Mostrar el registro sencillo del ítem
dc.contributor.author | Ibáñez-Escriche, Noelia | es_ES |
dc.contributor.author | Gonzalez-Recio, Oscar | es_ES |
dc.date.accessioned | 2020-01-15T21:01:23Z | |
dc.date.available | 2020-01-15T21:01:23Z | |
dc.date.issued | 2011 | es_ES |
dc.identifier.issn | 1695-971X | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/134655 | |
dc.description.abstract | [EN] The aim of this work was to review the main challenges and pitfalls of the implementation of genomic selection in the breeding programs of different livestock species. Genomic selection is now one of the main challenges in animal breeding and genetics. Its application could considerably increase the genetic gain in traits of interest. However, the success of its practical implementation depends on the selection scheme characteristics, and these must be studied for each particular case. In dairy cattle, especially in Holsteins, genomic selection is a reality. However, in other livestock species (beef cattle, small ruminants, monogastrics and fish) genomic selection has mainly been used experimentally. The main limitation for its implementation in the mentioned livestock species is the high genotyping costs compared to the low selection value of the candidate. Nevertheless, nowadays the possibility of using single-nucleotide polymorphism (SNP) chips of low density to make genomic selection applications economically feasible is under study. Economic studies may optimize the benefits of genomic selection (GS) to include new traits in the breeding goals. It is evident that genomic selection offers great potential; however, a suitable genotyping strategy and recording system for each case is needed in order to properly exploit it. | es_ES |
dc.description.abstract | [ES] El objetivo principal de este trabajo fue revisar las oportunidades y riesgos de la implementación de la selección genómica en las diferentes especies de producción animal. La selección genómica es actualmente uno de los principales retos en mejora genética animal. Su aplicación podría incrementar de forma considerable la tasa de ganancia genética en caracteres de interés. Sin embargo, el éxito de su implementación práctica depende de las particularidades de cada esquema de selección y por tanto debe ser estudiada para cada caso en concreto. En vacuno de leche, especialmente en Holstein, la selección genómica es una realidad. En el resto de especies de producción animal, vacuno carne, pequeños rumiantes, monogástricos y peces, la selección genómica, hasta ahora, se ha utilizado principalmente de manera experimental. El limitante principal para su implementación, común para todas las especies mencionadas, es el alto coste del genotipado en comparación con el bajo valor de los candidatos a la selección. No obstante, se está estudiando actualmente la posibilidad de utilizar chips de baja densidad, de manera que sea económicamente viable su aplicación. Serán necesarios estudios económicos para optimizar las ventajas de la selección genómica a la hora de incluir nuevos caracteres en los objetivos de selección. La selección genómica ofrece muchas posibilidades; sin embargo, para poder aprovecharlas es necesario adecuar la estrategia de genotipado y recolección de datos en cada caso. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria | es_ES |
dc.relation.ispartof | Spanish Journal of Agricultural Research | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Breeding scheme | es_ES |
dc.subject | Chip technology | es_ES |
dc.subject | Genotyping | es_ES |
dc.subject | SNP | es_ES |
dc.subject | Esquemas de selección | es_ES |
dc.subject | Genotipado | es_ES |
dc.subject | Tecnología de chip | es_ES |
dc.subject.classification | PRODUCCION ANIMAL | es_ES |
dc.title | Review. Promises, pitfalls and challenges of genomic selection in breeding program | es_ES |
dc.title.alternative | Revisión. Promesas, peligros y oportunidades de la selección genómica en los programas de mejora genética | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.5424/sjar/20110902-447-10 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal | es_ES |
dc.description.bibliographicCitation | Ibáñez-Escriche, N.; Gonzalez-Recio, O. (2011). Review. Promises, pitfalls and challenges of genomic selection in breeding program. Spanish Journal of Agricultural Research. 9(2):404-413. https://doi.org/10.5424/sjar/20110902-447-10 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.5424/sjar/20110902-447-10 | es_ES |
dc.description.upvformatpinicio | 404 | es_ES |
dc.description.upvformatpfin | 413 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 9 | es_ES |
dc.description.issue | 2 | es_ES |
dc.relation.pasarela | S\393273 | es_ES |
dc.description.references | Calus, M. P. L., & Veerkamp, R. F. (2007). Accuracy of breeding values when using and ignoring the polygenic effect in genomic breeding value estimation with a marker density of one SNP per cM. Journal of Animal Breeding and Genetics, 124(6), 362-368. doi:10.1111/j.1439-0388.2007.00691.x | es_ES |
dc.description.references | Daetwyler, H. D., Villanueva, B., Bijma, P., & Woolliams, J. A. (2007). Inbreeding in genome-wide selection. Journal of Animal Breeding and Genetics, 124(6), 369-376. doi:10.1111/j.1439-0388.2007.00693.x | es_ES |
dc.description.references | Gianola, D., Fernando, R. L., & Stella, A. (2006). Genomic-Assisted Prediction of Genetic Value With Semiparametric Procedures. Genetics, 173(3), 1761-1776. doi:10.1534/genetics.105.049510 | es_ES |
dc.description.references | Gjerde, B., Gunnes, K., & Gjedrem, T. (1983). Effect of inbreeding on survival and growth in rainbow trout. Aquaculture, 34(3-4), 327-332. doi:10.1016/0044-8486(83)90212-0 | es_ES |
dc.description.references | Goddard, M. (2008). Genomic selection: prediction of accuracy and maximisation of long term response. Genetica, 136(2), 245-257. doi:10.1007/s10709-008-9308-0 | es_ES |
dc.description.references | González-Recio, O., & Forni, S. (2011). Genome-wide prediction of discrete traits using bayesian regressions and machine learning. Genetics Selection Evolution, 43(1). doi:10.1186/1297-9686-43-7 | es_ES |
dc.description.references | González-Recio, O., Gianola, D., Long, N., Weigel, K. A., Rosa, G. J. M., & Avendaño, S. (2008). Nonparametric Methods for Incorporating Genomic Information Into Genetic Evaluations: An Application to Mortality in Broilers. Genetics, 178(4), 2305-2313. doi:10.1534/genetics.107.084293 | es_ES |
dc.description.references | GONZÁLEZ-RECIO, O., WEIGEL, K. A., GIANOLA, D., NAYA, H., & ROSA, G. J. M. (2010). L2-Boosting algorithm applied to high-dimensional problems in genomic selection. Genetics Research, 92(3), 227-237. doi:10.1017/s0016672310000261 | es_ES |
dc.description.references | Habier, D., Fernando, R. L., & Dekkers, J. C. M. (2009). Genomic Selection Using Low-Density Marker Panels. Genetics, 182(1), 343-353. doi:10.1534/genetics.108.100289 | es_ES |
dc.description.references | Hayes, B. J., Bowman, P. J., Chamberlain, A. C., Verbyla, K., & Goddard, M. E. (2009). Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genetics Selection Evolution, 41(1). doi:10.1186/1297-9686-41-51 | es_ES |
dc.description.references | Ibánẽz-Escriche, N., Fernando, R. L., Toosi, A., & Dekkers, J. C. (2009). Genomic selection of purebreds for crossbred performance. Genetics Selection Evolution, 41(1), 12. doi:10.1186/1297-9686-41-12 | es_ES |
dc.description.references | Ibáñez-Escriche, N., & Blasco, A. (2011). Modifying growth curve parameters by multitrait genomic selection1. Journal of Animal Science, 89(3), 661-668. doi:10.2527/jas.2010-2984 | es_ES |
dc.description.references | Kizilkaya, K., Fernando, R. L., & Garrick, D. J. (2010). Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes1. Journal of Animal Science, 88(2), 544-551. doi:10.2527/jas.2009-2064 | es_ES |
dc.description.references | König, S., Simianer, H., & Willam, A. (2009). Economic evaluation of genomic breeding programs. Journal of Dairy Science, 92(1), 382-391. doi:10.3168/jds.2008-1310 | es_ES |
dc.description.references | Long, N., Gianola, D., Rosa, G. J. M., Weigel, K. A., & Avendaño, S. (2007). Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers. Journal of Animal Breeding and Genetics, 124(6), 377-389. doi:10.1111/j.1439-0388.2007.00694.x | es_ES |
dc.description.references | Muir, W. M. (2007). 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, 124(6), 342-355. doi:10.1111/j.1439-0388.2007.00700.x | es_ES |
dc.description.references | Nielsen, H. M., Sonesson, A. K., Yazdi, H., & Meuwissen, T. H. E. (2009). Comparison of accuracy of genome-wide and BLUP breeding value estimates in sib based aquaculture breeding schemes. Aquaculture, 289(3-4), 259-264. doi:10.1016/j.aquaculture.2009.01.027 | es_ES |
dc.description.references | Ødegård, J., Sonesson, A. K., Yazdi, M. H., & Meuwissen, T. H. (2009). Introgression of a major QTL from an inferior into a superior population using genomic selection. Genetics Selection Evolution, 41(1). doi:10.1186/1297-9686-41-38 | es_ES |
dc.description.references | Ødegård, J., Yazdi, M. H., Sonesson, A. K., & Meuwissen, T. H. E. (2008). Incorporating Desirable Genetic Characteristics From an Inferior Into a Superior Population Using Genomic Selection. Genetics, 181(2), 737-745. doi:10.1534/genetics.108.098160 | es_ES |
dc.description.references | Pedersen, L. D., Sørensen, A. C., & Berg, P. (2009). Marker-assisted selection can reduce true as well as pedigree-estimated inbreeding. Journal of Dairy Science, 92(5), 2214-2223. doi:10.3168/jds.2008-1616 | es_ES |
dc.description.references | Pedersen, L. D., Sørensen, A. C., & Berg, P. (2009). Marker-assisted selection reduces expected inbreeding but can result in large effects of hitchhiking. Journal of Animal Breeding and Genetics, 127(3), 189-198. doi:10.1111/j.1439-0388.2009.00834.x | es_ES |
dc.description.references | Sonesson, A. K., & Meuwissen, T. H. (2009). Testing strategies for genomic selection in aquaculture breeding programs. Genetics Selection Evolution, 41(1). doi:10.1186/1297-9686-41-37 | es_ES |
dc.description.references | Su, G.-S., Liljedahl, L.-E., & Gall, G. A. E. (1996). Effects of inbreeding on growth and reproductive traits in rainbow trout (Oncorhynchus mykiss). Aquaculture, 142(3-4), 139-148. doi:10.1016/0044-8486(96)01255-0 | es_ES |
dc.description.references | Toro, M. A., & Varona, L. (2010). A note on mate allocation for dominance handling in genomic selection. Genetics Selection Evolution, 42(1). doi:10.1186/1297-9686-42-33 | es_ES |
dc.description.references | VanRaden, P. M., & Sullivan, P. G. (2010). International genomic evaluation methods for dairy cattle. Genetics Selection Evolution, 42(1). doi:10.1186/1297-9686-42-7 | es_ES |
dc.description.references | VanRaden, P. M., Van Tassell, C. P., Wiggans, G. R., Sonstegard, T. S., Schnabel, R. D., Taylor, J. F., & Schenkel, F. S. (2009). Invited Review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science, 92(1), 16-24. doi:10.3168/jds.2008-1514 | es_ES |
dc.description.references | Weigel, K. A., de los Campos, G., González-Recio, O., Naya, H., Wu, X. L., Long, N., … Gianola, D. (2009). Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. Journal of Dairy Science, 92(10), 5248-5257. doi:10.3168/jds.2009-2092 | es_ES |
dc.description.references | Weigel, K. A., Van Tassell, C. P., O’Connell, J. R., VanRaden, P. M., & Wiggans, G. R. (2010). Prediction of unobserved single nucleotide polymorphism genotypes of Jersey cattle using reference panels and population-based imputation algorithms. Journal of Dairy Science, 93(5), 2229-2238. doi:10.3168/jds.2009-2849 | es_ES |