102181 20230519145442.0 doi 10.3168/jds.2020-19978 sideral 124145 ART-2021-124145 eng Granado-Tajada, I. Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed 2021 Access copy available to the general public Unrestricted Genomic selection has been implemented over the years in several livestock species, due to the achievable higher genetic progress. The use of genomic information in evaluations provides better prediction accuracy than do pedigree-based evaluations, and the makeup of the genotyped population is a decisive point. The aim of this work is to compare the effect of different genotyping strategies (number and type of animals) on the prediction accuracy for dairy sheep Latxa breeds. A simulation study was designed based on the real data structure of each population, and the phenotypic and genotypic data obtained were used in genetic (BLUP) and genomic (single-step genomic BLUP) evaluations of different genotyping strategies. The genotyping of males was beneficial when they were genetically connected individuals and if they had daughters with phenotypic records. Genotyping females with their own lactation records increased prediction accuracy, and the connection level has less relevance. The differences in genotyping females were independent of their estimated breeding value. The combined genotyping of males and females provided intermediate accuracy results regardless of the female selection strategy. Therefore, assuming that genotyping rams is interesting, the incorporation of genotyped females would be beneficial and worthwhile. The benefits of genotyping individuals from various generations were highlighted, although it was also possible to gain prediction accuracy when historic individuals were not considered. Greater genotyped population sizes resulted in more accuracy, even if the increase seems to reach a plateau. info:eu-repo/grantAgreement/EUR/INTERREG-POCTEFA/ARDI-EFA208/16 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 4.225 2021 AGRICULTURE, DAIRY & ANIMAL SCIENCE 6 / 63 = 0.095 2021 Q1 T1 FOOD SCIENCE & TECHNOLOGY 48 / 144 = 0.333 2021 Q2 T2 1.215 2021 Food Science 2021 Q1 Animal Science and Zoology 2021 Q1 7.1 2021 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Varona, L. Universidad de Zaragoza (orcid)0000-0001-6256-5478 Ugarte, E. 1001 420 Universidad de Zaragoza Dpto. Anatom.,Embri.Genét.Ani. Área Genética 104, 6 (2021), P6861-6872 J. dairy sci. Journal of Dairy Science 0022-0302 770731 http://zaguan.unizar.es/record/102181/files/texto_completo.pdf Versión publicada 3210005 http://zaguan.unizar.es/record/102181/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:102181 articulos driver 2023-05-18-14:34:35 ARTICLE