title: Strategies for genotype imputation in composite beef cattle.
abstract: BACKGROUND
  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)).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Departamento de Ciências Exatas, UNESP - Univ Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, Brazil. tatischud@gmail.com.
authors.forename: Tatiane C S
authors.initials: TC
authors.lastname: Chud
authors.affiliation: Beef Improvement Opportunities, Guelph, ON, Canada. rvventura@gmail.com.|University of Guelph, Guelph, ON, Canada. rvventura@gmail.com.
authors.forename: Ricardo V
authors.initials: RV
authors.lastname: Ventura
authors.affiliation: University of Guelph, Guelph, ON, Canada. schenkel@uoguelph.ca.
authors.forename: Flavio S
authors.initials: FS
authors.lastname: Schenkel
authors.affiliation: Departamento de Zootecnia, UNESP - Univ Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, Brazil. rcar@fcav.unesp.br.
authors.forename: Roberto
authors.initials: R
authors.lastname: Carvalheiro
authors.affiliation: Departamento de Ciências Exatas, UNESP - Univ Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, Brazil. marcosbuz@yahoo.com.br.
authors.forename: Marcos E
authors.initials: ME
authors.lastname: Buzanskas
authors.affiliation: Departamento de Ciências Exatas, UNESP - Univ Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, Brazil. jaqueolrosa@hotmail.com.
authors.forename: Jaqueline O
authors.initials: JO
authors.lastname: Rosa
authors.affiliation: Embrapa Southeast Livestock - Brazilian Corporation of Agricultural Research, São Carlos, SP, Brazil. mauricio.mudadu@embrapa.br.
authors.forename: Maurício de Alvarenga
authors.initials: Mde A
authors.lastname: Mudadu
authors.affiliation: Embrapa Dairy Cattle - Brazilian Corporation of Agricultural Research, Juiz de Fora, MG, Brazil. marcos.vb.silva@embrapa.br.
authors.forename: Marcos Vinicius G B
authors.initials: MV
authors.lastname: da Silva
authors.affiliation: Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, Brazil. fabiana_barichello@yahoo.com.br.
authors.forename: Fabiana B
authors.initials: FB
authors.lastname: Mokry
authors.affiliation: Embrapa Southeast Livestock - Brazilian Corporation of Agricultural Research, São Carlos, SP, Brazil. cintia.marcondes@embrapa.br.
authors.forename: Cintia R
authors.initials: CR
authors.lastname: Marcondes
authors.affiliation: Embrapa Southeast Livestock - Brazilian Corporation of Agricultural Research, São Carlos, SP, Brazil. luciana.regitano@embrapa.br.
authors.forename: Luciana C A
authors.initials: LC
authors.lastname: Regitano
authors.affiliation: Departamento de Ciências Exatas, UNESP - Univ Estadual Paulista "Júlio de Mesquita Filho", Jaboticabal, SP, Brazil. danisio@fcav.unesp.br.
authors.forename: Danísio P
authors.initials: DP
authors.lastname: Munari
mesh_terms: D000483:Alleles; D000818:Animals; D001938:Brazil; D001947:Breeding; D002417:Cattle; D003433:Crosses, Genetic; D005260:Female; D055106:Genome-Wide Association Study; D005838:Genotype; D015810:Linkage Disequilibrium; D008297:Male; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D000069466:Red Meat