1- سید دخت، ع.، ع. ا. اسلمی نژاد، و م. طهمورث پور. 1391. آنالیز ژنتیکی صفت تولید شیر گاوهای هلشتاین استان تهران با استفاده از مدل روز آزمون. نشریه پژوهش های علوم دامی ایران. 4: 174-168.
2- Buch, L. H., M. K. Sørensen, P. Berg, L. D. Pedersen, and A. C. Sørensen. 2012. Genomic selection strategies in dairy cattle: strong positive interaction between use of genotypic information and intensive use of young bulls. J. Anim. Breed. Gene. 129(2):138-51.
3- Browning, B. L., and S. R. Browning. 2008. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84:210-223.
4- Chen, J., Z. Liu, F. Reinhardt, and R. Reents. 2011. Reliability of genomic prediction using imputed genotypes for German Holsteins: Illumina 3K to 54K bovine chip. The 2011 Interbull Open Meeting, Stavanger, Norway. Interbull, Uppsala, Sweden.
5- Daetwyler, H. D., B. Villanueva, and J. A. Woolliams. 2008. Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS ONE 3:e3395.
6- Daetwyler, H. D., G. R. Wiggans, B. J. Hayes, J. A. Woolliams, and M. E. Goddard. 2010. Imputation of missing genotypes fromsparse to high density using long-range phasing. Manuscript 539in Proc. World Congress of Genetics Applied to Livestock Production, Leipzig, Germany.www.wcgalp2010.org.
7- Dassonneville, R., R. F. Brøndum, T. Druet, S. Fritz, F. Guillaume, B. Guldbrandtsen, M. S. Lund, V. Ducrocq, and G. Su. 2011. Effectofimputingmarkersfromalow-densitychiponthereliabilityofgenomic breeding values in Holstein populations. J. Dairy Sci.94:3679–3686.
8- Druet, T., and M. Georges. 2010. A hidden Markov model combining linkage and linkage disequilibrium information for haplotype reconstruction and quantitative trait locus fine mapping. Genetics, 184:789–798.
9- Goddard, M. 2009. Genomic selection: prediction of accuracy and maximization of long term response. Genetica 136, 245–257.
10- Habier, D., R. L. Fernando, and J. C. Dekkers. 2009. Genomic selection using low-density marker panels. Genetics 182:343–353.
11- Harris, B. L., and D. L. Johnson. 2010. Genomic predictions for New Zealand dairy bulls and integration with national genetic evaluation. J. Dairy Sci. 93:1243–1252.
12- Hayes, B. J., P. J. Bowman, A. J. Chamberlain, and M. E. Goddard. 2009. Invited review: Genomic selection in dairy cattle: Progress and challenges. J. Dairy Sci. 92:433–443.
13- Johnston, J., G. Kistemaker. 2011. Comparison of different imputation methods. Interbull open meeting. Stavanger, Norway.
14- Kolbehdari, D., L. R. Schaeffer, and J. A. B. Robinson. 2007. Estimation of genome wide haplotype effect in half sib designs. J. Anim. Breed. Genet. 124:356-361.
15- Liu, Z. T., F. R. Seefried, F. Reinhardt, S. Rensing, G. Thaller, and R. Reents. 2011. Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction. Genet. Sel. Evol. 43:19.
16- Long, N., D. Gianola, G. J. M.Rosa, K. A. Weigel, and S. Avendano. 2007. Machine learning classification procedure for selecting SNPs in genomic selection: Application to early mortality in broilers. J. Anim. Breed. Genet. 124:377-389.
17- Ma, P., R. F. Brøndum, Q. Zhang, M. S. Lund, and G. Su. 2013. Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle. J. Dairy Sci. 96:4666–4677.
18- Madsen P., and J. Jensen. 2007. DMU: A user’s Guide. A Package for Analyzing Multivariate Mixed Models. Version 6, Release 4.7. http://dmu.agrsci.dk/dmuv6_guideR4-6-7.pdf Accessed Nov. 15.
19- Meuwissen, T. H. E., B. J. Hayes, and M. E. Goddard. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics. 157:1819-1829.
20- Meuwissen, T., and M. Goddard. 2010. Accurate prediction of genetic values for complex traits by whole-genome resequencing. Genetics. 185:623–631.
21- Moser, G., M. S. Khatkar, B. J. Hayes, and H. W. Raadsma. 2010. Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers. Genet. Sel. Evol. 42:37.
22- Muir, W. M. 2007. Comparison of genomic and traditional BLUP- estimated breeding value accuracy and selection response under alternative trait and genomic parameters. J. Anim. Breed. Genet. 124:342–355.
23- Pedersen, L. D., A. C. Sørensen, M. Henryon, S. Ansari-Mahyari, and P. Berg. 2009. ADAM: A computer program to simulate selective breeding schemes for animals. Livestock sci. 121(2-3): 343-344.
24- Pryce, J. E., M. E. Goddard, H. W. Raadsma, and B. J. Hayes. 2010. Deterministic models of breeding scheme designs that incorporate genomic selection. J. Dairy Sci. 93:5455–5466.
25- Pszczola, M., A. Mulder, and M. P. L. Calus. 2010. Effect of enlarging the reference population with (un) genotyped animals on the accuracy of genomic selection in dairy cattle. J. Dairy Sci. 94:431-441.
26- Sargolzaei, M., J. P. Chesnais, and F. S. Schenkel. 2011. FImpute- An efficient imputation algorithm for dairy cattle populations. J. Dairy Sci. 94(E-Suppl. 1):421. (Abstr).
27- Schaeffer, L. R. 2006. Strategy for applying genome-wide selection in dairy cattle. J. Anim. Breed. Genet. 123:218–223.
28- Scheet, P., and M. Stephens. 2006. A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 78:629–644.
29- Su, G., R. F. Brøndum, P. Ma, B. Guldbrandtsen, G. P. Aamand, and M. S. Lund. 2012. Comparison of genomic predictions using medium-density (~54,000) and high-density (~777,000) single nucleotide polymorphism marker panelsin Nordic Holstein and Red Dairy Cattle populations. J. Dairy Sci. 95:4657–4665.
30- VanRaden, P. M. 2008. Efficient methods to compute genomic predictions. J. Dairy Sci. 91:4414–4423.
31- VanRaden, P. M., C. P. Van Tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel, J. F. Taylor, and F. S. Schenkel. 2009. Invited review: Reliability of genomic predictions for North American Holstein bulls. J. Dairy Sci. 92:16–24.
32- Weigel, K. A., C. P. Van Tassell, J. R. O’Connell, P. M. VanRaden, and G. R. Wiggans. 2010. Prediction of unobserved single nucleotide polymorphism genotypes of Jersey cattle using panels and population-based imputation algorithms. J. Dairy Sci. 93:2229– 2238.
33- Zhang, Z., and T. Druet. 2010. Marker imputation with low-density marker panels in Dutch Holstein cattle. J. Dairy Sci. 93:5487–5494.
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