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Functional Genomics

Functional Genomics. Global Gene Expression. A global picture of gene expression A pathway (inflammation) can be studied Study under a specific condition Compare, experimental with control Both are simultaneously studied on same array = two experiments on one array.

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Functional Genomics

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  1. Functional Genomics Global Gene Expression

  2. A global picture of gene expression A pathway (inflammation) can be studied Study under a specific condition Compare, experimental with control Both are simultaneously studied on same array = two experiments on one array

  3. FASEB J. 16: 61-71 (2002)

  4. Background - Glucocorticoids • Immuno-modulatory agent • Anti-inflammatory & immunosuppressive = both beneficial & harmful • Better understanding of its action will lead to useful in designing more specific and efficient treatment strategies. • Study revealed hitherto unknown enhancing and suppressive actions on immune cells

  5. Study Design • PBMC – subjected to various concentrations of GC for various time • RNA extracted – cDNA cy3/ cy5 labelled • Hybridized to 9182 (GEM microarray, Incyte Genomics): • Detection range – 2 – 2000 pg

  6. Quality control • Reproducibility evaluated by validaiton study – www.incyte.com/incyte_science/technology/gem/reproducibility.shtml • Special Control DNA & known RNA set in each Hybridization experiment • All results assessed for labelling, hybridization & sensitivity

  7. Global Gene Expression Analysis 9% , 845+41 genes 12%, 1125+135 genes

  8. Correlation between Differential Gene Expression on one expt with another.

  9. Over / under expressed Genes

  10. Quantitation of mRNA expression in TaqMan Resting CD3/CD28 Activated

  11. Differential Gene Expression Identifies Novel Markers of CD4+ and CD8+ T Cell Activation Following Stimulation by Mycobacterium tuberculosis1 Jacqueline M. Cliff2,*, Iryna N. J. Andrade*, Rohit Mistry  ,  , Christopher L. Clayton  , Mark G. Lennon  , Alan P. Lewis  , Ken Duncan  , Pauline T. Lukey   and Hazel M. Dockrell* * Department of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom; GlaxoSmithKline Research and Development, Stevenage, United Kingdom; and Medical Research Council Centre forMolecular & Cellular Studies, University of Stellenbosch, Cape Town, South Africa J.Immunol. 173: 485-493 (2004) T cell activation in response to antigenic stimulation is acomplex process, involving changes in the expression level ofa large number of genes. We have used cDNA array technologyto characterize the differences in gene expression between humanCD4+ and CD8+ T cells. PBMC from six healthy donors were stimulatedwith live Mycobacterium tuberculosis, and the gene expressionprofiles of each donor’s CD4+ and CD8+ T cells were analyzedseparately. ANOVA revealed 518 genes that were consistentlydifferentially expressed between CD4+ and CD8+ T cells. Thesedifferentially expressed genes include a combination of well-known,previously characterized genes with a range of biological functionsand unknown in silico predicted hypothetical genes. Where possible,the novel genes have been characterized using bioinformatics,and putative transcription factors, signaling molecules, transmembrane,and secreted factors have been identified. A subset of thesedifferentially expressed genes could be exploited as markersof CD4+ and CD8+ T cell activation for use in vaccine trials.These observed differences in the gene expression profile ofCD4+ and CD8+ T cells following activation by a human pathogencontribute to an increased understanding of T cell activationand differentiation and the roles these T cell subsets may playin immunity to infection.

  12. Healthy Blood Donors, N = 6 PBMC from buffy coats H37Rv 1:1 incubated 6 days ctl / 1:1 H37Rv 16 hrs restimulation CD4 / CD8 isolation DynaBead magnetic isolaiton 15ug RNA 5ug used for cDNA synthesis with cy3 / cy5

  13. Conclusion • The purpose of experiment is important • A robust design is essential • Speficific pathways can be studied (few 100 genes / questions can be asked)

  14. 2005 Functional Genomics Pulmonary Tuberculosis Global Gene Expression Analysis 19k

  15. Microarray expts • PBMCs Pts/Ctls 1x10 • Stimulate with antigen (PPD) – 18hrs • Extract total RNA / cDNA • Label with cy3 or cy5 • Hybridize to 1.7k / 19 k UHN Toronto chips (slides)

  16. Each gene probe = 10 nl spot PE ScanArray Express

  17. genes CTL PTB Comparison of 4 controls with 4 caste, sex, age matched Pulmonary tuberculosis patients Heat Diagram: Microarray 1.7k Toronto Human array

  18. Comparison of Gene expression in BCG negative and BCG positive healthy endemic controls using UHN Toronto 1.7k cDNA array BCG Neg BCG Pos

  19. genes DR2 POS DR2 NEG Heat Diagram: Microarray 1.7k Toronto Human array of 13 Endemic Controls HLA DR2 status

  20. Heat map analysis of gene expression in HLA DR2 negative and DR2 positive healthy endemic controls using UHN Toronto 19k cDNA array DR2 Neg DR2 Pos Metabolic pathways Membrane receptors Immunological pathways Th1/Th2 pathways Inflammatory pathways Stress pathways Etc.,

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