Stan Gaj

UNLABELLED: We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g. gene, protein or metabolite). GO-Elite exploits the structured nature of biological ontologies to report a minimal set of non-overlapping terms. The results can be visualized on WikiPathways or as networks. Built-in support is provided for over 60 species and 50 ID systems, covering gene, disease and phenotype ontologies, multiple pathway databases, biomarkers, and transcription factor and microRNA targets. GO-Elite is available as a web interface, GenMAPP-CS plugin and as a cross-platform application. AVAILABILITY: http://www.genmapp.org/go_elite

The chain of events leading from a toxic compound exposure to carcinogenicity is still barely understood. With the emergence of high-throughput sequencing, it is now possible to discover many different biological components simultaneously. Using two different RNA libraries, we sequenced the complete transcriptome of human HepG2 liver cells exposed to benzo[a]pyrene, a potent human carcinogen, across six time points. Data were integrated in order to reveal novel complex chemical-gene interactions. Notably, we hypothesized that the inhibition of MGMT, a DNA damage response enzyme, by the over-expressed miR-181a-1_3p induced by BaP, may lead to liver cancer over time.

Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.

Selenium is an essential micronutrient. Its recommended daily allowance is not attained by a significant proportion of the population in many countries and its intake has been suggested to affect colorectal carcinogenesis. Therefore, microarrays were used to determine how both selenoprotein and global gene expression patterns in the mouse colon were affected by marginal selenium deficiency comparable to variations in human dietary intakes. Two groups of 12 mice each were fed a selenium-deficient (0.086 mg Se/kg) or a selenium-adequate (0.15 mg Se/kg) diet. After 6 wk, plasma selenium level, liver, and colon glutathione peroxidase (GPx) activity in the deficient group was 12, 34, and 50%, respectively, of that of the adequate group. Differential gene expression was analysed with mouse 44K whole genome microarrays. Pathway analysis by GenMAPP identified the protein biosynthesis pathway as most significantly affected, followed by inflammation, Delta-Notch and Wnt pathways. Selected gene expression changes were confirmed by quantitative real-time PCR. GPx1 and the selenoproteins W, H, and M, responded significantly to selenium intake making them candidates as biomarkers for selenium status. Thus, feeding a marginal selenium-deficient diet resulted in distinct changes in global gene expression in the mouse colon. Modulation of cancer-related pathways may contribute to the higher susceptibility to colon carcinogenesis in low selenium status.