D. Boichard, R. Dassonneville, S. Mattalia, V. Ducrocq, and S. Fritz, All cows are worth to be genotyped, ! Interbull Bull, vol.47, pp.256-260, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01004649

D. Boichard, F. Guillaume, A. Baur, P. Croiseau, M. Rossignol et al., Genomic selection in French dairy cattle, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01000202

, Anim. Prod. Sci, vol.52, pp.115-120

J. B. Coulon, L. Perochon, and F. Lescouret, Modelling the effect of the stage of pregnancy on dairy cows' milk yield, Anim. Sci, vol.60, pp.401-408, 1995.
URL : https://hal.archives-ouvertes.fr/hal-02712041

C. Dezetter, N. Bareille, D. Billon, C. Côrtes, C. Lechartier et al., Changes in animal performance and profitability of Holstein dairy operations after introduction of crossbreeding with Montbéliarde, Normande, and Scandinavian Red, J. Dairy Sci, vol.100, pp.8239-8264, 2017.

J. F. Ettema, S. Østergaard, and M. Sørensen, Effect of including genetic progress in milk yield on evaluating the use of sexed semen and other reproduction strategies in a dairy herd, Animal, vol.5, pp.1887-1897, 2011.

J. F. Ettema, J. R. Thomasen, L. Hjortø, M. Kargo, S. Østergaard et al., Economic opportunities for using sexed semen and semen of beef bulls in dairy herds, J. Dairy Sci, vol.100, pp.4161-4171, 2017.

L. Hjortø, J. F. Ettema, M. Kargo, and A. C. Sørensen, Genomic testing interacts with reproductive surplus in reducing genetic lag and increasing economic net return, J. Dairy Sci, vol.98, pp.646-658, 2015.

W. D. Hohenboken, Applications of sexed semen in cattle production, Theriogenology, vol.52, pp.1421-1433, 1999.

S. A. Holden and S. Butler, Review: Applications and benefits of sexed semen in dairy and beef herds, Animal, vol.12, pp.97-103, 2018.

. Insee, Taux d'inflation en 2018, données annuelles de, 1991.

T. Johnson, K. Eketone, L. Mcnaughton, K. Tiplady, J. Voogt et al., Mating strategies to maximize genetic merit in dairy cattle herds, J. Dairy Sci, vol.101, pp.4650-4659, 2018.

K. Kaniyamattam, M. A. Elzo, J. B. Cole, and A. Vries, Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies, J. Dairy Sci, vol.99, pp.8187-8202, 2016.

L. Mézec and P. , Le point sur l'utilisation de semence sexée en 2015. Institut de l'Elevage, 2016.

R. Lenth, emmeans: Estimated Marginal Means, aka Least-Squares Means, 2018.

K. Mccullock, D. Hoag, J. Parsons, M. Lacy, G. Seidel et al., Factors affecting economics of using sexed semen in dairy cattle, J. Dairy Sci, vol.96, pp.6366-6377, 2013.

J. E. Newton, B. J. Hayes, and J. E. Pryce, The cost-benefit of genomic testing of heifers and using sexed semen in pasture-based dairy herds, J. Dairy Sci, vol.101, pp.2017-13476, 2018.

H. D. Norman, J. L. Hutchison, and R. H. Miller, Use of sexed semen and its effect on conception rate, calf sex, dystocia, and stillbirth of Holsteins in the United States, J. Dairy Sci, vol.93, pp.3880-3890, 2010.

J. Pryce and B. Hayes, A review of how dairy farmers can use and profit from genomic technologies, Anim. Prod. Sci, vol.52, pp.180-184, 2012.

. R-core-team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2018.

K. A. Weigel, P. C. Hoffman, W. Herring, and T. J. Lawlor, Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves on commercial dairy farms, J. Dairy Sci, vol.95, pp.2215-2225, 2012.

P. D. Wood, Algebraic model of the lactation curve in cattle, Nature, vol.216, pp.164-165, 1967.

S. Floriot, C. Vesque, S. Rodriguez, F. Bourgain-guglielmetti, A. Karaiskou et al., C-Nap1 mutation affects centriole cohesion and is associated with a Seckel-like syndrome in cattle, Nature Communications, vol.6, p.6894, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01194104

S. Fritz, A. Capitan, A. Djari, S. Rodriguez, A. Barbat et al., Detection of haplotypes associated with prenatal death in dairy cattle and identification of deleterious mutations in GART, SHBG, and SLC37A2, Plos One, vol.8, p.65550, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01000118

N. Gengler, P. Mayeres, and M. Szydlowski, A simple method to approximate gene content in large pedigree populations: application to the myostatin gene in dual-purpose Belgian Blue cattle, Animal, vol.1, p.28, 2007.

J. Howard, J. Pryce, C. Baes, and C. Maltecca, Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability, Journal of Dairy Science, vol.100, pp.1-16, 2017.

C. Hozé, S. Fritz, A. Baur, C. Grohs, C. Danchin-burge et al., Prise en compte des gènes d'intérêt dans les objectifs de sélection en bovins laitiers, Name of the "3R -Rencontres autour des Recherches sur les Ruminants" meeting pp. 1-4, 2017.

G. Jansen and J. Wilton, Selecting mating pairs with linear programming techniques, Journal of Dairy Science, vol.68, pp.1302-1305, 1985.

G. Malécot, Les Mathématiques de L'hérédité, 1948.

P. Michot, S. Fritz, A. Barbat, M. Boussaha, M. Deloche et al., , 2017.

, Les accouplements réellement effectués en élevage ne sont pas toujours identiques à ceux programmés lors de l'établissement du plan d'accouplement. De plus, les index génétiques ou génomiques des animaux (mâles et femelles) sont recalculés plusieurs fois par an afin de tenir compte des nouvelles données et performances disponibles. Enfin, de nouveaux jeunes taureaux ayant atteint leur maturité sexuelle arrivent sur le marché

, Un des logiciels d'accouplement utilisé en race Montbéliarde, appelé « GENERATIONS » (Mickaël Brochard, communication personnelle), propose une mise à jour fréquente des plans

D. Akdemir and J. I. Sánchez, Efficient breeding by genomic mating, Frontiers in Genetics, vol.7, pp.1-12, 2016.

A. , Principes et méthodes du génotypage, 2019.

O. T. Avery, C. M. Mcleod, and M. Mccarthy, Induction of transformation by a desoxyribonucleic acid fraction isolated from Pneumococcus Type III, Journal of Experimental Medicine, vol.79, pp.137-158, 1944.

C. F. Baes, B. O. Makanjuola, F. Miglior, G. Marras, J. T. Howard et al., Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance, Journal of Dairy Science, vol.102, pp.2807-2817, 2019.

M. Bérodier, P. Berg, T. Meuwissen, M. Brochard, and . Ducrocq-v-2019a, Improving mating plans at herd level using genomic information, EAAP Annual Meeting

B. Gand,

M. Bérodier, M. Brochard, D. Boichard, C. Dezetter, N. Bareille et al., , 2019.

, Dairy Science, vol.102, pp.10073-10087

M. Bérodier, M. Brochard, C. Dezetter, N. Bareille, and V. Ducrocq, Effect of mating strategies on genetic and economic outcomes in a Montbéliarde dairy herd, EAAP Annual Meeting, p.199, 2018.

D. Boichard, R. Dassonneville, S. Mattalia, V. Ducrocq, and S. Fritz, All cows are worth to be genotyped, Interbull Bulletin, vol.47, pp.256-260, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01004649

D. Boichard, C. Grohs, C. Danchin-burge, and . Capitan-a-2016a, Les anomalies génétiques: Définition, origine, transmission et évolution, mode d'action, INRA Productions Animales, vol.29, pp.297-305

D. Boichard, C. Grohs, P. Michot, C. Danchin-burge, A. Capitan et al., Prise en compte des anomalies génétiques en sélection: Le cas des bovins, INRA Productions Animales, vol.29, pp.351-358

D. Boichard, F. Guillaume, A. Baur, P. Croiseau, M. Rossignol et al.,

L. , C. J. Journaux, L. Ducrocq, V. Fritz, and S. , Genomic selection in French dairy cattle, Animal Production Science, vol.52, pp.115-120, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01000202

S. Bouyssiere, M. Carlier, and B. Lelyon, Le croisement viande en élevage laitier : état des lieux des pratiques et perspectives, Rencontres autour de la recherche sur les ruminants, pp.225-228, 2013.

M. Brochard, D. Boichard, A. Capitan, G. Fayolle, F. S. et al., pANO, le risque d'anomalie létale pour les produits d'accouplements : principe et utilisation en race Montbéliarde sur la zone GEN'IAtest, Rencontres autour de la recherche sur les ruminants, 2018.

S. T. Butler, I. A. Hutchinson, A. R. Cromie, and L. Shalloo, , 2014.

M. Calus, P. Bijma, and R. F. Veerkamp, Evaluation of genomic selection for replacement strategies using selection index theory, Journal of Dairy Science, vol.98, pp.6499-6509, 2015.

T. R. Carthy, J. Mccarthy, and D. P. Berry, A mating advice system in dairy cattle incorporating genomic information, Journal of Dairy Science, 2019.

, Les mammites j'anticipe -Prévenir et réduire les mammites en élevage laitier -Chiffres clés, 2019.

J. B. Cole, , 2015.

J. B. Cole, D. J. Null, and P. M. Vanraden, Phenotypic and genetic effects of recessive haplotypes on yield, longevity, and fertility, Journal of Dairy Science, vol.99, pp.7274-7288, 2016.

J. J. Colleau, K. Tual, D. Preaumont, H. Regaldo, and D. , A mating method accounting for inbreeding and multi-trait selection in dairy cattle populations, Genetics Selection Evolution, vol.41, pp.1-10, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02662992

J. F. Crow and M. Kimura, An introduction to population genetic theory, 1970.

H. D. Daetwyler, A. Capitan, H. Pausch, P. Stothard, R. Van-binsbergen et al.,

X. , D. A. Rodriguez, S. C. Grohs, C. Esquerré, D. Bouchez et al., Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle, Nature Genetics, vol.46, p.858, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193853

C. Darwin, Des bons effets du croisement, et des résultats nuisibles de la reproduction consanguine, De la variation des animaux et des plantes sous l'action de la domestication, pp.121-153

C. Dezetter, Evaluation de l'intérêt du croisement entre races bovines laitières, 2015.

. Thèse, Oniris -l'École Nationale Vétérinaire Agroalimentaire et de l'Alimentation Nantes-Atlantique, p.226

C. Dezetter, N. Bareille, D. Billon, C. Côrtes, C. Lechartier et al., Changes in animal performance and profitability of Holstein dairy operations after introduction of crossbreeding with Montbéliarde, Normande, and Scandinavian Red, Journal of Dairy Science, vol.100, pp.8239-8264, 2017.

C. Dezetter, H. Leclerc, S. Mattalia, A. Barbat, D. Boichard et al., Inbreeding and crossbreeding parameters for production and fertility traits in, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01194131

M. Holstein and N. Cows, Journal of Dairy Science, vol.98, pp.4904-4913

H. P. Doekes, R. F. Veerkamp, P. Bijma, G. De-jong, H. Sj et al., , 2019.

H. P. Doekes, R. F. Veerkamp, S. J. Hiemstra, P. Bijma, and J. J. Windig, , 2017.

A. Doublet, P. Croiseau, S. Fritz, A. Michenet, C. Hozé et al., The impact of genomic selection on genetic diversity and genetic gain in three French dairy cattle breeds, Genetics Selection Evolution, vol.51, p.52, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02300856

. Draaf-bourgogne-franche-comté, DRAAF Bourgogne-Franche-Comté -Filière lait. Retrieved on, 2019.

A. Duchesne, C. Grohs, P. Michot, M. Bertaud, D. Boichard et al., , 2016.

, Du phénotype à la mutation causale: Le cas des anomalies récessives bovines, INRA Productions Animales, vol.29, pp.319-327

A. Duchesne, L. Manciaux, M. Gautier, S. Floriot, C. Grohs et al., A Generalized Caprine-like Hypoplasia Syndrome is, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02659723

J. F. Ettema and S. Østergaard, Economic decision making on prevention and control of clinical lameness in Danish dairy herds, Livestock Science, vol.102, pp.92-106, 2006.

J. F. Ettema, S. Østergaard, and M. K. Sørensen, , pp.1887-1897, 20115.

J. F. Ettema, J. R. Thomasen, L. Hjortø, M. Kargo, S. Østergaard et al., , 2017.

S. Floriot, C. Vesque, S. Rodriguez, F. Bourgain-guglielmetti, A. Karaiskou et al., , 2015.

, Enquête mensuelle laitière -Lait biologique -N°48 / Février, FranceAgriMer, 2019.

/. Données-de-décembre, 2Fproductions animales%2Flait et produits laitiers%2Fenquête mensuelle laitière%2Flait biologique%2FENQ-LAI-EML-Bio-A18, 2018.

. M12 and . Pdf&telechargersanscomptage=oui,

S. Fritz, A. Capitan, A. Djari, S. C. Rodriguez, A. Barbat et al.,

M. , E. D. Klopp, C. Rocha, D. Boichard, and D. , Detection of Haplotypes Associated with Prenatal Death in Dairy Cattle and Identification of Deleterious Mutations in GART, SHBG and SLC37A2, PLoS ONE, vol.8, pp.2-9, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01000118

S. Fritz, P. Michot, C. Hoze, C. Grohs, A. Barbat-leterrier et al., Anticiper l'émergence d'anomalies génétiques grâce aux données génomiques, INRA Productions Animales, vol.29, pp.339-349, 2016.

B. Fuerst-waltl, C. Fuerst, W. Obritzhauser, and C. Egger-danner, Sustainable breeding objectives and possible selection response: Finding the balance between economics and breeders' preferences, Journal of Dairy Science, vol.99, pp.9796-9809, 2016.

T. Fujii, A. Naito, H. Hirayama, M. Kashima, H. Yoshino et al., Potential of preimplantation genomic selection for carcass traits in Japanese Black cattle. The journal of reproduction and devleopment 65, pp.251-258, 2019.

. Geb-institut-de-l'elevage, Evaluation génétique des taureaux montbéliards. Production laitière -Morphologie -Caractères fonctionnels, 2018.

G. Hossein-zadeh, N. Nejati-javaremi, A. Miraei-ashtiani, S. R. Kohram, and H. , , 2010.

, Bio-economic evaluation of the use of sexed semen at different conception rates and herd sizes in Holstein populations, Animal Reproduction Science, vol.121, pp.17-23

J. Guerrier, OSIRIS : Objectifs de Sélection Innovants en Ruminants et Indices de Synthèses, Élevage. Retrieved on, 2015.

F. Guignot, C. Perreau, F. Reigner, B. Bed'hom, M. et al., , 2013.

, Premières gestations après transfert d'embryons équins biopsés et sexés, p.39

, L'Equitation), pp.28-33

B. J. Hayes, M. Carrick, P. Bowman, and G. Me, Genotype × Environment Interaction for Milk Production of Daughters of Australian Dairy Sires from Test-Day Records, Journal of Dairy Science, vol.86, pp.3736-3744, 2003.

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

C. Herrera, Clinical Applications of Preimplantation Genetic Testing in Equine, Bovine, and Human Embryos, Journal of Equine Veterinary Science, vol.41, pp.29-34, 2016.

L. Hjortø, J. F. Ettema, M. Kargo, and A. C. Sørensen, Genomic testing interacts with reproductive surplus in reducing genetic lag and increasing economic net return, Journal of Dairy Science, vol.98, pp.646-658, 2015.

W. D. Hohenboken, Applications of sexed semen in cattle production, 1999.

, Theriogenology, vol.52, pp.1421-1433

S. A. Holden and S. T. Butler, Review: Applications and benefits of sexed semen in dairy and beef herds, Animal, vol.12, pp.97-103, 2018.

J. T. Howard, J. E. Pryce, C. Baes, and C. Maltecca, Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability, Journal of Dairy Science, vol.100, pp.6009-6024, 2017.

B. Huquet, Utilisation des données de contrôles élémentaires pour la modélisation et l'estimation des interactions génotype x milieu, Sciences et Industries du Vivant et de l'Environnement (AgroParisTech), p.178, 2012.

, IFOAM. Les principes de l'agriculture biologique, 2019.

. Inao and . Inao, , 2019.

, Résultats de Contrôle Laitier, 2018.

D. Jónás, Evaluation of haplotype-based genomic selection methods with focus on their performances in a multi-breed context in dairy cattle, p.225, 2016.

K. Kaniyamattam, M. A. Elzo, C. J. , D. Vries, and A. , Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies, Journal of Dairy Science, vol.99, pp.8187-8202, 2016.

M. Kardos, G. Luikart, and F. W. Allendorf, Measuring individual inbreeding in the age of genomics: Marker-based measures are better than pedigrees, Heredity, vol.115, p.63, 2015.

C. M. Kariuki, J. Van-arendonk, A. K. Kahi, and H. Komen, , 2017.

M. Kirin, R. Mcquillan, C. S. Franklin, H. Campbell, P. M. Mckeigue et al., , 2010.

, Genomic runs of homozygosity record population history and consanguinity, PloS one, vol.5, pp.13996-13996

A. B. Kudahl, S. S. Nielsen, and S. Østergaard, Economy, Efficacy, and Feasibility of a Risk-Based Control Program Against Paratuberculosis, Journal of Dairy Science, vol.91, pp.4599-4609, 2008.

L. Mezec and P. , Le point sur l'insémination en semence sexée en 2015, 2016.

L. Mezec, P. Guerrier, J. Roinsard, and A. , Les élevages de bovins bio en France : choix de conduite, génétique et résultats techniques, Sommet de l'Elevage, p.29, 2016.

B. Leclerc and B. Vissac, Les vaches de la République -Saisons et raisons d'un chercheur citoyen, 2002.

G. Leroy, Inbreeding depression in livestock species: Review and meta-analysis, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193843

, Animal Genetics, vol.45, pp.618-628

G. Malecot, Les Mathématiques de l'Hérédité, 1948.

K. Mccullock, D. Hoag, J. Parsons, M. Lacy, G. E. Seidel et al., Factors affecting economics of using sexed semen in dairy cattle, Journal of Dairy Science, vol.96, pp.6366-6377, 2013.

T. H. Meuwissen, H. Bj, and G. Me, Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, pp.1819-1829, 2001.

T. Meuwissen and A. K. Sonesson, Maximizing the Response of Selection with a, 1998.

, Predefined Rate of Inbreeding: Overlapping Generations, Journal of Animal Science, vol.76, pp.2575-2583

R. Meyermans, W. Gorssen, N. Buys, and S. Jansses, Missing ROHrecommendantions for tuning PLINK in ROH analyses, EAAP Annual Meeting, 2019.

B. Gand,

P. Michot, S. Chahory, A. Marete, C. Grohs, D. Dagios et al.,

C. Burge, S. Fritz, D. Boichard, and A. Capitan, A reverse genetic approach identifies, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01479315

P. Michot, S. Fritz, A. Barbat, M. Boussaha, M. C. Deloche et al., , 2017.

S. Minery, Adaptation des animaux en fonction des systèmes d'élevage -Les interactions génotype x milieu, 2016.

E. Molliex, Analyse des plans d'accouplement « génomiques, 2019.

, Montbéliarde -Comparaison de cette nouvelle méthode face aux conseils actuels donnés en race Montbéliarde. Rapport de stage, ISARA, p.76

, Montbéliarde Association. Montbéliarde Association. Retrieved on, 2019.

H. A. Mulder, R. F. Veerkamp, B. J. Ducro, J. Van-arendonk, and P. Bijma, Optimization of Dairy Cattle Breeding Programs for Different Environments with Genotype by Environment Interaction, Journal of Dairy Science, vol.89, pp.1740-1752, 2006.

J. E. Newton, H. Bj, and J. E. Pryce, The cost-benefit of genomic testing of heifers and using sexed semen in pasture-based dairy herds, Journal of Dairy Science, vol.101, pp.6159-6173, 2018.

H. D. Norman, J. L. Hutchison, and R. H. Miller, Use of sexed semen and its effect on conception rate, calf sex, dystocia, and stillbirth of Holsteins in the United States, Journal of Dairy Science, vol.93, pp.3880-3890, 2010.

S. Østergaard, M. Chagunda, N. C. Friggens, T. W. Bennedsgaard, and K. Ic, A Stochastic Model Simulating Pathogen-Specific Mastitis Control in a Dairy Herd, Journal of Dairy Science, vol.88, pp.4243-4257, 2005.

L. D. Pedersen, A. C. Sørensen, M. Henryon, S. Ansari-mahyari, and P. Berg, , 2009.

C. Pfeiffer, C. Fuerst, H. Schwarzenbacher, and B. Fuerst-waltl, , 2016.

F. Phocas, C. Belloc, L. Delaby, J. Y. Dourmad, C. Ducrot et al., , 2015.

. Procross and . Procross, Comment ça marche ?, 2019.

P. J. Hayes and B. , A review of how dairy farmers can use and pro fi t from genomic technologies, Animal Production Science, vol.52, pp.180-184, 2012.

J. E. Pryce, H. Bj, and G. Me, , 2011.

M. Pszczola and M. Calus, Updating the reference population to achieve constant genomic prediction reliability across generations, vol.10, pp.1018-1024, 2016.

. Reproscope and . Reproscope, , 2019.

D. Santos, J. B. Cole, T. J. Lawlor, P. M. Vanraden, H. Tonhati et al., Variance of gametic diversity and its application in selection programs, Journal of Dairy Science, vol.102, pp.5279-5294, 2019.

L. R. Schaeffer, Strategy for applying genome-wide selection in dairy cattle, Journal of Animal Breeding and Genetics, vol.123, pp.218-223, 2006.

A. Simherd, Simulation model of a dairy herd, 2019.

M. Slagboom, M. Kargo, A. C. Sørensen, J. R. Thomasen, and H. A. Mulder, , 2019.

M. Slagboom, A. Wallenbeck, L. Hjortø, A. C. Sørensen, L. Rydhmer et al.,

M. Kargo, Simulating consequences of choosing a breeding goal for organic dairy production, Journal of Dairy Science, vol.101, pp.11086-11096, 2018.

A. K. Sonesson and T. H. Meuwissen, Mating schemes for optimum contribution selection with constrained rates of inbreeding, Genetics Selection Evolution, vol.32, pp.231-248, 2000.
URL : https://hal.archives-ouvertes.fr/hal-00894333

A. K. Sonesson, J. A. Woolliams, and T. Meuwissen, Genomic selection requires genomic control of inbreeding, Genetics Selection Evolution, vol.44, pp.1-10, 2012.

J. T. Sørensen, E. S. Kristensen, and I. Thysen, A stochastic model simulating the dairy herd on a PC, Agricultural Systems, vol.39, pp.177-200, 1992.

A. C. Sørensen, P. Madsen, M. K. Sørensen, and P. Berg, Udder Health Shows Inbreeding Depression in Danish Holsteins, Journal of Dairy Science, vol.89, pp.4077-4082, 2010.

E. Strandberg, Animal Genetic * Environment Interaction, Encyclopedia of Sustainability Science and Technology, 2011.

P. G. Sullivan and J. H. Jakobsen, GMACE Pilot #4: Adjusting the National Reliability Input Data, Interbull Bulletin, vol.48, pp.40-45, 2014.

C. Sun, P. M. Vanraden, J. R. O'connell, K. A. Weigel, and D. Gianola, Mating programs including genomic relationships and dominance effects, Journal of Dairy Science, vol.96, pp.8014-8023, 2013.

F. Tiezzi, G. De-los-campos, P. Gaddis, K. L. Maltecca, and C. , Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle, Journal of Dairy Science, vol.100, pp.2042-2056, 2017.

F. Tiezzi, P. Gaddis, K. L. , C. Js, and C. Maltecca, , 2015.

P. M. Vanraden, Efficient Methods to Compute Genomic Predictions, Journal of Dairy Science, vol.91, pp.4414-4423, 2008.

K. A. Weigel, Exploring the role of sexed semen in dairy production systems, Journal of Dairy Science, vol.87, pp.120-130, 2004.

K. A. Weigel, P. C. Hoffman, W. Herring, and T. J. Lawlor, Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves on commercial dairy farms, Journal of Dairy Science, vol.95, pp.2215-2225, 2012.

S. Wright, Coefficients of inbreeding and relationship, The American Naturalist, pp.330-338, 1922.

, Interface de l'application web MyUmo -Mootic (web service proposé par Umotest) permettant aux éleveurs de simuler les accouplements de leur troupeau. Les données des colonnes ISUG?, ISUG et parenté (avec exposant G) (encadrées en vert) sont directement inspirées des travaux de cette thèse

, un embryon atteint d'une anomalie génétique. Enfin, nous nous sommes intéressés à des objectifs de sélection « systèmes spécifiques », différents de l'objectif racial, et à leurs conséquences sur la planification des couples lors de l'établissement des plans d'accouplement. Nous avons construit trois objectifs de sélection différents de l'objectif racial, soit au total quatre systèmes d'élevage différents (deux en système « standard » et deux en système « agriculture biologique »). Nos résultats nous permettent de conclure que la prise en compte d'objectifs de sélection spécifiques