Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.

Detalhes bibliográficos
Autor(a) principal: SILVA, A. A.
Data de Publicação: 2019
Outros Autores: SILVA, F. F., SILVA, D. A., SILVA, H. T., COSTA, C. N., LOPES, P. S., VERONEZE, R., THOMPSON, G., CARVALHEIRA, J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117818
https://doi.org/10.17221/120/2019-CJAS
Resumo: Although several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strate-gies for the Portuguese Holstein cattle population considering several commercially available single nucleotide poly-morphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with theirgenotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate rang-ing from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation.
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spelling Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.Genomic evaluationImputation accuracyDairy cattleAlthough several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strate-gies for the Portuguese Holstein cattle population considering several commercially available single nucleotide poly-morphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with theirgenotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate rang-ing from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation.ALESSANDRA ALVES SILVAFABYANO FONSECA SILVADELVAN ALVES SILVAHUGO TEIXEIRA SILVACLAUDIO NAPOLIS COSTA, CNPGLPAULO SÁVIO LOPESRENATA VERONEZEGERTRUDE THOMPSONJULIO CARVALHEIRA.SILVA, A. A.SILVA, F. F.SILVA, D. A.SILVA, H. T.COSTA, C. N.LOPES, P. S.VERONEZE, R.THOMPSON, G.CARVALHEIRA, J.2019-12-30T00:36:34Z2019-12-30T00:36:34Z2019-12-2920192020-01-09T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCzech Journal of Animal Science, v. 64, n. 9, p. 377-386, 2019.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117818https://doi.org/10.17221/120/2019-CJASenginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2019-12-30T00:36:50Zoai:www.alice.cnptia.embrapa.br:doc/1117818Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542019-12-30T00:36:50falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542019-12-30T00:36:50Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
title Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
spellingShingle Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
SILVA, A. A.
Genomic evaluation
Imputation accuracy
Dairy cattle
title_short Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
title_full Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
title_fullStr Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
title_full_unstemmed Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
title_sort Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.
author SILVA, A. A.
author_facet SILVA, A. A.
SILVA, F. F.
SILVA, D. A.
SILVA, H. T.
COSTA, C. N.
LOPES, P. S.
VERONEZE, R.
THOMPSON, G.
CARVALHEIRA, J.
author_role author
author2 SILVA, F. F.
SILVA, D. A.
SILVA, H. T.
COSTA, C. N.
LOPES, P. S.
VERONEZE, R.
THOMPSON, G.
CARVALHEIRA, J.
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv ALESSANDRA ALVES SILVA
FABYANO FONSECA SILVA
DELVAN ALVES SILVA
HUGO TEIXEIRA SILVA
CLAUDIO NAPOLIS COSTA, CNPGL
PAULO SÁVIO LOPES
RENATA VERONEZE
GERTRUDE THOMPSON
JULIO CARVALHEIRA.
dc.contributor.author.fl_str_mv SILVA, A. A.
SILVA, F. F.
SILVA, D. A.
SILVA, H. T.
COSTA, C. N.
LOPES, P. S.
VERONEZE, R.
THOMPSON, G.
CARVALHEIRA, J.
dc.subject.por.fl_str_mv Genomic evaluation
Imputation accuracy
Dairy cattle
topic Genomic evaluation
Imputation accuracy
Dairy cattle
description Although several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strate-gies for the Portuguese Holstein cattle population considering several commercially available single nucleotide poly-morphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with theirgenotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate rang-ing from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-30T00:36:34Z
2019-12-30T00:36:34Z
2019-12-29
2019
2020-01-09T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Czech Journal of Animal Science, v. 64, n. 9, p. 377-386, 2019.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117818
https://doi.org/10.17221/120/2019-CJAS
identifier_str_mv Czech Journal of Animal Science, v. 64, n. 9, p. 377-386, 2019.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117818
https://doi.org/10.17221/120/2019-CJAS
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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