L. Andersson, Genetic dissection of phenotypic diversity in farm animals, Nat Rev Genet, vol.2, pp.130-138, 2001.

M. E. Goddard and B. J. Hayes, Mapping genes for complex traits in domestic animals and their use in breeding programmes, Nat Rev Genet, vol.10, issue.6, pp.381-91, 2009.

E. Lander and L. Kruglyak, Genetic dissection of complex traits, guidelines for interpreting and reporting linkage results, Nat Genet, vol.11, issue.3, pp.241-247, 1995.

T. Meuwissen, A. Karlsen, S. Lien, I. Olsaker, and M. E. Goddard, Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping, Genetics, vol.161, pp.373-379, 2002.

D. Habier, R. Fernando, K. Kizilkaya, and D. J. Garrick, Extension of the bayesian alphabet for genomic selection, BMC Bioinformatics, vol.12, p.186, 2011.

S. H. Lee and J. Van-der-wref, The efficiency of designs for fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage, Genet Sel Evol, vol.36, pp.145-161, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00894479

S. R. Browning and B. L. Browning, Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering, Am J Hum Genet, vol.81, pp.1084-1097, 2007.

C. Hozé, M. N. Fouilloux, E. Venot, F. Guillaume, R. Dassonneville et al., High-density marker imputation accuracy in sixteen French cattle breeds, Genet Sel Evol, vol.45, p.33, 2013.

D. J. Garrick, J. F. Taylor, and R. L. Fernando, Deregressing estimated breeding values and weighting information for genomic regression analyses, Genet Sel Evol, vol.41, p.55, 2009.

F. Phocas and J. Sapa, Genetic parameters for growth, reproductive performance, calving ease and suckling performance in beef cattle heifers, Anim Sci, vol.79, pp.41-48, 2004.
URL : https://hal.archives-ouvertes.fr/hal-02681778

K. Kizilkaya, R. L. Fernando, and D. J. Garrick, Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes, J Anim Sci, vol.88, pp.544-551, 2010.

A. Legarra, R. A. Filangi, O. Gs3, and U. Manual, , 2013.

A. Schurink, L. Janss, and H. Heuven, Bayesian Variable Selection to identify QTL affecting a simulated quantitative trait, BMC Proceedings, vol.6, issue.2, p.8, 2012.

R. E. Kass and A. E. Raftery, Bayes Factor, J American Statistical Association, vol.90, pp.773-795, 1995.

L. Varona, L. A. García-cortés, and M. Péres-enciso, Bayes factors for detection of Quantitative Trait Loci, Genet Sel Evol, vol.33, pp.133-152, 2001.
URL : https://hal.archives-ouvertes.fr/hal-02671417

P. De-oliveira, A. Cesar, M. L. Do-nascimento, A. S. Chaves, P. C. Tizioto et al., Identification of genomic regions associated with feed efficiency in Nelore cattle, BMC Genet, vol.15, p.100, 2014.

M. Saatchi, R. D. Schnabel, J. F. Taylor, and D. J. Garrick, Large-effect pleiotropic or closely linked QTL segregate within and across ten US cattle breeds, BMC Genomics, vol.15, p.442, 2014.

S. Rothammer, P. V. Kremer, M. Bernau, I. Fernandez-figares, J. Pfister-schär et al., Genome-wide QTL mapping of nine body composition and bone mineral density traits in pigs, Genet Sel Evol, vol.46, p.68, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01341243

Z. L. Hu, C. A. Park, X. L. Wu, and J. M. Reecy, Animal QTLdb: an improved database tool for livestock animal QTL/association data dissemination in the post-genome era, Nucleic Acids Research, vol.41, pp.871-879, 2013.

W. G. Hill and A. Robertson, Linkage disequilibrium in finite populations, Theor Appl Genet, vol.38, pp.226-231, 1968.

M. C. Mcclure, N. S. Morsci, R. D. Schnabel, J. W. Kim, P. Yao et al., A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle, Anim Genet, vol.41, pp.597-607, 2010.

M. S. Khatkar, G. Moser, B. J. Hayes, and H. W. Raadsma, Strategies and utility of imputed SNP genotypes for genomic analysis in dairy cattle, BMC Genomics, vol.13, p.538, 2012.

A. C. Bouwman, M. H. Visker, J. M. Van-arendonk, and H. Bovenhuis, Fine mapping of a quantitative trait locus for bovine milk fat composition on Bos taurus autosome 19, J Dairy Sci, vol.97, pp.1139-1149, 2014.

S. Hassani, M. Saatchi, R. L. Fernando, and D. J. Garrick, Accuracy of prediction of simulated polygenic phenotypes and their underlying quantitative trait loci genotypes using real or imputed whole genome markers in cattle, Genet Sel Evol, vol.47, p.99, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01341333

J. Höglund, B. Guldbrandtsen, M. Lund, and G. Sahana, Analyzes of genome-wide association follow-up study for calving traits in dairy cattle, BMC Genetics, vol.13, p.71, 2012.

S. D. Mccarthy, J. F. Roche, and N. Forde, Temporal changes in endometrial gene expression and protein localization of members of the IGF family in cattle: effects of progesterone and pregnancy, Physiol Genomic.s, vol.44, issue.2, pp.130-140, 2012.

M. Calus, Y. De-haas, and R. F. Veerkamp, Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies, J Dairy Sci, vol.96, pp.6703-6715, 2013.

I. Van-den-berg, S. Fritz, and D. Boichard, QTL fine mapping with Bayes C(?): a simulation study, Genet Sel Evol, vol.45, p.19, 2013.

R. Zhang and X. Li, Association between IGF-IR, m-calpain and UCP-3 gene polymorphisms and growth traits in Nanyang cattle, Mol Biol Rep, vol.38, pp.2179-2184, 2011.

M. M. Rolf, J. F. Taylor, R. D. Schnabel, S. D. Mckay, M. C. Mcclure et al., Genome-wide association analysis for feed efficiency in Angus cattle, Animal Genet, vol.43, pp.367-374, 2011.

A. Takasuga, T. Watanabe, Y. Mizoguchi, T. Hirano, N. Ihara et al., Identification of bovine QTL for growth and carcass traits in Japanese Black cattle by replication and identical-bydescent mapping, Livest Prod Sci, vol.18, pp.49-65, 1988.

T. Roughsedge, P. R. Amer, R. Thompson, and G. Simm, Genetic parameters for a maternal breeding goal in beef production, J Anim Sci, vol.83, issue.10, pp.2319-2348, 2005.

R. M. Enns and G. B. Nicoll, Genetic change results from selection on an economic breeding objective in beef cattle, J Anim Sci, vol.86, pp.3348-57, 2008.

N. Mchugh, A. R. Cromie, R. D. Evans, and D. P. Berry, Validation of national genetic evaluations for maternal beef cattle traits using Irish field data, J Anim Sci, vol.92, issue.4, pp.1423-1455, 2014.

M. Saatchi, R. D. Schnabel, J. F. Taylor, and D. J. Garrick, Large-effect pleiotropic or closely linked QTL segregate within and across ten US cattle breeds, BMC Genomics, vol.15, p.442, 2014.

D. C. Purfield, D. G. Bradley, R. D. Evans, F. G. Kearney, and D. P. Berry, Genome-wide association study for calving performance using high-density genotypes in dairy and beef cattle, Genet Sel Evol, vol.47, p.47, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01330629

C. Hozé, M. N. Fouilloux, E. Venot, F. Guillaume, R. Dassonneville et al., High-density marker imputation accuracy in sixteen French cattle breeds

, Genet Sel Evol, vol.45, p.33, 2013.

. Idele, Methods and results of the genetic evaluation IBOVAL 2015 for the beef cattle breeds, 2015.

D. J. Garrick, J. F. Taylor, and R. L. Fernando, Deregressing estimated breeding values and weighting information for genomic regression analyses, Genet Sel Evol, vol.41, p.55, 2009.

. Idele, Results of suckler cattle's performance recording, 2014.

F. Phocas and J. Sapa, Genetic parameters for growth, reproductive performance, calving ease and suckling performance in beef cattle heifers, Anim Sci, vol.79, pp.41-49, 2004.
URL : https://hal.archives-ouvertes.fr/hal-02681778

D. Habier, R. L. Fernando, K. Kizilkaya, and D. J. Garrick, Extension of the bayesian alphabet for genomic selection, BMC Bioinformatics, vol.12, p.186, 2011.

L. A. Goonewardene, Z. Wang, M. A. Price, R. C. Yang, R. C. Berg et al., Effect of udder type and calving assistance on weaning traits of beef and dairy × beef calves, Livest Prod Sci, vol.81, pp.47-56, 2003.

M. Von-keyserlingk and D. M. Weary, Maternal behavior in cattle, Horm Behav, vol.52, pp.106-119, 2007.

G. L. Williams, O. S. Gazal, L. S. Leshin, R. L. Stanko, and L. L. Anderson, Physiological regulation of maternal behavior in heifers: roles of genital stimulation, intracerebral oxytocin release, and ovarian steroids, Biol Reprod, vol.65, pp.295-300, 2001.

R. M. Akers and A. M. Lefcourt, Effect of presence of calf on milking-induced release of prolactin and oxytocin during early lactation of dairy cows, J Dairy Sci, vol.67, pp.115-137, 1984.

A. C. Barrier, E. Ruelle, M. J. Haskell, and C. M. Dwyer, Effect of a difficult calving on the vigour of the calf, the onset of maternal behaviour, and some behavioural indicators of pain in the dam, Prev Vet Med, vol.103, pp.248-56, 2012.

F. Phocas, C. Bloch, P. Chapelle, F. Bécherel, G. Renand et al., Developing a breeding objective for a French purebred beef cattle selection programme, Livest Prod Sci, vol.57, pp.49-65, 1998.
URL : https://hal.archives-ouvertes.fr/hal-02686167

M. Gautier, D. Laloë, and K. Moazami-goudarzi, Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds, PLoS One, vol.5, p.13038, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193678

. Os-blonde-d'-aquitaine, , 2015.

C. Hozé, M. N. Fouilloux, E. Venot, F. Guillaume, R. Dassonneville et al., High-density marker imputation accuracy in sixteen French cattle breeds

, Genet Sel Evol, vol.45, p.33, 2013.

R. Saintilan, A. Capitan, M. Benoit, S. Barbier, and S. Fritz, Développement d'un outil génomique de présélection sur aptitudes bouchères et facilité de naissance en races Charolaise, Limousine et Blonde d' Aquitaine, Renc Rech Rumin, vol.21, pp.241-245, 2014.

A. Meijering and D. Gianola, Linear versus nonlinear methods of sire evaluation for categorical traits: a simulation study, Genet Sel Evol, vol.17, pp.115-147, 1985.
URL : https://hal.archives-ouvertes.fr/hal-00893632

F. Phocas and D. Laloë, Evaluation models and genetic parameters for calving difficulty in beef cattle, J Anim Sci, vol.81, pp.933-941, 2003.

H. N. Kadarmideen, R. Thompson, M. P. Coffey, and M. A. Kossaibati, Genetic parameters and evaluations from single and multiple trait analysis of dairy cow fertility and milk production, Livest Prod Sci, vol.81, pp.183-95, 2003.

K. Meyer, WOMBAT''-digging deep for quantitative genetic analyses by restricted maximum likelihood, Proceedings of the 8th world congress on genetics applied to livestock production, pp.13-18, 2006.

D. Habier, R. L. Fernando, K. Kizilkaya, and D. J. Garrick, Extension of the Bayesian alphabet for genomic selection, BMC Bioinformatics, vol.12, p.186, 2011.

A. Legarra, R. A. Filangi, and O. Gs3, , 2013.

A. Schurink, L. L. Janss, and H. C. Heuven, Bayesian variable selection to identify QTL affecting a simulated quantitative trait, BMC Proc, vol.6, p.8, 2012.

R. E. Kass and A. E. Raftery, Bayes factor, J Am Stat Assoc, vol.90, pp.773-95, 1995.

A. Legarra, P. Croiseau, M. P. Sanchez, S. Teyssèdre, G. Sallé et al., A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species, Genet Sel Evol, vol.47, p.6, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01190172

J. Wakefield, Bayes factors for genome-wide association studies: comparison with P-values, Genet Epidemiol, vol.33, pp.79-86, 2009.

F. Phocas, X. Boivin, J. Sapa, G. Trillat, A. Boissy et al., Genetic correlations between temperament and breeding traits in Limousin heifers
URL : https://hal.archives-ouvertes.fr/hal-02661838

, Anim Sci, vol.82, pp.805-816, 2006.

A. Vallée, I. Breider, J. A. Van-arendonk, and H. Bovenhuis, Genetic parameters for large-scale behavior traits and type traits in Charolais beef cows, J Anim Sci, vol.93, pp.4277-84, 2015.

J. P. Gutiérrez and F. Goyache, Estimation of genetic parameters of type traits in Asturiana de los Valles beef cattle breed, J Anim Breed Genet, vol.119, pp.93-100, 2002.

M. D. Macneil and T. B. Mott, Genetic analysis of gain from birth to weaning, milk production, and udder conformation in line 1 Hereford cattle, J Anim Sci, vol.84, pp.1639-1684, 2006.

S. Mazza, N. Guzzo, C. Sartori, D. P. Berry, and R. Mantovani, Genetic parameters for linear type traits in the Rendena dual-purpose breed, J Anim Breed Genet, vol.131, pp.27-35, 2014.

F. Phocas and D. Laloë, Genetic parameters for birth and weaning traits in French specialized beef cattle breeds, Livest Prod Sci, issue.89, pp.121-129, 2004.
URL : https://hal.archives-ouvertes.fr/hal-02679885

F. Phocas and J. Sapa, Genetic parameters for growth, reproductive performance, calving ease and suckling performance in beef cattle heifers
URL : https://hal.archives-ouvertes.fr/hal-02681778

, Anim Sci, vol.79, pp.41-49, 2004.

P. Waller, K. Persson, Y. Nyman, A. K. Stengärde, and L. , Udder health in beef cows and its association with calf growth, Acta Vet Scand, vol.56, p.9, 2014.

D. P. Berry, F. Buckley, P. P. Dillon, R. D. Evans, and R. F. Veerkamp, Genetic relationships among linear type traits, milk yield, body weight, fertility and somatic cell count in primiparous dairy cows, Irish J Agric Food Res, vol.43, pp.161-76, 2004.

A. Longo, P. Mele, I. Bertocchi, A. Oberto, A. Bachmann et al., Conditional inactivation of neuropeptide Y Y1 receptors unravels the role of Y1 and Y5 receptors coexpressing neurons in anxiety, Biol Psychiatry, vol.76, pp.840-849, 2014.

Y. Muroi and T. Ishii, Neuropeptide Y is crucial for nutritional state-dependent regulation of maternal behavior, Psychoneuroendocrinology, vol.51, pp.392-402, 2015.

K. T. Schmidt and D. Weinshenker, Adrenaline rush: the role of adrenergic receptors in stimulant-induced behaviors, Mol Pharmacol, vol.85, pp.640-50, 2014.

M. E. Goddard, I. M. Macleod, K. E. Kemper, V. Jagt, C. J. Savin et al., A research plan for the identification of QTL, Proceedings of the 10th world congress on genetics applied to livestock production, pp.17-22, 2014.

R. L. Horst, J. P. Goff, and T. A. Reinhardt, Adapting to the transition between gestation and lactation: differences between rat, human and dairy cow, J Mammary Gland Biol Neoplasia, vol.10, pp.141-56, 2005.

N. Montalbetti, M. G. Dalghi, C. Albrecht, and M. A. Hediger, Nutrient transport in the mammary gland: calcium, trace minerals and water soluble vitamins, J Mammary Gland Biol Neoplasia, vol.19, pp.73-90, 2014.

D. Cai, S. Dhe-paganon, P. A. Melendez, J. Lee, and S. E. Shoelson, Two new substrates in insulin signaling, IRS5/DOK4 and IRS6/DOK5, J Biol Chem, vol.278, pp.25323-25353, 2003.

S. A. Burgos and J. P. Cant, IGF-1 stimulates protein synthesis by enhanced signaling through mTORC1 in bovine mammary epithelial cells, Domest Anim Endocrinol, vol.38, pp.211-232, 2010.

E. V. Kazakova, Y. Wu, Z. Zhou, M. Chen, T. Wang et al., Association between UBE2E2 variant rs7612463 and type 2 diabetes mellitus in a Chinese Han population, Acta Biochim Pol, vol.62, pp.241-246, 2015.

L. A. Winkelman and T. R. Overton, Long-acting insulins alter milk composition and metabolism of lactating dairy cows, J Dairy Sci, vol.96, pp.7565-77, 2013.

T. J. Kaitu'u-lino, L. Ye, L. Tuohey, E. Dimitriadis, J. Bulmer et al., an enzyme with a putative role in spiral artery remodeling, is upregulated in late secretory endometrium and first trimester decidua, Hum Reprod, vol.28, pp.1172-80, 2013.

B. Kadenbach and M. Hüttemann, The subunit composition and function of mammalian cytochrome c oxidase, Mitochondrion, vol.24, pp.64-76, 2015.

C. Kutzleb, G. Sanders, R. Yamamoto, X. Wang, B. Lichte et al., Paralemmin, a prenyl-palmitoyl-anchored phosphoprotein abundant in neurons and implicated in plasma membrane dynamics and cell process formation, J Cell Biol, vol.143, pp.795-813, 1998.

S. Sukegawa, T. Miyake, T. Ibi, Y. Takahagi, H. Murakami et al., Multiple marker effects of single nucleotide polymorphisms in three genes, AKIRIN2, EDG1 and RPL27A, for marbling development in Japanese Black cattle, Anim Sci J, vol.85, pp.193-200, 2014.

M. D. Turner, C. J. Wilde, and R. D. Burgoyne, Exocytosis from permeabilized lactating mouse mammary epithelial cells. Stimulation by Ca2 + and phorbol ester, but inhibition of regulated exocytosis by guanosine 5?-[gammathio]triphosphate, Biochem J, vol.286, pp.13-18, 1992.

D. C. Croteau-chonka, A. F. Marvelle, E. M. Lange, N. R. Lee, L. S. Adair et al., Genome-wide association study of anthropometric traits and evidence of interactions with age and study year in Filipino women, Obesity (Silver Spring), vol.19, pp.1019-1046, 2011.

B. Servin, S. Boitard, C. Chevalet, M. I. Fariello, F. Phocas et al., Accounting for population structure and haplotype diversity in whole genome scans for selection signatures, Proceedings of the 10th world congress on genetics applied to livestock production, pp.17-22, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02740609

A. Kalyanasundaram, S. Viatchenko-karpinski, A. E. Belevych, V. A. Lacombe, H. S. Hwang et al., Functional consequences of stably expressing a mutant calsequestrin (CASQ2D307H) in the CASQ2 null background, Am J Physiol Heart Circ Physiol, vol.302, pp.253-61, 2012.

N. K. Gray, L. Hrabálková, J. P. Scanlon, and R. W. Smith, Poly(A)-binding proteins and mRNA localization: who rules the roost?, Biochem Soc Trans, vol.43, pp.1277-84, 2015.

I. Bibliographie-Álvarez, L. Pérez-pardal, A. Traoré, I. Fernández, and F. Goyache, Lack of haplotype structuring for two candidate genes for trypanotolerance in cattle, J Anim Breed Genet, vol.133, issue.2, pp.105-119, 2016.

. Abri, Getting started with Breedplan, 2015.

A. Victoria, Breeds of beef cattle, 2016.

I. Aguilar, I. Misztal, D. L. Johnson, A. Legarra, S. Tsuruta et al., Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score, J Dairy Sci, vol.93, issue.2, pp.743-52, 2010.
URL : https://hal.archives-ouvertes.fr/hal-02668766

I. Aguilar, I. Misztal, S. Tsuruta, A. Legarra, and H. Wang, PREGSF90 -POSTGSF90: Computational tools for the implementation of single-step genomic selection and genomewide association with ungenotyped individuals in BLUPF90 programs, Proc 10th World Congr Genet Appl Livest Prod, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02743809

W. Al-husseini, C. Gondro, K. Quinn, R. M. Herd, J. P. Gibson et al., Expression of candidate genes for residual feed intake in Angus cattle, Anim Genet. 2014, vol.45, issue.1, pp.12-21

S. Allais, H. Levéziel, N. Payet-duprat, J. F. Hocquette, J. Lepetit et al., The two mutations, Q204X and nt821, of the myostatin gene affect carcass and meat quality in young heterozygous bulls of French beef breeds, J Anim Sci, vol.88, issue.2, pp.446-54, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193527

S. Arico, Tests génomiques en race Limousine : de nouveaux produits sur le marché. Bovins Limousins, vol.188, pp.20-21, 2011.

M. S. Ashwell, D. W. Heyen, J. I. Weller, R. M. Sonstegard, T. S. Van-tassell et al., Detection of quantitative trait loci influencing conformation traits and calving ease in Holstein-Friesian cattle, J Dairy Sci, vol.200, issue.11, pp.4111-4120

, Australian lot feeders' association. Australian Feedlot Industry Statistics, 2015.

R. G. Banks, Progress in implementation of a beef information nucleus portfolio in the Australina beef industry, Proc. Assoc. Advmt. Anim. Breed. Genet, vol.19, pp.399-402, 2011.

M. Barbat, T. Tribout, R. Saintilan, E. Venot, M. N. Fouilloux et al., Comparison of accuracies of genomic prediction in french limousin cattle population according to the number of markers and to pedigree relationship between training and validation populations, Proc 10th World Congr Genet Appl Livest Prod, 2014.

U. Beef and . Statistic, , 2016.

D. P. Berry, E. Wall, and J. E. Pryce, Genetics and genomics of reproductive performance in dairy and beef cattle, Animal, issue.1, pp.105-126, 2014.

D. P. Berry and R. D. Evans, Genetics of reproductive performance in seasonal calving beef cows and its association with performance traits, J Anim Sci, vol.92, issue.4, pp.1412-1434, 2014.

D. P. Berry, J. F. Garcia, and D. J. Garrick, Development and implementation of genomic predictions in beef cattle, Animal Frontiers, vol.6, p.1, 2016.

P. Boddhireddy, K. Prayaga, P. Barros, R. Lôbo, and D. S. , Genomic predictions of economically important traits in Nelore cattle of Brazil, Proc 10th World Congr Genet Appl Livest Prod, 2014.

V. Boerner, D. J. Johnston, and B. Tier, Accuracies of genomically estimated breeding values from pure-breed and across-breed predictions in Australian beef cattle, Genet Sel Evol, vol.46, p.61, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01341242

D. Boichard, H. Chung, R. Dassonneville, X. David, A. Eggen et al., Design of a bovine low-density SNP array optimized for imputation, PLoS One. 2012, vol.7, issue.3, p.34130
URL : https://hal.archives-ouvertes.fr/hal-01019774

D. Boichard, F. Guillaume, A. Baur, P. Croiseau, M. N. Rossignol et al., Genomic selection in French dairy cattle, Anim. Prod. Sci, vol.52, pp.115-120, 2012.
URL : https://hal.archives-ouvertes.fr/hal-02822373

D. Boichard, Quel futur pour l'amélioration génétique chez les espèces domestiques ? Bulletin de l'Académie Vétérinaire de France, 2014.

A. Bouquet, G. Renand, and F. Phocas, Evolution de la diversité génétique des populations françaises de bovins allaitants spécialisés de, Inra Prod. Anim, vol.22, issue.4, p.317, 1979.

C. Bouyer, L. Forestier, G. Renand, and A. Oulmouden, Deep intronic mutation and pseudo exon activation as a novel muscular hypertrophy modifier in cattle, PLoS One. 2014, vol.9, issue.5, p.97399
URL : https://hal.archives-ouvertes.fr/hal-01193857

G. A. Bowling, The Introduction of Cattle into Colonial North America, 1942.

R. F. Brøndum, B. Guldbrandtsen, G. Sahana, M. S. Lund, and G. Su, Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle, BMC Genomics, vol.15, p.728, 2014.

D. Bullock, M. Spangler, A. Van-eenennaam, and R. Weaber, National Beef Cattle Evaluation Consortium (NBCEC) White Paper -Delivering Genomics Technology to the Beef Industry

M. G. Bulmer, The mathematical theory of quantitative genetics, 1980.

E. Casas, D. D. Lunstra, and R. T. Stone, Quantitative trait loci for male reproductive traits in beef cattle, Anim Genet, vol.35, issue.6, pp.451-454, 2004.

, Central Statistics Office, 2016.

A. J. Chamberlain, B. J. Hayes, K. Savin, S. Bolormaa, H. C. Mcpartlan et al., Validation of single nucleotide polymorphisms associated with milk production traits in dairy cattle, J Dairy Sci, vol.95, issue.2, pp.864-75, 2012.

J. P. Chesnais, T. A. Cooper, G. R. Wiggans, M. Sargolzaei, J. E. Pryce et al., Using genomics to enhance selection of novel traits in North American dairy cattle, J Dairy Sci, vol.99, issue.3, pp.2413-2440, 2016.

V. Clément, B. Bibé, E. Verrier, J. M. Elsen, E. Manfredi et al., Simulation analysis to test the influence of model adequacy and data structure on the estimation of genetic parameters for traits with direct and maternal effects, Genet Sel Evol, vol.33, issue.4, pp.369-95, 2001.

S. A. Clark, J. M. Hickey, and J. H. Van-der-werf, Different models of genetic variation and their effect on genomic evaluation, Genet Sel Evol, vol.43, p.18, 2011.

J. B. Cole, B. Waurich, M. Wensch-dorendorf, D. M. Bickhart, and H. H. Swalve, A genome-wide association study of calf birth weight in Holstein cattle using single nucleotide polymorphisms and phenotypes predicted from auxiliary traits, J Dairy Sci, vol.97, issue.5, p.3156, 2014.

C. Colombani, A. Legarra, S. Fritz, F. Guillaume, P. Croiseau et al., Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCp methods for genomic selection in French Holstein and Montbéliarde breeds, J Dairy Sci, vol.96, issue.1, pp.575-91, 2013.

A. R. Cromie, F. Kearney, R. Evans, and D. P. Berry, Genomics for Pedigree and Cross-bred Beef Cattle Populations: Some experiences from Ireland, Proc 10th World Congr Genet Appl Livest Prod, 2014.

D. C. Croteau-chonka, A. F. Marvelle, E. M. Lange, N. R. Lee, L. S. Adair et al.,

, Genome-wide association study of anthropometric traits and evidence of interactions with age and study year in Filipino women, Obesity, vol.19, issue.5, pp.1019-1046, 2011.

H. D. Daetwyler, A. Capitan, H. Pausch, P. Stothard, R. Van-binsbergen et al., Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle, Nat Genet, vol.46, issue.8, pp.858-65, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193853

H. D. Daetwyler, R. Pong-wong, B. Villanueva, and J. A. Woolliams, The impact of genetic architecture on genome-wide evaluation methods, Genetics, vol.185, issue.3, pp.1021-1052, 2010.

H. D. Daetwyler, F. S. Schenkel, M. Sargolzaei, and J. A. Robinson, A genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using two methods and a dense single nucleotide polymorphism map, J Dairy Sci, vol.91, issue.8, pp.3225-3261, 2008.

C. Delisle, Irlande -Sur l'île verte, l'élevage est roi. Magazine Réussir bovins, 2011.

H. Dobson, R. Smith, M. Royal, K. Ch, and I. Sheldon, The high-producing dairy cow and its reproductive performance, Reprod Domest Anim, vol.42, issue.2, pp.17-23, 2007.

A. C. Dockès, P. Magdelaine, D. Daridan, A. Guillaumin, M. Rémondet et al., Attentes en matière d'élevage des acteurs de la sélection animale, des filières de l'agroalimentaire et des associations, INRA Prod. Anim. 2011, vol.24, issue.4, pp.285-296

J. Dodenhoff, L. D. Van-vleck, and W. De, Comparison of models to estimate genetic effects of weaning weight of Angus cattle, J Anim Sci, vol.77, issue.12, pp.3176-84, 1999.

T. Druet, I. M. Macleod, and B. J. Hayes, Toward genomic prediction from whole-genome sequence data: impact of sequencing design on genotype imputation and accuracy of predictions, Heredity, vol.112, issue.1, pp.39-47, 2014.

S. Dunner, M. E. Miranda, Y. Amigues, J. Cañón, M. Georges et al., Haplotype diversity of the myostatin gene among beef cattle breeds, Genet Sel Evol, vol.35, issue.1, pp.103-121, 2003.
URL : https://hal.archives-ouvertes.fr/hal-02678661

. Eurostat, Agri-environmental indicator -livestock patterns, 2013.

J. L. Evans, B. L. Golden, R. M. Bourdon, and K. L. Long, Additive genetic relationships between heifer pregnancy and scrotal circumference in Hereford cattle, J Anim Sci, vol.77, issue.10, pp.2621-2629, 1999.

E. Bazadaise, Site Internet de l'organisme de sélection, 2016.

J. Ferraz and P. E. De-felicio, Production systems -An example from Brazil. Meat Science, vol.84, pp.238-243, 2010.

, Fine mapping of a calving QTL on Bos taurus autosome 18 in Holstein cattle, J Anim Breed Genet, vol.133, issue.3, pp.207-225, 2016.

R. A. Fisher, The correlation between relatives on the supposition of mendelian inheritance

, Trans R Soc Edingburgh, vol.52, pp.399-433, 1918.

M. R. Fortes, K. L. Deatley, S. A. Lehnert, B. M. Burns, A. Reverter et al., Genomic regions associated with fertility traits in male and female cattle: advances from microsatellites to high-density chips and beyond, Anim Reprod Sci. 2013a, vol.141, issue.1-2, pp.1-19

M. R. Fortes, K. Kemper, S. Sasazaki, A. Reverter, J. E. Pryce et al., Evidence for pleiotropism and recent selection in the PLAG1 region in Australian Beef cattle, Anim Genet. 2013b, vol.44, issue.6, pp.636-683

M. R. Fortes, Y. Li, E. Collis, Y. Zhang, and R. J. Hawken, The IGF1 pathway genes and their association with age of puberty in cattle, Anim Genet. 2013c, vol.44, issue.1, pp.91-96

M. R. Fortes, L. T. Nguyen, P. Neto, L. R. Reverter, A. Moore et al., Polymorphisms and genes associated with puberty in heifers, Theriogenology, vol.86, issue.1, pp.333-342, 2016.

. France-génétique-elevage, Races bovines françaises, 2010.

. L. France-génétique-elevage and . France, Le Pays des races à viande, 2012.

. France-génétique-elevage, Dispositif génétique -Chiffres clés ruminants, 2015.

. France-génétique-elevage, Bovins viande : la sélection génomique en France, 2016.

. Franceagrimer, Les filières de l'élevage Français, 2014.

N. C. Friggens and E. H. Van-der-waaij, Modelling of resource allocation patterns, Resource Allocation Theory Applied to Farm Animal Production, pp.302-320, 2009.

N. Gao, J. Li, J. He, G. Xiao, Y. Luo et al., Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model, BMC Genet, vol.16, p.120, 2015.

D. J. Garrick, J. F. Taylor, and R. L. Fernando, Deregressing estimated breeding values and weighting information for genomic regression analyses, Genet Sel Evol, vol.41, p.55, 2009.

D. J. Garrick and B. L. Golden, Producing and using genetic evaluations in the United States beef industry of today, J Anim Sci, vol.87, pp.11-19, 2009.

D. J. Garrick, Current Status of Genomics applied to Beef Cattle Improvement in North America, Interbeef Genomic workshop. Dublin, 2014.

D. J. Garrick, The nature, scope and impact of genomic prediction in beef cattle in the United States, Genet Sel Evol, vol.43, p.17, 2011.

D. J. Garrick, Hereford Genomic Developments, Hereford World. 2011b

M. Gautier, T. Faraut, K. Moazami-goudarzi, V. Navratil, M. Foglio et al., Genetic and haplotypic structure in 14 European and African cattle breeds, Genetics, vol.177, issue.2, pp.1059-70, 2007.
URL : https://hal.archives-ouvertes.fr/hal-02660515

, Genomik. Les techniques du génotypage, 2016.

S. Gerstmayr, Impact of the data structure on the reliability of the estimated genetic parameters in an animal model with maternal effects, Journal of Animal Breeding and Genetics, vol.109, pp.321-336, 1992.

M. Goddard, Genomic selection: prediction of accuracy and maximisation of long term response, Genetica, vol.136, issue.2, pp.245-57, 2009.

M. E. Goddard and B. J. Hayes, Mapping genes for complex traits in domestic animals and their use in breeding programmes, Nat Rev Genet, vol.10, issue.6, pp.381-91, 2009.

A. Govignon-gion, D. Boichard, P. Croiseau, A. Barbat-leterrier, C. Hoze et al., Identification de mutations candidates affectant la composition du lait en acides gras et protéines par analyse d'association sur la séquence du génome dans les races Holstein, 2015.

L. Griffon, Génomique bovin viande : comment s'y retrouver dans l'offre de typage ? Terra, vol.502, pp.32-33, 2015.

A. R. Guarini, H. H. Neves, F. S. Schenkel, R. Carvalheiro, J. A. Oliveira et al., Genetic relationship among reproductive traits in Nellore cattle, Animal. 2015, vol.9, issue.5, pp.760-765

J. Guerrier, M. N. Fouilloux, J. L. Brunet, A. Delpeuch, A. Havy et al., Ouverture pelvienne : des paramètres génétiques aux index de sélection en station

F. Guillaume, M. Gautier, B. Jemaa, S. Fritz, S. Eggen et al., Refinement of two female fertility QTL using alternative phenotypes in French Holstein dairy cattle, Anim Genet, vol.38, issue.1, pp.72-76, 2007.
URL : https://hal.archives-ouvertes.fr/hal-02659988

M. Gunia, R. Saintilan, E. Venot, C. Hozé, M. N. Fouilloux et al., Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers, J Anim Sci, vol.92, issue.8, pp.3258-69, 2014.

J. K. Höglund, B. Guldbrandtsen, G. Su, B. Thomsen, and M. S. Lund, Genome scan detects quantitative trait loci affecting female fertility traits in Danish and Swedish Holstein cattle, J Dairy Sci, vol.92, issue.5, pp.2136-2179, 2009.

D. Habier, R. Fernando, K. Kizilkaya, and D. J. Garrick, Extension of the bayesian alphabet for genomic selection, BMC Bioinformatics, vol.12, p.186, 2011.

D. Habier, R. L. Fernando, and J. C. Dekkers, The impact of genetic relationship information on genome-assisted breeding values, Genetics, vol.177, issue.4, pp.2389-97, 2007.

. Hammack, Texas Adapted Genetic Strategies for Beef Cattle VI: Creating Breeds. AgriLIFE EXTENSION, 2014.

M. Hannachi and M. Tichit, Does biotechnological innovation require organizational innovation? Learning from the cattle breeding industry in France, Animal Frontiers, vol.6, issue.1, pp.80-85
URL : https://hal.archives-ouvertes.fr/hal-01532516

S. Hassani, M. Saatchi, R. L. Fernando, and D. J. Garrick, Accuracy of prediction of simulated polygenic phenotypes and their underlying quantitative trait loci genotypes using real or imputed whole-genome markers in cattle, Genet Sel Evol, vol.47, p.99, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01341333

R. J. Hawken, Y. D. Zhang, M. R. Fortes, E. Collis, W. C. Barris et al., Genome-wide association studies of female reproduction in tropically adapted beef cattle, J Anim Sci. 2012, vol.90, issue.5, pp.1398-410

B. J. Hayes, P. J. Bowman, A. J. Chamberlain, and M. E. Goddard, Invited review: Genomic selection in dairy cattle: progress and challenges, J Dairy Sci, vol.92, issue.2, pp.433-476, 2009.

B. J. Hayes, P. M. Visscher, and M. E. Goddard, Increased accuracy of artificial selection by using the realized relationship matrix, Genet Res (Camb), vol.91, issue.1, pp.47-60, 2009.

B. J. Hayes, P. J. Chamberlain, A. J. Bowman, P. J. Goddard, and M. E. , Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits, PLoS Genet, vol.6, issue.9, p.1001139, 2010.

C. R. Henderson, O. Kempthorne, S. R. Searle, V. Krosigk, and C. M. , Estimation of environnemental and genetics trends from records subject to culling, Biometrics, vol.15, pp.192-218, 1959.

C. R. Henderson, Applications of Linear Models in Animal Breeding, 1984.

C. Hozé, M. N. Fouilloux, E. Venot, F. Guillaume, R. Dassonneville et al., High-density marker imputation accuracy in sixteen French cattle breeds, Genet Sel Evol, vol.45, p.33, 2013.

. Idele, Note IBOVAL -Première large diffusion des index ABjbf, 2008.

. Idele, Note IBL -les objectifs de sélection évoluent, 2012.

. Idele, Résultats du contrôle de performance bovins allaitants, 2014.

. Idele, Note IBOVAL -Première publication de l'efficacité de carrière, 2014.

. Idele, Note IBOVAL -Première publication de la réussite à l'IA première des génisses en ferme, 2014.

. Idele, Guide pratique du pointage des bovins de race à viande, du sevrage à l'âge adulte, 2014.

. Idele, Chiffres-clés bovins de janvier 2015, issus de la BDNI, 2015.

. Idele, Flux des reproducteurs 2014 dans les races allaitantes. 2015b. idele.fr/?eID=cmis_download&oID=workspace://SpacesStore/e11d0f72-731d-424f-a305-c011752ca5ef

. Idele, Indicateurs de variabilité génétique Prim'Holstein, 2015.

. Idele, Indicateurs de variabilité génétique Blonde d'Aquitaine, 2015.

. Idele, Methods and results of the genetic evaluation IBOVAL 2015 for the beef cattle breeds, 2015.

. Idele, Economie de l'élevage Bovin Viande, 2015.

. Interbev, L'essentiel de la filière viande bovine française, 2015.

, Irish Cattle Breeding Federation. Beef and dairy breed statistics, 2015.

, Irish Cattle Breeding Federation. Beef Genetic Evaluation Files, 2015.

. Irish-food and . Board, Live Cattle Exports, 2016.

D. J. Johnston, . Tier, and H. U. Graser, Beef cattle breeding in Australia with genomics: opportunities and needs, Animal Production Science, vol.52, pp.100-106, 2012.

D. J. Johnston, Genetic improvement of reproduction in beef cattle, Proc 10th World Congr Genet Appl Livest Prod, 2014.

N. K. Kadri, G. Sahana, C. Charlier, T. Iso-touru, B. Guldbrandtsen et al., A 660-Kb deletion with antagonistic effects on fertility and milk production segregates at high frequency in Nordic Red cattle: additional evidence for the common occurrence of balancing selection in livestock, PLoS Genet, vol.10, issue.1, p.1004049, 2014.

T. J. Kaitu'u-lino, L. Ye, L. Tuohey, E. Dimitriadis, J. Bulmer et al., Corin, an enzyme with a putative role in spiral artery remodeling, is up-regulated in late secretory endometrium and first trimester decidua, Hum Reprod. 2013, vol.28, issue.5, pp.1172-80

L. Karim, H. Takeda, L. Lin, T. Druet, J. A. Arias et al., Variants modulating the expression of a chromosome domain encompassing PLAG1 influence bovine stature, Nat Genet. 2011, vol.43, issue.5, pp.405-418

R. E. Kass and A. E. Raftery, Bayes Factor, J American Statistical Association, vol.90, pp.773-795, 1995.

F. Kearney, Genomic selection in beef, Interbeef Genomic workshop. Dublin, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01333705

K. E. Kemper, B. J. Hayes, H. D. Daetwyler, and M. E. Goddard, How old are quantitative trait loci and how widely do they segregate?, J Anim Breed Genet, vol.132, issue.2, pp.121-155, 2015.

K. E. Kemper, C. M. Reich, P. J. Bowman, V. Jagt, C. J. Chamberlain et al., Improved precision of QTL mapping using a nonlinear Bayesian method in a multi-breed population leads to greater accuracy of across-breed genomic predictions, Genet Sel Evol, vol.47, p.29, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01303213

B. W. Kirkpatrick, B. M. Byla, and K. E. Gregory, Mapping quantitative trait loci for bovine ovulation rate, Mamm Genome, vol.11, issue.2, pp.136-145, 2000.

D. C. Knutson, A. M. Mitzey, L. E. Talton, and M. Clagett-dame, Mice null for NEDD9 (HEF1a) display extensive hippocampal dendritic spine loss and cognitive impairment, Brain Res, vol.1632, pp.141-55, 2016.

R. Lande and R. Thompson, Efficiency of marker-assisted selection in the improvement of quantitative traits, Genetics, vol.124, issue.3, pp.743-56, 1990.

R. R. Lareu, M. D. Lacher, R. R. Friis, and A. M. Dharmarajan, Cloning and characterization of a novel zinc finger protein (rZFP96) in the rat corpus luteum, Biochim Biophys Acta, vol.1732, issue.1-3, pp.69-75, 2005.

A. Legarra, C. Robert-granié, E. Manfredi, and J. M. Elsen, Performance of genomic selection in mice, Genetics, vol.180, issue.1, pp.611-619, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02669161

A. Legarra, R. A. Filangi, O. Gs3, and U. Manual, , 2013.

C. Legault, F. Ménissier, P. Mérat, G. Ricodeau, and R. Rouvier, Les lignées originales de l'INRA : historique, développement et impact sur les productions animales. INRA Prod. Anim. Hors série, pp.41-56, 1996.

M. Littlejohn, T. Grala, K. Sanders, C. Walker, G. Waghorn et al., Genetic variation in PLAG1 associates with early life body weight and peripubertal weight and growth in Bos taurus, Animal Genetics, vol.43, pp.591-595, 2011.

S. Llewellyn, R. Fitzpatrick, D. A. Kenny, J. J. Murphy, R. J. Scaramuzzi et al., Effect of negative energy balance on the insulin-like growth factor system in pre-recruitment ovarian follicles of post partum dairy cows. Reproduction, vol.133, pp.627-666, 2007.

D. A. Lourenco, I. Misztal, S. Tsuruta, I. Aguilar, E. E. et al., Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses, J Dairy Sci, vol.97, issue.3, pp.1742-52, 2014.

D. A. Lourenco, S. Tsuruta, B. O. Fragomeni, Y. Masuda, I. Aguilar et al., Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus, J Anim Sci, vol.93, issue.6, pp.2653-62, 2015.
URL : https://hal.archives-ouvertes.fr/hal-02639641

M. S. Lund, A. P. Roos, A. G. Vries, T. Druet, V. Ducrocq et al., A common reference population from four European Holstein populations increases reliability of genomic predictions, Genet Sel Evol, vol.43, p.43, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01191309

J. M. Macdonald and W. D. Mcbride, The Transformation of U.S. Livestock Agriculture, Scale, Efficiency, and Risks, 2009.

I. M. Macleod, P. J. Bowman, V. Jagt, C. J. Haile-mariam, M. Kemper et al., Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits, BMC Genomics, vol.17, p.144, 2016.

M. D. Macneil and T. B. Mott, Genetic analysis of gain from birth to weaning, milk production, and udder conformation in line 1 Hereford cattle, J Anim Sci, vol.84, pp.1639-1684, 2006.

L. Mannini, F. Cucco, V. Quarantotti, C. Amato, M. Tinti et al., SMC1B is present in mammalian somatic cells and interacts with mitotic cohesin proteins, Sci Rep, vol.5, p.18472, 2015.

J. Mantes, Pérennisation du programme DEGERAM : informatisation des données des Fiches Vêlage. Bovins Limousins, vol.204, pp.22-24, 2015.

J. Mantes, Un exemple de construction de population de référence : le programme DEGERAM, 2015.

X. Mao, N. K. Kadri, J. R. Thomasen, D. Koning, D. J. Sahana et al.,

W. D. Mcbride and K. Mathews, The Diverse Structure and Organization of U.S. Beef Cow-Calf Farms, Economic Information Bulletin Number 73, 2011.

&. Meat and . Australia, Production of Australian Beef, 2016.

F. Menissier, L. Journaux, D. Laloë, E. Rehben, C. Lecomte et al., « IBOVAL » : une révolution tranquille dans l'évaluation génétique des bovins allaitants en France, 1996.

T. H. Meuwissen, B. J. Hayes, and M. E. Goddard, Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, issue.4, pp.1819-1848, 2001.

T. H. Meuwissen, Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping, Genet Sel Evol, vol.41, p.35, 2009.

K. Meyer, M. J. Carrick, and B. J. Donnelly, Genetic parameters for milk production of Australian beef cows and weaning weight of their calves, J Anim Sci, vol.72, issue.5, pp.1155-65, 1994.

M. M. Mialon, G. Renand, D. Krauss, and F. Ménissier, Genetic variability of the length of postpartum anoestrus in Charolais cows and its relationship with age at puberty, Genet Sel Evol. 2000, vol.32, issue.4, pp.403-417
URL : https://hal.archives-ouvertes.fr/hal-00894344

A. Michenet, M. Barbat, R. Saintilan, E. Venot, and F. Phocas, Detection of Quantitative Trait Loci for maternal traits using high-density genotypes of Blonde d'Aquitaine beef cattle, BMC Genetics, vol.17, p.88, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02635606

A. Michenet, R. Saintilan, E. Venot, and F. Phocas, Insights into the genetic variation of maternal behavior and suckling performance of continental beef cows, Genet Sel Evol, vol.48, p.45, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01341379

A. Michenet, E. Venot, R. Saintilan, and F. Phocas, Genome-wide scan for reproductive traits of beef heifers using high density SNP panels, Proc 10th World Congr Genet Appl Livest Prod, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01731142

I. Misztal, A. Legarra, and I. Aguilar, Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information, J Dairy Sci, vol.92, issue.9, pp.4648-55, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02755662

I. Misztal, S. Tsuruta, T. Strabel, B. Auvray, T. Druet et al.,

, Proc 7th World Congr Genet Appl Livest Prod, 2002.

H. H. Neves, R. Carvalheiro, A. M. O'brien, Y. T. Utsunomiya, A. S. Do-carmo et al., Accuracy of genomic predictions in Bos indicus (Nellore) cattle, Genet Sel Evol, vol.46, p.17, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01341276

T. Pabiou, Répertoire des méthodes et procédures de contrôle des bovins de races à viande

. Compte-rendu, Département Génétiques, p.91, 10579105.

N. Payet, A. Malafosse, G. Renand, F. Menissier, J. F. Hocquette et al., mise en évidence du polymorphisme des gènes impliqués dans les qualités de la viande en races Charolaise, Limousine et Blonde d'Aquitaine. 3R Communication, 2006.

F. Phocas and D. Laloë, Genetic parameters for birth and weaning traits in French specialized beef cattle breeds. Livest Prod Sci, vol.89, pp.121-129, 2004.
URL : https://hal.archives-ouvertes.fr/hal-02679885

F. Phocas, C. Belloc, J. Bidanel, L. Delaby, J. Y. Dourmad et al., Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes. II. Breeding strategies, Animal, vol.13, pp.1-10, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01533886

M. Pszczola, T. Strabel, H. A. Mulder, and M. P. Calus, Reliability of direct genomic values for animals with different relationships within and to the reference population, J Dairy Sci. 2012, vol.95, issue.1, pp.389-400

F. Race-de,

L. A. Raven, B. G. Cocks, K. E. Kemper, A. J. Chamberlain, V. Jagt et al., Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle, Mamm Genome, vol.27, issue.1-2, pp.81-97, 2016.

C. V. Reeves, X. Wang, P. C. Charles-horvath, J. Y. Vink, V. Y. Borisenko et al., Anthrax toxin receptor 2 functions in ECM homeostasis of the murine reproductive tract and promotes MMP activity, PLoS One. 2012, vol.7, issue.4, p.34862

D. L. Robinson, Models which might explain negative correlations between direct and maternal genetic effects. Livestock Production Science, vol.45, pp.111-122, 1996.

M. Saatchi, M. C. Mcclure, S. D. Mckay, M. M. Rolf, J. Kim et al., Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation, Genet Sel Evol, vol.43, p.40, 2011.

M. Saatchi, R. D. Schnabel, M. M. Rolf, J. F. Taylor, and D. J. Garrick, Accuracy of direct genomic breeding values for nationally evaluated traits in US Limousin and Simmental beef cattle

, Genet Sel Evol, vol.44, p.38, 2012.

M. Saatchi, R. D. Schnabel, J. F. Taylor, and D. J. Garrick, Large-effect pleiotropic or closely linked QTL segregate within and across ten US cattle breeds, BMC Genomics, vol.15, p.442, 2014.

G. Sahana, B. Guldbrandtsen, B. Thomsen, L. E. Holm, F. Panitz et al., Genome-wide association study using high-density single nucleotide polymorphism arrays and whole-genome sequences for clinical mastitis traits in dairy cattle, J Dairy Sci, vol.97, issue.11, pp.7258-75, 2014.

M. Sargolzaei, J. P. Chesnais, and F. S. Schenkel, A new approach for efficient genotype imputation using information from relatives, BMC Genomics, vol.15, p.478, 2014.

C. Schrooten, H. Bovenhuis, W. Coppieters, and J. A. Van-arendonk, Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle, J Dairy Sci, vol.83, issue.4, pp.795-806, 2000.

T. Shimizu, Y. Hirai, and A. Miyamoto, Expression of cyclins and cyclin-dependent kinase inhibitors in granulosa cells from bovine ovary, Reprod Domest Anim. 2013, vol.48, issue.5, pp.65-74

L. Smith, N. Van-hateren, J. Willan, R. Romero, G. Blanco et al., Candidate testis-determining gene, Maestro (Mro), encodes a novel HEAT repeat protein, Dev Dyn, vol.227, issue.4, pp.600-607, 2003.

J. R. Thomasen, B. Guldbrandtsen, G. Su, R. F. Brøndum, and M. S. Lund, Reliabilities of genomic estimated breeding values in Danish Jersey, Animal. 2012, vol.6, issue.5, pp.789-96

J. A. Torres-vázquez and M. L. Spangler, Genetic parameters for docility, weaning weight, yearling weight, and intramuscular fat percentage in Hereford cattle, J Anim Sci. 2016, vol.94, issue.1, pp.21-28

T. Tribout, M. Gunia, R. Saintilan, E. Venot, M. N. Fouilloux et al., Accuracy of genomic prediction in French Charolais cattle population using high-density chip, Proc 10th World Congr Genet Appl Livest Prod, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01194078

T. Tribout, M. Barbat, R. Saintilan, M. N. Fouilloux, E. Venot et al., Mise en place d'évaluations génomiques nationales dans les populations bovines allaitantes françaises Charolaise, Limousine et Blonde d'Aquitaine, 2015.

Y. T. Utsunomiya, A. S. Do-carmo, R. Carvalheiro, H. H. Neves, M. C. Matos et al., Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height, BMC Genet, vol.14, p.52, 2013.

A. Van-eenennaam, Recent Developments in Genetic Evaluations and Genomic Testing. Extension, 2016.

P. M. Vanraden, Efficient methods to compute genomic predictions, J Dairy Sci, vol.91, issue.11, pp.4414-4437, 2008.

E. Venot, P. Schneider, S. Miller, M. Aignel, M. Barbat et al., New French genetic evaluations of fertility and productive life of beef cows, Interbull Bulletin, vol.47, pp.211-216, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01189870

E. Verrier, X. Rognon, G. Leroy, and T. Heams, Le croisement : apports potentiels du croisement, principaux plans de croisement. Cours de génétique AgroParisTech, 2009.

A. Vinet, F. Menissier, G. Caste, S. Astruc, and G. Renand, Bilan génétique de 15 ans de sélection du troupeau souche INRA95, 2006.

A. Vinet, J. L. Touzé, J. Sapa, L. Bodin, S. Fabre et al., Genetic control of ovulation rate in Maine-Anjou cattle, Proc 10th World Congr Genet Appl Livest Prod
URL : https://hal.archives-ouvertes.fr/hal-02742579

S. W. Walsh, E. J. Williams, and A. C. Evans, A review of the causes of poor fertility in high milk producing dairy cows, Anim Reprod Sci. 2011, vol.123, issue.3-4, pp.127-165
URL : https://hal.archives-ouvertes.fr/hal-02651355

H. Wang, I. Misztal, I. Aguilar, A. Legarra, and W. M. Muir, Genome-wide association mapping including phenotypes from relatives without genotypes, Genet Res (Camb). 2012, vol.94, issue.2, p.73
URL : https://hal.archives-ouvertes.fr/hal-02652510

H. Wang, L. Jiang, X. Liu, J. Yang, J. Wei et al., A post-GWAS replication study confirming the PTK2 gene associated with milk production traits in Chinese Holstein, PLoS One, vol.8, issue.12, p.83625, 2013.

D. C. Wathes, G. E. Pollott, K. F. Johnson, H. Richardson, and J. S. Cooke, Heifer fertility and carry over consequences for life time production in dairy and beef cattle, Animal. 2014, vol.8, issue.1, p.91

Y. C. Wientjes, M. P. Calus, M. E. Goddard, and B. J. Hayes, Impact of QTL properties on the accuracy of multi-breed genomic prediction, Genet Sel Evol, vol.47, p.42, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01312613

S. Y. Wu and A. K. Sood, New roles opined for OPCML. Cancer Discov, vol.2, pp.115-121, 2012.

Z. Zhang, U. Ober, M. Erbe, H. Zhang, N. Gao et al., Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across Breed Prediction in Dairy Cattle: A Simulation Study, e93017. van den Berg I, vol.9

A. Michenet, E. Venot, R. Saintilan, and F. Phocas, Genome-wide scan for reproductive traits of beef heifers using high density SNP panels, Proc 10th World Congr Genet Appl Livest Prod
URL : https://hal.archives-ouvertes.fr/hal-01731142

C. Vancouver, , 2014.

A. Michenet, M. Barbat, R. Saintilan, E. Venot, and F. Phocas, Candidate genes for milk production traits in Limousin beef cattle. Plant and Animal Genome Conference, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02741791

;. ). Vancouver, , 2014.

, Annexe 2 Liste des QTL de vêlage et d'allaitement en race Blonde d'Aquitaine

, Annexe 3 Résumé du poster présenté à la conférence Plant et Animal Genome, 2016.

, Annexe 4 Liste des QTL de vêlage et d'allaitement

, Annexe 5 Moyenne et écart type des valeurs brutes pour les caractères évalués en station, p.208

, Annexe 6 Effets fixes et covariables d'environnement pris en compte pour l'évaluation des caractères évalués en station

, Annexe 7 Héritabilités et corrélations génétiques des conditions de vêlage en station (CV) et des effets directs (CNd) et maternels (CNm) des conditions de naissance en ferme, p.208

D. Grohs, C. Bourgeois, and F. , Annexe 8 Index publiés à partir des mesures collectées en station de contrôle sur descendance des qualités maternelles, 2003.

, Sel. Evol, vol.35, pp.77-101

B. L. Browning and S. R. Browning, Am. J. Hum. Genet, vol.84, pp.210-223, 2009.

E. Casas, D. D. Lunstra, and R. T. Stone, Animal Genetics, vol.35, pp.451-453, 2004.

H. D. Daetwyler, F. S. Schenkel, and M. Sargolzaei,

, J. Dairy Sci, vol.91, pp.3225-3236

N. Forde, G. B. Duffy, and P. A. Mcgettigan, Physiol Genomics, vol.44, pp.799-810, 2012.

F. Guillaume, M. Gautier, and S. Ben-jemaa, Animal Genetic.s, vol.38, pp.72-74, 2007.

D. Habier, R. L. Fernando, and K. Kizilkaya, , 2011.

, BMC Bioinformatics, vol.12, p.186

J. K. Hoglund, B. Guldbrandtsen, and G. Su, , 2009.

, J. Dairy Sci, vol.92, pp.2136-2143

C. Hozé, M. N. Fouilloux, and E. Venot, , 2013.

, Genet. Sel. Evol, vol.45, p.33

Z. L. Hu, C. A. Park, and X. L. Wu, Nucleic Acids Research, vol.41, pp.871-879, 2012.

E. Kass and E. Raftery, J. American Statistical Association, vol.430, pp.773-795, 1995.

B. W. Kirkpatrick, B. M. Byla, and K. E. Gregory, Mammalian Genome, vol.11, pp.136-139, 2000.

A. Legarra, A. Ricard, and O. Filangi, , 2013.

M. M. Mialon, G. Renand, and D. Krauss, Genet. Sel. Evol, vol.32, pp.403-414, 2000.

F. Phocas and J. Sapa, J. Anim. Sci, vol.79, pp.41-48, 2004.

E. C. Pimentel, S. Bauersachs, and M. Tietzeet, Animal Genetics, vol.42, pp.251-262, 2011.

M. Saatchi, R. D. Schnabel, and M. M. Rolf, , 2012.

A. Schurink, L. L. Janss, and H. C. Heuven, Genet. Sel. Evol, vol.44, p.38, 2011.

, BMC Proceedings, vol.6, issue.2, p.8

C. Shrooten, H. Bovenhuis, and W. Coppieterset, , 2000.

, J. Dairy. Sci, vol.83, pp.795-806

W. M. Snelling, R. A. Cushman, and M. R. Fortes, J. Anim. Sci, vol.90, pp.1152-1165, 2011.