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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
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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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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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
29/03/2021 |
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Actualizado : |
31/03/2021 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
RAVAGNOLO, O.; AGUILAR, I.; CROWLEY, J. J.; PRAVIA, M.I.; LEMA, O.M.; MACEDO, F.; SCOTT, S.; NAVAJAS, E. |
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Afiliación : |
OLGA RAVAGNOLO GUMILA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; J.J. CROWLEY, Canadian Beef Breeds Council, Calgary, Alberta, Canada; Livestock Gentec, University of Alberta, Edmonton, Canada; MARIA ISABEL PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSCAR MARIO LEMA QUEIJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO LIBER MACEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; S. SCOTT, Canadian Hereford Association, Calgary, Alberta, Canada; ELLY ANA NAVAJAS VALENTINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Accuracy of genomic predictions of residual feed intake in Hereford with Uruguayan and Canadian training populations. |
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Complemento del título : |
Volume: Electronic Poster Session - Species - Bovine (beef) 1, p. 723. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. |
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Páginas : |
6 p. |
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Idioma : |
Inglés |
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Contenido : |
SUMMARY.
Dataset from Canadian and Uruguayan training populations were joined to analyse improvement of predictability for RFI. Three training populations where defined, URY (only data from Uruguay, 731), CAN (only data from Canada, 1168) and TOTAL (joint dataset, 1899). Genealogical information from the two countries was merged based on the international identification and cross reference list, with the pedigree file resulting in 17289 animals.
The demands for livestock products are increasing, and beef production seems not to be an exception. This implies a challenge to beef production that has to increase productivity without increasing area or environmental footprint (a finite commodity), increasing costs (competing in disadvantage with chicken and pigs) or lowering product quality (its main advantage).
The objective of present study was to compare the accuracy of genomic predictions for RFI based on national and bi-national training populations. |
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Palabras claves : |
Accuracy; Beef cattle; BEEF PRODUCTION; Feed efficiency; Genomic selection; Training population. |
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Thesagro : |
ALIMENTACION ANIMAL; GANADO DE CARNE. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15398/1/accuracy-genomic-predictions-residual-feed-intake-hereford-uruguayan-and-canadian-training.pdf
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Marc : |
LEADER 01939nam a2200301 a 4500
001 1061876
005 2021-03-31
008 2018 bl uuuu u01u1 u #d
100 1 $aRAVAGNOLO, O.
245 $aAccuracy of genomic predictions of residual feed intake in Hereford with Uruguayan and Canadian training populations.$h[electronic resource]
260 $aIn: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018.$c2018
300 $a6 p.
520 $aSUMMARY. Dataset from Canadian and Uruguayan training populations were joined to analyse improvement of predictability for RFI. Three training populations where defined, URY (only data from Uruguay, 731), CAN (only data from Canada, 1168) and TOTAL (joint dataset, 1899). Genealogical information from the two countries was merged based on the international identification and cross reference list, with the pedigree file resulting in 17289 animals. The demands for livestock products are increasing, and beef production seems not to be an exception. This implies a challenge to beef production that has to increase productivity without increasing area or environmental footprint (a finite commodity), increasing costs (competing in disadvantage with chicken and pigs) or lowering product quality (its main advantage). The objective of present study was to compare the accuracy of genomic predictions for RFI based on national and bi-national training populations.
650 $aALIMENTACION ANIMAL
650 $aGANADO DE CARNE
653 $aAccuracy
653 $aBeef cattle
653 $aBEEF PRODUCTION
653 $aFeed efficiency
653 $aGenomic selection
653 $aTraining population
700 1 $aAGUILAR, I.
700 1 $aCROWLEY, J. J.
700 1 $aPRAVIA, M.I.
700 1 $aLEMA, O.M.
700 1 $aMACEDO, F.
700 1 $aSCOTT, S.
700 1 $aNAVAJAS, E.
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