Accuracy of genome-wide imputation in Braford and Hereford beef cattle
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/114805 |
Resumo: | Background: Strategies for imputing genotypes from the Illumina-Bovine3K, Illumina-BovineLD (6K), BeefLD-GGP (8K), a non-commercial-15K and IndicusLD-GGP (20K) to either Illumina-BovineSNP50 (50K) or to Illumina-BovineHD (777K) SNP panel, as well as for imputing from 50K, GGP-IndicusHD (90iK) and GGP-BeefHD (90tK) to 777K were investigated. Imputation of low density (<50K) genotypes to 777K was carried out in either one or two steps. Imputation of ungenotyped parents (n = 37 sires) with four or more offspring to the 50K panel was also assessed. There were 2,946 Braford, 664 Hereford and 88 Nellore animals, from which 71, 59 and 88 were genotyped with the 777K panel, while all others had 50K genotypes. The reference population was comprised of 2,735 animals and 175 bulls for 50K and 777K, respectively. The low density panels were simulated by masking genotypes in the 50K or 777K panel for animals born in 2011. Analyses were performed using both Beagle and FImpute software. Genotype imputation accuracy was measured by concordance rate and allelic R2 between true and imputed genotypes. Results: The average concordance rate using FImpute was 0.943 and 0.921 averaged across all simulated low density panels to 50K or to 777K, respectively, in comparison with 0.927 and 0.895 using Beagle. The allelic R2 was 0.912 and 0.866 for imputation to 50K or to 777K using FImpute, respectively, and 0.890 and 0.826 using Beagle. One and two steps imputation to 777K produced averaged concordance rates of 0.806 and 0.892 and allelic R2 of 0.674 and 0.819, respectively. Imputation of low density panels to 50K, with the exception of 3K, had overall concordance rates greater than 0.940 and allelic R2 greater than 0.919. Ungenotyped animals were imputed to 50K panel with an average concordance rate of 0.950 by FImpute. Conclusion: FImpute accuracy outperformed Beagle on both imputation to 50K and to 777K. Two-step outperformed one-step imputation for imputing to 777K. Ungenotyped animals that have four or more offspring can have their 50K genotypes accurately inferred using FImpute. All low density panels, except the 3K, can be used to impute to the 50K using FImpute or Beagle with high concordance rate and allelic R2. |
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Piccoli, Mario LuizBraccini Neto, JoséCardoso, Fernando FloresSargolzaei, M.Larmer, Steven G.Schenkel, Flavio Schramm2015-04-02T02:00:31Z20141471-2156http://hdl.handle.net/10183/114805000951773Background: Strategies for imputing genotypes from the Illumina-Bovine3K, Illumina-BovineLD (6K), BeefLD-GGP (8K), a non-commercial-15K and IndicusLD-GGP (20K) to either Illumina-BovineSNP50 (50K) or to Illumina-BovineHD (777K) SNP panel, as well as for imputing from 50K, GGP-IndicusHD (90iK) and GGP-BeefHD (90tK) to 777K were investigated. Imputation of low density (<50K) genotypes to 777K was carried out in either one or two steps. Imputation of ungenotyped parents (n = 37 sires) with four or more offspring to the 50K panel was also assessed. There were 2,946 Braford, 664 Hereford and 88 Nellore animals, from which 71, 59 and 88 were genotyped with the 777K panel, while all others had 50K genotypes. The reference population was comprised of 2,735 animals and 175 bulls for 50K and 777K, respectively. The low density panels were simulated by masking genotypes in the 50K or 777K panel for animals born in 2011. Analyses were performed using both Beagle and FImpute software. Genotype imputation accuracy was measured by concordance rate and allelic R2 between true and imputed genotypes. Results: The average concordance rate using FImpute was 0.943 and 0.921 averaged across all simulated low density panels to 50K or to 777K, respectively, in comparison with 0.927 and 0.895 using Beagle. The allelic R2 was 0.912 and 0.866 for imputation to 50K or to 777K using FImpute, respectively, and 0.890 and 0.826 using Beagle. One and two steps imputation to 777K produced averaged concordance rates of 0.806 and 0.892 and allelic R2 of 0.674 and 0.819, respectively. Imputation of low density panels to 50K, with the exception of 3K, had overall concordance rates greater than 0.940 and allelic R2 greater than 0.919. Ungenotyped animals were imputed to 50K panel with an average concordance rate of 0.950 by FImpute. Conclusion: FImpute accuracy outperformed Beagle on both imputation to 50K and to 777K. Two-step outperformed one-step imputation for imputing to 777K. Ungenotyped animals that have four or more offspring can have their 50K genotypes accurately inferred using FImpute. All low density panels, except the 3K, can be used to impute to the 50K using FImpute or Beagle with high concordance rate and allelic R2.application/pdfengBMC Genetics. London. Vol. 15, n. 157 (dez. 2014)Bovino de corteMelhoramento genetico animalReprodução animalBrafordImputation accuracyLow density panelHerefordHigh density panelAccuracy of genome-wide imputation in Braford and Hereford beef cattleEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000951773.pdf000951773.pdfTexto completo (inglês)application/pdf2728406http://www.lume.ufrgs.br/bitstream/10183/114805/1/000951773.pdf38d8a6247d203ed494315985db27a42eMD51TEXT000951773.pdf.txt000951773.pdf.txtExtracted Texttext/plain57953http://www.lume.ufrgs.br/bitstream/10183/114805/2/000951773.pdf.txte829cd6a80a19240deae31c684b68783MD52THUMBNAIL000951773.pdf.jpg000951773.pdf.jpgGenerated Thumbnailimage/jpeg2010http://www.lume.ufrgs.br/bitstream/10183/114805/3/000951773.pdf.jpg0d01f0c17957fe0c0a53fdb10d8503cdMD5310183/1148052018-10-19 10:12:49.916oai:www.lume.ufrgs.br:10183/114805Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2018-10-19T13:12:49Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
title |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
spellingShingle |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle Piccoli, Mario Luiz Bovino de corte Melhoramento genetico animal Reprodução animal Braford Imputation accuracy Low density panel Hereford High density panel |
title_short |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
title_full |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
title_fullStr |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
title_full_unstemmed |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
title_sort |
Accuracy of genome-wide imputation in Braford and Hereford beef cattle |
author |
Piccoli, Mario Luiz |
author_facet |
Piccoli, Mario Luiz Braccini Neto, José Cardoso, Fernando Flores Sargolzaei, M. Larmer, Steven G. Schenkel, Flavio Schramm |
author_role |
author |
author2 |
Braccini Neto, José Cardoso, Fernando Flores Sargolzaei, M. Larmer, Steven G. Schenkel, Flavio Schramm |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Piccoli, Mario Luiz Braccini Neto, José Cardoso, Fernando Flores Sargolzaei, M. Larmer, Steven G. Schenkel, Flavio Schramm |
dc.subject.por.fl_str_mv |
Bovino de corte Melhoramento genetico animal Reprodução animal |
topic |
Bovino de corte Melhoramento genetico animal Reprodução animal Braford Imputation accuracy Low density panel Hereford High density panel |
dc.subject.eng.fl_str_mv |
Braford Imputation accuracy Low density panel Hereford High density panel |
description |
Background: Strategies for imputing genotypes from the Illumina-Bovine3K, Illumina-BovineLD (6K), BeefLD-GGP (8K), a non-commercial-15K and IndicusLD-GGP (20K) to either Illumina-BovineSNP50 (50K) or to Illumina-BovineHD (777K) SNP panel, as well as for imputing from 50K, GGP-IndicusHD (90iK) and GGP-BeefHD (90tK) to 777K were investigated. Imputation of low density (<50K) genotypes to 777K was carried out in either one or two steps. Imputation of ungenotyped parents (n = 37 sires) with four or more offspring to the 50K panel was also assessed. There were 2,946 Braford, 664 Hereford and 88 Nellore animals, from which 71, 59 and 88 were genotyped with the 777K panel, while all others had 50K genotypes. The reference population was comprised of 2,735 animals and 175 bulls for 50K and 777K, respectively. The low density panels were simulated by masking genotypes in the 50K or 777K panel for animals born in 2011. Analyses were performed using both Beagle and FImpute software. Genotype imputation accuracy was measured by concordance rate and allelic R2 between true and imputed genotypes. Results: The average concordance rate using FImpute was 0.943 and 0.921 averaged across all simulated low density panels to 50K or to 777K, respectively, in comparison with 0.927 and 0.895 using Beagle. The allelic R2 was 0.912 and 0.866 for imputation to 50K or to 777K using FImpute, respectively, and 0.890 and 0.826 using Beagle. One and two steps imputation to 777K produced averaged concordance rates of 0.806 and 0.892 and allelic R2 of 0.674 and 0.819, respectively. Imputation of low density panels to 50K, with the exception of 3K, had overall concordance rates greater than 0.940 and allelic R2 greater than 0.919. Ungenotyped animals were imputed to 50K panel with an average concordance rate of 0.950 by FImpute. Conclusion: FImpute accuracy outperformed Beagle on both imputation to 50K and to 777K. Two-step outperformed one-step imputation for imputing to 777K. Ungenotyped animals that have four or more offspring can have their 50K genotypes accurately inferred using FImpute. All low density panels, except the 3K, can be used to impute to the 50K using FImpute or Beagle with high concordance rate and allelic R2. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2015-04-02T02:00:31Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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1471-2156 |
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000951773 |
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http://hdl.handle.net/10183/114805 |
dc.language.iso.fl_str_mv |
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dc.relation.ispartof.pt_BR.fl_str_mv |
BMC Genetics. London. Vol. 15, n. 157 (dez. 2014) |
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openAccess |
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