02356naa a2200337 a 450000100080000000500110000800800410001902400350006010000190009524500880011426000090020230000100021152014240022165000350164565300180168065300210169865300170171965300220173670000190175870000200177770000200179770000210181770000160183870000210185470000230187570000170189870000210191570000260193670000180196277300380198020296942023-03-15       2015    bl uuuu     u00u1 u    #d7 a10.1186/s12863-015-0251-72DOI1 aCHUD, T. C. S.  aStrategies for genotype imputation in composite beef cattle.h[electronic resource]  c2015  a10 p.  aGenotype 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 (R2).  asingle nucleotide polymorphism  aCanchim breed  aCrossbred cattle  aGenomic data  aLow density panel1 aVENTURA, R. V.1 aSCHENKEL, F. S.1 aCARVALHEIRO, R.1 aBUZANSKAS, M. E.1 aROSA, J. O.1 aMUDADU, M. de A.1 aSILVA, M. V. G. B.1 aMOKRY, F. B.1 aMARCONDES, C. R.1 aREGITANO, L. C. de A.1 aMUNARI, D. P.  tBMC Genomicsgv. 16, n. 99, 2015.