000102181 001__ 102181
000102181 005__ 20230519145442.0
000102181 0247_ $$2doi$$a10.3168/jds.2020-19978
000102181 0248_ $$2sideral$$a124145
000102181 037__ $$aART-2021-124145
000102181 041__ $$aeng
000102181 100__ $$aGranado-Tajada, I.
000102181 245__ $$aGenotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed
000102181 260__ $$c2021
000102181 5060_ $$aAccess copy available to the general public$$fUnrestricted
000102181 5203_ $$aGenomic 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.
000102181 536__ $$9info:eu-repo/grantAgreement/EUR/INTERREG-POCTEFA/ARDI-EFA208/16
000102181 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000102181 590__ $$a4.225$$b2021
000102181 592__ $$a1.215$$b2021
000102181 594__ $$a7.1$$b2021
000102181 591__ $$aAGRICULTURE, DAIRY & ANIMAL SCIENCE$$b6 / 63 = 0.095$$c2021$$dQ1$$eT1
000102181 593__ $$aFood Science$$c2021$$dQ1
000102181 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b48 / 144 = 0.333$$c2021$$dQ2$$eT2
000102181 593__ $$aAnimal Science and Zoology$$c2021$$dQ1
000102181 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000102181 700__ $$0(orcid)0000-0001-6256-5478$$aVarona, L.$$uUniversidad de Zaragoza
000102181 700__ $$aUgarte, E.
000102181 7102_ $$11001$$2420$$aUniversidad de Zaragoza$$bDpto. Anatom.,Embri.Genét.Ani.$$cÁrea Genética
000102181 773__ $$g104, 6 (2021), P6861-6872$$pJ. dairy sci.$$tJournal of Dairy Science$$x0022-0302
000102181 8564_ $$s770731$$uhttps://zaguan.unizar.es/record/102181/files/texto_completo.pdf$$yVersión publicada
000102181 8564_ $$s3210005$$uhttps://zaguan.unizar.es/record/102181/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000102181 909CO $$ooai:zaguan.unizar.es:102181$$particulos$$pdriver
000102181 951__ $$a2023-05-18-14:34:35
000102181 980__ $$aARTICLE