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. … Cystic Fibrosis (CF) 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.

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. … GeneChips AFFYMETRIX 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

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

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

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

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. KCNK5 This gene encodes one of the members of the superfamily of potassium channel proteins. The protein is highly sensitive to external pH. 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.

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 Pathway activation Promoter analysis 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. Find a specific inhibitor and validate 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. RNA extraction Nuli cells: Normal Lung Cufi cells: Cystic Fibrosis, (homozygote ∆F508) Future work hybridation Scanning by bioanalyzer Data acquisition Normalization by RMA express Statistical analysis with Bioconductor (AffyLM package).CEL DEGs Cut off Observation !! Pathway-express Onto-express Interest DEGs Biological question Q-PCR protein expression Pathway activation Promoter analysis Conclusion about biological question Others microarray experiments Same problematic. Same technology Different model Different organism Different design + experimental conditions : oxydant Berthiaume Xu Radzioch Virella-Lowell ZabnerWright.CEL Normalization by RMA express Statistical analysis with Bioconductor (AffyLM package) DEGs Comparaison Conclusion more precise about biological question 1. Zabner J, Scheetz TE, Almabrazi HG, Casavant TL, Huang J, Keshavjee S, McCray PB Jr.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.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.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.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.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.

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

22. Analyse ontologique…....sur l’ensemble des probesets modulés...sur l’ensemble des...sur l’ensemble des 1296 probesets down-regules 1296 probesets down-regules...sur l’ensemble...sur l’ensemble 1039 probesetsup-regules 1039 probesets up-regules 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. 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

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 B statistic 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