Strategies for genotype imputation in composite beef cattle

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorChud, Tatiane Cristina Seleguim
dc.creatorVentura, Ricardo Vieira
dc.creatorSchenkel, Flavio Schramm
dc.creatorCarvalheiro, Roberto
dc.creatorBuzanskas, Marcos Eli
dc.creatorRosa, Jaqueline Oliveira
dc.creatorMudadu, Maurício de Alvarenga
dc.creatorSilva, Marcos Vinicius Gualberto Barbosa da
dc.creatorMokry, Fabiana Barichello
dc.creatorMarcondes, Cintia R.
dc.creatorRegitano, Luciana Correia de Almeida
dc.creatorMunari, Danísio Prado
dc.date2015-12-07T15:36:49Z
dc.date2016-10-25T21:23:43Z
dc.date2015-12-07T15:36:49Z
dc.date2016-10-25T21:23:43Z
dc.date2015-08-07
dc.date.accessioned2017-04-06T09:31:12Z
dc.date.available2017-04-06T09:31:12Z
dc.identifierBMC Genetics, v. 16, p. 99-108, 2015.
dc.identifier1471-2156
dc.identifierhttp://hdl.handle.net/11449/131518
dc.identifierhttp://acervodigital.unesp.br/handle/11449/131518
dc.identifier10.1186/s12863-015-0251-7
dc.identifierPMC4527250.pdf
dc.identifier26250698
dc.identifierPMC4527250
dc.identifierhttp://dx.doi.org/10.1186/s12863-015-0251-7
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/942058
dc.descriptionGenotype 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.
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.languageeng
dc.publisherBioMed Central LTD
dc.relationBMC Genetics
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCanchim breed
dc.subjectCrossbred cattle
dc.subjectGenomic data
dc.subjectLow-density panel
dc.subjectSingle nucleotide polymorphism
dc.titleStrategies for genotype imputation in composite beef cattle
dc.typeOtro


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