small molecules of interest. It is an excellent representative of Gram-negative commensal bacteria. E. coli may represent a perfect model organism for systems biology that is aimed at elucidating both its free-living and commensal life-styles, which should open the door to whole-cell modeling and simulation.

Computational Biology↗
PubMed2000

Twin studies of schizophrenia: from bow-and-arrow concordances to star wars Mx and functional genomics.

Twin studies have been vital for establishing an important genetic contribution to the etiology of schizophrenia. The five newest studies since 1995 from Europe and Japan have confirmed earlier findings. They yielded probandwise concordance rates of 41-65% in monozygotic (MZ) pairs and 0-28% in dizygotic (DZ) pairs, and heritability estimates of approximately 80-85%. Twin studies are also valuable for investigating the etiological relationships between schizophrenia and other disorders, and the genetic basis of clinical heterogeneity within schizophrenia. Studies of discordant MZ pairs provide further insights into non-inherited factors that contribute to the multifactorial etiology of this disorder. More recently, twin studies have begun to be used to directly investigate molecular genetic and epigenetic processes underlying schizophrenia.

Data Interpretation, Statistical↗
PubMed2001

Functional genomics and cell wall biosynthesis in loblolly pine.

Loblolly pine (Pinus taeda L.) is the most widely planted tree species in the USA and an important tree in commercial forestry world-wide. The large genome size and long generation time of this species present obstacles to both breeding and molecular genetic analysis. Gene discovery by partial DNA sequence determination of cDNA clones is an effective means of building a knowledge base for molecular investigations of mechanisms governing aspects of pine growth and development, including the commercially relevant properties of secondary cell walls in wood. Microarray experiments utilizing pine cDNA clones can be used to gain additional information about the potential roles of expressed genes in wood formation. Different methods have been used to analyze data from first-generation pine microarrays, with differing degrees of success. Disparities in predictions of differential gene expression between cDNA sequencing experiments and microarray experiments arise from differences in the nature of the respective analyses, but both approaches provide lists of candidate genes which should be further investigated for potential roles in cell wall formation in differentiating pine secondary xylem. Some of these genes seem to be specific to pine, while others also occur in model plants such as Arabidopsis, where they could be more efficiently investigated.

Arabidopsis↗