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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
28/09/2020 |
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Actualizado : |
28/09/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
SILVA, R.P.; ESPIGOLAN, R.; BERTON, M.P.; STAFUZZA, N.B.; SANTOS, F.S.; NEGREIROS, M.P.; SCHUCHMANN, R.K.; RODRIGUEZ, J.D.; LÔBO, R.B.; BANCHERO, G.; PEREIRA, A.S.C.; BERGMANN, J.A.G.; BALDI, F. |
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Afiliación : |
ROSIANE P. SILVA, Department of Veterinary Medicine, College of Animal Science and Food Engineer, University of São Paulo (USP), 225 Duque de Caxias Norte Avenue, Jardim Elite, 13635-900, Pirassununga/SP, Brazil.; RAFAEL ESPIGOLAN, Department of Veterinary Medicine, College of Animal Science and Food Engineer, University of São Paulo (USP), 225 Duque de Caxias Norte Avenue, Jardim Elite, 13635-900, Pirassununga/SP, Brazil.; MARIANA PIATTO BERTON, Department of Animal Science, College of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Professor Paulo Donato Castellane s/n, 14884-900, Jaboticabal/SP, Brazil.; NEDENIA STAFUZZA, Department of Animal Science, College of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Professor Paulo Donato Castellane s/n, 14884-900, Jaboticabal/SP, Brazil.; F. S. SANTOS, Department of Veterinary Medicine, College of Animal Science and Food Engineer, University of São Paulo (USP), 225 Duque de Caxias Norte Avenue, Jardim Elite, 13635-900, Pirassununga/SP, Brazil.; Department of Veterinary Medicine, College of Animal Science and Food Engineer, University of São Paulo (USP), 225 Duque de Caxias Norte Avenue, Jardim Elite, 13635-900, Pirassununga/SP, Brazil.; Department of Animal Science, College of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Professor Paulo Donato Castellane s/n, 14884-900, Jaboticabal/SP, Brazil.; Department of Animal Science, College of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Professor Paulo Donato Castellane s/n, 14884-900, Jaboticabal/SP, Brazil.; RAYSILDO B. LÔBO, Nacional Association of Breeders and Researchers (ANCP), 463 João Godoy Street, Jardim América, 14020-230, Ribeirão Preto/SP, Brazil.; GEORGGET ELIZABETH BANCHERO HUNZIKER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANGÉLICA SIMONE CRAVO PEREIRA, Department of Veterinary Medicine, College of Animal Science and Food Engineer, University of São Paulo (USP), 225 Duque de Caxias Norte Avenue, Jardim Elite, 13635-900, Pirassununga/SP, Brazil.; JOSÉ AURÉLIO GARCIA BERGMANN, Department of Animal Science, Minas Gerais Federal University (UFMG), Escola de Veterinária da UFMG, Pampulha, 31270-901, Caixa Postal 567, Belo Horizonte/MG, Brazil.; FERNANDO BALDI, Department of Animal Science, College of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Professor Paulo Donato Castellane s/n, 14884-900, Jaboticabal/SP, Brazil. |
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Título : |
Genetic parameters and genomic regions associated with calving ease in primiparous Nellore heifers. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Livestock Science, October 2020, Volume 240, Article number 104183. Doi: https://doi.org/10.1016/j.livsci.2020.104183 |
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DOI : |
10.1016/j.livsci.2020.104183 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 19 February 2020 /Received in revised form 25 June 2020 /Accepted 1 August 2020/Available online 02 August 2020. /Corresponding author: E-mail address: fernandobaldiuy@gmail.com (F. Baldi). This work was supported by the São Paulo Research Foundation -
FAPESP through grant #2018/18921-9, grant #2017/10493-5 and grant #2019/10438-0 for authors Rafael Espigolan, Mariana P. Berton
and Nedenia B. Stafuzza, respectively. |
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Contenido : |
ABSTRACT: The aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). A pedigree structure containing the identification of the animal's sire and dam was used, with the relationship matrix comprising a total of 6,511
animals. Genotypic data from 1,201 animals were obtained using low-density panel (Clarifide Nelore 3.1) encompassing over 29,001 single nucleotide polymorphisms (SNP) markers. A threshold sire-maternal grandsire model (S-MGS) was used to estimate the genetic parameters, which included sire, maternal grandsire and residual effects as random effects and the fixed effects of contemporary groups (farm and year of calving, sex) and birth weight of the calf as covariable (linear effect). Genomic breeding values were estimated using an animal model with the direct and maternal genetic variances which were previously obtained by means of a S-MGS threshold model. The direct and maternal heritability estimates for CE were obtained considering the covariance of direct and maternal effects fixed as zero. Regions that accounted for more than 0.5% of the additive genetic variance were used. The direct and maternal heritability estimates for CE were low (0.18) and moderate (0.39)
respectively, indicating that genetic progress for this trait is feasible, and so, it would respond favorably to direct selection. Genes identified within the significant windows, such as CA8, FAM110B, TOX, ARID1A, RBM15, HSF1 and PLAG1 were found to be related with maternal and direct effects on CE. Gene enrichment analysis revealed processes that might directly influence fetal processes involved in female pregnancy and stress response. These results should help to better understand the genetic and physiological mechanisms regulating placenta development and fetal development, and this information might be useful for future genomic studies in Nellore cattle. MenosABSTRACT: The aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). A pedigree structure containing the identification of the animal's sire and dam was used, with the relationship matrix comprising a total of 6,511
animals. Genotypic data from 1,201 animals were obtained using low-density panel (Clarifide Nelore 3.1) encompassing over 29,001 single nucleotide polymorphisms (SNP) markers. A threshold sire-maternal grandsire model (S-MGS) was used to estimate the genetic parameters, which included sire, maternal grandsire and residual effects as random effects and the fixed effects of contemporary groups (farm and year of calving, sex) and birth weight of the calf as covariable (linear effect). Genomic breeding values were estimated using an animal model with the direct and maternal genetic variances which were previously obtained by means of a S-MGS threshold model. The direct and maternal heritability estimates for CE were obtained considering the covariance of direct and maternal effects fixed as zero. Regions that accounted for more than 0.5% of the additive genetic variance were used. The direct and maternal heritabili... Presentar Todo |
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Palabras claves : |
BEEF CATTLE; CANDIDATE GENES; DISTOCIA; FUNCTIONAL ANALYSES; REPRODUCTION TRAITS. |
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Thesagro : |
GANADO VACUNO. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
LEADER 03747naa a2200361 a 4500
001 1061351
005 2020-09-28
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1016/j.livsci.2020.104183$2DOI
100 1 $aSILVA, R.P.
245 $aGenetic parameters and genomic regions associated with calving ease in primiparous Nellore heifers.$h[electronic resource]
260 $c2020
500 $aArticle history: Received 19 February 2020 /Received in revised form 25 June 2020 /Accepted 1 August 2020/Available online 02 August 2020. /Corresponding author: E-mail address: fernandobaldiuy@gmail.com (F. Baldi). This work was supported by the São Paulo Research Foundation - FAPESP through grant #2018/18921-9, grant #2017/10493-5 and grant #2019/10438-0 for authors Rafael Espigolan, Mariana P. Berton and Nedenia B. Stafuzza, respectively.
520 $aABSTRACT: The aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). A pedigree structure containing the identification of the animal's sire and dam was used, with the relationship matrix comprising a total of 6,511 animals. Genotypic data from 1,201 animals were obtained using low-density panel (Clarifide Nelore 3.1) encompassing over 29,001 single nucleotide polymorphisms (SNP) markers. A threshold sire-maternal grandsire model (S-MGS) was used to estimate the genetic parameters, which included sire, maternal grandsire and residual effects as random effects and the fixed effects of contemporary groups (farm and year of calving, sex) and birth weight of the calf as covariable (linear effect). Genomic breeding values were estimated using an animal model with the direct and maternal genetic variances which were previously obtained by means of a S-MGS threshold model. The direct and maternal heritability estimates for CE were obtained considering the covariance of direct and maternal effects fixed as zero. Regions that accounted for more than 0.5% of the additive genetic variance were used. The direct and maternal heritability estimates for CE were low (0.18) and moderate (0.39) respectively, indicating that genetic progress for this trait is feasible, and so, it would respond favorably to direct selection. Genes identified within the significant windows, such as CA8, FAM110B, TOX, ARID1A, RBM15, HSF1 and PLAG1 were found to be related with maternal and direct effects on CE. Gene enrichment analysis revealed processes that might directly influence fetal processes involved in female pregnancy and stress response. These results should help to better understand the genetic and physiological mechanisms regulating placenta development and fetal development, and this information might be useful for future genomic studies in Nellore cattle.
650 $aGANADO VACUNO
653 $aBEEF CATTLE
653 $aCANDIDATE GENES
653 $aDISTOCIA
653 $aFUNCTIONAL ANALYSES
653 $aREPRODUCTION TRAITS
700 1 $aESPIGOLAN, R.
700 1 $aBERTON, M.P.
700 1 $aSTAFUZZA, N.B.
700 1 $aSANTOS, F.S.
700 1 $aNEGREIROS, M.P.
700 1 $aSCHUCHMANN, R.K.
700 1 $aRODRIGUEZ, J.D.
700 1 $aLÔBO, R.B.
700 1 $aBANCHERO, G.
700 1 $aPEREIRA, A.S.C.
700 1 $aBERGMANN, J.A.G.
700 1 $aBALDI, F.
773 $tLivestock Science, October 2020, Volume 240, Article number 104183. Doi: https://doi.org/10.1016/j.livsci.2020.104183
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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 : |
08/03/2022 |
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Actualizado : |
02/12/2022 |
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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 : |
RODRÍGUEZ NEIRA, J.D.; PERIPOLLI, E.; DE NEGREIROS M.P.M.; ESPIGOLAN, R.; LÓPEZ-CORREA R.; AGUILAR, I.; LOBO R.B.; BALDI, F. |
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Afiliación : |
JUAN DIEGO RODRIGUEZ NEIRA, Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; ELISA PERIPOLLI, Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; MARIA PAULA MARINHO DE NEGREIROS, Departamento de Medicina Veterinária, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo (Usp), Pirassununga, 13535-900, Brazil; RAFAEL ESPIGOLAN, Departamento de Medicina Veterinária, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo (Usp), Pirassununga, 13535-900, Brazil; RODRIGO LÓPEZ-CORREA, Departamento de Genética y Mejoramiento Animal, Facultad de Veterinaria, Universidad de La República, Montevideo, Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RAYSILDO B. LOBO, Associação Nacional de Criadores e Pesquisadores (ANCP), Ribeirão Preto, Brazil; FERNANDO BALDI, Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil. |
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Título : |
Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Journal of Applied Genetics, 2022, Volume 63, Issue 2, pages 389-400. doi: https://doi.org/10.1007/s13353-022-00685-0 |
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ISSN : |
1234-1983 |
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DOI : |
10.1007/s13353-022-00685-0 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 26 September 2021; Revised 25 January 2022; Accepted 2 February 2022.
Corresponding author: Rodriguez Neira, J.D.; Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, Brazil; email:juan.diego@unesp.br -- This study was supported in conjunction by Programa Estudantes Convênio de Pós-Graduação da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (PECPG-CAPES, call no. 32/2017); the National Association of Breeders and Researchers (ANCP), the Programa Escala de Estudiantes de Pós-Graduação of Asociación de Universidades GRUPO MONTEVIDEO (PEEPg/AUGM-2019); the Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias (FCAV/Unesp); the Universidad de la Republica, Facultad de Veterinaria (UdelaR), Departamento de Genética y Mejoramiento Animal; and the Instituto Nacional de Investigación Agropecuaria of Uruguay (INIA). |
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Contenido : |
ABSTRACT. - This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.
© 2022, The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences. MenosABSTRACT. - This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10... Presentar Todo |
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Palabras claves : |
Accuracy; Beef cattle; Genomic selection; Inflation; Minor allele frequency; SNP arrays. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 03798naa a2200313 a 4500
001 1062807
005 2022-12-02
008 2022 bl uuuu u00u1 u #d
022 $a1234-1983
024 7 $a10.1007/s13353-022-00685-0$2DOI
100 1 $aRODRÍGUEZ NEIRA, J.D.
245 $aPrediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 26 September 2021; Revised 25 January 2022; Accepted 2 February 2022. Corresponding author: Rodriguez Neira, J.D.; Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (Unesp), Jaboticabal, Brazil; email:juan.diego@unesp.br -- This study was supported in conjunction by Programa Estudantes Convênio de Pós-Graduação da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (PECPG-CAPES, call no. 32/2017); the National Association of Breeders and Researchers (ANCP), the Programa Escala de Estudiantes de Pós-Graduação of Asociación de Universidades GRUPO MONTEVIDEO (PEEPg/AUGM-2019); the Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias (FCAV/Unesp); the Universidad de la Republica, Facultad de Veterinaria (UdelaR), Departamento de Genética y Mejoramiento Animal; and the Instituto Nacional de Investigación Agropecuaria of Uruguay (INIA).
520 $aABSTRACT. - This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection. © 2022, The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.
653 $aAccuracy
653 $aBeef cattle
653 $aGenomic selection
653 $aInflation
653 $aMinor allele frequency
653 $aSNP arrays
700 1 $aPERIPOLLI, E.
700 1 $aDE NEGREIROS M.P.M.
700 1 $aESPIGOLAN, R.
700 1 $aLÓPEZ-CORREA R.
700 1 $aAGUILAR, I.
700 1 $aLOBO R.B.
700 1 $aBALDI, F.
773 $tJournal of Applied Genetics, 2022, Volume 63, Issue 2, pages 389-400. doi: https://doi.org/10.1007/s13353-022-00685-0
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