Functional differentiation of goat mammary epithelium. A microarray preliminary approach

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Martin 1 1 Unité Génomique et Physiologie de la Lactation, PICT-GEL, INRA, Jouy en Josas, 78352, France 2 Institut

1 Functional differentiation of goat mammary epithelium. A microarray preliminary approach F. Faucon 1,2, E. Zalachas 1, S. Robin 3 and P. Martin 1 1 Unité Génomique et Physiologie de la Lactation, PICT-GEL, INRA, Jouy en Josas, 78352, France 2 Institut Elevage, Paris, 75012, France 3 Unité Mixte de Recherche 518, AgroParisTech, Paris, 75005, France felicie.faucon@jouy.inra.fr patrice.martin@jouy.inra.fr Session 34 Theatre 8-58 th Annual EAAP Meeting, Dublin, August 2007

2 Introduction : mammary gland differentiation during pregnancy P R E G N A N C Y Fertilization Hormonal regulation Endocrine : ovarian; pituitary; placental; suprarenal Paracrine Lactation Adapted from «Cours sur la Biologie de la Lactation», Université de Sherbrooke, P. Lacasse ; Zhou et al., 2005, The EMBO Journal, 24,

3 Main issue Tissue interactions and tissue differentiation mechanisms Mechanisms of mammary gland development - Main hormonal regulations Knowledge What are the main functional networks operating in the mammary tissue during its differentiation?

4 How to proceed? By drawing expression profile of genes during goat pregnancy 4 developmental stages (P46, P70, P90, P110) 1 lactation stage (L40) G N A P R E N P46 P70 P90 C Y Fertilization P days Lactation L40 3 primiparous goats for each developmental stage Transcriptomic approach : microarray experiment

5 Materials and methods : animals and experimental plan 18 oligoarrays (22 k, Operon and Illumina bovine sets, CRB INRA Jouy-en-Josas, France) Mammary tissue harvesting Loop experimental design (kinetic approach) 9 dye-swaps P46-1 L40-2 L40-1 P110-3 P110-2 L40-3 P46-2 P46-3 P70-1 P70-2 P70-3 Optimization by variance minimization P110-1 P90-3 P90-2 P90-1

Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Crushing Total

6 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Crushing Total RNA extraction RNA RNA Reverse transcription cdna Cy3 Labelling Cy5 cdna cdna cdna Hybridization Scan Swap = CyDyes inversion in the 2 nd slide

7 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Feature Extraction software (Agilent Technologies) All flag* settings were taken into account * Flag = elimination

8 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Lowess normalization method (R, Anapuce library, J. Aubert) M = log(cyanine 5) log(cyanine 3) A = (log[cyanine 5+ log[cyanine 3]) / 2

9 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Linear regression : Y = XΘ + E Y : signal log(cyanine 5/Cyanine 3) X : experimental design Θ : difference between stage n+1 and stage n E : residual Significance threshold : 0.05

10 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection K means clustering (selection of 7 clusters, TMeV software)

11 Materials and methods : microarray experiment Lab extraction normalization Statistical analysis Clustering Network detection Ingenuity Pathways Analysis web data base

12 Results : general data information Amongst 23,232 probes No regression available data 16,556 probes 2,258 genes with regression parameters significantly not null (expression profiles not flat)

13 Results : overview of 5 clusters Cluster 1 (399 probes) Θ 1 Θ 2 Θ 3 P46 P70 P90 P110 L40 Lipid metabolism Θ 1 Θ 2 Θ 3 Cluster 2 (68 probes) P70 P110 Θ 1 Θ 2 Θ 3 P46 P90 L40 Immune response Θ 1 Θ 2 Θ 3

14 Results : overview of 5 clusters Cluster 3 (654 probes) Θ 1 Θ 2 Θ P46 P70 P90 3 P110 L40 Cell cycle Θ 1 Θ 2 Θ 3 Cluster 4 (608 probes) P46 Tissue development Organ development Θ 1 Θ 2 Θ P70 P90 3 P110 L40 Θ 1 Θ 2 Θ 3

15 Results : overview of 5 clusters Cluster 5 (529 probes) Θ 2 Θ 3 P70 P90 P110 L40 Θ 1 P46 Energy production Carbohydrate metabolism Θ 1 Θ 2 Θ 3

16 Discussion : results validation DAVID database using GO-Biological Process (Dennis et al., 2003, Genome Biology) Literature validation (Rudolph et al., 2003, Clarkson et al., 2004) Determination of key genes in functional networks and validation of their expression profile by RT-PCRq

17 Discussion : oncoming prospects Search tools to understand and characterize the Immune response observed in Ingenuity functional network at P70 and P110 Proteomic study to validate the mrna-protein transition From tissue to cell : Laser Capture Microdissection as tool to specifically characterize the mammary epithelial cell differentiation

Advanced Animal Science TEKS/LINKS Student Objectives One Credit

Advanced Animal Science TEKS/LINKS Student Objectives One Credit First Six Weeks Career/Safety/Work Habits AAS 1(A) The student will identify career development and entrepreneurship opportunities in the field of animal systems. AAS 1(B) The student will apply competencies