RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis

<p>Abstract</p> <p>Background</p> <p>The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such as GoMiner can leverage GO to perform ontological analysis of microarray and proteomics studies, typically generating a list of significant functional categories. Two or more of the categories are often redundant, in the sense that identical or nearly-identical sets of genes map to the categories. The redundancy might typically inflate the report of significant categories by a factor of three-fold, create an illusion of an overly long list of significant categories, and obscure the relevant biological interpretation.</p> <p>Results</p> <p>We now introduce a new resource, RedundancyMiner, that de-replicates the redundant and nearly-redundant GO categories that had been determined by first running GoMiner. The main algorithm of RedundancyMiner, MultiClust, performs a novel form of cluster analysis in which a GO category might belong to several category clusters. Each category cluster follows a "complete linkage" paradigm. The metric is a similarity measure that captures the overlap in gene mapping between pairs of categories.</p> <p>Conclusions</p> <p>RedundancyMiner effectively eliminated redundancies from a set of GO categories. For illustration, we have applied it to the clarification of the results arising from two current studies: (1) assessment of the gene expression profiles obtained by laser capture microdissection (LCM) of serial cryosections of the retina at the site of final optic fissure closure in the mouse embryos at specific embryonic stages, and (2) analysis of a conceptual data set obtained by examining a list of genes deemed to be "kinetochore" genes.</p

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

Gene expression changes associated with Barrett's esophagus and Barrett's-associated adenocarcinoma cell lines after acid or bile salt exposure

<p>Abstract</p> <p>Background</p> <p>Esophageal reflux and Barrett's esophagus represent two major risk factors for the development of esophageal adenocarcinoma. Previous studies have shown that brief exposure of the Barrett's-associated adenocarcinoma cell line, SEG-1, or primary cultures of Barrett's esophageal tissues to acid or bile results in changes consistent with cell proliferation. In this study, we determined whether similar exposure to acid or bile salts results in gene expression changes that provide insights into malignant transformation.</p> <p>Methods</p> <p>Using previously published methods, Barrett's-associated esophageal adenocarcinoma cell lines and primary cultures of Barrett's esophageal tissue were exposed to short pulses of acid or bile salts followed by incubation in culture media at pH 7.4. A genome-wide assessment of gene expression was then determined for the samples using cDNA microarrays. Subsequent analysis evaluated for statistical differences in gene expression with and without treatment.</p> <p>Results</p> <p>The SEG-1 cell line showed changes in gene expression that was dependent on the length of exposure to pH 3.5. Further analysis using the Gene Ontology, however, showed that representation by genes associated with cell proliferation is not enhanced by acid exposure. The changes in gene expression also did not involve genes known to be differentially expressed in esophageal adenocarcinoma. Similar experiments using short-term primary cultures of Barrett's esophagus also did not result in detectable changes in gene expression with either acid or bile salt exposure.</p> <p>Conclusion</p> <p>Short-term exposure of esophageal adenocarcinoma SEG-1 cells or primary cultures of Barrett's esophagus does not result in gene expression changes that are consistent with enhanced cell proliferation. Thus other model systems are needed that may reflect the impact of acid and bile salt exposure on the esophagus <it>in vivo</it>.</p

Glucocorticoids with different chemical structures but similar glucocorticoid receptor potency regulate subsets of common and unique genes in human trabecular meshwork cells

<p>Abstract</p> <p>Background</p> <p>In addition to their well-documented ocular therapeutic effects, glucocorticoids (GCs) can cause sight-threatening side-effects including ocular hypertension presumably via morphological and biochemical changes in trabecular meshwork (TM) cells. In the present study, we directly compared the glucocorticoid receptor (GR) potency for dexamethasone (DEX), fluocinolone acetonide (FA) and triamcinolone acetonide (TA), examined the expression of known GRα and GRβ isoforms, and used gene expression microarrays to compare the effects of DEX, FA, and TA on the complete transcriptome in two primary human TM cell lines.</p> <p>Methods</p> <p>GR binding affinity for DEX, FA, and TA was measured by a cell-free competitive radio-labeled GR binding assay. GR-mediated transcriptional activity was assessed using the GeneBLAzer beta-lactamase reporter gene assay. Levels of GRα and GRβ isoforms were assessed by Western blot. Total RNA was extracted from TM 86 and TM 93 cells treated with 1 μM DEX, FA, or TA for 24 hr and used for microarray gene expression analysis. The microarray experiments were repeated three times. Differentially expressed genes were identified by Rosetta Resolver Gene Expression Analysis System.</p> <p>Results</p> <p>The GR binding affinity (IC₅₀) for DEX, FA, and TA was 5.4, 2.0, and 1.5 nM, respectively. These values are similar to the GR transactivation EC₅₀of 3.0, 0.7, and 1.5 nM for DEX, FA, and TA, respectively. All four GRα translational isoforms (A-D) were expressed in TM 86 and TM 93 total cell lysates, however, the C and D isoforms were more highly expressed relative to A and B. All four GRβ isoforms (A-D) were also detected in TM cells, although GRβ-D isoform expression was lower compared to that of the A, B, or C isoforms. Microarray analysis revealed 1,968 and 1,150 genes commonly regulated by DEX, FA, and TA in TM 86 and TM 93, respectively. These genes included RGC32, OCA2, ANGPTL7, MYOC, FKBP5, SAA1 and ZBTB16. In addition, each GC specifically regulated a unique set of genes in both TM cell lines. Using Ingenuity Pathway Analysis (IPA) software, analysis of the data from TM 86 cells showed that DEX significantly regulated transcripts associated with RNA post-transcriptional modifications, whereas FA and TA modulated genes involved in lipid metabolism and cell morphology, respectively. In TM 93 cells, DEX significantly regulated genes implicated in histone methylation, whereas FA and TA altered genes associated with cell cycle and cell adhesion, respectively.</p> <p>Conclusion</p> <p>Human trabecular meshwork cells in culture express all known GRα and GRβ translational isoforms, and GCs with similar potency but subtly different chemical structure are capable of regulating common and unique gene subsets and presumably biologic responses in these cells. These GC structure-dependent effects appear to be TM cell-lineage dependent.</p

Adding a Little Reality to Building Ontologies for Biology

BACKGROUND: Many areas of biology are open to mathematical and computational modelling. The application of discrete, logical formalisms defines the field of biomedical ontologies. Ontologies have been put to many uses in bioinformatics. The most widespread is for description of entities about which data have been collected, allowing integration and analysis across multiple resources. There are now over 60 ontologies in active use, increasingly developed as large, international collaborations. There are, however, many opinions on how ontologies should be authored; that is, what is appropriate for representation. Recently, a common opinion has been the "realist" approach that places restrictions upon the style of modelling considered to be appropriate. METHODOLOGY/PRINCIPAL FINDINGS: Here, we use a number of case studies for describing the results of biological experiments. We investigate the ways in which these could be represented using both realist and non-realist approaches; we consider the limitations and advantages of each of these models. CONCLUSIONS/SIGNIFICANCE: From our analysis, we conclude that while realist principles may enable straight-forward modelling for some topics, there are crucial aspects of science and the phenomena it studies that do not fit into this approach; realism appears to be over-simplistic which, perversely, results in overly complex ontological models. We suggest that it is impossible to avoid compromise in modelling ontology; a clearer understanding of these compromises will better enable appropriate modelling, fulfilling the many needs for discrete mathematical models within computational biology

Modulation of gene expression in heart and liver of hibernating black bears (Ursus americanus)

<p>Abstract</p> <p>Background</p> <p>Hibernation is an adaptive strategy to survive in highly seasonal or unpredictable environments. The molecular and genetic basis of hibernation physiology in mammals has only recently been studied using large scale genomic approaches. We analyzed gene expression in the American black bear, <it>Ursus americanus</it>, using a custom 12,800 cDNA probe microarray to detect differences in expression that occur in heart and liver during winter hibernation in comparison to summer active animals.</p> <p>Results</p> <p>We identified 245 genes in heart and 319 genes in liver that were differentially expressed between winter and summer. The expression of 24 genes was significantly elevated during hibernation in both heart and liver. These genes are mostly involved in lipid catabolism and protein biosynthesis and include RNA binding protein motif 3 (<it>Rbm3</it>), which enhances protein synthesis at mildly hypothermic temperatures. Elevated expression of protein biosynthesis genes suggests induction of translation that may be related to adaptive mechanisms reducing cardiac and muscle atrophies over extended periods of low metabolism and immobility during hibernation in bears. Coordinated reduction of transcription of genes involved in amino acid catabolism suggests redirection of amino acids from catabolic pathways to protein biosynthesis. We identify common for black bears and small mammalian hibernators transcriptional changes in the liver that include induction of genes responsible for fatty acid β oxidation and carbohydrate synthesis and depression of genes involved in lipid biosynthesis, carbohydrate catabolism, cellular respiration and detoxification pathways.</p> <p>Conclusions</p> <p>Our findings show that modulation of gene expression during winter hibernation represents molecular mechanism of adaptation to extreme environments.</p

Identification and characterization of seed-specific transcription factors regulating anthocyanin biosynthesis in black rice

Black rice is rich in anthocyanin and is expected to have more healthful dietary potential than white rice. We assessed expression of anthocyanin in black rice cultivars using a newly designed 135 K Oryza sativa microarray. A total of 12,673 genes exhibited greater than 2.0-fold up- or down-regulation in comparisons between three rice cultivars and three seed developmental stages. The 137 transcription factor genes found to be associated with production of anthocyanin pigment were classified into 10 groups. In addition, 17 unknown and hypothetical genes were identified from comparisons between the rice cultivars. Finally, 15 out of the 17 candidate genes were verified by RT-PCR analysis. Among the genes, nine were up-regulated and six exhibited down-regulation. These genes likely play either a regulatory role in anthocyanin biosynthesis or are related to anthocyanin metabolism during flavonoid biosynthesis. While these genes require further validation, the results here underline the potential use of the new microarray and provide valuable insight into anthocyanin pigment production in rice