G. Dummerstorf and P. , Box 65, 8200 AB, Lelystad, The Netherlands. 9 Wageningen UR Livestock Research The Netherlands. 10 Department of Basic Sciences and Aquatic Medicine, Animal Breeding and Genomics Centre, P.O. Box Norwegian School of Veterinary Science, P.O. Box, vol.65, issue.81460033 11, p.12, 20133.

I. Di-biologia-e-biotecnologia-agraria and C. Nazionale-delle-ricerche, 13 INRA-ENVT, UMR1225, Interactions Hôtes Agents Pathogènes, F-31300 Toulouse, France. 14 INRA, UR631, Station d'Amélioration Génétique des Animaux, F-31326 Castanet-Tolosan, France. 15 Department of Clinical Studies, School of Veterinary Medicine, 16 Quality Milk Production Services 1313 de Génétique Animale et Biologie Intégrative, 19104.

G. Davies, S. Genini, S. Bishop, and E. Giuffra, An assessment of opportunities to dissect host genetic variation in resistance to infectious diseases in livestock, animal, vol.94, issue.03, pp.415-436, 2009.
DOI : 10.1017/S1751731108003522

L. Hedges and I. Olkin, Statistical Methods for Meta-Analysis, 1985.

D. Stangl and D. Berry, Meta-Analysis in Medicine and Health Policy, 2000.
DOI : 10.1201/9780203909935

D. Rhodes, T. Barrette, M. Rubin, D. Ghosh, and A. Chinnaiyan, Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer, Cancer Res, issue.15, pp.624427-4433, 2002.

J. Choi, U. Yu, S. Kim, and O. Yoo, Combining multiple microarray studies and modeling interstudy variation, Bioinformatics, vol.19, issue.Suppl 1, pp.84-90, 2003.
DOI : 10.1093/bioinformatics/btg1010

J. Choi, J. Choi, D. Kim, D. Choi, B. Kim et al., Integrative analysis of multiple gene expression profiles applied to liver cancer study, FEBS Lett, vol.565, pp.1-393, 2004.

D. Rhodes, J. Yu, K. Shanker, N. Deshpande, R. Varambally et al., Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression, Proceedings of the National Academy of Sciences, vol.101, issue.25, pp.9309-9314, 2004.
DOI : 10.1073/pnas.0401994101

J. De-magalhaes, J. Curado, and G. Church, Meta-analysis of age-related gene expression profiles identifies common signatures of aging, Bioinformatics, vol.25, issue.7, pp.875-881, 2009.
DOI : 10.1093/bioinformatics/btp073

D. Greco, P. Somervuo, D. Lieto, A. Raitila, T. Nitsch et al., Physiology, Pathology and Relatedness of Human Tissues from Gene Expression Meta-Analysis, PLoS ONE, vol.4, issue.2, p.1880, 2008.
DOI : 10.1371/journal.pone.0001880.s006

R. Jelier, P. Hoen, E. Sterrenburg, J. Den-dunnen, G. Van-ommen et al., Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease, BMC Bioinformatics, vol.9, issue.1, p.291, 2008.
DOI : 10.1186/1471-2105-9-291

V. Pihur, S. Datta, and S. Datta, Finding common genes in multiple cancer types through meta???analysis of microarray experiments: A rank aggregation approach, Genomics, vol.92, issue.6, pp.400-403, 2008.
DOI : 10.1016/j.ygeno.2008.05.003

J. Pennings, T. Kimman, and R. Janssen, Identification of a Common Gene Expression Response in Different Lung Inflammatory Diseases in Rodents and Macaques, PLoS ONE, vol.277, issue.7, p.2596, 2008.
DOI : 10.1371/journal.pone.0002596.s003

D. Sohal, A. Yeatts, K. Ye, A. Pellagatti, L. Zhou et al., Meta-Analysis of Microarray Studies Reveals a Novel Hematopoietic Progenitor Cell Signature and Demonstrates Feasibility of Inter-Platform Data Integration, PLoS ONE, vol.280, issue.8, p.2965, 2008.
DOI : 10.1371/journal.pone.0002965.s001

B. Gyorffy and R. Schafer, Meta-analysis of gene expression profiles related to relapse-free survival in 1,079 breast cancer patients, Breast Cancer Research and Treatment, vol.100, issue.3, pp.433-441, 2009.
DOI : 10.1007/s10549-008-0242-8

URL : https://hal.archives-ouvertes.fr/hal-00535315

Y. Edwards, K. Bryson, and D. Jones, A Meta-Analysis of Microarray Gene Expression in Mouse Stem Cells: Redefining Stemness, PLoS ONE, vol.35, issue.7, p.2712, 2008.
DOI : 10.1371/journal.pone.0002712.s001

L. Hedges and T. Pigott, The power of statistical tests in meta-analysis., Psychological Methods, vol.6, issue.3, pp.203-217, 2001.
DOI : 10.1037/1082-989X.6.3.203

L. Hedges and T. Pigott, The Power of Statistical Tests for Moderators in Meta-Analysis., Psychological Methods, vol.9, issue.4, pp.426-445, 2004.
DOI : 10.1037/1082-989X.9.4.426

T. Loughin, A systematic comparison of methods for combining p-values from independent tests, Computational Statistics & Data Analysis, vol.47, issue.3, pp.467-485, 2004.
DOI : 10.1016/j.csda.2003.11.020

G. Marot, J. Foulley, and C. Mayer, Jaffrezic F: Moderated effect size and Pvalue combinations for microarray meta-analyses, Bioinformatics, issue.20, pp.252692-2699, 2009.

D. Hwang, A. Rust, S. Ramsey, J. Smith, D. Leslie et al., A data integration methodology for systems biology, Proceedings of the National Academy of Sciences, vol.102, issue.48, pp.10217296-17301, 2005.
DOI : 10.1073/pnas.0508647102

D. Hwang, J. Smith, D. Leslie, A. Weston, A. Rust et al., A data integration methodology for systems biology: Experimental verification, Proceedings of the National Academy of Sciences, vol.102, issue.48, pp.10217302-17307, 2005.
DOI : 10.1073/pnas.0508649102

Y. Moreau, S. Aerts, D. Moor, B. , D. Strooper et al., Comparison and meta-analysis of microarray data: from the bench to the computer desk, Trends in Genetics, vol.19, issue.10, pp.570-577, 2003.
DOI : 10.1016/j.tig.2003.08.006

A. Fierro, F. Vandenbussche, K. Engelen, Y. Van-de-peer, and K. Marchal, Meta Analysis of Gene Expression Data within and Across Species, Current Genomics, vol.9, issue.8, pp.525-534, 2008.
DOI : 10.2174/138920208786847935

G. Nau, J. Richmond, A. Schlesinger, E. Jennings, E. Lander et al., Human macrophage activation programs induced by bacterial pathogens, Proceedings of the National Academy of Sciences, vol.99, issue.3, pp.1503-1508, 2002.
DOI : 10.1073/pnas.022649799

Q. Huang, D. Liu, P. Majewski, L. Schulte, J. Korn et al., The Plasticity of Dendritic Cell Responses to Pathogens and Their Components, Science, vol.294, issue.5543, pp.294870-875, 2001.
DOI : 10.1126/science.294.5543.870

R. Jenner and R. Young, Insights into host responses against pathogens from transcriptional profiling, Nature Reviews Microbiology, vol.77, issue.4, pp.281-294, 2005.
DOI : 10.1073/pnas.242741699

W. Petzl, H. Zerbe, J. Gunther, W. Yang, H. Seyfert et al., triggers an early increased expression of factors contributing to the innate immune defense in the udder of the cow, Veterinary Research, vol.39, issue.2, p.18, 2008.
DOI : 10.1051/vetres:2007057

URL : https://hal.archives-ouvertes.fr/hal-00902900

F. Liu and K. Walters, Multitasking with ubiquitin through multivalent interactions, Trends in Biochemical Sciences, vol.35, issue.6, pp.352-360
DOI : 10.1016/j.tibs.2010.01.002

A. Ciechanover, The ubiquitin-proteasome pathway: on protein death and cell life, The EMBO Journal, vol.17, issue.24, pp.7151-7160, 1998.
DOI : 10.1093/emboj/17.24.7151

A. Rytkonen and D. Holden, Bacterial Interference of Ubiquitination and Deubiquitination, Cell Host & Microbe, vol.1, issue.1, pp.13-22, 2007.
DOI : 10.1016/j.chom.2007.02.003

G. Ramadori and C. B. , Cytokines and the hepatic acute-phase response. Semin Liver Dis, pp.141-155, 1999.

J. Carroll, R. Reuter, C. Chase, . Jr, S. Coleman et al., Profile of the bovine acute-phase response following an intravenous bolus-dose lipopolysaccharide challenge, Innate Immunity, vol.15, issue.2, pp.81-89, 2009.
DOI : 10.1177/1753425908099170

L. Suojala, T. Orro, H. Jarvinen, J. Saatsi, and S. Pyorala, Acute phase response in two consecutive experimentally induced E. coli intramammary infections in dairy cows, Acta Veterinaria Scandinavica, vol.50, issue.1, p.18, 2008.
DOI : 10.1186/1751-0147-50-18

A. Bendelac, L. Teyton, and P. Savage, Lipid presentation by CD1: the short and the long lipid story, Nature Immunology, vol.3, issue.5, pp.421-422, 2002.
DOI : 10.1038/ni0502-421

M. Gomez-lechon, Oncostatin M: Signal transduction and biological activity, Life Sciences, vol.65, issue.20, pp.2019-2030, 1999.
DOI : 10.1016/S0024-3205(99)00296-9

D. Hava, M. Brigl, P. Van-den-elzen, D. Zajonc, I. Wilson et al., CD1 assembly and the formation of CD1???antigen complexes, Current Opinion in Immunology, vol.17, issue.1, pp.188-94, 2005.
DOI : 10.1016/j.coi.2004.12.003

K. Moyes, J. Drackley, D. Morin, M. Bionaz, S. Rodriguez-zas et al., Gene network and pathway analysis of bovine mammary tissue challenged with Streptococcus uberis reveals induction of cell proliferation and inhibition of PPAR?? signaling as potential mechanism for the negative relationships between immune response and lipid metabolism, BMC Genomics, vol.10, issue.1, p.542, 2009.
DOI : 10.1186/1471-2164-10-542

K. Moyes, J. Drackley, D. Morin, S. Rodriguez-zas, R. Everts et al., Predisposition of cows to mastitis in non-infected mammary glands: effects of dietary-induced negative energy balance during mid-lactation on immune-related genes, Functional & Integrative Genomics, vol.10, issue.1, pp.151-156, 2011.
DOI : 10.1007/s10142-010-0186-z

E. Ibeagha-awemu, A. Ibeagha, S. Messier, and X. Zhao, Proteomics, genomics, and pathway analyses of Escherichia coli and Staphylococcus aureus infected milk whey reveal molecular pathways and networks involved in mastitis, J Proteome Res, vol.2010, issue.99, pp.4604-4619

H. Imtiyaz and M. Simon, Hypoxia-Inducible Factors as Essential Regulators of Inflammation, Curr Top Microbiol Immunol, vol.810, pp.105-120, 2010.
DOI : 10.1007/82_2010_74

W. Lin, H. Harding, R. D. Popko, and B. , Endoplasmic reticulum stress modulates the response of myelinating oligodendrocytes to the immune cytokine interferon-??, The Journal of Cell Biology, vol.1, issue.4, pp.603-612, 2005.
DOI : 10.1101/gad.12.7.982

DOI : 10.1097/00024382-200014020-00012

K. Swanson, S. Gorodetsky, L. Good, S. Davis, D. Musgrave et al., Expression of a beta-defensin mRNA, lingual antimicrobial peptide, in bovine mammary epithelial tissue is induced by mastitis, Infect Immun, issue.12, pp.727311-7314, 2004.

Y. Lutzow, L. Donaldson, C. Gray, T. Vuocolo, R. Pearson et al., Identification of immune genes and proteins involved in the response of bovine mammary tissue to Staphylococcus aureus infection, BMC Veterinary Research, vol.4, issue.1, p.18, 2008.
DOI : 10.1186/1746-6148-4-18

M. Schroder and R. Kaufman, THE MAMMALIAN UNFOLDED PROTEIN RESPONSE, Annual Review of Biochemistry, vol.74, issue.1, pp.739-789, 2005.
DOI : 10.1146/annurev.biochem.73.011303.074134

G. Norata, M. Ongari, P. Uboldi, F. Pellegatta, and A. Catapano, Liver X receptor and retinoic X receptor agonists modulate the expression of genes involved in lipid metabolism in human endothelial cells, Int J Mol Med, vol.16, issue.4, pp.717-722, 2005.

D. Morris, S. Waters, S. Mccarthy, J. Patton, B. Earley et al., Pleiotropic effects of negative energy balance in the postpartum dairy cow on splenic gene expression: repercussions for innate and adaptive immunity, Physiological Genomics, vol.39, issue.1, pp.28-37, 2009.
DOI : 10.1152/physiolgenomics.90394.2008

N. Iwakoshi, A. Lee, and L. Glimcher, The X-box binding protein-1 transcription factor is required for plasma cell differentiation and the unfolded protein response, Immunological Reviews, vol.412, issue.1, pp.29-38, 2003.
DOI : 10.1126/science.1061965

L. Zeng, Y. Liu, H. Sha, H. Chen, L. Qi et al., XBP-1 Couples Endoplasmic Reticulum Stress to Augmented IFN-?? Induction via a cis-Acting Enhancer in Macrophages, The Journal of Immunology, vol.185, issue.4, pp.2324-2330, 2010.
DOI : 10.4049/jimmunol.0903052

R. Sriburi, H. Bommiasamy, G. Buldak, G. Robbins, M. Frank et al., Coordinate Regulation of Phospholipid Biosynthesis and Secretory Pathway Gene Expression in XBP-1(S)-induced Endoplasmic Reticulum Biogenesis, Journal of Biological Chemistry, vol.282, issue.10, pp.2827024-7034, 2007.
DOI : 10.1074/jbc.M609490200

K. Sauer and M. Cooke, Regulation of immune cell development through soluble inositol-1,3,4,5-tetrakisphosphate, Nature Reviews Immunology, vol.584, issue.4, pp.257-271, 2010.
DOI : 10.1038/nri2745

S. Mitterhuemer, W. Petzl, S. Krebs, D. Mehne, A. Klanner et al., Escherichia coli infection induces distinct local and systemic transcriptome responses in the mammary gland, BMC Genomics, vol.11, issue.1, p.138, 2010.
DOI : 10.1186/1471-2164-11-138

A. Conesa, M. Nueda, A. Ferrer, and M. Talon, maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments, Bioinformatics, vol.22, issue.9, pp.1096-1102, 2006.
DOI : 10.1093/bioinformatics/btl056

C. Burvenich, V. Van-merris, J. Mehrzad, A. Diez-fraile, and L. Duchateau, mastitis is mainly determined by cow factors, Veterinary Research, vol.34, issue.5, pp.521-564, 2003.
DOI : 10.1051/vetres:2003023

URL : https://hal.archives-ouvertes.fr/hal-00902764

W. Yang, H. Zerbe, W. Petzl, R. Brunner, J. Gunther et al., Bovine TLR2 and TLR4 properly transduce signals from Staphylococcus aureus and E. coli, but S. aureus fails to both activate NF-kappaB in mammary epithelial cells and to quickly induce TNFalpha and interleukin-8 (CXCL8) expression in the udder, Mol Immunol, issue.5, pp.451385-1397, 2008.
DOI : 10.1016/j.molimm.2007.09.004

Y. Benjamini and Y. Hochberg, Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing, Journal of the Royal Statistical Society Series B, vol.57, issue.1, pp.289-300, 1995.

S. Suchyta, S. Sipkovsky, R. Kruska, A. Jeffers, A. Mcnulty et al., Development and testing of a high-density cDNA microarray resource for cattle, Physiological Genomics, vol.15, issue.2, pp.158-164, 2003.
DOI : 10.1152/physiolgenomics.00094.2003

E. Talla, F. Tekaia, L. Brino, and B. Dujon, A novel design of whole-genome microarray probes for Saccharomyces cerevisiae which minimizes crosshybridization, BMC Genomics, vol.4, issue.1, p.38, 2003.
DOI : 10.1186/1471-2164-4-38

F. Baldino, . Jr, M. Chesselet, and M. Lewis, High-resolution in situ hybridization histochemistry, Methods Enzymol, vol.168, pp.761-777, 1989.
DOI : 10.1016/0076-6879(89)68057-3

P. Casel, F. Moreews, S. Lagarrigue, and C. Klopp, sigReannot: an oligo-set re-annotation pipeline based on similarities with the Ensembl transcripts and Unigene clusters, BMC Proceedings, vol.3, issue.Suppl 4, p.3, 2009.
DOI : 10.1186/1753-6561-3-s4-s3

T. Sonstegard, R. Stone, Y. Sugimoto, A. Takasuga, J. Taylor et al., The genome sequence of taurine cattle: a window to ruminant biology and evolution, Science, issue.5926, pp.324522-528, 2009.

R. Tibshirani, T. Hastie, B. Narasimhan, and G. Chu, Diagnosis of multiple cancer types by shrunken centroids of gene expression, Proceedings of the National Academy of Sciences, vol.99, issue.10, pp.996567-6572, 2002.
DOI : 10.1073/pnas.082099299

F. Jaffrezic, D. De-koning, P. Boettcher, A. Bonnet, B. Buitenhuis et al., Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication), Genetics Selection Evolution, vol.39, issue.6, pp.39633-650, 2007.
DOI : 10.1186/1297-9686-39-6-633

URL : https://hal.archives-ouvertes.fr/hal-00894624

D. De-koning, F. Jaffrezic, M. Lund, M. Watson, C. Channing et al., The EADGENE Microarray Data Analysis Workshop (Open Access publication), Genetics Selection Evolution, vol.39, issue.6, pp.39621-631, 2007.
DOI : 10.1186/1297-9686-39-6-621

URL : https://hal.archives-ouvertes.fr/hal-00894623

G. Pisoni, B. Castiglioni, A. Stella, P. Boettcher, S. Genini et al., Microarray analysis of gene expression of milk leukocytes in healthy goats, Veterinary Research Communications, vol.15, issue.2, pp.219-240, 2008.
DOI : 10.1007/s11259-008-9154-7

G. Pisoni, P. Moroni, S. Genini, A. Stella, P. Boettcher et al., Differentially expressed genes associated with Staphylococcus aureus mastitis in dairy goats, Veterinary Immunology and Immunopathology, vol.135, issue.3-4, pp.3-4208, 2010.
DOI : 10.1016/j.vetimm.2009.11.016

. Genini, Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources, BMC Genomics, vol.135, issue.3-4, p.225, 2011.
DOI : 10.1186/1471-2164-12-225

URL : https://hal.archives-ouvertes.fr/inserm-00601542