D. Boichard, F. Guillaume, A. Baur, P. Croiseau, M. N. Rossignol et al., Genomic selection in French dairy cattle, Animal Production Science, vol.52, issue.3, 2010.
DOI : 10.1071/AN11119

URL : https://hal.archives-ouvertes.fr/hal-01000520

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, The American Journal of Human Genetics, vol.81, issue.5, pp.1084-1097, 2007.
DOI : 10.1086/521987

P. Croiseau, C. Colombani, A. Legarra, F. Guillaume, S. Fritz et al., Improving genomic evaluation strategies in dairy cattle through SNP pre-selection, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193548

H. D. Daetwyler, G. R. Wiggans, B. J. Hayes, J. A. Wooliams, and M. E. Goddard, Imputation of Missing Genotypes From Sparse to High Density Using Long-Range Phasing, Genetics, vol.189, issue.1, 2010.
DOI : 10.1534/genetics.111.128082

T. Druet, S. Fritz, M. Boussaha, S. Ben-jemaa, F. Guillaume et al., Fine Mapping of Quantitative Trait Loci Affecting Female Fertility in Dairy Cattle on BTA03 Using a Dense Single-Nucleotide Polymorphism Map, Genetics, vol.178, issue.4, pp.2227-2235, 2008.
DOI : 10.1534/genetics.107.085035

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

T. Druet, C. Schrooten, and A. P. De-roos, Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle, Journal of Dairy Science, vol.93, issue.11, pp.5443-5454, 2010.
DOI : 10.3168/jds.2010-3255

R. Fernando and M. Grossman, Marker assisted selection using best linear unbiased prediction, Genetics Selection Evolution, vol.21, issue.4, pp.467-477, 1989.
DOI : 10.1186/1297-9686-21-4-467

URL : https://hal.archives-ouvertes.fr/hal-00893817

I. Illumina, Illumina GenCall Data Analysis Software -GenCall software algorithms for clustering, calling, and scoring genotypes, Illumina. Pub, pp.370-2004, 2005.

M. S. Lund, A. P. De-roos, A. G. De-vries, T. Druet, V. Ducrocq et al., Improving Genomic Prediction by EuroGenomics Collaboration, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193765

L. K. Matukumalli, C. T. Lawley, R. D. Schnabel, J. F. Taylor, M. F. Allan et al., Development and Characterization of a High Density SNP Genotyping Assay for Cattle, PLoS ONE, vol.37, issue.4, p.5350, 2009.
DOI : 10.1371/journal.pone.0005350.s010

T. H. Meuwissen and M. E. Goddard, Prediction of identity by descent probabilities from marker-haplotypes, Genetics Selection Evolution, vol.33, issue.6, pp.605-634, 2001.
DOI : 10.1186/1297-9686-33-6-605

URL : https://hal.archives-ouvertes.fr/hal-00894392

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.

G. Moser, M. S. Khatkar, B. J. Hayes, and H. W. Raadsma, Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-37

P. Scheet and M. Stephens, A Fast and Flexible Statistical Model for Large-Scale Population Genotype Data: Applications to Inferring Missing Genotypes and Haplotypic Phase, The American Journal of Human Genetics, vol.78, issue.4, pp.629-644, 2006.
DOI : 10.1086/502802

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

D. P. Berry and J. F. Kearney, Imputation of genotypes from low- to high-density genotyping platforms and implications for genomic selection, animal, vol.39, issue.08, pp.1162-1169, 2011.
DOI : 10.1017/S1751731111000309

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, vol.6, issue.4, 2012.
DOI : 10.1371/journal.pone.0034130.s001

URL : https://hal.archives-ouvertes.fr/hal-01019774

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, The American Journal of Human Genetics, vol.81, issue.5, pp.1084-1097, 2007.
DOI : 10.1086/521987

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

T. Druet, C. Schrooten, and A. P. De-roos, Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle, Journal of Dairy Science, vol.93, issue.11, pp.5443-5454, 2010.
DOI : 10.3168/jds.2010-3255

R. Dassonneville, R. F. Brøndum, 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

C. G. Elsik, R. L. Tellam, K. C. Worley, R. A. Gibbs, D. M. Muzny et al., The genome sequence of taurine cattle: a window to ruminant biology and evolution, Science, issue.5926, pp.324522-528, 2009.

J. M. Hickey, B. P. Kinghorn, B. Tier, J. F. Wilson, N. Dunstan et al., A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes, Genetics Selection Evolution, vol.43, issue.1, p.12, 2011.
DOI : 10.1016/j.ajhg.2008.08.007

J. M. Hickey, J. Crossa, R. Babu, G. De, and . Campos, Factors Affecting the Accuracy of Genotype Imputation in Populations from Several Maize Breeding Programs, Crop Science, vol.52, issue.2, 2011.
DOI : 10.2135/cropsci2011.07.0358

J. Johnston, G. Kistemaker, and S. P. , Comparison of different imputation methods. Preliminary proceedings of 2011 Interbull meeting, 2007.

M. S. Lund, A. P. De-roos, A. G. De-vries, T. Druet, V. Ducrocq et al., A common reference population from four European Holstein populations increases reliability of genomic predictions, Genetics Selection Evolution, vol.43, issue.1, p.43, 2011.
DOI : 10.1186/1297-9686-43-43

URL : https://hal.archives-ouvertes.fr/hal-01191309

L. K. Matukumalli, C. T. Lawley, R. D. Schnabel, J. F. Taylor, M. F. Allan et al., Development and Characterization of a High Density SNP Genotyping Assay for Cattle, PLoS ONE, vol.37, issue.4, 2009.
DOI : 10.1371/journal.pone.0005350.s010

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.

M. Sargolzaei, J. P. Chesnais, F. S. Schenkel, and . Fimpute, An efficient imputation algorithm for dairy cattle populations, J. Anim. Sci.J. Dairy Sci, vol.89, issue.94, p.421, 2011.

P. M. Vanraden, J. R. O-'connell, G. R. Wiggans, and K. A. , Genomic evaluations with many more genotypes, Genetics Selection Evolution, vol.43, issue.1, p.10, 2011.
DOI : 10.1186/1471-2156-10-19

K. A. Weigel, G. De-los-campos, A. I. Vazquez, G. J. Rosa, D. Gianola et al., Accuracy of direct genomic values derived from imputed single nucleotide polymorphism genotypes in Jersey cattle, Journal of Dairy Science, vol.93, issue.11, pp.935423-5435, 2010.
DOI : 10.3168/jds.2010-3149

Z. Zhang and T. Druet, Marker imputation with low-density marker panels in Dutch Holstein cattle, Journal of Dairy Science, vol.93, issue.11, pp.5487-5494, 2010.
DOI : 10.3168/jds.2010-3501

A. V. Zimin, A. L. Delcher, L. Florea, D. R. Kelley, M. C. Schatz et al., A whole-genome assembly of the domestic cow, Bos taurus Prediction of total genetic value using genome-wide dense marker maps, R42. REFERENCES 1. Meuwissen THE, pp.1819-1829, 2001.

E. Heffner, J. Jannink, and M. Sorrells, Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program, The Plant Genome Journal, vol.4, issue.1, pp.65-75, 2011.
DOI : 10.3835/plantgenome.2010.12.0029

G. Wiggans, P. Vanraden, and T. Cooper, The genomic evaluation system in the United States: Past, present, future, Journal of Dairy Science, vol.94, issue.6, pp.3202-3211, 2011.
DOI : 10.3168/jds.2010-3866

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

J. Pryce, M. Goddard, H. Raadsma, and B. 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

J. Pryce and H. Daetwyler, press) Designing dairy cattle breeding schemes under genomic selection?a review of international research, Anim Prod Sci

A. Van-eenennaam, J. Van-der-werf, and M. Goddard, The value of using DNA markers for beef bull selection in the seedstock sector, Journal of Animal Science, vol.89, issue.2, pp.307-320, 2011.
DOI : 10.2527/jas.2010-3223

P. Scheet and M. Stephens, A Fast and Flexible Statistical Model for Large-Scale Population Genotype Data: Applications to Inferring Missing Genotypes and Haplotypic Phase, The American Journal of Human Genetics, vol.78, issue.4, 2006.
DOI : 10.1086/502802

S. Browning and B. Browning, Haplotype phasing: existing methods and new developments, Nature Reviews Genetics, vol.447, issue.10, pp.703-714, 2011.
DOI : 10.1038/nrg3054

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3217888

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

L. Genestout, J. J. Colleau, L. Journaux, V. Ducrocq, and S. Fritz, Genomic Selection in French Dairy Cattle, Animal Production Science, vol.52, pp.115-120, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01000520

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, vol.6, issue.4, p.34130, 2012.
DOI : 10.1371/journal.pone.0034130.s001

URL : https://hal.archives-ouvertes.fr/hal-01019774

P. Croiseau, A. Legarra, F. Guillaume, S. Fritz, A. Baur et al., Fine tuning genomic evaluations in dairy cattle through SNP pre-selection with the Elastic-Net algorithm, Genetics Research, vol.33, issue.06, pp.409-417, 2011.
DOI : 10.1111/j.1439-0388.2007.00702.x

URL : https://hal.archives-ouvertes.fr/hal-01000269

D. Lechner, C. Charon, D. Boichard, I. G. Gut, A. Eggen et al., Fine Mapping of Quantitative Trait Loci Affecting Female Fertility in Dairy Cattle on BTA03 Using a Dense Single-Nucleotide Polymorphism Map, Genetics, vol.178, pp.2227-2235, 2008.

M. E. Goddard and B. J. Hayes, Mapping genes for complex traits in domestic animals and their use in breeding programmes, Nature Reviews Genetics, vol.39, issue.6, pp.381-391, 2009.
DOI : 10.1038/nrg2575

M. T. Kuhn, A. E. Boettcher, and . Freeman, Potential Biases in Predicted Transmitting Abilities of Females from Preferential Treatment, Journal of Dairy Science, vol.77, issue.8, pp.2428-2437, 1994.
DOI : 10.3168/jds.S0022-0302(94)77185-X

B. Guldbrandtsen, Z. Liu, R. Reents, C. Schrooten, F. Seefried et al., A common reference population from four European Holstein populations increases reliability of genomic predictions, Genet Sel Evol, pp.43-43, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01191309

I. Misztal, A. Legarra, and I. Aguilar, Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information, Journal of Dairy Science, vol.92, issue.9, pp.4648-4655, 2009.
DOI : 10.3168/jds.2009-2064

URL : http://prodinra.inra.fr/ft/9E17979C-691A-4D55-8D23-FBE1BDF94A4F

P. M. Vanraden and G. R. Wiggans, Derivation, Calculation, and Use of National Animal Model Information, Journal of Dairy Science, vol.74, issue.8, pp.2737-2746, 1991.
DOI : 10.3168/jds.S0022-0302(91)78453-1

L. D. Van-vleck, Contemporary Groups for Genetic Evaluations, Journal of Dairy Science, vol.70, issue.11, pp.2456-2464, 1987.
DOI : 10.3168/jds.S0022-0302(87)80309-0

D. Boichard, F. Guillaume, A. Baur, P. Croiseau, M. N. Rossignol et al., Genomic selection in French dairy cattle, Animal Production Science, vol.52, issue.3, pp.115-120, 2012.
DOI : 10.1071/AN11119

URL : https://hal.archives-ouvertes.fr/hal-01000520

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, The American Journal of Human Genetics, vol.81, issue.5, pp.1084-1097, 2007.
DOI : 10.1086/521987

L. H. Buch, M. Kargo, P. Berg, J. Lassen, and A. C. Sørensen, The value of cows in reference populations for genomic selection of new functional traits, animal, vol.157, issue.06, pp.880-886, 2012.
DOI : 10.3168/jds.2008-1646

J. Chesnais, Utiliser la génomique pour maximiser les profits des éleveurs laitiers. Proceedings of " symposium sur les bovins laitiers, Drumondville, 2011.

J. J. Colleau, Impact of the use of bovine somatotropin (BST) on dairy cattle selection, Genetics Selection Evolution, vol.21, issue.4, pp.479-491, 1989.
DOI : 10.1186/1297-9686-21-4-479

URL : https://hal.archives-ouvertes.fr/hal-00893818

D. Eggen and . Boichard, Simulation des potentialités de la sélection génomique chez les bovins laitiers, Proceeding. Renc. Rech. Ruminants, 2009.

H. D. Daetwyler, G. R. Wiggans, B. J. Hayes, J. A. Woolliams, and M. E. Goddard, Imputation of Missing Genotypes From Sparse to High Density Using Long-Range Phasing, Genetics, vol.189, issue.1, pp.317-327, 2011.
DOI : 10.1534/genetics.111.128082

C. Lechner, D. Charon, I. G. Boichard, A. Gut, M. Eggen et al., Fine mapping of quantitative trait loci affecting female fertility in dairy cattle on BTA03 using a dense single-nucleotide polymorphism map, Genetics, vol.178, issue.4, pp.2227-2235, 2008.

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

T. Druet, C. Schrooten, and A. P. De-roos, Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle, Journal of Dairy Science, vol.93, issue.11, pp.5443-5454, 2010.
DOI : 10.3168/jds.2010-3255

V. Ducrocq and E. Santus, Moving away from progeny testing schemes: consequences on conventional (inter)national evaluations. in Interbull technical workshop, 2011.

A. Sargent, M. R. Sorensen, X. Steele, J. E. Zhao, I. Womack et al., Mapping quantitative trait loci controlling milk production in dairy cattle by exploiting progeny testing, Genetics, vol.139, pp.907-920, 1995.

F. Dunner, J. Ménissier, R. Massabanda, R. Fries, M. Hanset et al., A deletion in the myostatin gene causes double-muscling in cattle, Nat. Genet, vol.17, p.7174, 1997.

J. M. Hickey, J. Crossa, R. Babu, G. De, and . Campos, Factors Affecting the Accuracy of Genotype Imputation in Populations from Several Maize Breeding Programs, Crop Science, vol.52, issue.2, 2011.
DOI : 10.2135/cropsci2011.07.0358

J. Johnston, G. Kistemaker, and P. G. Sullivan, Comparison of different imputation methods. Preliminary proceedings of 2011 Interbull meeting, 2007.

D. F. Thorsteinsdottir, H. Gudbjartsson, K. Stefansson, and . Stefansson, Detection of sharing by descent, long-range phasing and haplotype imputation, Nat Genet, vol.40, pp.1068-1075, 2008.

M. T. Kuhn, A. E. Boettcher, and . Freeman, Potential Biases in Predicted Transmitting Abilities of Females from Preferential Treatment, Journal of Dairy Science, vol.77, issue.8, pp.2428-2437, 1994.
DOI : 10.3168/jds.S0022-0302(94)77185-X

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 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

E. Mäntysaari, Z. Liu, and P. Vanraden, Interbull validation test for genomic evaluations, Interbull bulletin, vol.41, pp.17-22, 2010.

J. Marchini, S. Howie, G. Myers, P. Mcvean, and . Donnelly, A new multipoint method for genome-wide association studies by imputation of genotypes, Nature Genetics, vol.164, issue.7, pp.906-913, 2007.
DOI : 10.1038/nrg1916

J. Marchini and B. Howie, Genotype imputation for genome-wide association studies, Nature Reviews Genetics, vol.42, issue.7, pp.499-511
DOI : 10.1038/nrg2796

T. H. Meuwissen and M. E. Goddard, Prediction of identity by descent probabilities from marker-haplotypes, Genetics Selection Evolution, vol.33, issue.6, pp.605-634, 2001.
DOI : 10.1186/1297-9686-33-6-605

URL : https://hal.archives-ouvertes.fr/hal-00894392

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.

I. Misztal, A. Legarra, and I. Aguilar, Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information, Journal of Dairy Science, vol.92, issue.9, pp.4648-4655, 2009.
DOI : 10.3168/jds.2009-2064

G. Moser, M. S. Khatkar, B. J. Hayes, and H. W. Raadsma, Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers, Genetics Selection Evolution, vol.42, issue.1, 2010.
DOI : 10.1186/1297-9686-42-37

C. Patry and V. Ducrocq, Evidence of biases in genetic evaluations due to genomic preselection in dairy cattle, Journal of Dairy Science, vol.94, issue.2, pp.1011-1020, 2011.
DOI : 10.3168/jds.2010-3804

URL : https://hal.archives-ouvertes.fr/hal-01000597

R. L. Powell and H. D. Norman, Major Advances in Genetic Evaluation Techniques, Journal of Dairy Science, vol.89, issue.4, pp.1337-1348, 2006.
DOI : 10.3168/jds.S0022-0302(06)72201-9

J. E. Pryce and B. J. Hayes, A review of how dairy farmers can use and profit from genomic technologies, Animal Production Science, vol.52, issue.3, pp.180-184
DOI : 10.1071/AN11172

J. E. Pryce, B. J. Hayes, and M. E. Goddard, Genotyping dairy females can improve the reliability of genomic selection for young bulls and heifers and provide farmers with new management tools, 2012.

J. M. Rendel and A. Robertson, Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle, Journal of Genetics, vol.2, issue.1, pp.1-10, 1950.
DOI : 10.1007/BF02986789

C. Robert-granié, B. Bona??-ti, D. Boichard, and A. Barbat, Accounting for variance heterogeneity in French dairy cattle genetic evaluation, Livestock Production Science, vol.60, issue.2-3, pp.343-357, 1999.
DOI : 10.1016/S0301-6226(99)00105-0

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

P. Scheet and M. Stephens, A Fast and Flexible Statistical Model for Large-Scale Population Genotype Data: Applications to Inferring Missing Genotypes and Haplotypic Phase, The American Journal of Human Genetics, vol.78, issue.4, 2006.
DOI : 10.1086/502802

A. E. Shrimpton and A. Robertson, The Isolation of Polygenic Factors Controlling Bristle Score in Drosophila melanogaster. II. Distribution of Third Chromosome Bristle Effects Within Chromosome Sections, Genetics, vol.118, pp.445-459, 1988.

M. Stephens, N. J. Smith, and P. Donnelly, A New Statistical Method for Haplotype Reconstruction from Population Data, The American Journal of Human Genetics, vol.68, issue.4, pp.978-89, 2001.
DOI : 10.1086/319501

J. H. Van-der-werf, T. H. Meuwissen, and G. Jong, Effects of Correction for Heterogeneity of Variance on Bias and Accuracy of Breeding Value Estimation for Dutch Dairy Cattle, Journal of Dairy Science, vol.77, issue.10, pp.3174-3184, 1994.
DOI : 10.3168/jds.S0022-0302(94)77260-X

P. M. Vanraden and G. R. Wiggans, Derivation, Calculation, and Use of National Animal Model Information, Journal of Dairy Science, vol.74, issue.8, pp.2737-2746, 1991.
DOI : 10.3168/jds.S0022-0302(91)78453-1

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, G. R. Wiggans, C. P. Van-tassell, T. S. Sonstegard, and F. Schenkel, Benefits from cooperation in genomics, 2009.

P. M. Vanraden, J. R. O-'connell, G. R. Wiggans, and K. A. , Genomic evaluations with many more genotypes, Genetics Selection Evolution, vol.43, issue.1, p.10, 2011.
DOI : 10.1186/1471-2156-10-19

L. D. Van-vleck, Contemporary Groups for Genetic Evaluations, Journal of Dairy Science, vol.70, issue.11, pp.2456-2464, 1987.
DOI : 10.3168/jds.S0022-0302(87)80309-0

R. Veerkamp, Selection for feed intake in dairy cattle using genomic selection, Proceeding ICAR congress, 2012.

W. E. Vinson, Potential Bias in Genetic Evaluations from Differences in Variation Within Herds, Journal of Dairy Science, vol.70, issue.11, pp.2450-2455, 1987.
DOI : 10.3168/jds.S0022-0302(87)80308-9

K. A. Weigel, C. P. Van-tassell, J. R. O-'connell, P. M. Vanraden, and G. R. Wiggans, Prediction of unobserved single nucleotide polymorphism genotypes of Jersey cattle using reference panels and population-based imputation algorithms, Journal of Dairy Science, vol.93, issue.5, pp.2229-2238, 2009.
DOI : 10.3168/jds.2009-2849

K. A. Weigel, G. De-los-campos, A. I. Vazquez, G. J. Rosa, D. Gianola et al., Accuracy of direct genomic values derived from imputed single nucleotide polymorphism genotypes in Jersey cattle, Journal of Dairy Science, vol.93, issue.11, pp.935423-5435, 2010.
DOI : 10.3168/jds.2010-3149

K. A. Weigel, P. C. Hoffman, W. J. Herring, and . 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, issue.4, pp.2215-2225, 2012.
DOI : 10.3168/jds.2011-4877

G. R. Wiggans, T. A. Cooper, P. M. Vanraden, and J. B. Cole, Technical note: Adjustment of traditional cow evaluations to improve accuracy of genomic predictions, Journal of Dairy Science, vol.94, issue.12, pp.6188-6193, 2011.
DOI : 10.3168/jds.2011-4481

Z. Zhang and T. Druet, Marker imputation with low-density marker panels in Dutch Holstein cattle, Journal of Dairy Science, vol.93, issue.11, pp.5487-5494, 2010.
DOI : 10.3168/jds.2010-3501