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| Registros recuperados : 15 | |
| 2. |  | SANTOS, D. J.; BOISON, S. A.; UTSUNOMIYA, Y. T.; PEIXOTO, M. G. C. D.; TONHATI, H.; SÖLKNER, J.; SILVA, M. V. G. B. An approach to genomic analysis of longitudinal data using random regression In: WORLD CONGRESS ON GENETICS APPLIED TO LIVESTOCK PRODUCTION, 10., 2014, Vancouver. Proceedings... Champaign: ASAS, 2014. 3 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 3. | | SANTIAGO, G. G.; SIQUEIRA, F.; BOISON, S. A.; CARDOSO, F. F.; REGITANO, L. C. de A.; TORRES JUNIOR, R. A. de A. Acurácia de imputação de genótipos para estudos de associação genômica em bovinos da raça Canchim. In: JORNADA CIENTÍFICA EMBRAPA GADO DE CORTE, 10., 2014, Campo Grande, MS. [Anais da..]. Campo Grande, MS: Embrapa Gado de Corte, 2014. p. 52-53. 2 p. (Embrapa Gado de Corte. Documentos, 208). Comissão organizadora: Grácia Maria Soares Rosinha, Alexandra Rocha de Oliveir, Rodrigo Carvalho Alva.| Biblioteca(s): Embrapa Gado de Corte. |
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| 4. | | MÉSZÁROS, G.; BOISON, S. A.; O'BRIEN, A. M. P.; FERENCAKOVIC, M.; CURIK, I.; SILVA, M. V. G. B.; UTSONOMIYA, Y. T.; GARCIA, J. F.; SÖLKNER, J. Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle. Frontiers in Genetics, v. 6, p. 192-203, 2015. Article 173.| Biblioteca(s): Embrapa Gado de Leite. |
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| 5. | | BOISON, S. A.; SANTOS, D. J. A. dos; GARCIA, J. F.; SÖLKNER, J.; PEIXOTO, M. G. C. D.; SILVA, M. V. G. B. Genomic Evaluation Using 50K and Imputed HD Genotypes in Guzera (Bos indicus) Breed. In: WORLD CONGRESS OF GENETICS APPLIED TO LIVESTOCK PRODUCTION, 10., 2014, Vancouver. Proceedings... Champaign: American Society of Animal Science, 2014. 3 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 6. | | BOISON, S. A.; NEVES, H. H. R.; O'BRIEN, A. M. P.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; SILVA, M. V. G. B.; SÖLKNER, J.; GARCIA, J. F. Imputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed. Livestock Science, v. 166, p. 176-189, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 7. | | BOISON, S. A.; UTSUNOMIYA, A. T. H.; SANTOS, D. J. A.; NEVES, H. H. R.; MÉSZÁROS, G.; CARVALHEIRO, R.; GARCIA, J. F.; SILVA, M. V. G. B.; SÖLKNER, J. Accuracy of genomic predictions for dairy traits in Gyr cattle (Bos indicus) Warsaw: EAAP, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 8. | | MACHADO, M. A.; UTSUNOMIYA, A. T. H.; BOISON, S. A.; SANTOS, D. J. A. dos; UTSUNOMIYA, Y. T.; FONSECA, R. da; SÖLKNER, J.; GARCIA, J. F.; VERNEQUE, R. da S.; SILVA, M. V. G. B. Genome Wide Association Study for Calving Interval in Gyr Dairy Cattle. In: WORLD CONGRESS OF GENETICS APPLIED TO LIVESTOCK PRODUCTION, 10., 2014, Vancouver. Proceedings... Champaign: American Society of Animal Science, 2014. 3 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 9. | | UTSUNOMIYA, A. T. H.; BOISON, S. A.; SANTOS, D. J. A. dos; UTSUNOMIYA, Y. T.; MACHADO, M. A.; VERNEQUE, R. da S.; SÖLKNER, J.; GARCIA, J. F.; FONSECA, R. da; SILVA, M. V. G. B. Genome Wide Scan for Age at First Calving in Gyr Dairy Cattle. In: WORLD CONGRESS OF GENETICS APPLIED TO LIVESTOCK PRODUCTION, 10., 2014, Vancouver. Proceedings... Champaign: American Society of Animal Science, 2014. 3 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 10. | | UTSUNOMIYA, A. T. H.; SANTOS, D. J. A.; BOISON, S. A.; UTSUNOMIYA, Y. T.; MILANESI, M.; BICKHART, D. M.; AJMONE-MARSAN, P.; SOLKNER, J.; GARCIA, J. F.; FONSECA, R. da; SILVA, M. V. G. B. Revealing misassembled segments in the bovine reference genome by high resolution linkage disequilibrium scan. BMC Genomics, v. 17, article 705, 2016.| Biblioteca(s): Embrapa Gado de Leite. |
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| 11. | | SILVA, M. V. G. B.; SANTOS, D. J. A. dos; BOISON, S. A.; UTSUNOMIYA, A. T. H.; CARMO, A. S.; SONSTEGARD, T. S.; COLE, J. B.; TASSELL, C. P. V. The development of genomics applied to dairy breeding. Livestock Science, v. 166, p. 66-75, 2014.| Biblioteca(s): Embrapa Gado de Leite. |
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| 12. | | BOISON, S. A.; SANTOS, D. J. A.; UTSONOMIYA, A. H. T.; CARVALHEIRO, R.; NEVES, H. H. R.; O'BRIEN, A. M. P.; GARCIA, J. F.; SÖLKNER, J.; SILVA, M. V. G. B. Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips. Journal of Dairy Science, v. 98, n. 7, p. 4969-4989, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 13. | | BOISON, S. A.; UTSUNOMIYA, A. T. H.; SANTOS, D. J. A.; NEVES, H. H. R.; CARVALHEIRO, R.; MÉSZÁROS, G.; UTSUNOMIYA, Y. T.; CARMO, A. S. do; VERNEQUE, R. da S.; MACHADO, M. A.; PANETTO, J. C. do C.; GARCIA, J. F.; SÖLKNER, J.; SILVA, M. V. G. B. Accuracy of genomic predictions in Gyr (Bos indicus) dairy cattle. Journal of Dairy Science, v. 100, n. 7, p. 5479-5490, 2017.| Biblioteca(s): Embrapa Gado de Leite. |
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| 14. | | O'BRIEN, A. M. P.; HÖLLER, D.; BOISON, S. A.; MILANESI, M.; BOMBA, L.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; NEVES, H. H. R.; SILVA, M. V. G. B.; VAN TASSEL, C. P.; SOSTENGARD, T. S.; MÉSZÁROS, G.; AJMONE-MARSAN, P.; GARCIA, J. F.; SÖLKNER, J. Low levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations. Genetics Selection Evolution, v. 47, article 31, 2015.| Biblioteca(s): Embrapa Gado de Leite. |
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| 15. | | SÖLKNER, J.; PEREZ O'BRIEN, A. M.; HÖLLER, D.; BOISON, S. A.; MILANESI, M.; BOMBA, L.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; NEVES, H. H. R.; SILVA, M. V. G. B.; VAN TASSEL, C. P.; SOSTENGARD, T. S.; MÉSZÁROS, G.; AJMONE-MARSAN, P.; GARCIA, J. F. Zebuines kerngenom und taurine Mitochondrien: admixtur von Nelore, der größten brasilianischen rinderrasse. Nova Acta Leopoldina, NF 119, n. 404, p. 69-75, 2016.| Biblioteca(s): Embrapa Gado de Leite. |
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| Registros recuperados : 15 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
01/12/2014 |
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Data da última atualização: |
05/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
BOISON, S. A.; NEVES, H. H. R.; O'BRIEN, A. M. P.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; SILVA, M. V. G. B.; SÖLKNER, J.; GARCIA, J. F. |
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Afiliação: |
S.A. BOISON, Univ Nat Resources & Life Sci. BOKU; H.H.R. NEVES, UNESP; A.M. PÉREZ O?BRIEN, Univ Nat Resources & Life Sci. BOKU; Y.T. UTSUNOMIYA, UNESP; R. CARVALHEIRO, UNESP; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; J. SÖLKNER, Univ Nat Resources & Life Sci. BOKU; J. F. GARCIA, UNESP. |
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Título: |
Imputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Livestock Science, v. 166, p. 176-189, 2014. |
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DOI: |
https://doi.org/10.1016/j.livsci.2014.05.033 |
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Idioma: |
Inglês |
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Conteúdo: |
This study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero. In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably. MenosThis study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation alg... Mostrar Tudo |
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Palavras-Chave: |
FImpute; Imputation; MaCH; MERLIN; Non(un)-genotyped. |
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Thesaurus NAL: |
Beagle. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
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001 2001135
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008 2014 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.livsci.2014.05.033$2DOI
100 1 $aBOISON, S. A.
245 $aImputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed.$h[electronic resource]
260 $c2014
520 $aThis study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero. In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably.
650 $aBeagle
653 $aFImpute
653 $aImputation
653 $aMaCH
653 $aMERLIN
653 $aNon(un)-genotyped
700 1 $aNEVES, H. H. R.
700 1 $aO'BRIEN, A. M. P.
700 1 $aUTSUNOMIYA, Y. T.
700 1 $aCARVALHEIRO, R.
700 1 $aSILVA, M. V. G. B.
700 1 $aSÖLKNER, J.
700 1 $aGARCIA, J. F.
773 $tLivestock Science$gv. 166, p. 176-189, 2014.
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