| |
|
|
| Registros recuperados : 2 | |
| 1. |  | BELANCHE, A.; HRISTOV, A.; VAN LINGEN, H.; DENMAN, S. E.; KEBREAB, E.; SCHWARM, A.; KREUZER, M.; NIU, M.; EUGÈNE, M.; NIDERKORN, V.; MARTIN, C.; ARCHIMÈDE, H.; MCGEE, M.; REYNOLDS, C. K.; CROMPTON, L. A.; BAYAT, A. R.; YU, Z.; BANNINK, A.; DIJKSTRA, J.; CHAVES, A. V.; CLARK, H.; MUETZEL, S.; LIND, V.; MOORBY, J. M.; ROOKE, J. A.; AUBRY, A.; ANTEZANA, W.; WANG, M.; HEGARTY, R.; HUTTON O. V.; HILL, J.; VERCOE, P. E.; SAVIAN, J.V.; ABDALLA, A. L.; SOLTAN, Y. A.; GOMES MONTEIRO, A. L.; KU-VERA, J. C.; JAURENA, G.; GÓMEZ-BRAVO, C. A.; MAYORGA, O. L.; CONGIO, G. F. S.; YÁÑEZ-RUIZ, D. R. Prediction of enteric methane emissions by sheep using an intercontinental database. Journal of Cleaner Production, 15 January 2023, Volume 384, 135523. OPEN ACCESS. doi: https://doi.org/10.1016/j.jclepro.2022.135523 Article history: Received 24 May 2022; Received in revised form 11 November 2022; Accepted 3 December 2022; Available online 9 December 2022.
Corresponding author: Belanche, A.; Department of Animal Production and Food Sciences, IA2,...| Biblioteca(s): INIA Las Brujas; INIA Treinta y Tres. |
|    |
| 2. | | SOUZA CONGIO, G. F. DE; BANNINK, A.; MAYORGA, MOGOLLÓN, O. L.; NICOLOV HRISTOV, A.; JAURENA, G.; GONDA, H.; GERE, J. I.; CERÓN-CUCCHI, M.E.; ORTIZ-CHURA, A.; TIERI, M.P.; HERNÁNDEZ, O.; RICCI, P.; JULIARENA, M.P.; LOMBARDI, B.; ABDALLA, A.L.; ABDALLA-FILHO, A.L.; BERNDT, A.; ANCHAO OLIVEIRA, P. P.; HENRIQUE, F. L.; GOMEZ MONTEIRO, A.L.; BORGES, L. I.; RIBEIRO-FILHO, H.M.N.; RIBEIRO PEREIRA, L.G.; RIBEIRO TOMICH, T.; MAGALHAES CAMPOS, M.; SAMARINI MACHADO, F.; MARCONDES, M. I.; ZERLOTTI MERCADANTE, M. E.; SANNOMIYA SAKAMOTO, L.; GALVAO ALBUQUERQUE, L.; FACCIO CARVALHO, P. C. DE; ROSSETTO, J.; SAVIAN, J.V.; MAZZA RODRIGUES, P. H.; PERNA JÚNIOR, F.; MOREIRA, T.S.; MAURÍCIO, R. M.; PACHECO RODRIGUES, J.P.; CRUZ BORGES, A.L. DA C.; REIS E SILVA, R.; FERREIRA LAGE, H.; ANDRADE REIS, R.; RUGGIERI, A.C.; CARDOSO, A. DA SILVA; SILVA, S. CARNEIRO DA; BARBOSA CHIAVEGATO, M.; VALADARES-FILHO, S. DE CAMPOS; SILVA, F. A. DE SALES; ZANETTI, D.; BERCHIELLI, T.T.; DUARTE MESSANA, J.; MUÑOZ, C.; ARIZA-NIETO, C.J.; SIERRA-ALARCÓN, L.I.; GUALDRÓN-DUARTE, L.B.; MESTRA-VARGAS, L.I.; MOLINA-BOTERO, I. C.; BARAHONA-ROSALES, R.; ARANGO, J.; GAVIRIA-URIBE, X.; GIRALDO VALDERRAMA, L.A.; ROSERO-NOGUERA, J.R.; POSADA-OCHOA, S.L.; ABARCA-MONGE, SERGIO; SOTO-BLANCO, R.; KU-VERA, J.C.; JIMÉNEZ-OCAMPO, R.; FLORES-SANTIAGO, E. DEL J.; CASTELÁN-ORTEGA, O.A.; VÁZQUEZ-CARRILLO, M.F.; BENAOUDA, M.; GÓMEZ-BRAVO, C. A.; ALVARADO BOLOVICH, V.I.; DÍAZ CÉSPEDES, M.A.; ASTIGARRAGA, L. Enteric methane mitigation strategies for ruminant livestock systems in the Latin America and Caribbean region: a meta-analysis. Journal of Cleaner Production. 2021. v. 312, art. 127693, 13 p. Doi: https://doi.org/10.1016/j.jclepro.2021.127693 Article history: Receiived 22 December 2020; Received in revised form 24 April 2021; Accepted 25 May 2021. Available online 30 May 2021.
Latin America Methane Project Collaborators está integrada por 71 investigadores en este artículo.| Biblioteca(s): INIA Treinta y Tres. |
|  |
| Registros recuperados : 2 | |
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA La Estanzuela. |
|
Fecha actual : |
22/10/2021 |
|
Actualizado : |
22/10/2021 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
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 |
|
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. |
|
Título : |
Assessing the accuracy of imputation in the Gyr breed using different SNP panels. |
|
Fecha de publicación : |
2021 |
|
Fuente / Imprenta : |
Genome, 2021 Oct, Volume 64 , Issue 10, pag 893-899. Open Acces. Doi: https://doi.org/10.1139/gen-2020-0081 |
|
DOI : |
10.1139/gen-2020-0081 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received 22 May 2020./ Accepted 17 April 2021. Corresponding author: Alejandra Maria Toro Ospina (email: toroospina92@gmail.com) |
|
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 |
|
Palabras claves : |
Genomic analysis; Imputation accuracy; Tropical breeds. |
|
Asunto categoría : |
L10 Genética y mejoramiento animal |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16078/1/Genome-64.-p.-893899-2021.pdf
|
|
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
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA La Estanzuela (LE) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
