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Made available in DSpace on 2015-12-07T15:36:49Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-08-07. Added 1 bitstream(s) on 2015-12-07T15:54:24Z : No. of bitstreams: 1 PMC4527250.pdf: 1497402 bytes, checksum: 788681d54c019d5a0a161c2a7d7c043a (MD5) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Genotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R(2)). The highest imputation accuracy scenario consisted of a reference population with males and females and a target population with young females. Among the SNP panels in the tested scenarios, from the 50K, GGP75Ki and GGP80K were the most adequate to impute to HD in Canchim cattle. FImpute reduced computation run-time to impute genotypes from 20 to 100 times when compared to BEAGLE. The genotyping panels possessing at least 50 thousands markers are suitable for genotype imputation to HD with acceptable accuracy. The FImpute algorithm demonstrated a higher efficiency of imputed markers, especially in lower density panels. These considerations may assist to increase genotypic information, reduce genotyping costs, and aid in genomic selection evaluations in crossbred animals. Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brasil Beef Improvement Opportunities, Guelph, ON, Canada University of Guelph, Guelph, ON, Canada Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brasil Embrapa Southeast Livestock - Brazilian Corporation of Agricultural Research, São Carlos, SP, Brasil Embrapa Dairy Cattle - Brazilian Corporation of Agricultural Research, Juiz de Fora, MG, Brasil Departamento de Genética e Evolução, Universidade Federal de São Carlos (UFSCar), São Carlos, SP, Brasil Universidade Estadual Paulista, Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal Universidade Estadual Paulista, Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal FAPESP: 2012/21891-8 FAPESP: 2013/19335-2