1 / 25

Optimization of differential expression analysis in genetic disease : Cystic Fibrosis.

Optimization of differential expression analysis in genetic disease : Cystic Fibrosis. Voisin Grégory Lemieux’s lab -IRIC February 2007. Codirected by Dr Yves Berthiaume (CRCHUM). A few words about…. Clinical symptoms : Accumulation of mucus in lungs.

zeno
Download Presentation

Optimization of differential expression analysis in genetic disease : Cystic Fibrosis.

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Optimization of differential expression analysis in genetic disease : Cystic Fibrosis. Voisin Grégory Lemieux’s lab -IRIC February 2007. Codirected by Dr Yves Berthiaume (CRCHUM)

  2. A few words about…

  3. Clinical symptoms : Accumulation of mucus in lungs. Obstruction of pancreatic and hepatic ducts. Fibrosis of tissues. The hallmark: chronic infection (P. aeruginosa) and EXCESSIVE INFLAMMATION. … Cystic Fibrosis (CF)

  4. … CFTR • CFTR: Cystic Fibrosis Transmembrane conductance Regulator. • Member 7 of ATP binding cassette transporter family. • Critical Physiological Function: Chlorure ionic Channel. • + 1000 mutations (most frequent = ΔF508 ) .

  5. Based on hybrizidation mRNA/probe Human Genome U133.2 +: 47 000 transcripts and variants, (38 500 well characterized human genes). = 54675 numeric Data for exploitation … GeneChips AFFYMETRIX

  6. Problematics • Bioinformatics problematic: establish a robust methodology to allow effective data-mining. • Molecular and biological problematic: understand the molecular regulation of inflammation. • Clinical problematic: understand the developpement, inflammation installation of disease.

  7. Our microarray experiment

  8. Hypothesis (Inflammatory) genes regulation <=> CFTR ? CFTR deficiency in Human Alveolar Epithelium cells triggers specific pathways involved in the inflammatory response.

  9. Methodology .CEL DEGs Interesting DEGs RNA extraction Normalization by RMA express Cufi cells: Cystic Fibrosis, (homozygote ∆F508) Hybridation Statistical analysis with Bioconductor (AffyLM package) Scanning by bioanalyzer Nuli cells: Normal Lung Data acquisition Observation Q-PCR Pathway-express Protein expression Onto-express Biologicalquestion Pathway activation New elements about biological question Promoter analysis DEGs: Differential Expressed Gene

  10. Specific Objectives • Differential expression analysis. • Biological processes modulated. • Metabolic pathways modulated. • Promotor-oriented Analysis.

  11. Interesting DEGs DEGs Results 1659 annotated DEGS. Observation 2335 PROBESETS differentially expressed. 871 DEGs DOWN-regulated 788 DEGs UP-regulated 202 genes NA + 474 n-plicate Toll-like receptor Signaling Pathway Jak-Stat signaling Pathway Pathway-express Immune response, inflammatory response, chemotaxis, signal transduction, transport, lipid metabolism. Onto-express 28 tested genes. Confirmed expression: IL1b, IL8, IL6, CXCL10 ,CXCL11,CLCA4, KCNK5, STAT1, GSTT1. Q-PCR 10 tested proteins. Confirmed expression: CXCL11, IL8, 10,15, CCL 2,8, 7. Protein expression

  12. Microarray modulated genes in Toll-like Receptor Signaling Pathway.

  13. Microarray modulated genes in Jak-Stat Signaling Pathway.

  14. Non-inflammatory gene validated by QPCR Glutathione S-transferase (GST) theta 1 (GSTT1) is a memberof a superfamily of proteins that catalyze the conjugation of reduced glutathione to a variety of electrophilic and hydrophobic compounds. • CLCA4 • The protein encoded by this gene belongs to the • calcium sensitive chloride conductance protein family. • The exact function of this protein is not known. KCNK5 This gene encodes one of the members of the superfamily of potassium channel proteins . The protein is highly sensitive to external pH.

  15. Interpretations • In the absence of pathogen agents, we observe an up-regulation of several inflammatory actors in Cufi cells. • CFTR deficiency could be responsible for an excessive immune and inflammatory response. • There could be a dysregulation of TLR and Jak-Stat Signaling pathway in CF cells.

  16. Work in progress • Selection of 96 modulated genes with • GO = inflammatory response, immune response, • chemotaxis. • Analysis of 2200 bp of these promoters to find • Transcription Factor (TF) sites or module of TF • sites over represented. Promoter analysis Find a specific inhibitor and validate pathway activation. Pathway activation

  17. Limitations of our optimization • Over 1500 modulated genes. • Inconsistent and incomplete annotations. • Concepts used in methodology produce a technical bias. • Transcriptomics analysis only.

  18. Future work .CEL .CEL .CEL .CEL .CEL .CEL .CEL .CEL .CEL .CEL .CEL DEGs DEGs DEGs DEGs DEGs DEGs DEGs Interest DEGs Others microarray experiments RNA extraction Normalization by RMA express Cufi cells: Cystic Fibrosis, (homozygote ∆F508) hybridation Berthiaume Zabner Wright Same problematic. Same technology Different model Different organism Different design Statistical analysis with Bioconductor (AffyLM package) Scanning by bioanalyzer Xu Virella-Lowell Cut off Radzioch Nuli cells: Normal Lung Data acquisition + experimental conditions : oxydant 1. Zabner J, Scheetz TE, Almabrazi HG, Casavant TL, Huang J, Keshavjee S, McCray PB Jr. CFTR DeltaF508 mutation has minimal effect on the gene expression Am J Physiol Lung Cell Mol Physiol. 2005 Oct;289(4):L545-53. Epub 2005 Jun 3. 2. Wright JM, Merlo CA, Reynolds JB, Zeitlin PL, Garcia JG, Guggino WB, Boyle MP. Respiratory epithelial gene expression in patients with mild and severe cystic fibrosis lung disease.Am J Respir Cell Mol Biol. 2006 Sep;35(3):327-36. Epub 2006 Apr 13. ] 3. Xu Y, Liu C, Clark JC, Whitsett JA. Functional genomic responses to cystic fibrosis transmembrane conductance regulator (CFTR) and CFTR(delta508) in the lung.J Biol Chem. 2006 Apr 21;281(16):11279-91. Epub 2006 Feb 2. 4. Guilbault C, Novak JP, Martin P, Boghdady ML, Saeed Z, Guiot MC, Hudson TJ, Radzioch D. Distinct pattern of lung gene expression in the Cftr-KO mice developing spontaneous lung disease compared with their littermate controls.Physiol Genomics. 2006 Apr 13;25(2):179-93. Epub 2006 Jan 17. 5. Virella-Lowell I, Herlihy JD, Liu B, Lopez C, Cruz P, Muller C, Baker HV, Flotte TR. Effects of CFTR, interleukin-10, and Pseudomonas aeruginosa on gene expression profiles in a CF bronchial epithelial cell Line. Mol Ther. 2004 Sep;10(3):562-73. Normalization by RMA express Comparaison Statistical analysis with Bioconductor (AffyLM package) Observation !! Pathway-express Biologicalquestion Onto-express Q-PCR Conclusion more precise about biological question protein expression Conclusion about biological question Pathway activation Promoter analysis

  19. Acknowledgements • Dr Sébastien Lemieux. • Dr Yves Berthiaume. • Dr André Dagenais. • Members of Berthiaume’s Lab. • Members of Lemieux’s Lab. • IRIC’S Genomics Platform.

  20. EXTRA : Range values 0.01<Adjusted Pvalues<10℮-13 0.5<Expression probability<1 0.006<Expression Ratio <19

  21. EXTRA: :Confirmation by QPCR of gene expression . NULI CUFI RATIO qPCR 3,6 5,4 4,7 5,5 4,9 0,0004 0,028 0,02 0,01 P-value qPCR 0,002 RATIO MICROARRAY 4 17 9 18 2 EXPRES.PROBAB. MICROARRAY >95% >95 % >95 % >50% >95 %

  22. Analyse ontologique…. ...sur l’ensemble des 1296 probesets down-regules ...sur l’ensemble des probesets modulés ...sur l’ensemble 1039 probesetsup-regules METABOLISME: lipid metabolism protein biosynthesis MODIFICATION DE PROTEINE: protein amino acid phosphorylation Proteine byosynthese TRANSCRIPTION: TRANSPORT electron transport MECANISME DE DEFENSE: immune response inflammatory response COMMUNICATION CELLULAIRE: cell-cell signaling chemotaxis. cell adhesion METABOLISME: lipid metabolism protein biosynthesis VOIE DE SIGNALISATION TRANSPORT electron transport MECANISME DE DEFENSE: immune response inflammatory response COMMUNICATION CELLULAIRE: cell-cell signaling chemotaxis cell adhesion METABOLISME: lipid metabolism SIGNAL DE TRANSDUCTION: Cell surface receptor linked signal transduction Positive regulation of I-kappa b Intracellular signaling cascade.

  23. Activation of NF-kappa B in Cufi and Nuli Cells Hypothesis : Another system of TF could modulated inflammatory genes

  24. Empirical Bayes log posterior odds statistic • The Bstatistic is the log odds of differential expression (also known as a lod score). Bascially if it is greater than 0 then you have more than a 50/50 chance that your gene is truly differentially expressed given its fitted M value

More Related