T. M. Beissinger, G. J. Rosa, S. M. Kaeppler, D. Gianola, and N. De-leon, Defining window-boundaries for genomic analyses using smoothing spline techniques, Genet. Sel. Evol, vol.47, p.30, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01303215

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-01000520

M. P. Calus, T. H. Meuwissen, J. J. Windig, E. F. Knol, C. Schrooten et al., Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values, Genet. Sel. Evol, vol.41, p.11, 2009.

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, pp.553-561, 2008.

P. Croiseau, A. Baur, D. Jónás, C. Hozé, J. Promp et al., Comparison of different MarkerAssisted BLUP models for a new French genomic evaluation, Page 248 in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science, 2015.

P. Croiseau, M. N. Fouilloux, D. Jónás, S. Fritz, A. Baur et al., Extension to haplotypes of genomic evaluation algorithms, Abstract 708 in Proc. 10th World Congress of Genetics Applied to Livestock Production, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193907

B. C. Cuyabano, G. Su, and M. S. Lund, Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population, BMC Genomics, vol.15, p.1171, 2014.

B. Diedenhofen and J. Musch, cocor: A comprehensive solution for the statistical comparison of correlations, PLoS ONE, vol.10, p.121945, 2015.

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, J. Dairy Sci, vol.95, pp.4114-4129, 2012.

D. J. Garrick and R. Fernando, Genomic prediction and genome-wide association studies in beef and dairy cattle. Pages 474-501 in: The Genetics of Cattle, 2014.

L. Grapes, M. Z. Firat, J. C. Dekkers, M. F. Rothschild, and R. L. Fernando, Optimal haplotype structure for linkage disequilibrium-based fine mapping of quantitative trait loci using identity by descent, Genetics, vol.172, pp.1955-1965, 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.

B. J. Hayes, A. J. Chamberlain, H. Mcpartlan, I. Macleod, L. Sethuraman et al., Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle, Genet. Res, vol.89, pp.215-220, 2007.

A. Legarra, A. Ricard, and O. Filangi, GS3 software package and documentation. Accessed, 2013.

P. Ma, M. S. Lund, X. Ding, Q. Zhang, and G. Su, Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population, J. Anim. Breed. Genet, vol.131, pp.462-472, 2014.

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.

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, J. Dairy Sci, vol.96, pp.668-678, 2013.

T. M. Villumsen, L. Janss, and M. S. Lund, The importance of haplotype length and heritability using genomic selection in dairy cattle, J. Anim. Breed. Genet, vol.126, pp.3-13, 2009.

G. Y. Zou, Toward using confidence intervals to compare correlations, Psychol. Methods, vol.12, pp.399-413, 2007.

R. Boichard, D. Chung, H. Dassonneville, R. David, X. Eggen et al., for the Bovine LD Consortium (2012a) Design of a bovine low-density SNP array optimized for imputation, PLoS ONE, vol.7, p.34130

D. Boichard, V. Ducrocq, and S. Fritz, Sustainable dairy cattle selection in the genomic era, J. Anim. Breed. Genet, vol.132, pp.135-143, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01194086

P. Croiseau, A. Baur, D. Hoz-e, C. Promp, J. Boichard et al., Comparison of different marker-assisted BLUP models for a new French genomic evaluation, Book of abstracts of the 66th annual meeting of the European federation of animal science. Warsaw, (Poland), vol.31, 2015.

B. Diedenhofen and J. Musch, cocor: a comprehensive solution for the statistical comparison of correlations, PLoS ONE, vol.10, p.121945, 2015.

D. J. Garrick and R. Fernando, Genomic prediction and genome-wide association studies in beef and dairy cattle, The Genetics of Cattle, pp.474-501, 2014.

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

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.

B. L. Harris, A. M. Winkelman, and D. L. Johnson, Impact of including a large number of female genotypes on genomic selection, Interbull Bull, vol.47, pp.23-27, 2013.

B. J. Hayes, P. J. Bowman, A. C. Chamberlain, K. Verbyla, M. E. Goddard et al., Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population, Genet. Sel. Evol, vol.41, pp.3918-3929, 2009.

, R esultats de côntrole laitierFrance, 2014.

D. Ducrocq, V. Fouilloux, M. Croiseau, and P. , Alternative haplotype construction methods for genomic evaluation, J. Dairy Sci, vol.99, pp.4537-4546, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01533890

A. Legarra, A. Ricard, and O. Filangi, GS3 software package and documentation, 2013.

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, Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle, vol.43, pp.1503-1512, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01191309

A. P. De-roos, B. J. Hayes, and M. E. Goddard, Reliability of genomic predictions across multiple populations, Genetics, vol.183, pp.1545-1553, 2009.

A. P. De-roos, C. Schrooten, E. Mullaart, S. Van-der-beek, G. De-jong et al., Genomic selection at CRV, Interbull Bull, vol.39, pp.47-50, 2009.

P. M. Vanraden, C. P. Van-tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel et al.,

N. Alexandratos and J. Bruinsma, , 2012.

S. J. Baird, Exploring linkage disequilibrium, Mol. Ecol. Resourc, vol.15, issue.5, pp.1017-1019, 2015.

J. Bennewitz, N. Reinsch, J. Szyda, F. Reinhardt, C. Kühn et al., Marker assisted selection in German Holstein dairy cattle breeding: Outline of the program and marker assisted breeding value estimation, Book of abstracts of the 54th annual meeting of the European Federation of Animal Science, 2003.

D. R. Bentley, Whole-genome re-sequencing, Curr. Opin. Genet. Dev, vol.16, issue.6, 2006.

V. Boerner and B. Tier, BESSiE: A program for best linear unbiased prediction and Bayesian analysis of linear mixed models. BESSiE version 1.0 software documentation. Downloaded 1st of March, 2016.

D. Boichard, V. Ducrocq, and S. Fritz, Sustainable dairy cattle selection in the genomic era, J. Anim. Breed. Genet, vol.132, issue.2, pp.135-143, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01194086

D. Boichard, S. Fritz, M. N. Rossignol, M. Y. Boscher, A. Malafosse et al., Implementation of marker-assisted selection in French dairy cattle. Communication no. 22-03, Proc. of the 7 th WCGALP, 2002.

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.7, issue.3, p.34130, 2012.

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

T. Druet, L. Genestout, J. J. Colleau, L. Journaux, V. Ducrocq et al., Genomic selection in French dairy cattle, Anim. Prod. Sci, vol.52, pp.115-120, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01000520

M. Boussaha, P. Michot, R. Letaief, C. Hozé, S. Fritz et al.,

A. Duchesne, R. Philippe, V. Blanquet, F. Phocas, S. Floriot et al., Construction of a large collection of small genome variations in French dairy and beef breeds using whole genome sequences, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01479216

, Genet. Sel Evol, vol.48, issue.1, p.87

A. C. Bouwman and R. F. Veerkamp, Consequences of splitting wholegenome sequencing effort over multiple breeds on imputation accuracy, BMC Genet, vol.15, p.105, 2014.

R. F. Brøndum, E. Rius-vilarrasa, I. Strandén, G. Su, B. Guldbrandtsen et al.,

F. Kund and M. S. , Reliabilities of genomic prediction using combined reference data of the Nordic Red dairy cattle populations, J. Dairy. Sci, vol.94, pp.4700-4707, 2011.

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, issue.5, pp.1084-1097, 2007.

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.

L. Chen, C. Li, S. Miller, and F. Schenkel, Multi-population genomic prediction using a multi-task Bayesian learning model, BMC. Genet, vol.15, p.53, 2014.

J. J. Colleau, P. Quéméré, H. Larroque, J. Sergent, and C. Wagner, Gestion génétique de la race bovine Bretonne Pie-Noire : bilan et perspectives

, Anim, vol.15, issue.3, pp.221-230

G. Coop, X. Wen, C. Ober, J. K. Pritchard, and M. Przeworski, Highresolution mapping of crossoversreveals extensive variation in fine-scale recombination patterns among humans, Science, vol.319, issue.5868, pp.1395-1398, 2008.

P. Croiseau, A. Baur, D. Jónás, C. Hozé, J. Promp et al., A new Marker-Assisted BLUP genomic evaluation for French dairy breeds, Interbull Interbull meeting, 2015.

P. Croiseau, A. Baur, D. Jónás, C. Hozé, J. Promp et al., Comparison of different marker-assisted BLUP models for a new, 2015.

P. Croiseau, M. Fouilloux, D. Jónás, S. Fritz, A. Baur et al., Extension to haplotypes of genomic evaluation algorithms, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193907

, AB#708 in Proc. 10th World Congress of Genetics Applied to Livestock Production

C. Vancouver,

B. C. Cuyabano, G. Su, and M. S. Lund, Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population, BMC Genomics, vol.15, p.1171, 2014.

B. C. Cuyabano, G. Su, and M. Lund, Selection of haplotype variables from a high-density marker map for genomic evaluation, Genet. Sel. Evol, vol.47, p.61, 2015.

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

O. Bouchez, M. Rossignol, C. Klopp, D. Rocha, S. Fritz et al., Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle, Nat. Genet, vol.46, issue.8, pp.858-865, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01193853

B. Devlin and N. Risch, A comparison of linkage disequilibrium measures for fine-scale mapping, Genomics, vol.29, pp.311-322, 1995.

G. De-los-campos, H. Naya, D. Gianola, J. Crossa, A. Legarra et al., Predicting quantitative traits with regression models for dense molecular markers and pedigree, Genetics, vol.182, issue.1, pp.375-385, 2009.
URL : https://hal.archives-ouvertes.fr/pasteur-00606555

A. P. De-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.

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.

A. P. De-roos, C. Schrooten, E. Mullaart, S. Van-der-beek, G. De-jong et al., Genomic selection at CRV, Interbull Bull, vol.39, pp.47-50, 2009.

V. Ducrocq, S. Fritz, F. Guillaume, and D. Boichard, French report on the use of genomic evaluation. Page 17 in, Proc. of the Interbull technical workshop, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01193754

T. Druet and M. Georges, A hidden markov model combining linkage and linkage disequilibrium information for haplotype reconstruction and quantitative trait loci fine mapping, Genetics, vol.184, issue.3, pp.789-798, 2009.

J. M. Engels and H. Fassil, Plant and animal genebanks. Pages 144-175 in: The role of food, agriculture forestry, and fisheries in human nutrition, 2007.

R. Squires, Developed under the Auspices of the UNESCO, Encyclopedia of Life Support Systems (EOLSS)

. Ensembl, , 2016.

M. Erbe, G. Ni, H. Pausch, R. Emmerling, T. H. Meuwissen et al., Experiences from genomic prediction with imputed sequence data in different species. Page 103 in Book of abstracts of the 67th annual References meeting of the European Federation of Animal Science. The waterfront conference and exhibition centre, 2016.

D. Fallin and N. J. Schork, Accuracy of Haplotype Frequency Estimation for, 2000.

, Biallelic Loci, via the Expectation-Maximization Algorithm for Unphased Diploid Genotype Data, Am. J. Hum. Genet, vol.67, issue.4, pp.947-959

. Fao, Livestock's long shadow -environmental issues and options, 2006.

. Fao, World population prospects -2015 revision, 2015.

R. L. Fernando and M. Grossman, Marker assisted selection using best linear unbiased prediction, Genet. Sel. Evol, vol.21, pp.467-477, 1989.
URL : https://hal.archives-ouvertes.fr/hal-00893817

S. B. Gabriel, S. F. Schaffner, H. Nguyen, J. M. Moore, J. Roy et al.,

J. Higgins, M. Defelice, A. Lochner, M. Faggart, S. N. Liu-cordero et al.,

A. Adeyemo, R. Cooper, R. Ward, E. S. Lander, M. J. Daly et al., The structure of haplotype blocks in the human genome, Science, vol.296, issue.5576, pp.2225-2229, 2002.

D. J. Garrick and R. Fernando, Genomic prediction and genome-wide association studies in beef and dairy cattle. Pages 474-501 in: The genetics of cattle, 2014.

D. J. Garrick and A. Ruvinsky,

G. Gibson and S. V. Muse, A primer of genome science, 2009.

S. Associates, M. A. Sunderland, and U. ,

A. García-ruiz, J. B. Cole, P. M. Vanraden, G. R. Wiggans, F. J. Ruiz-lópez et al., Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection, Proc. Natl. Acad. Sci. U. S. A, vol.113, issue.28, pp.9995-4004, 2016.

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, issue.9, p.13038, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01193678

D. Gianola, G. De-los-campos, W. G. Hill, E. Manfredi, and R. Fernando, Additive genetic variability and the Bayesian alphabet, Genetics, vol.183, issue.1, pp.347-363, 2009.

M. Goddard, Genomic selection: prediction of accuracy and maximisation of long term response, Genetica, vol.136, pp.245-257, 2009.

K. A. Goddard, P. J. Hopkins, J. M. Hall, and J. S. Witte, Linkage disequilibrium and allele-frequency distributions for 114 single-nucleotide polymorphisms in five populations, Több támogatás az ?shonos állatok tartóinak Accessed 2nd of October, vol.66, pp.216-234, 2000.

F. Guillaume, S. Fritz, D. Boichard, and T. Druet, Correlations of markerassisted breeding values with progeny-test breeding values for eight hundred ninetynine French Holstein bulls, J. Dairy Sci, vol.91, issue.6, pp.2520-2522, 2008.

F. Guillaume, S. Fritz, D. Boichard, and T. Druet, Estimation by simulation of the efficiency of the French marker-assisted selection program in dairy cattle, Genet. Sel. Evol, vol.40, issue.1, pp.91-102, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00894611

B. Grisart, W. Coppieters, F. Farnir, L. Karim, C. Ford et al.,

M. Mni, S. Reid, P. Simon, R. Spelman, M. Georges et al., Positional candidate cloning of a QTL in dairy cattle: identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition, Genome Res, vol.12, issue.2, pp.222-231, 2002.

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.

B. L. Harris and D. L. Johnson, Genomic prediction for New Zealand dairy bulls and integration with national genetic evaluation, J. Dairy. Sci, vol.93, pp.1243-1252, 2010.

B. L. Harris and D. L. Johnson, The impact of high density SNP chips on genomic evaluation in dairy cattle, Interbull Bull, vol.42, pp.40-43, 2010.

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, 2009.

B. J. Hayes, P. J. Bowman, A. C. Chamberlain, K. Verbyla, and M. E. Goddard, Accuracy of genomic breeding values in multi-breed dairy cattle populations, 2009.

, Genet. Sel. Evol, vol.41, p.51

B. Hayes and M. E. Goddard, The distribution of the effects of genes affecting quantitative traits in livestock, Genet. Sel. Evol, vol.33, pp.209-229, 2001.
URL : https://hal.archives-ouvertes.fr/hal-00894372

C. R. Henderson, Applications of linear models in animal breeding, 1984.

P. M. Holland, R. D. Abramson, R. Watson, and D. H. Gelfand, Detection of specific polymerase chain reaction product by utilizing the 5' ? 3' exonuclease activity of Thermus aquaticus DNA polymerase, Proc. Natl. Acad. Sci. U. S. A, vol.88, issue.16, pp.7276-7280, 1991.

C. Hozé, M. 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.

C. Hozé, S. Fritz, F. Phocas, D. Boichard, V. Ducrocq et al., Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population, J. Dairy. Sci, vol.97, pp.3918-3929, 2014.

, Bilan de l'indexation des races bovines laitières, 2014.

, Chiffres clés Bovins, Accessed 28 th of December, 2015.

, Résultats de Contrôle Laitier, 2015.

, Indicateurs de variabilité génétique -races bovinesEdition, Accessed 2nd of October, 2015.

, Le point sur l'insémination en semence sexée en 2015. Accessed 11 th of, 2016.

A. J. Jeffreys, R. Neumann, M. Panayi, S. Myers, and P. Donnelly, Human recombination hot spots hidden in regions of strong marker association, Nat. Genet, vol.37, issue.6, pp.601-606, 2005.

M. Khansefid, J. E. Pryce, S. Bolormaa, S. P. Miller, Z. Wang et al., Estimation of genomic breeding values for residual feed intake in a multibreed cattle population, J. Anim. Sci, vol.92, issue.8, pp.3270-3283, 2014.

A. Lauvie, A. Audiot, N. Couix, F. Casabianca, H. Brives et al., Diversity of rare breed management programs: Between conservation and development, Livest. Sci, vol.140, pp.161-170, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01019761

A. Legarra, A. Ricard, and O. Filangi, GS3 software package and documentation, 2013.

A. Legarra, C. Robert-granié, P. Croiseau, F. Guillaume, and S. Fritz, Improved Lasso for genomic selection, Genet. Res, vol.93, pp.77-87, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01000151

L. Mézec, P. Benoit, M. Moureaux, S. Patry, and C. , Genomics, sexed semen: changes in reproduction choices in French dairy herds, 2015.

Y. Li, C. Willer, S. Sanna, and G. Abecasis, Genotype imputation, Annu. Rev. Genomics Hum. Genet, vol.10, pp.387-406, 2009.

Z. Liu, F. Reinhardt, A. Bünger, and R. Reents, Derivation and calculation of approximate reliabilities and daughter yield-deviations of a random regression testday model for genetic evaluation of dairy cattle, J. Dairy. Sci, vol.87, pp.1896-1907, 2004.

Y. Liu, X. Qin, X. H. Song, H. Jiang, Y. Shen et al., Bos Taurus genome assembly, BMC Genomics, vol.10, p.180, 2009.

D. A. Lourenco, S. Tsuruta, B. O. Fragomeni, C. Y. Chen, and W. O. Herring,

I. Misztal, Crossbreed evaluations in single-step genomic best linear unbiased predictor using adjusted realized relationship matrices, J. Anim. Sci, vol.94, issue.3, pp.909-919, 2016.

B. Luki?, R. Pong-wong, S. J. Rowe, D. J. De-koning, I. Velander et al.,

A. L. Archibald and J. A. Woolliams, Efficiency of genomic prediction for boar taint reduction in Danish landrace pigs, Anim. Genet, vol.46, pp.607-616, 2015.

M. S. Lund, A. P. De-roos, A. G. De-vries, T. Druet, V. Ducrocq et al.,

F. Guillaume, B. Guldbrandtsen, Z. Liu, R. Reents, C. Schrooten et al., A common reference population from four European Holstein populations increases reliability of genomic predictions, Genet. Sel. Evol, vol.43, issue.1, 1998.
URL : https://hal.archives-ouvertes.fr/hal-01191309

T. Knürr, I. Strandén, M. Koivula, G. P. Aamand, and E. A. Mäntysaari, , 2013.

, Haplotype-assisted genomic evaluations in Nordic red dairy cattle. Page 454 in Book of Abstracts of the 64th Annual Meeting of the European Federation of, Animal Science

L. Ma, J. R. O'connell, P. M. Vanraden, B. Shen, A. Padhi et al.,

M. Cole, J. B. Null, D. J. Liu, G. E. Da, Y. Wiggans et al., Cattle sexspecific recombination and genetic control from a large pedigree analysis, PLOS Genet, vol.11, issue.11, p.1005387, 2015.

I. M. Macleod, P. J. Bowman, C. J. Vander-jagt, M. Haile-mariam, and K. E. Kemper,

A. J. Chamberlain, C. Schrooten, B. J. Hayes, and M. E. Goddard, Exploiting biological priors and sequence variants enhance QTL discovery and genomic prediction of complex traits, BMC Genomics, vol.17, p.144, 2016.

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.4, issue.4, p.5350, 2009.

L. K. Matukumalli, S. Schroeder, S. K. Denise, T. Sonstegard, and C. T. Lawley,

M. Georges, W. Coppieters, K. Gietzen, J. F. Medrano, G. Rincon et al., Analyzing LD blocks and CNV segments in cattle: Novel genomic features identified using the BovineHD BeadChip, 2011.

A. F. Mcrae, J. C. Mcewan, K. G. Dodds, T. Wilson, A. M. Crawford et al., Linkage disequilibrium in domestic sheep, Genetics, vol.160, pp.1113-1122, 2002.

T. H. Meuwissen and M. E. Goddard, The use of marker haplotypes in animal breeding schemes, Genet. Sel. Evol, vol.28, pp.161-176, 1996.
URL : https://hal.archives-ouvertes.fr/hal-00894128

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, Complex models, more data: simpler programming, Proc. Inter, 1999.

, Workshop Comput. Cattle Breed, Tuusala, Finland. Interbull Bul, vol.20, pp.33-42, 1920.

I. Misztal, BLUPF90 software package and documentation

K. M. Olson, P. M. Vanraden, and M. E. Tooker, Multibreed genomic evaluations using purebred Holsteins, Jerseys and Brown Swiss, J. Dairy. Sci, vol.95, pp.5378-5383, 2012.

T. Park and G. Casella, The Bayesian Lasso, J. Am. Stat. Assoc, vol.103, pp.681-686, 2008.

L. R. Porto-neto, W. Barendse, J. M. Henshall, S. M. Mcwilliam, S. A. Lehnert et al., Genomic correlation: harnessing the benefit of combining two unrelated populations for genomic selection, Genet. Sel. Evol, vol.47, p.84, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01341318

J. E. Pryce, B. Gredler, S. Bolormaa, P. J. Bowman, C. Egger-danner et al., Short communication: Genomic selection using a multi-breed, across-country reference population, J. Dairy. Sci, vol.94, pp.2625-2630, 2011.

W. M. Rauw and L. Gomez-raya, Genotype by environment interaction and breeding for robustness in livestock, Front. Genet, vol.6, p.310, 2015.

G. Rincon, K. L. Weber, A. L. Van-eenennaam, B. L. Golden, and J. F. Medrano, Hot topic: Performance of bovine high-density genotyping platforms in Holsteins and Jersyes, J. Dairy Sci, vol.94, pp.6116-6121, 2011.

J. M. Rendel and A. Robertson, Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle, J. Genet, vol.50, issue.1, pp.1-8, 1950.

R. Saintilan, A. Capitan, M. Benoit, S. Barbier, and S. Fritz, Implementing a genomic preselection tool in the three main French beef cattle breeds. 22 nd International 3R Congress, 2015.

M. Sanchez, D. Jónás, A. Baur, V. Ducrocq, C. Hozé et al.,

S. Fritz, D. Boichard, and P. Crouseau, Implementation of genomic selection in three French regional dairy cattle breeds. Page 601 in Book of abstracts of the 67th annual meeting of the European Federation of Animal Science, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01531682

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.

L. R. Schaeffer, Strategy for applying genome-wide selection in dairy cattle, J. Anim. Breed. Genet, vol.123, issue.4, pp.218-223, 2006.

R. Shen, J. Fan, D. Campbell, W. Chang, J. Chen et al.,

M. Bibikova, E. W. Garcia, C. Mcbride, F. Steemers, F. Garcia et al., High-throughput SNP genotyping on universal bead arrays, Mutat. Res, vol.573, issue.1-2, pp.70-82, 2005.

J. C. Stephens, J. A. Schneider, D. A. Tanguay, J. Choi, T. Acharya et al.,

E. Jiang, R. Messer, J. C. Chew, A. Han, J. Duan et al.,

B. Koshy, A. M. Kumar, G. Zhang, W. R. Newell, A. Windemuth et al., Haplotype variation and linkage disequilibrium in 313 human genes, Am. J. Hum. Genet, vol.63, issue.2, pp.595-612, 2001.

S. Støier, H. D. Larsen, M. D. Aaslyng, and L. Lykke, Improved animal welfare, the right technology and increased business, Meat. Sci, vol.120, pp.71-77, 2016.

J. Szyda, E. Ptak, J. Komisarek, and A. Zarnecki, Practical application of daughter yield deviations in dairy cattle breeding, J. Appl. Genet, vol.49, pp.183-191, 2008.

Y. V. Thaxton, K. D. Christensen, J. A. Mench, E. R. Rumley, C. Daugherty et al., Symposium: Animal welfare challenges for today and tomorrow, Poult. Sci, vol.95, issue.9, pp.2198-2207, 2016.

, The International HapMap Consortium, Nature, vol.437, pp.1299-1320, 2005.

A. R. Tobler, S. Short, M. R. Andersen, T. M. Paner, J. C. Briggs et al.,

P. P. Wu, Y. Wang, A. Y. Spoonde, R. T. Koehler, N. Peyret et al., The SNPlex Genotyping System: A Flexible and Scalable Platform for SNP Genotyping, J. Biomol. Tech, vol.16, issue.4, pp.398-406, 2005.

P. M. Vanraden, Efficient methods to compute genomic predictions, J. Dairy Sci, vol.91, pp.4414-4423, 2008.

K. L. Verbyla, B. J. Hayes, P. J. Bowman, and M. E. Goddard, Accuracy of genomic selection using stochastic search variable selection in Australian Holstein Friesian dairy cattle, Genet. Res, vol.91, pp.307-311, 2009.

T. M. Villumsen, L. Janss, and M. S. Lund, The importance of haplotype length and heritability using genomic selection in dairy cattle, J. Anim. Breed. Genet, vol.126, pp.3-13, 2009.

T. Wang, Y. P. Chen, M. E. Goddard, T. H. Meuwissen, and K. E. Kemper,

B. J. Hayes, A computationally efficient algorithm for genomic prediction using a Bayesian model, Genet. Sel. Evol, vol.47, p.34, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01309643

K. A. Weigel, G. De-los-campos, O. González-recio, H. Naya, X. L. Wu et al.,

G. J. Rosa and D. Gianola, Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers, J. Dairy Sci, vol.92, pp.5248-5257, 2009.

Z. Weng, M. Saatchi, R. D. Schnabel, J. F. Taylor, and D. J. Garrick, Recombination locations and rates in beef cattle assessed from parent-offspring pairs, Genet. Sel. Evol, vol.46, p.34, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01341266

Y. C. Wientjes, M. P. Calus, M. E. Goddard, and B. J. Hayes, Impact of QTL properties in the accuracy of multi-breed genomic prediction, Genet. Sel. Evol, vol.47, p.42, 2015.

G. R. Wiggans, P. M. Vanraden, and T. A. Cooper, The genomic evaluation system in the United States: Past, present future, J. Dairy Sci, vol.94, pp.3202-3211, 2011.

Z. Zhang, J. Liu, X. Ding, P. Bijma, D. De-koning et al., Best linear unbiased prediction of genomic breeding values using a trait-specific markerderived relationship matrix, PLoS One, vol.5, issue.9, p.12648, 2010.

J. Yang, B. Benyamin, B. P. Mcevoy, S. Gordon, A. K. Henders et al.,

P. M. Visscher, Common SNPs explain a large proportion of the heritability for human height, Nat. Genet, vol.42, issue.7, pp.565-569, 2010.

D. Jónás, V. Ducrocq, and P. Croiseau, The combined use of LD-based haploblock and allele frequency-based haplotype selection method enhances genomic evaluation in dairy cattle, J. Dairy Sci

D. Jónás, V. Ducrocq, S. Fritz, A. Baur, S. et al., Genomic evaluation of regional dairy cattle breeds in single-breed and multi-breed contexts, J. Anim. Breed. Genet, vol.134, issue.1, pp.3-13, 2016.

D. Jónás, V. Ducrocq, M. Fouilloux, and P. Croiseau, Alternative haplotype construction methods for genomic evaluation, J. Dairy Sci, vol.99, issue.6, pp.4537-4546, 2016.

M. P. Sanchez, D. Jónás, A. Baur, V. Ducrocq, C. Hozé et al.,

S. Fritz, D. Boichard, and P. Croiseau, Implementation of genomic selection in three French regional dairy cattle breeds. Oral presentation at the 67 th Annual meeting of the European Federation of Animal Science, p.29, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01531682

D. Jónás, V. Ducrocq, M. Fouilloux, and P. Croiseau, Haplotype construction methods to enhance genomic evaluation. Oral presentation at the 66, 2015.

D. Jónás, C. Hozé, D. Boichard, and P. Croiseau, Application of a threehaplotype LDLA model to the French Holstein population. Oral presentation at the 10 th World congress on genetics applied to livestock production, p.215, 2014.

. Seminars and . Seminar, , pp.25-26, 2014.

D. Jónás, P. Croiseau, and V. Ducrocq, Evaluation of haplotype-based genomic selection methods in a multi, pp.23-24, 2014.

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D. Ducrocq, V. Fouilloux, M. Croiseau, and P. , Alternative haplotype construction methods for genomic evaluation, Poster presentation: Jónás, pp.14-15, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01533890

&. Doc and . Seminar,

D. Croiseau, P. Ducrocq, V. Croiseau, P. Ducrocq, and V. , Evaluation of haplotype-based genomic selection methods in multi-breed context, Oral presentation: Jónás, pp.16-17, 2015.