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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
27/01/2020 |
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Actualizado : |
29/05/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
SILVA, D.A.; COSTA, C.N.; SILVA, A.A.; SILVA, H.T.; LOPES, P.S.; SILVA, F.F.; VERONEZE, R.; THOMPSON, G.; AGUILAR, I.; CARVALHEIRA, J. |
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Afiliación : |
DELVAN ALVES SILVA, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; CLAUDIO NÁPOLIS COSTA, Embrapa Dairy Cattle, Juiz de Fora, Brazil; ALESSANDRA ALVES SILVA, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; HUGO TEIXEIRA SILVA, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; PAULO SÁVIO LOPES, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; FABYANO FONSECA SILVA, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; RENATA VERONEZE, Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Brazil; GERTRUDE THOMPSON, Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão, Portugal; Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Vairão, Portugal; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JÚLIO CARVALHEIRA, Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão, Portugal; Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Vairão, Portugal. |
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Título : |
Autoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 1 May 2020, Volume 137, Issue 3, Pages 305-315. Doi: https://doi.org/10.1111/jbg.12459 |
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ISSN : |
0931-2668 |
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DOI : |
10.1111/jbg.12459 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 10 July 2019 / Revised: 31 October 2019 / Accepted: 3 November 2019 / First published: 08 December 2019.
Funding information: The authors acknowledge the Brazilian Holstein Cattle Breeders Association (ABCBRH) for providing data for this study. This study was partially financed by Coordination for the Improvement of Higher Education Personnel and Portuguese National Funding Agency for Science, Research and Technology (CAPES/FCT, nº 99999.008462/2014‐03 and 88887.125450/2016‐00), and National Council of Technological and Scientific Development (CNPq 465377/2014‐9 ‐ PROGRAMA INCT and CNPq 142467/20154). |
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Contenido : |
ABSTRACT.
Autoregressive (AR) and random regression (RR) models were fitted to test-day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and −0.019 (−0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and −0.022 (−0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder.
© 2019 Blackwell Verlag GmbH |
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Palabras claves : |
Autoregression; Dairy cattle; Legendre polynomials; Random regression. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 03092naa a2200313 a 4500
001 1060695
005 2020-05-29
008 2020 bl uuuu u00u1 u #d
022 $a0931-2668
024 7 $a10.1111/jbg.12459$2DOI
100 1 $aSILVA, D.A.
245 $aAutoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle.$h[electronic resource]
260 $c2020
500 $aArticle history: Received: 10 July 2019 / Revised: 31 October 2019 / Accepted: 3 November 2019 / First published: 08 December 2019. Funding information: The authors acknowledge the Brazilian Holstein Cattle Breeders Association (ABCBRH) for providing data for this study. This study was partially financed by Coordination for the Improvement of Higher Education Personnel and Portuguese National Funding Agency for Science, Research and Technology (CAPES/FCT, nº 99999.008462/2014‐03 and 88887.125450/2016‐00), and National Council of Technological and Scientific Development (CNPq 465377/2014‐9 ‐ PROGRAMA INCT and CNPq 142467/20154).
520 $aABSTRACT. Autoregressive (AR) and random regression (RR) models were fitted to test-day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and −0.019 (−0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and −0.022 (−0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder. © 2019 Blackwell Verlag GmbH
653 $aAutoregression
653 $aDairy cattle
653 $aLegendre polynomials
653 $aRandom regression
700 1 $aCOSTA, C.N.
700 1 $aSILVA, A.A.
700 1 $aSILVA, H.T.
700 1 $aLOPES, P.S.
700 1 $aSILVA, F.F.
700 1 $aVERONEZE, R.
700 1 $aTHOMPSON, G.
700 1 $aAGUILAR, I.
700 1 $aCARVALHEIRA, J.
773 $tJournal of Animal Breeding and Genetics, 1 May 2020, Volume 137, Issue 3, Pages 305-315. Doi: https://doi.org/10.1111/jbg.12459
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
22/10/2021 |
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Actualizado : |
22/10/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
TORO OSPINA, A.M.; AGUILAR, I.; VARGAS DE OLIVEIRA, M.H.; CRUZ DOS SANTOS CORREIA, L. E.; VERCESI FILHO, A. E.; ALBUQUERQUE, L.G.; JOSINEUDSON AUGUSTO II DE VASCONCELOS SILVA |
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Afiliación : |
ALEJANDRA MARIA TORO OSPINA, Faculdade de Ciências Agrárias e Veterinárias - Unesp, CEP 14.884-900, Jaboticabal, São Paulo, Brasil.; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MATHEUS HENRIQUE VARGAS DE OLIVEIRA, Faculdade de Ciências Agrárias e Veterinárias - Unesp, CEP 14.884-900, Jaboticabal, São Paulo, Brasil.; LUIZ EDUARDO CRUZ DOS SANTOS CORREIA, Faculdade de Ciências Agrárias e Veterinárias - Unesp, CEP 14.884-900, Jaboticabal, São Paulo, Brasil.; ANIBAL EUGÊNIO VERCESI FILHO, Instituto de Zootecnia, CEP 13.460-000, Nova Odessa, São Paulo, Brasil.; LUCIA GALVÃO ALBUQUERQUE; VASCONCELOS SILVA, J., Faculdade de Medicina Veterinária e Zootecnia - Unesp, CEP 18.618-307 - Botucatu, São Paulo, Brasil. |
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Título : |
Assessing the accuracy of imputation in the Gyr breed using different SNP panels. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Genome, 2021 Oct, Volume 64 , Issue 10, pag 893-899. Open Acces. Doi: https://doi.org/10.1139/gen-2020-0081 |
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DOI : |
10.1139/gen-2020-0081 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 22 May 2020./ Accepted 17 April 2021. Corresponding author: Alejandra Maria Toro Ospina (email: toroospina92@gmail.com) |
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Contenido : |
Abstract: The aim of this study was to evaluate the accuracy of imputation in a Gyr population using two medium-density panels (Bos taurus - Bos indicus) and to test whether the inclusion of the Nellore breed increases the imputation accuracy in the Gyr population. The database consisted of 289 Gyr females from Brazil genotyped with the GGP Bovine LDv4 chip containing 30 000 SNPs and 158 Gyr females from Colombia genotyped with the GGP indicus chip containing 35 000 SNPs. A customized chip was created that contained the information of 9109 SNPs (9K) to test the imputation accuracy in Gyr populations; 604 Nellore animals with information of LD SNPs tested in the scenarios were included in the reference population. Four scenarios were tested:LD9K_30KGIR, LD9K_35INDGIR, LD9K_30KGIR_NEL, and LD9K_35INDGIR_NEL. Principal component analysis (PCA) was computed for the genomic matrix and sample-specific imputation accuracies were calculated using
Pearson?s correlation (CS) and the concordance rate (CR) for imputed genotypes. The results of PCA of the Colombian and Brazilian Gyr populations demonstrated the genomic relationship between the two populations. The CS and CR ranged from 0.88 to 0.94 and from 0.93 to 0.96, respectively. Among the scenarios tested,the highest CS (0.94) was observed for the LD9K_30KGIR scenario. The present results highlight the importance of the choice of chip for imputation in the Gyr breed. However, the variation in SNPs may reduce the imputation accuracy even when the chip of the Bos indicus subspecies is used.
Résumé : Le but de cette étude était d?évaluer la justesse de l?imputation au sein d?une population de bovins de race Gir à partir de deux puces de génotypage de densité moyenne (Bos taurus ? Bos indicus) et de déterminer si l?inclusion de la race Nellore accroissait la précision de l?imputation chez la population de Girs. La base de données comprenait 289 femelles du Brésil génotypées avec la puce GGP Bovine LDv4, laquelle compte 30 000 SNP, et 158 femelles de Colombie génotypées avec la puce GGP indicus, laquelle compte 35 000 SNP. Une puce sur
mesure totalisant 9109 SNP (9K) a été produite pour mesurer la justesse de l?imputation chez les populations de Girs. De plus, 604 bovins de race Nellore fournissant de l?information sur le LD des SNP testés ont été inclus dans la population de référence. Quatre scénarios ont été testés : LD9K_30KGIR, LD9K_35INDGIR,LD9K_30KGIR_NEL et LD9K_35INDGIR_NEL. Une analyse en composantes principales (PCA) a été réalisée à l?aide de la matrice génomique, la justesse de l?imputation pour chaque échantillon a été calculée à l?aide d?une corrélation de Pearson (CS) et le taux de concordance (CR) a été calculé pour les génotypes imputés. Les résultats de l?analyse PCA chez les populations colombiennes et brésiliennes ont démontré la relation génomique entre les deux populations. Les valeurs de CS et de CR variaient respectivement entre 0,88 et 0,94, ainsi qu?entre 0,93 et 0,96. Parmi les scénarios testés, la plus forte valeur de CS (0,94) a été obtenue
dans le scénario LD9K_30KGIR. Les résultats obtenus montrent l?importance du choix de la puce en vue de ?imputation chez les bovins de race Gir. Cependant, la variation dans les SNP peut réduire la justesse de l?imputation même lorsque la puce de la sous-espèces Bos indicus est employée. MenosAbstract: The aim of this study was to evaluate the accuracy of imputation in a Gyr population using two medium-density panels (Bos taurus - Bos indicus) and to test whether the inclusion of the Nellore breed increases the imputation accuracy in the Gyr population. The database consisted of 289 Gyr females from Brazil genotyped with the GGP Bovine LDv4 chip containing 30 000 SNPs and 158 Gyr females from Colombia genotyped with the GGP indicus chip containing 35 000 SNPs. A customized chip was created that contained the information of 9109 SNPs (9K) to test the imputation accuracy in Gyr populations; 604 Nellore animals with information of LD SNPs tested in the scenarios were included in the reference population. Four scenarios were tested:LD9K_30KGIR, LD9K_35INDGIR, LD9K_30KGIR_NEL, and LD9K_35INDGIR_NEL. Principal component analysis (PCA) was computed for the genomic matrix and sample-specific imputation accuracies were calculated using
Pearson?s correlation (CS) and the concordance rate (CR) for imputed genotypes. The results of PCA of the Colombian and Brazilian Gyr populations demonstrated the genomic relationship between the two populations. The CS and CR ranged from 0.88 to 0.94 and from 0.93 to 0.96, respectively. Among the scenarios tested,the highest CS (0.94) was observed for the LD9K_30KGIR scenario. The present results highlight the importance of the choice of chip for imputation in the Gyr breed. However, the variation in SNPs may reduce the imputation accuracy... Presentar Todo |
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Palabras claves : |
Genomic analysis; Imputation accuracy; Tropical breeds. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16078/1/Genome-64.-p.-893899-2021.pdf
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Marc : |
LEADER 04403naa a2200253 a 4500
001 1062493
005 2021-10-22
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1139/gen-2020-0081$2DOI
100 1 $aTORO OSPINA, A.M.
245 $aAssessing the accuracy of imputation in the Gyr breed using different SNP panels.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 22 May 2020./ Accepted 17 April 2021. Corresponding author: Alejandra Maria Toro Ospina (email: toroospina92@gmail.com)
520 $aAbstract: The aim of this study was to evaluate the accuracy of imputation in a Gyr population using two medium-density panels (Bos taurus - Bos indicus) and to test whether the inclusion of the Nellore breed increases the imputation accuracy in the Gyr population. The database consisted of 289 Gyr females from Brazil genotyped with the GGP Bovine LDv4 chip containing 30 000 SNPs and 158 Gyr females from Colombia genotyped with the GGP indicus chip containing 35 000 SNPs. A customized chip was created that contained the information of 9109 SNPs (9K) to test the imputation accuracy in Gyr populations; 604 Nellore animals with information of LD SNPs tested in the scenarios were included in the reference population. Four scenarios were tested:LD9K_30KGIR, LD9K_35INDGIR, LD9K_30KGIR_NEL, and LD9K_35INDGIR_NEL. Principal component analysis (PCA) was computed for the genomic matrix and sample-specific imputation accuracies were calculated using Pearson?s correlation (CS) and the concordance rate (CR) for imputed genotypes. The results of PCA of the Colombian and Brazilian Gyr populations demonstrated the genomic relationship between the two populations. The CS and CR ranged from 0.88 to 0.94 and from 0.93 to 0.96, respectively. Among the scenarios tested,the highest CS (0.94) was observed for the LD9K_30KGIR scenario. The present results highlight the importance of the choice of chip for imputation in the Gyr breed. However, the variation in SNPs may reduce the imputation accuracy even when the chip of the Bos indicus subspecies is used. Résumé : Le but de cette étude était d?évaluer la justesse de l?imputation au sein d?une population de bovins de race Gir à partir de deux puces de génotypage de densité moyenne (Bos taurus ? Bos indicus) et de déterminer si l?inclusion de la race Nellore accroissait la précision de l?imputation chez la population de Girs. La base de données comprenait 289 femelles du Brésil génotypées avec la puce GGP Bovine LDv4, laquelle compte 30 000 SNP, et 158 femelles de Colombie génotypées avec la puce GGP indicus, laquelle compte 35 000 SNP. Une puce sur mesure totalisant 9109 SNP (9K) a été produite pour mesurer la justesse de l?imputation chez les populations de Girs. De plus, 604 bovins de race Nellore fournissant de l?information sur le LD des SNP testés ont été inclus dans la population de référence. Quatre scénarios ont été testés : LD9K_30KGIR, LD9K_35INDGIR,LD9K_30KGIR_NEL et LD9K_35INDGIR_NEL. Une analyse en composantes principales (PCA) a été réalisée à l?aide de la matrice génomique, la justesse de l?imputation pour chaque échantillon a été calculée à l?aide d?une corrélation de Pearson (CS) et le taux de concordance (CR) a été calculé pour les génotypes imputés. Les résultats de l?analyse PCA chez les populations colombiennes et brésiliennes ont démontré la relation génomique entre les deux populations. Les valeurs de CS et de CR variaient respectivement entre 0,88 et 0,94, ainsi qu?entre 0,93 et 0,96. Parmi les scénarios testés, la plus forte valeur de CS (0,94) a été obtenue dans le scénario LD9K_30KGIR. Les résultats obtenus montrent l?importance du choix de la puce en vue de ?imputation chez les bovins de race Gir. Cependant, la variation dans les SNP peut réduire la justesse de l?imputation même lorsque la puce de la sous-espèces Bos indicus est employée.
653 $aGenomic analysis
653 $aImputation accuracy
653 $aTropical breeds
700 1 $aAGUILAR, I.
700 1 $aVARGAS DE OLIVEIRA, M.H.
700 1 $aCRUZ DOS SANTOS CORREIA, L. E.
700 1 $aVERCESI FILHO, A. E.
700 1 $aALBUQUERQUE, L.G.
700 1 $aJOSINEUDSON AUGUSTO II DE VASCONCELOS SILVA
773 $tGenome, 2021 Oct, Volume 64 , Issue 10, pag 893-899. Open Acces. Doi: https://doi.org/10.1139/gen-2020-0081
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