Animal Molecular Breeding 2024, Vol.14, No.1, 95-105 http://animalscipublisher.com/index.php/amb 105 Elsen J., 2003, Utilization of genomic information in livestock improvement, Outlook on Agriculture, 32: 241-245. https://doi.org/10.5367/000000003322740793 Fang L., Sahana G., Ma P., Su G., Yu Y., Zhang S., Lund M., and Sørensen P., 2017, Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds, BMC Genomics, 18: 1-12. https://doi.org/10.1186/s12864-017-4004-z Georges M., 2001, Recent progress in livestock genomics and potential impact on breeding programs, Theriogenology, 55(1): 15-21. https://doi.org/10.1016/S0093-691X(00)00442-8 Gutierrez-Reinoso M., Aponte P., and García-Herreros M., 2021, Genomic Analysis, progress and future perspectives in dairy cattle selection: a review, Animals, 11(3): 599. https://doi.org/10.3390/ani11030599 Hayes B., and Goddard M., 2010, Genome-wide association and genomic selection in animal breeding, Genome, 53(11): 876-883. https://doi.org/10.1139/G10-076 Hayes B., Pryce J., Chamberlain A., Bowman P., and Goddard M., 2010, Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in holstein cattle as contrasting model traits, PLoS Genetics, 6(9): e1001139. https://doi.org/10.1371/journal.pgen.1001139 Karaman E., Su G., Croué I., and Lund M., 2021, Genomic prediction using a reference population of multiple pure breeds and admixed individuals, Genetics, Selection, Evolution: GSE, 53(1): 46. https://doi.org/10.1186/s12711-021-00637-y Kemper K., and Goddard M., 2012, Understanding and predicting complex traits: knowledge from cattle, Human Molecular Genetics, 21(R1): R45-51. https://doi.org/10.1093/HMG/DDS332 Liang M., Miao J., Wang X., Chang T., An B., Duan X., Xu L., Gao X., Zhang L., Li J., and Gao H., 2020, Application of ensemble learning to genomic selection in chinese simmental beef cattle, Journal of Animal Breeding and Genetics, 2021, 138(3): 291-299. https://doi.org/10.1111/jbg.12514 Lopes F., Baldi F., Passafaro T., Brunes L., Costa M., Eifert E., Narciso M., Rosa G., Lôbo R., and Magnabosco C., 2020, Genome-enabled prediction of meat and carcass traits using Bayesian regression, single-step genomic best linear unbiased prediction and blending methods in Nelore cattle, Animal, 15(1): 100006. https://doi.org/10.1016/j.animal.2020.100006 Lu D., Akanno E., Crowley J., Schenkel F., Li H., Pauw M., Moore S., Wang Z., Li C., Stothard P., Plastow G., Miller S., and Basarab J., 2016, Accuracy of genomic predictions for feed efficiency traits of beef cattle using 50K and imputed HD genotypes, Journal of Animal Science, 94(4): 1342-1353. https://doi.org/10.2527/jas.2015-0126 Meuwissen T., Hayes B., and Goddard M., 2016, Genomic selection: A paradigm shift in animal breeding. Animal Frontiers, 6: 6-14. Srivastava S., Lopez B., Kumar H., Jang M., Chai H., Park W., Park J., and Lim D., 2021, Prediction of hanwoo cattle phenotypes from genotypes using machine learning methods, Animals, 11(7): 2066. https://doi.org/10.3390/ani11072066 Swami M., 2010, Complex traits: Using genetic architecture to improve predictions, Nature Reviews Genetics, 11: 748. https://doi.org/10.1038/nrg2888 Teng J., Gao N., Zhang H., Li X., Li J., Zhang H., Zhang X., and Zhang Z., 2019, Performance of whole genome prediction for growth traits in a crossbred chicken population, Poultry Science, 98: 1968-1975. https://doi.org/10.3382/ps/pey604 Woolliams J., 2011, How far and how fast can genomics take us towards precision breeding?, Journal of Animal Breeding And Genetics, 128(6): 407-408. https://doi.org/10.1111/j.1439-0388.2011.00974.x Zhang Z., Ober U., Erbe M., Zhang H., Gao N., He J., Li J., and Simianer H., 2014, Improving the accuracy of whole genome prediction for complex traits using the results of genome wide association studies, PLoS ONE, 9(3): e93017. https://doi.org/10.1371/journal.pone.0093017 Disclaimer/Publisher’s Note The statements, opinions, and data contained in all publications are solely those of the individual authors and contributors and do not represent the views of the publishing house and/or its editors. The publisher and/or its editors disclaim all responsibility for any harm or damage to persons or property that may result from the application of ideas, methods, instructions, or products discussed in the content. Publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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