H. D. Daetwyler, B. Villanueva, P. Bijma, and J. A. Woolliams, Inbreeding in genome-wide selection, Journal of Animal Breeding and Genetics, vol.80, issue.6, pp.369-376, 2007.
DOI : 10.1111/j.1439-0388.2007.00693.x

H. D. Daetwyler, B. Villanueva, and J. A. Woolliams, Accuracy of Predicting the Genetic Risk of Disease Using a Genome-Wide Approach, PLoS ONE, vol.5, issue.10, pp.1-8, 2008.
DOI : 10.1371/journal.pone.0003395.s002

J. C. Dekkers, Abstract, Animal Production, vol.50, issue.03, pp.351-360, 1992.
DOI : 10.1016/0301-6226(88)90058-9

D. Habier, J. Tetens, F. R. Seefried, P. Lichtner, and G. Thaller, The impact of genetic relationship information on genomic breeding values in German Holstein cattle, Genetics Selection Evolution, vol.42, issue.1, p.5, 2010.
DOI : 10.1186/1297-9686-42-5

B. Hayes and M. E. Goddard, The distribution of the effects of genes affecting quantitative traits in livestock, Genetics Selection Evolution, vol.33, issue.3, pp.209-229, 2001.
DOI : 10.1186/1297-9686-33-3-209

URL : https://hal.archives-ouvertes.fr/hal-00894372

B. J. Hayes, P. J. Bowman, A. J. Chamberlain, and M. E. Goddard, Genomic selection in dairy cattle: Progress and challenges, 2009.

W. G. Hill, Effects of population size on response to short and long term selection1, Journal of Animal Breeding and Genetics, vol.153, issue.1-5, pp.161-173, 1985.
DOI : 10.1111/j.1439-0388.1985.tb00684.x

J. L. Jannink, Dynamics of long-term genomic selection, Genetics Selection Evolution, vol.42, issue.1, p.35, 2010.
DOI : 10.1186/1297-9686-42-35

M. Lillehammer, T. H. Meuwissen, and A. K. Sonesson, Genomic selection for maternal traits in pigs, Journal of Animal Science, vol.89, issue.12, pp.3908-3916, 2011.
DOI : 10.2527/jas.2011-4044

T. H. Meuwissen, Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping, Genetics Selection Evolution, vol.41, issue.1, p.35, 2009.
DOI : 10.1186/1297-9686-41-35

T. H. Meuwissen, B. J. Hayes, and M. E. Goddard, Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, pp.1819-1829, 2001.

T. Meuwissen, B. Hayes, and M. Goddard, Prediction of total genetic value using genome-wide dense marker maps, Genetics, vol.157, pp.1819-1829, 2001.

B. Hayes, P. Bowman, A. Chamberlain, and M. Goddard, Invited review: Genomic selection in dairy cattle: Progress and challenges, Journal of Dairy Science, vol.92, issue.2, pp.433-443, 2009.
DOI : 10.3168/jds.2008-1646

L. Schaeffer, Strategy for applying genome-wide selection in dairy cattle, Journal of Animal Breeding and Genetics, vol.83, issue.4, pp.218-223, 2006.
DOI : 10.1111/j.1439-0388.2006.00595.x

F. Du, A. Clutter, and M. Lohuis, Characterizing Linkage Disequilibrium in Pig Populations, International Journal of Biological Sciences, vol.3, pp.166-178, 2007.
DOI : 10.7150/ijbs.3.166

P. Uimari and M. Tapio, Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds, Journal of Animal Science, vol.89, issue.3, pp.609-614, 2011.
DOI : 10.2527/jas.2010-3249

M. Lillehammer, T. Meuwissen, and A. Sonesson, Genomic selection for maternal traits in pigs, Journal of Animal Science, vol.89, issue.12, pp.3908-3916, 2011.
DOI : 10.2527/jas.2011-4044

T. Tribout and C. Larzul, Efficiency of genomic selection in a purebred pig male line, Journal of Animal Science, vol.90, issue.12, pp.4164-4176, 2012.
DOI : 10.2527/jas.2012-5107

URL : https://hal.archives-ouvertes.fr/hal-01001279

B. Hayes and M. Goddard, The distribution of the effects of genes affecting quantitative traits in livestock, Genetics Selection Evolution, vol.33, issue.3, pp.209-229, 2001.
DOI : 10.1186/1297-9686-33-3-209

URL : https://hal.archives-ouvertes.fr/hal-00894372

R. Quaas and E. Pollak, Mixed Model Methodology for Farm and Ranch Beef Cattle Testing Programs, Journal of Animal Science, vol.51, issue.6, pp.1277-1287, 1980.
DOI : 10.2527/jas1981.5161277x

T. Meuwissen, Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping, Genetics Selection Evolution, vol.41, issue.1, p.35, 2009.
DOI : 10.1186/1297-9686-41-35

D. Boichard, PEDIG: a FORTRAN package for pedigree analysis suited for large populations, Montpellier: Proceedings of the 7th World Congress on Genetics Applied to Livestock Production, pp.19-2328, 2002.

J. Hickey, B. Kinghorn, B. Tier, J. Van-der-werf, and M. Cleveland, A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation, Genetics Selection Evolution, vol.44, issue.1, p.9, 2012.
DOI : 10.1186/1297-9686-42-2

G. Wiggans, T. Cooper, P. Vanraden, K. Olson, and M. Tooker, Use of the Illumina Bovine3K BeadChip in dairy genomic evaluation1, Journal of Dairy Science, vol.95, issue.3, pp.1552-1558, 2012.
DOI : 10.3168/jds.2011-4985

R. Dassonneville, R. Brondum, T. Druet, S. Fritz, F. Guillaume et al., Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations, Journal of Dairy Science, vol.94, issue.7, pp.3679-3686, 2011.
DOI : 10.3168/jds.2011-4299

URL : https://hal.archives-ouvertes.fr/hal-01000513

M. Calus and R. Veerkamp, Accuracy of multi-trait genomic selection using different methods, Genetics Selection Evolution, vol.43, issue.1, p.26, 2011.
DOI : 10.1111/j.1365-294X.2007.03499.x

Y. Jia and J. Jannink, Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy, Genetics, vol.192, issue.4, pp.1513-1522, 2012.
DOI : 10.1534/genetics.112.144246

A. Coster, J. Bastiaansen, M. Calus, J. Van-arendonk, and H. Bovenhuis, Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance, Genetics Selection Evolution, vol.42, issue.1
DOI : 10.1186/1297-9686-42-9

H. Daetwyler, R. Pong-wong, B. Villanueva, and J. Woolliams, The Impact of Genetic Architecture on Genome-Wide Evaluation Methods, Genetics, vol.185, issue.3, pp.1021-1031, 2010.
DOI : 10.1534/genetics.110.116855

T. Meuwissen and M. Goddard, Accurate Prediction of Genetic Values for Complex Traits by Whole-Genome Resequencing, Genetics, vol.185, issue.2, pp.623-631, 2010.
DOI : 10.1534/genetics.110.116590

D. Habier, J. Tetens, F. Seefried, P. Lichtner, and G. Thaller, The impact of genetic relationship information on genomic breeding values in German Holstein cattle, Genetics Selection Evolution, vol.42, issue.1, p.5, 2010.
DOI : 10.1186/1297-9686-42-5

T. Solberg, A. Sonesson, J. Woolliams, J. Odegard, and T. Meuwissen, Persistence of accuracy of genome-wide breeding values over generations when including a polygenic effect, Genetics Selection Evolution, vol.41, issue.1, p.53, 2009.
DOI : 10.1186/1297-9686-41-53

A. Wolc, J. Arango, P. Settar, J. Fulton, O. Sullivan et al., Persistence of accuracy of genomic estimated breeding values over generations in layer chickens, Genetics Selection Evolution, vol.43, issue.1
DOI : 10.1534/genetics.110.116590

H. Daetwyler, B. Villanueva, P. Bijma, and J. Woolliams, Inbreeding in genome-wide selection, Journal of Animal Breeding and Genetics, vol.80, issue.6, pp.369-376, 2007.
DOI : 10.1111/j.1439-0388.2007.00693.x

Y. Huang, J. Hickey, M. Cleveland, and C. Maltecca, Assessment of alternative genotyping strategies to maximize imputation accuracy at minimal cost, Genetics Selection Evolution, vol.44, issue.1
DOI : 10.1186/1297-9686-43-12

X. Yu, J. Woolliams, and T. Meuwissen, Which animals are to be densely genotyped in order to impute the missing genotypes of sparsely genotyped animals, Edinburgh: Proceedings of the 4th International Conference of Quantitative Genetics, pp.17-22165, 2012.

A. Kinsman, M. Sargolzaei, F. Schenkel, V. Voort, G. Jafarikia et al., Accuracy of genotype imputation in Canadian Yorkshire pigs using FIMPUTE software, Edinburgh: Proceedings of the 4th International Conference of Quantitative Genetics, pp.17-22192, 2012.

M. Goddard, Genomic selection: prediction of accuracy and maximisation of long term response, Genetica, vol.169, issue.2, pp.245-257, 2009.
DOI : 10.1007/s10709-008-9308-0

E. Van-grevenhof, J. Van-arendonk, and P. Bijma, Response to genomic selection: The Bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting, Genetics Selection Evolution, vol.44, issue.1, p.26, 2012.
DOI : 10.1017/S1751731111002205

M. Pszczola, T. Strabel, H. Mulder, and M. Calus, Reliability of direct genomic values for animals with different relationships within and to the reference population, Journal of Dairy Science, vol.95, issue.1, pp.389-400, 2012.
DOI : 10.3168/jds.2011-4338

M. Henryon, P. Berg, T. Ostersen, B. Nielsen, and A. Sørensen, Most of the benefits from genomic selection can be realized by genotyping a small proportion of available selection candidates, Journal of Animal Science, vol.90, issue.13, pp.4681-4689, 2012.
DOI : 10.2527/jas.2012-5158

I. Aguilar, I. Misztal, D. 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 score1, Journal of Dairy Science, vol.93, issue.2, pp.743-752, 2010.
DOI : 10.3168/jds.2009-2730

O. Christensen and M. Lund, Genomic prediction when some animals are not genotyped, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-2

URL : http://doi.org/10.1186/1297-9686-42-2

I. Aguilar, I. Misztal, D. 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 score1, Journal of Dairy Science, vol.93, issue.2, pp.743-752, 2010.
DOI : 10.3168/jds.2009-2730

J. Bastiaansen, A. Coster, M. Calus, J. Van-arendonk, and H. Bovenhuis, Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures, Genetics Selection Evolution, vol.44, issue.1, 2012.
DOI : 10.1098/rstb.2005.1668

D. Boichard, PEDIG: a FORTRAN package for pedigree analysis suited for large populations, Proceedings of the 7 th World Congress on Genetics Applied to Livestock Production, pp.19-23, 2002.

F. V. Brito, J. B. Neto, M. Sargolzaei, J. A. Cobuci, and F. S. Schenkel, Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle, BMC Genetics, vol.12, issue.1, 2011.
DOI : 10.1111/j.1439-0388.2007.00700.x

L. H. Buch, M. K. Sørensen, P. Berg, L. D. Pedersen, and A. C. Sørensen, Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain, Journal of Animal Breeding and Genetics, vol.93, issue.2, pp.138-151, 2011.
DOI : 10.1111/j.1439-0388.2011.00947.x

A. Caballero and P. D. Keightley, A pleiotropic nonadditive model of variation in quantitative traits, Genetics, vol.138, pp.883-900, 1994.

M. P. Calus, Y. De-haas, M. Pszczola, and R. F. Veerkamp, Predicted accuracy of and response to genomic selection for new traits in dairy cattle, animal, vol.3, issue.02, pp.183-191, 2013.
DOI : 10.1017/S175173110999070X

M. P. Calus, T. H. Meuwissen, A. P. De-roos, and R. F. Veerkamp, Accuracy of Genomic Selection Using Different Methods to Define Haplotypes, Genetics, vol.178, issue.1, pp.553-561, 2008.
DOI : 10.1534/genetics.107.080838

M. P. Calus and R. F. Veerkamp, Accuracy of multi-trait genomic selection using different methods, Genetics Selection Evolution, vol.43, issue.1, 2011.
DOI : 10.1111/j.1365-294X.2007.03499.x

O. Christensen and M. Lund, Genomic prediction when some animals are not genotyped, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-2

URL : http://doi.org/10.1186/1297-9686-42-2

O. F. Christensen, P. Madsen, B. Nielsen, T. Ostersen, and G. Su, Single-step methods for genomic evaluation in pigs, animal, vol.59, issue.10, pp.1565-1571, 2012.
DOI : 10.1038/nrg2865

S. Clark, J. Hickey, H. Daetwyler, and J. Van-der-werf, The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes, Genetics Selection Evolution, vol.44, issue.1, 2012.
DOI : 10.1371/journal.pone.0004668

M. A. Cleveland, J. M. Hickey, and S. Forni, A Common Dataset for Genomic Analysis of Livestock Populations, G3: Genes|Genomes|Genetics, pp.429-435, 2012.
DOI : 10.1534/g3.111.001453

A. Coster, J. W. Bastiaansen, M. P. Calus, J. A. Van-arendonk, and H. Bovenhuis, Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-9

H. D. Daetwyler, M. P. Calus, R. Pong-wong, G. De, J. M. Campos et al., Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting, and Benchmarking, Genetics, vol.193, issue.2, pp.347-365, 2013.
DOI : 10.1534/genetics.112.147983

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.1021-1031, 2010.
DOI : 10.1534/genetics.110.116855

H. D. Daetwyler, B. Villanueva, P. Bijma, and J. A. Woolliams, Inbreeding in genome-wide selection, Journal of Animal Breeding and Genetics, vol.80, issue.6, pp.369-376, 2007.
DOI : 10.1111/j.1439-0388.2007.00693.x

H. D. Daetwyler, B. Villanueva, and J. A. Woolliams, Accuracy of Predictiong the Genetic Risk of Disease Using a Genome-Wide Approach, Plos One, vol.3, issue.10, pp.1-8, 2008.

R. Dassonneville, R. Brondum, T. Druet, S. Fritz, F. Guillaume et al., Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations, Journal of Dairy Science, vol.94, issue.7, pp.3679-3686, 2011.
DOI : 10.3168/jds.2011-4299

URL : https://hal.archives-ouvertes.fr/hal-01000513

G. De-los-campos, J. M. Hickey, R. Pong-wong, H. D. Daetwyler, and M. P. Calus, Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding, Genetics, vol.193, issue.2, 2013.
DOI : 10.1534/genetics.112.143313

A. P. De-roos, B. J. Hayes, R. Spelman, and M. E. Goddard, Linkage Disequilibrium and Persistence of Phase in Holstein-Friesian, Jersey and Angus Cattle, Genetics, vol.179, issue.3, pp.1503-1512, 2008.
DOI : 10.1534/genetics.107.084301

A. P. De-roos, B. J. Hayes, and M. E. Goddard, Reliability of Genomic Predictions Across Multiple Populations, Genetics, vol.183, issue.4, pp.1545-1553, 2009.
DOI : 10.1534/genetics.109.104935

A. P. De-roos, C. Schrooten, R. F. Veerkamp, and J. A. Van-arendonk, Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls, Journal of Dairy Science, vol.94, issue.3, pp.1559-1571, 2010.
DOI : 10.3168/jds.2010-3354

J. C. Dekkers, Abstract, Animal Production, vol.50, issue.03, pp.351-360, 1992.
DOI : 10.1016/0301-6226(88)90058-9

J. C. Dekkers, Marker-assisted selection for commercial crossbred performance, Journal of Animal Science, vol.85, issue.9, pp.2104-2114, 2007.
DOI : 10.2527/jas.2006-683

J. C. Dekkers, Prediction of response to marker-assisted and genomic selection using selection index theory, Journal of Animal Breeding and Genetics, vol.49, issue.6, pp.331-341, 2007.
DOI : 10.1111/j.1439-0388.2007.00701.x

T. Druet and M. Georges, A Hidden Markov Model Combining Linkage and Linkage Disequilibrium Information for Haplotype Reconstruction and Quantitative Trait Locus Fine Mapping, Genetics, vol.184, issue.3, pp.789-798, 2010.
DOI : 10.1534/genetics.109.108431

F. X. Du, A. C. Clutter, and M. M. Lohuis, Characterizing Linkage Disequilibrium in Pig Populations, International Journal of Biological Sciences, vol.3, issue.3, pp.166-178, 2007.
DOI : 10.7150/ijbs.3.166

M. Erbe, B. J. Hayes, L. K. Matukumalli, S. Goswami, P. J. Bowman et al., Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels, Journal of Dairy Science, vol.95, issue.7, pp.4114-4129, 2012.
DOI : 10.3168/jds.2011-5019

D. S. Falconer, Introduction to quantitative genetics. 2 nd Ed, 1981.

S. Fritz, J. J. Colleau, T. Druet, M. Y. Boscher, M. N. Rossignol et al., Mise en place d'une selection assistée par marqueurs dans les trios principales races bovines laitières françaises, Rencontres Recherches Ruminants, vol.10, pp.53-56, 2003.

A. Gallais, Théorie de la sélection en amélioration des plantes, 1990.

D. Gianola, Priors in Whole-Genome Regression: The Bayesian Alphabet Returns, Genetics, vol.194, issue.3, pp.573-596, 2013.
DOI : 10.1534/genetics.113.151753

M. E. Goddard, Genomic selection: prediction of accuracy and maximisation of long term response, Genetica, vol.169, issue.2, pp.245-257, 2009.
DOI : 10.1007/s10709-008-9308-0

F. Guillaume, D. Boichard, V. Ducrocq, and S. Fritz, Utilisation de la sélection génomique chez les bovins laitiers, INRA Productions Animales, vol.24, issue.4, pp.363-368, 2011.

D. Habier, R. L. Fernando, and J. C. Dekkers, The impact of genetic relationship information on genome-assisted breeding values, Genetics, vol.177, pp.2389-2397, 2007.
DOI : 10.1534/genetics.107.081190

D. Habier, R. L. Fernando, and D. J. Garrick, Genomic BLUP Decoded: A Look into the Black Box of Genomic Prediction, Genetics, vol.194, issue.3, pp.597-607, 2013.
DOI : 10.1534/genetics.113.152207

D. Habier, R. L. Fernando, K. Kizilkay, and D. J. Garrick, Extension of the bayesian alphabet for genomic selection, BMC Bioinformatics, vol.12, issue.1, p.186, 2011.
DOI : 10.3168/jds.2008-1514

D. Habier, K. U. Gotz, and L. Dempfle, Estimation of genetic parameters on test stations using purebred and crossbred progeny of sires of the Bavarian Pi??train, Livestock Science, vol.107, issue.2-3, pp.142-151, 2007.
DOI : 10.1016/j.livsci.2006.09.012

D. Habier, J. Tetens, F. Seefried, P. Lichtner, and G. Thaller, The impact of genetic relationship information on genomic breeding values in German Holstein cattle, Genetics Selection Evolution, vol.42, issue.1, p.5, 2010.
DOI : 10.1186/1297-9686-42-5

C. S. Haley and P. M. Visscher, Strategies to Utilize Marker-Quantitative Trait Loci Associations, Journal of Dairy Science, vol.81, pp.85-97, 1998.
DOI : 10.3168/jds.S0022-0302(98)70157-2

B. L. Harris, D. L. Johnson, and R. J. Spelman, Genomic selection in New Zealand and the implications for national genetic evaluations, Proceedings if the Interbull meeting, 2008.

B. Hayes and M. E. Goddard, The distribution of the effects of genes affecting quantitative traits in livestock, Genetics Selection Evolution, vol.33, issue.3, pp.209-229, 2001.
DOI : 10.1186/1297-9686-33-3-209

URL : https://hal.archives-ouvertes.fr/hal-00894372

B. J. Hayes, QTL Mapping, MAS and Genomic Selection, Course Notes. 12-16 Septembre, 2011.

B. J. Hayes, P. J. Bowman, A. J. Chamberlain, and M. E. Goddard, Invited review: Genomic selection in dairy cattle: Progress and challenges, Journal of Dairy Science, vol.92, issue.2, pp.433-443, 2009.
DOI : 10.3168/jds.2008-1646

B. J. Hayes, H. D. Daetwyler, P. Bowman, G. Moser, B. Tier et al., Accuracy of genomic selection: comparing theory and results, Pages 352-355 in Proceedings of the Association for the Advencement of Animal Breeding and Genetics, 2009.

B. J. Hayes, P. M. Visscher, and M. E. Goddard, Increased accuracy of artificial selection by using the realized relationship matrix, Genetics Research, vol.91, issue.01, pp.47-60, 2009.
DOI : 10.1017/S0016672308009981

B. J. Hayes, P. M. Visscher, H. C. Mcpartlan, and M. E. Goddard, Novel Multilocus Measure of Linkage Disequilibrium to Estimate Past Effective Population Size, Genome Research, vol.13, issue.4, pp.635-643, 2003.
DOI : 10.1101/gr.387103

C. R. Henderson, Best Linear Unbiased Estimation and Prediction under a Selection Model, Biometrics, vol.31, issue.2, pp.423-447, 1975.
DOI : 10.2307/2529430

M. Henryon, P. Berg, T. Ostersen, B. Nielsen, and A. C. Sørensen, Most of the benefits from genomic selection can be realized by genotyping a small proportion of available selection candidates, Journal of Animal Science, vol.90, issue.13, pp.4681-4689, 2012.
DOI : 10.2527/jas.2012-5158

J. M. Hickey, B. P. Kinghorn, B. Tier, J. H. Van-der-werf, and M. A. Cleveland, A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation, Genetics Selection Evolution, vol.44, issue.1, p.9, 2012.
DOI : 10.1186/1297-9686-42-2

W. G. Hill and A. Robertson, Linkage disequilibrium in finite populations, Theoretical and Applied Genetics, vol.19, issue.6, pp.226-231, 1968.
DOI : 10.1007/BF01245622

W. G. Hill, Effects of population size on response to short and long term selection1, Journal of Animal Breeding and Genetics, vol.153, issue.1-5, pp.161-173, 1985.
DOI : 10.1111/j.1439-0388.1985.tb00684.x

A. E. Hoerl and R. W. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems, Technometrics, vol.24, issue.1, pp.55-67, 1970.
DOI : 10.2307/1909769

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, issue.D1, pp.871-879, 2013.
DOI : 10.1093/nar/gks1150

Z. L. Hu and J. M. Reecy, Animal QTLdb: beyond a repository, Mammalian Genome, vol.31, issue.10, pp.1-4, 2007.
DOI : 10.1007/s00335-006-0105-8

Y. Huang, J. M. Hickey, M. A. Cleveland, and C. Maltecca, Assessment of alternative genotyping strategies to maximize imputation accuracy at minimal cost, Genetics Selection Evolution, vol.44, issue.1, p.25, 2012.
DOI : 10.1186/1297-9686-43-12

N. Ibanez-escriche, R. L. Fernando, A. Toosi, and J. C. Dekkers, Genomic selection of purebreds for crossbred performance, Genetics Selection Evolution, vol.41, issue.1, pp.12-21, 2009.
DOI : 10.1186/1297-9686-41-12

J. L. Jannink, Dynamics of long-term genomic selection, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-35

Y. Jia and J. L. Jannink, Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy, Genetics, vol.192, issue.4, pp.1513-1522, 2012.
DOI : 10.1534/genetics.112.144246

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3512156

B. P. Kinghorn, J. M. Hickey, and J. H. Van-der-werf, Reciprocal recurrent genomic selection for total genetic merit in crossbred individuals, Proceedings of the 9th WCGALP, 2010.

A. Kinsman, M. Sargolzaei, F. Schenkel, G. Vender, M. Voort et al., Accuracy of genotype imputation in Canadian Yorkshire pigs using FIMPUTE software, Proceedings of the 4 th International Conference of Quantitative Genetics, pp.17-22, 2012.

S. König, H. Simianer, and A. Willam, Economic evaluation of genomic breeding programs, Journal of Dairy Science, vol.92, issue.1, pp.382-391, 2009.
DOI : 10.3168/jds.2008-1310

R. Lande and R. Thompson, Efficiency of marker-assisted selection in the improvement of quantitative traits, Genetics, vol.124, issue.3, pp.743-756, 1990.

A. Legarra, I. Aguilar, and I. Misztal, A relationship matrix including full pedigree and genomic information, Journal of Dairy Science, vol.92, issue.9, pp.4656-4663, 2009.
DOI : 10.3168/jds.2009-2061

A. Legarra and V. Ducrocq, Computational strategies for national integration of phenotypic, genomic, and pedigree data in a single-step best linear unbiased prediction, Journal of Dairy Science, vol.95, issue.8, pp.4629-4645, 2012.
DOI : 10.3168/jds.2011-4982

URL : https://hal.archives-ouvertes.fr/hal-01001202

M. Lillehammer, T. H. Meuwissen, and A. K. Sonesson, A comparison of dairy cattle breeding designs that use genomic selection, Journal of Dairy Science, vol.94, issue.1, pp.493-500, 2011.
DOI : 10.3168/jds.2010-3518

M. Lillehammer, T. H. Meuwissen, and A. K. Sonesson, Genomic selection for maternal traits in pigs, Journal of Animal Science, vol.89, issue.12, pp.3908-3916, 2011.
DOI : 10.2527/jas.2011-4044

M. S. Lund, A. P. De-roos, A. G. De-vries, T. Druet, V. Ducrocq et al., Improving genomic prediction by EuroGenomics collaboration, Paper 880 in Proceedings of the 9 th WCGALP, pp.1-6, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193765

E. Lutaaya, I. Misztal, J. W. Mabry, T. Short, H. H. Timm et al., Genetic parameter estimates from joint evaluation of purebreds and crossbreds in swine using the crossbred model., Journal of Animal Science, vol.79, issue.12, pp.3002-3007, 2001.
DOI : 10.2527/2001.79123002x

H. Luther, P. Vögeli, and A. Hofer, Increasing genetic E. coli F18 resistance in Swiss pigs. Pages Comm. 18-03, Proceedings of the 60 th EAAP, pp.24-27, 2009.

L. Maignel, T. Tribout, D. Boichard, J. P. Bidanel, and R. Guéblez, Analyse de la variabilité génétique des races porcines Large White, Landrace Français et Piétrain, sur la base de l'information généalogique, pp.109-116, 1998.

J. M. Merks, Genetic improvement at the commercial level compared at the genetic progress at the nucleus level, Proceedings of the National Swine Improvement Federation, 2001.

J. W. Merks, Genotype ?? environment interactions in pig breeding programmes. VI. Genetic relations between performances in central test, on-farm test and commercial fattening, Livestock Production Science, vol.22, issue.3-4, pp.325-339, 1989.
DOI : 10.1016/0301-6226(89)90064-X

T. H. Meuwissen, Maximizing the response of selection with a predefined rate of inbreeding., Journal of Animal Science, vol.75, issue.4, pp.934-940, 1997.
DOI : 10.2527/1997.754934x

T. H. Meuwissen, Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping, Genetics Selection Evolution, vol.41, issue.1, 2009.
DOI : 10.1186/1297-9686-41-35

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.1819-1829, 2001.

T. H. Meuwissen and M. E. Goddard, Accurate Prediction of Genetic Values for Complex Traits by Whole-Genome Resequencing, Genetics, vol.185, issue.2, pp.623-631, 2010.
DOI : 10.1534/genetics.110.116590

K. Meyer, B. Tier, and H. U. Graser, Technical note: Updating the inverse of the genomic relationship matrix, Journal of Animal Science, vol.91, issue.6, pp.2583-2586, 2013.
DOI : 10.2527/jas.2012-6056

F. Minvielle, Principes d'amélioration génétique des animaux domestiques. Les Presses de l, 1990.

G. Moser, B. Tier, R. E. Crump, M. S. Khatkar, and H. W. Raadsma, A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers, Genetics Selection Evolution, vol.41, issue.1, 2009.
DOI : 10.1186/1297-9686-41-56

W. Muir, Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters, Journal of Animal Breeding and Genetics, vol.163, issue.6, pp.342-355, 2007.
DOI : 10.1111/j.1439-0388.2007.00700.x

H. Nielsen, A. Sonesson, and T. Meuwissen, Optimum contribution selection using traditional best linear unbiased prediction and genomic breeding values in aquaculture breeding schemes, Journal of Animal Science, vol.89, issue.3, pp.630-638, 2011.
DOI : 10.2527/jas.2009-2731

J. L. Noguera, M. C. Rodríguez, L. Varona, A. Tomas, G. Muñoz et al., Epistasis is a fundamental component of the genetic architecture of prolificacy in pigs, Proceedings of the 8 th WCGALP, pp.13-18, 2006.

T. Ostersen, O. F. Christensen, M. Henryon, B. Nielsen, G. Su et al., Deregressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs, Genetics Selection Evolution, vol.43, issue.1, 2011.
DOI : 10.3168/jds.2008-1514

E. C. Pimentel and S. König, Genomic selection for the improvement of meat quality in beef, Journal of Animal Science, vol.90, issue.10, pp.3418-3426, 2012.
DOI : 10.2527/jas.2011-5005

J. E. Pryce, M. E. Goddard, H. W. Raadsma, and B. J. Hayes, Deterministic models of breeding scheme designs that incorporate genomic selection, Journal of Dairy Science, vol.93, issue.11, pp.5455-5466, 2010.
DOI : 10.3168/jds.2010-3256

M. Pszczola, T. Strabel, H. Mulder, and M. Calus, Reliability of direct genomic values for animals with different relationships within and to the reference population, Journal of Dairy Science, vol.95, issue.1, pp.389-400, 2012.
DOI : 10.3168/jds.2011-4338

R. L. Quaas and E. J. Pollak, Mixed Model Methodology for Farm and Ranch Beef Cattle Testing Programs, Journal of Animal Science, vol.51, issue.6, pp.1277-1287, 1980.
DOI : 10.2527/jas1981.5161277x

R. Rincent, D. Laloë, S. Nicolas, T. Altmann, D. Brunel et al., Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds (Zea mays L.), Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds, pp.715-728, 2012.
DOI : 10.1534/genetics.112.141473

URL : https://hal.archives-ouvertes.fr/hal-01019845

C. Robert-granié, A. Legarra, and V. Ducrocq, Principes de base de la sélection génomique, INRA Productions Animales, vol.24, issue.4, pp.331-340, 2011.

A. P. Roos, B. J. Hayes, R. J. Spelman, and M. E. Goddard, Linkage Disequilibrium and Persistence of Phase in Holstein-Friesian, Jersey and Angus Cattle, Genetics, vol.179, issue.3, pp.1503-1512, 2008.
DOI : 10.1534/genetics.107.084301

L. R. Schaeffer, Strategy for applying genome-wide selection in dairy cattle, Journal of Animal Breeding and Genetics, vol.83, issue.4, pp.218-223, 2006.
DOI : 10.1111/j.1439-0388.2006.00595.x

S. Schwob, J. Riquet, T. Bellec, L. Kernaleguen, T. Tribout et al., Mise en place d'un programme de sélection assistée par marqueurs dans la population sinoeuropéenne Duochan, Journees de la Recherche Porcine, vol.41, pp.29-30, 2009.

C. R. Jullien, C. Leymarie, M. Moreno, I. Orlianges, G. Palhière et al., The french ovine scrapie plan: results and prospects, Proceedings of the 9 th WCGALP, pp.1-6, 2010.

T. R. Solberg, A. K. Sonesson, J. A. Woolliams, J. Odegard, and T. H. Meuwissen, Persistence of accuracy of genome-wide breeding values over generations when including a polygenic effect, Genetics Selection Evolution, vol.41, issue.1, 2009.
DOI : 10.1186/1297-9686-41-53

G. Su, R. F. Brøndum, P. Ma, B. Guldbrandtsen, G. P. Aamand et al., Comparison of genomic predictions using medium-density (???54,000) and high-density (???777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle populations, Journal of Dairy Science, vol.95, issue.8, pp.4657-4665, 2013.
DOI : 10.3168/jds.2012-5379

J. A. Sved, Linkage disequilibrium and homozygosity of chromosome segments in finite populations, Theoretical Population Biology, vol.2, issue.2, pp.125-141, 1971.
DOI : 10.1016/0040-5809(71)90011-6

R. Tibshirani, Regression shrinkage and selection via the Lasso, Journal of the Royal Statistical Society, Series B, vol.58, pp.267-288, 1996.

T. Tribout, Perspectives d'application de la sélection génomique dans les schémas d'amélioration génétique porcins, INRA Productions Animales, vol.24, issue.4, pp.369-376, 2011.

T. Tribout, J. C. Caritez, J. Gogué, J. Gruand, Y. Billon et al., Estimation, par utilisation de semence congelée, du progrès génétique réalisé en France entre, dans la race porcine Large White : résultats pour quelques caractères de reproduction femelle. Journées de la Recherche Porcine, pp.285-292, 1977.

T. Tribout, J. C. Caritez, J. Gogué, J. Gruand, M. Bouffaud et al., Estimation, par utilisation de semence congelée, du progrès génétique réalisé en France entre, dans la race porcine Large White : résultats pour quelques caractères de production et de qualité des tissus gras et maigres. Journées de la Recherche Porcine, pp.275-282, 1977.

T. Tribout, C. Larzul, and F. Phocas, Efficiency of genomic selection in a purebred pig male line, Journal of Animal Science, vol.90, issue.12, pp.4164-4176, 2012.
DOI : 10.2527/jas.2012-5107

URL : https://hal.archives-ouvertes.fr/hal-01001279

T. Tribout, C. Larzul, and F. Phocas, Economic interest of implementing genomic evaluations in a pig male line breeding scheme, Genetics Selection Evolution, 2013.

S. Tsuruta, I. Misztal, I. Aguilar, and T. Lawlor, Multiple-trait genomic evaluation of linear type traits using genomic and phenotypic data in US Holsteins, Journal of Dairy Science, vol.94, issue.8, pp.4198-4204, 2011.
DOI : 10.3168/jds.2011-4256

P. Uimari and M. Tapio, Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds, Journal of Animal Science, vol.89, issue.3, pp.609-614, 2011.
DOI : 10.2527/jas.2010-3249

H. A. Van-der-steen, G. F. Prall, and G. S. Plastow, Application of genomics to the pork industry, Journal of Animal Science, vol.83, pp.1-8, 2005.

E. M. Van-grevenhof, J. A. Van-arendonk, and P. Bijma, Response to genomic selection: The Bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting, Genetics Selection Evolution, vol.44, issue.1, p.26, 2012.
DOI : 10.1017/S1751731111002205

P. M. Vanraden, Efficient Methods to Compute Genomic Predictions, Journal of Dairy Science, vol.91, issue.11, pp.4414-4423, 2008.
DOI : 10.3168/jds.2007-0980

P. M. Vanraden, D. J. Null, M. Sargolzaei, G. R. Wiggans, M. E. Tooker et al., Genomic imputation and evaluation using high-density Holstein genotypes, Journal of Dairy Science, vol.96, issue.1, pp.668-678, 2013.
DOI : 10.3168/jds.2012-5702

P. M. Vanraden, C. P. Van-tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel et al., Invited Review: Reliability of genomic predictions for North American Holstein bulls, Journal of Dairy Science, vol.92, issue.1, pp.16-24, 2009.
DOI : 10.3168/jds.2008-1514

K. Verbyla, P. Bowman, B. Hayes, H. Raadsma, M. Khatkar et al., Comparison of Bayesian methods for genomic selection using real dairy data, Proceedings of the 60th EAAP, pp.24-27, 2009.

M. Wei and H. A. Van-der-steen, Comparison of reciprocal recurrent selection with pure-line selection systems in animal breeding (a review), Animal Breeding Abstract, vol.59, pp.281-298, 1991.

M. Wensch-dorendorf, T. Yin, H. H. Swalve, and S. König, Optimal strategies for the use of genomic selection in dairy cattle breeding programs, Journal of Dairy Science, vol.94, issue.8, pp.4140-4151, 2011.
DOI : 10.3168/jds.2010-4101

G. Wiggans, T. Cooper, P. Vanraden, K. Olson, and M. Tooker, Use of the Illumina Bovine3K BeadChip in dairy genomic evaluation1, Journal of Dairy Science, vol.95, issue.3, pp.1552-1558, 2012.
DOI : 10.3168/jds.2011-4985

A. Wolc, J. Arango, P. Settar, J. Fulton, N. O-'sullivan et al., Persistence of accuracy of genomic estimated breeding values over generations in layer chickens, Genetics Selection Evolution, vol.43, issue.1, p.23, 2011.
DOI : 10.1534/genetics.110.116590

S. Wright, Evolution in mendelian populations, Genetics, vol.16, issue.2, pp.97-159, 1931.

S. Xu, Theoretical Basis of the Beavis Effect, Genetics, vol.165, issue.4, pp.2259-2268, 2003.

X. Yu, J. A. Woolliams, and T. H. Meuwissen, Which animals are to be densely genotyped in order to impute the missing genotypes of sparsely genotyped animals, Proceedings of the 4 th International Conference of Quantitative Genetics, pp.17-22, 2012.

J. Zeng, A. Toosi, R. L. Fernando, J. C. Dekkers, and D. J. Garrick, Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action, Genetics Selection Evolution, vol.45, issue.1, 2013.
DOI : 10.3168/jds.2011-4500

H. Zhou and T. Hastie, Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005.
DOI : 10.1073/pnas.201162998