R. Koch, L. Swiger, D. Chambers, and K. Gregory, Efficiency of Feed Use in Beef Cattle, Journal of Animal Science, vol.22, issue.2, pp.486-94, 1963.
DOI : 10.2527/jas1963.222486x

H. Gilbert, J. Bidanel, J. Gruand, J. Caritez, Y. Billon et al., Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits, Journal of Animal Science, vol.85, issue.12, pp.3182-3190, 2007.
DOI : 10.2527/jas.2006-590

S. Onteru, D. Gorbach, J. Young, D. Garrick, J. Dekkers et al., Whole Genome Association Studies of Residual Feed Intake and Related Traits in the Pig, PLoS ONE, vol.157, issue.6, p.61756, 2013.
DOI : 10.1371/journal.pone.0061756.s008

G. Sahana, V. Kadlecová, H. Hornshøj, B. Nielsen, and O. Christensen, A genome-wide association scan in pig identifies novel regions associated with feed efficiency trait, Journal of Animal Science, vol.91, issue.3, pp.1041-50, 2013.
DOI : 10.2527/jas.2012-5643

W. Barendse, A. Reverter, R. Bunch, B. Harrison, W. Barris et al., A Validated Whole-Genome Association Study of Efficient Food Conversion in Cattle, Genetics, vol.176, issue.3, pp.1893-905, 2007.
DOI : 10.1534/genetics.107.072637

M. De-almeida-santana, G. Junior, A. Cesar, M. Freua, G. Da-costa et al., Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle, Journal of Applied Genetics, vol.10, issue.3, pp.495-504, 2016.
DOI : 10.1146/annurev.genom.9.081307.164217

D. Do, A. Strathe, T. Ostersen, S. Pant, and H. Kadarmideen, Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake, Frontiers in Genetics, vol.3, issue.307, p.307, 2014.
DOI : 10.3389/fgene.2012.00307

S. Lkhagvadorj, L. Qu, W. Cai, O. Couture, C. Barb et al., Gene expression profiling of the short-term adaptive response to acute caloric restriction in liver and adipose tissues of pigs differing in feed efficiency, AJP: Regulatory, Integrative and Comparative Physiology, vol.298, issue.2, pp.494-501, 2010.
DOI : 10.1152/ajpregu.00632.2009

A. Vincent, I. Louveau, F. Gondret, C. Tréfeu, H. Gilbert et al., Divergent selection for residual feed intake affects the transcriptomic and proteomic profiles of pig skeletal muscle, Journal of Animal Science, vol.93, issue.6, pp.2745-58, 2015.
DOI : 10.2527/jas.2015-8928

URL : https://hal.archives-ouvertes.fr/hal-01211015

Y. Chen, C. Gondro, K. Quinn, R. Herd, P. Parnell et al., Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake, Animal Genetics, vol.69, issue.5, pp.475-90, 2011.
DOI : 10.1002/pros.20907

P. Alexandre, L. Kogelman, M. Santana, D. Passarelli, L. Pulz et al., Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle, BMC Genomics, vol.36, issue.Web Server issu, p.1073, 2015.
DOI : 10.1093/nar/gkn276

URL : https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/s12864-015-2292-8?site=bmcgenomics.biomedcentral.com

P. Tizioto, L. Coutinho, J. Decker, R. Schnabel, K. Rosa et al., Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes, BMC Genomics, vol.76, issue.4, pp.16-242, 2015.
DOI : 10.3168/jds.S0022-0302(93)77729-2

URL : http://doi.org/10.1186/s12864-015-1464-x

W. Al-husseini, Y. Chen, C. Gondro, R. Herd, J. Gibson et al., Characterization and Profiling of Liver microRNAs by RNA-sequencing in Cattle Divergently Selected for Residual Feed Intake, Asian-Australasian Journal of Animal Sciences, vol.29, issue.10, pp.1371-82, 2016.
DOI : 10.5713/ajas.15.0605

K. Weber, B. Welly, A. Van-eenennaam, A. Young, L. Porto-neto et al., Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq, PLOS ONE, vol.8, issue.3, p.152274, 2016.
DOI : 10.1371/journal.pone.0152274.s002

J. Faure, L. Lefaucheur, N. Bonhomme, P. Ecolan, K. Meteau et al., Consequences of divergent selection for residual feed intake in pigs on muscle energy metabolism and meat quality, Meat Science, vol.93, issue.1, pp.37-45, 2013.
DOI : 10.1016/j.meatsci.2012.07.006

URL : https://hal.archives-ouvertes.fr/hal-01210320

L. Naou, T. , L. Floc-'h, N. Louveau, I. Gilbert et al., Metabolic changes and tissue responses to selection on residual feed intake in growing pigs, Journal of Animal Science, vol.90, issue.13, pp.4771-80, 2012.
DOI : 10.2527/jas.2012-5226

URL : https://hal.archives-ouvertes.fr/hal-01001044

G. Baracho, M. Cato, Z. Zhu, O. Jaren, E. Hobeika et al., PDK1 regulates B cell differentiation and homeostasis, Proceedings of the National Academy of Sciences, vol.46, issue.6, pp.9573-9581, 2014.
DOI : 10.1016/j.immuni.2006.08.015

URL : http://www.pnas.org/content/111/26/9573.full.pdf

R. Barea, S. Dubois, H. Gilbert, P. Sellier, J. Van-milgen et al., Energy utilization in pigs selected for high and low residual feed intake, Journal of Animal Science, vol.88, issue.6, pp.2062-72, 2010.
DOI : 10.2527/jas.2009-2395

URL : https://hal.archives-ouvertes.fr/hal-01193557

P. Suravajhala, L. Kogelman, and H. Kadarmideen, Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare, Genetics Selection Evolution, vol.10, issue.Suppl 2, p.38, 2016.
DOI : 10.1371/journal.pgen.1004192

URL : https://hal.archives-ouvertes.fr/hal-01341372

V. Mani, A. Harris, A. Keating, T. Weber, J. Dekkers et al., Intestinal integrity, endotoxin transport and detoxification in pigs divergently selected for residual feed intake, Journal of Animal Science, vol.91, issue.5, pp.2141-50, 2013.
DOI : 10.2527/jas.2012-6053

URL : http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1032&context=ans_pubs

F. Paradis, S. Yue, J. Grant, P. Stothard, J. Basarab et al., Transcriptomic analysis by RNA sequencing reveals that hepatic interferon-induced genes may be associated with feed efficiency in beef heifers, Journal of Animal Science, vol.93, issue.7, pp.3331-3372, 2015.
DOI : 10.2527/jas.2015-8975

R. Lochmiller and C. Deerenberg, Trade-offs in evolutionary immunology: just what is the cost of immunity?, Oikos, vol.88, issue.1, pp.87-98, 2000.
DOI : 10.1034/j.1600-0706.2000.880110.x

R. Elgueta, M. Benson, V. De-vries, A. Wasiuk, Y. Guo et al., Molecular mechanism and function of CD40/CD40L engagement in the immune system, Immunological Reviews, vol.102, issue.1, pp.152-72, 2009.
DOI : 10.4049/jimmunol.164.4.2200

M. Croft, C. Benedict, and C. Ware, Clinical targeting of the TNF and TNFR superfamilies, Nature Reviews Drug Discovery, vol.66, issue.2, pp.147-68, 2013.
DOI : 10.1136/ard.2006.055111

C. Pham, Neutrophil serine proteases fine-tune the inflammatory response, The International Journal of Biochemistry & Cell Biology, vol.40, issue.6-7, pp.1317-1350, 2008.
DOI : 10.1016/j.biocel.2007.11.008

B. Ramkhelawon, E. Hennessy, M. Ménager, T. Ray, F. Sheedy et al., Netrin-1 promotes adipose tissue macrophage retention and insulin resistance in obesity, Nature Medicine, vol.5, issue.4, pp.377-84, 2014.
DOI : 10.1016/j.cmet.2007.05.004

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981930

R. Frost, G. Nystrom, and C. Lang, Multiple Toll-like receptor ligands induce an IL-6 transcriptional response in skeletal myocytes, AJP: Regulatory, Integrative and Comparative Physiology, vol.290, issue.3, pp.773-84, 2006.
DOI : 10.1152/ajpregu.00490.2005

J. Tidball and C. Rinaldi, Immunologic responses to muscle injury Muscle: fundamental biology and mechanisms of disease, pp.899-907, 2012.

E. Merlot, H. Gilbert, L. Floc-'h, and N. , Metabolic response to an inflammatory challenge in pigs divergently selected for residual feed intake, Journal of Animal Science, vol.94, issue.2, pp.563-73, 2016.
DOI : 10.2527/jas.2015-9445

E. Labussière, S. Dubois, H. Gilbert, J. Thibault, L. Floc-'h et al., Effect of inflammation stimulation on energy and nutrient utilization in piglets selected for low and high residual feed intake, animal, vol.118, issue.10, pp.1653-61, 2015.
DOI : 10.1016/0301-6226(93)90056-N

A. Chatelet, F. Gondret, E. Merlot, H. Gilbert, and L. Floc, Performance, health, immune and metabolic responses of pigs during a sanitary challenge differed according to their potential for feed efficiency, 49th Journées de la Recherche Porcine, pp.195-202, 2017.

J. Dunkelberger, N. Boddicker, N. Serão, J. Young, R. Rowland et al., Response of pigs divergently selected for residual feed intake to experimental infection with the PRRS virus, Livestock Science, vol.177, pp.132-173, 2015.
DOI : 10.1016/j.livsci.2015.04.014

M. Mackness and B. Mackness, Human paraoxonase-1 (PON1): Gene structure and expression, promiscuous activities and multiple physiological roles, Gene, vol.567, issue.1, pp.12-21, 2015.
DOI : 10.1016/j.gene.2015.04.088

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458450

J. Chang, H. Jung, S. Jeong, H. Kim, J. Han et al., A mutation in the mitochondrial protein UQCRB promotes angiogenesis through the generation of mitochondrial reactive oxygen species, Biochemical and Biophysical Research Communications, vol.455, issue.3-4, pp.290-297, 2014.
DOI : 10.1016/j.bbrc.2014.11.005

W. Bottje, B. Kong, J. Song, J. Lee, B. Hargis et al., Gene expression in breast muscle associated with feed efficiency in a single male broiler line using a chicken 44K microarray. II. Differentially expressed focus genes, Poultry Science, vol.91, issue.10, pp.2576-87, 2012.
DOI : 10.3382/ps.2012-02204

J. Grubbs, A. Fritchen, E. Huff-lonergan, J. Dekkers, N. Gabler et al., Divergent genetic selection for residual feed intake impacts mitochondria reactive oxygen species production in pigs, Journal of Animal Science, vol.91, issue.5, pp.2133-2173, 2013.
DOI : 10.2527/jas.2012-5894

W. Bottje and G. Carstens, Association of mitochondrial function and feed efficiency in poultry and livestock species, Journal of Animal Science, vol.87, issue.Num 14,Supp 09, pp.48-63, 2009.
DOI : 10.2527/jas.2008-1379

S. Cruzen, A. Harris, K. Hollinger, R. Punt, J. Grubbs et al., Evidence of decreased muscle protein turnover in gilts selected for low residual feed intake, Journal of Animal Science, vol.91, issue.8, pp.4007-4023, 2013.
DOI : 10.2527/jas.2013-6413

A. Ernst, G. Avvakumov, J. Tong, Y. Fan, Y. Zhao et al., A Strategy for Modulation of Enzymes in the Ubiquitin System, Science, vol.281, issue.13, pp.590-595, 2013.
DOI : 10.1074/jbc.C500451200

D. Bier, The role of protein and amino acids in sustaining and enhancing performance. 5-The energy costs of protein metabolism: lean and mean on Uncle Sam's Team. Institute of medicine (US) committee on military nutrition research, US, 1999.

L. Lefaucheur, B. Lebret, P. Ecolan, I. Louveau, M. Damon et al., Muscle characteristics and meat quality traits are affected by divergent selection on residual feed intake in pigs, Journal of Animal Science, vol.89, issue.4, pp.996-1010, 2011.
DOI : 10.2527/jas.2010-3493

URL : https://hal.archives-ouvertes.fr/hal-01000532

B. Kong, K. Lassiter, A. Piekarski-welsher, S. Dridi, A. Reverter-gomez et al., Proteomics of Breast Muscle Tissue Associated with the Phenotypic Expression of Feed Efficiency within a Pedigree Male Broiler Line: I. Highlight on Mitochondria, PLOS ONE, vol.292, issue.16, p.155679, 2016.
DOI : 10.1371/journal.pone.0155679.s002

J. Qiu, R. Cheng, X. Zhou, J. Zhu, C. Zhu et al., Gene expression profiles of adipose tissue of high-fat diet-induced obese rats by cDNA microarrays, Molecular Biology Reports, vol.246, issue.8, pp.3691-3696, 2010.
DOI : 10.2337/diab.43.8.1066

J. Soh, D. Kwon, and Y. Cha, Hepatic Gene Expression Profiles Are Altered by Dietary Unsalted Korean Fermented Soybean (Chongkukjang) Consumption in Mice with Diet-Induced Obesity, Journal of Nutrition and Metabolism, vol.48, issue.1, p.260214, 2011.
DOI : 10.1126/science.1090776

P. Flachs, M. Rossmeisl, O. Kuda, and J. Kopecky, Stimulation of mitochondrial oxidative capacity in white fat independent of UCP1: A key to lean phenotype, Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids, vol.1831, issue.5, pp.986-989, 1831.
DOI : 10.1016/j.bbalip.2013.02.003

W. Rauw, O. Portolés, C. D. Soler, J. Reixach, J. Tibau et al., Behaviour influences cholesterol plasma levels in a pig model, animal, vol.20, issue.06, pp.865-71, 2007.
DOI : 10.1161/01.ATV.20.8.2005

URL : https://www.cambridge.org/core/services/aop-cambridge-core/content/view/9EEC940DC56C185A760B8C884CD0F04B/S1751731107000018a.pdf/div-class-title-behaviour-influences-cholesterol-plasma-levels-in-a-pig-model-div.pdf

L. Jing, Y. Hou, H. Wu, Y. Miao, X. Li et al., Transcriptome analysis of mRNA and miRNA in skeletal muscle indicates an important network for differential Residual Feed Intake in pigs, Scientific Reports, vol.9, issue.1, p.11953, 2015.
DOI : 10.1038/nmeth.2212

K. Bunter, W. Cai, D. Johnston, and J. Dekkers, Selection to reduce residual feed intake in pigs produces a correlated response in juvenile insulin-like growth factor-I concentration, Journal of Animal Science, vol.88, issue.6, pp.1973-81, 2010.
DOI : 10.2527/jas.2009-2445

M. Peng, G. Pelletier, M. Palin, S. Véronneau, D. Lebel et al., Ontogeny of IGFs and IGFBPs mRNA levels and tissue concentrations in liver, kidney and skeletal muscle of pig, Growth Dev Aging, vol.60, pp.171-87, 1996.

F. Gondret, I. Louveau, J. Mourot, M. Duclos, S. Lagarrigue et al., Dietary energy sources affect the partition of body lipids and the hierarchy of energy metabolic pathways in growing pigs differing in feed efficiency, Journal of Animal Science, vol.92, issue.11, pp.4865-77, 2014.
DOI : 10.2527/jas.2014-7995

URL : https://hal.archives-ouvertes.fr/hal-01207757

F. Gondret, A. Vincent, M. Houée-bigot, A. Siegel, S. Lagarrigue et al., Molecular alterations induced by a high-fat high-fiber diet in porcine adipose tissues: variations according to the anatomical fat location, BMC Genomics, vol.93, issue.1, p.120, 2016.
DOI : 10.2527/jas.2015-8928

URL : https://hal.archives-ouvertes.fr/hal-01286555

W. Fu, A. Stromberg, K. Viele, R. Carroll, and G. Wu, Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology???, The Journal of Nutritional Biochemistry, vol.21, issue.7, pp.561-72, 2010.
DOI : 10.1016/j.jnutbio.2009.11.007

H. Abdi, L. Williams, and D. Valentin, Multiple factor analysis: principal component analysis for multitable and multiblock data sets, Wiley Interdisciplinary Reviews: Computational Statistics, vol.44, issue.2, pp.149-79, 2013.
DOI : 10.1016/j.csda.2007.09.023

URL : https://hal.archives-ouvertes.fr/hal-01259094

D. Huang, B. Sherman, and R. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources, Nature Protocols, vol.99, issue.1, pp.44-57, 2009.
DOI : 10.6026/97320630002428