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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
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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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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Registro original : |
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 : |
31/08/2016 |
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Actualizado : |
05/11/2019 |
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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 : |
CALVO-SALAZAR, V.; SINGH, R. P.; HUERTA-ESPINO, J.; CRUZ-IZ QUIERDO, S.; LOBATO-ORTIZ, R.; SANDOVAL-ISLAS, S.; VARGAS-HERNÁNDEZ, M.; GERMAN, S.; SILVA, P.; BASNET, B. R.; LAN, C. X.; HERRERA-FOESSEL, S. A. |
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Afiliación : |
SILVIA ELISA GERMAN FAEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Genetic Analysis of Resistance to Leaf Rust and Yellow Rust in Spring Wheat Cultivar Kenya Kongoni. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Plant Disease, v. 99, no.1153-1160, 2015. |
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ISSN : |
0191-2917 |
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DOI : |
10.1094/PDIS- 07-14 -0718-RE |
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Idioma : |
Inglés |
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Notas : |
Article history: Accepted for publication 9 February 2015/Published Online:23 Jun 2015. |
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Contenido : |
Abstract: The Kenyan wheat (Triticum aestivum L.) ?Kenya Kongoni ?exhibits high levels of adult plant resistance (APR) to leaf rust (LR) and yellow
rust (YR). We determined the genomic regions associated with LR and YR resistance in a population of 148 recombinant inbred lines generated
from a cross between ? Avocet-YrA ?and Kenya Kongoni. Field experi-ments to characterize APR to LR and YR were conducted in four and
two Mexican or Uruguayan environments, respectively. A linkage map was constructed with 438 diversity arrays technology and 16 simple-
sequence repeat markers by JoinMap 4.1 software. Genetic analyses showed that resistance to both rusts was determined by four to five
APR genes, including Lr46/Yr29 and Sr2/Lr27/Yr30 . Quantitative trait loci (QTL) analysis indicated that pleiotropic APR loci QYLr.cim-1BL
corresponding to Lr46/Yr29 and QYLr.cim-7BL that is a putative novel QTL accounted for 5 to 57% and 12 to 35% of the phenotypic variation
for resistance to LR and YR, respectively. These loci, in combination with another three LR QTL and two YR QTL, respectively, conferred
high levels of resistance to both LR and YR in wheat under Mexican and Uruguayan environments. Among ot her detected QTL, QLr.cim-1DS,
QLr.cim-2BL, and QYLr.icm-7BL may be new loci for APR to both rusts in common wheat. |
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Thesagro : |
ENFERMEDADES DE LAS PLANTAS; PUCCINIA GRAMINIS; PUCCINIA STRIIFORMIS. |
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Asunto categoría : |
H20 Enfermedades de las plantas |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13737/1/Plant-Disease-v.-99-no.1153-1160-2015..pdf
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Marc : |
LEADER 02362naa a2200325 a 4500
001 1055482
005 2019-11-05
008 2015 bl uuuu u00u1 u #d
022 $a0191-2917
024 7 $a10.1094/PDIS- 07-14 -0718-RE$2DOI
100 1 $aCALVO-SALAZAR, V.
245 $aGenetic Analysis of Resistance to Leaf Rust and Yellow Rust in Spring Wheat Cultivar Kenya Kongoni.$h[electronic resource]
260 $c2015
500 $aArticle history: Accepted for publication 9 February 2015/Published Online:23 Jun 2015.
520 $aAbstract: The Kenyan wheat (Triticum aestivum L.) ?Kenya Kongoni ?exhibits high levels of adult plant resistance (APR) to leaf rust (LR) and yellow rust (YR). We determined the genomic regions associated with LR and YR resistance in a population of 148 recombinant inbred lines generated from a cross between ? Avocet-YrA ?and Kenya Kongoni. Field experi-ments to characterize APR to LR and YR were conducted in four and two Mexican or Uruguayan environments, respectively. A linkage map was constructed with 438 diversity arrays technology and 16 simple- sequence repeat markers by JoinMap 4.1 software. Genetic analyses showed that resistance to both rusts was determined by four to five APR genes, including Lr46/Yr29 and Sr2/Lr27/Yr30 . Quantitative trait loci (QTL) analysis indicated that pleiotropic APR loci QYLr.cim-1BL corresponding to Lr46/Yr29 and QYLr.cim-7BL that is a putative novel QTL accounted for 5 to 57% and 12 to 35% of the phenotypic variation for resistance to LR and YR, respectively. These loci, in combination with another three LR QTL and two YR QTL, respectively, conferred high levels of resistance to both LR and YR in wheat under Mexican and Uruguayan environments. Among ot her detected QTL, QLr.cim-1DS, QLr.cim-2BL, and QYLr.icm-7BL may be new loci for APR to both rusts in common wheat.
650 $aENFERMEDADES DE LAS PLANTAS
650 $aPUCCINIA GRAMINIS
650 $aPUCCINIA STRIIFORMIS
700 1 $aSINGH, R. P.
700 1 $aHUERTA-ESPINO, J.
700 1 $aCRUZ-IZ QUIERDO, S.
700 1 $aLOBATO-ORTIZ, R.
700 1 $aSANDOVAL-ISLAS, S.
700 1 $aVARGAS-HERNÁNDEZ, M.
700 1 $aGERMAN, S.
700 1 $aSILVA, P.
700 1 $aBASNET, B. R.
700 1 $aLAN, C. X.
700 1 $aHERRERA-FOESSEL, S. A.
773 $tPlant Disease$gv. 99, no.1153-1160, 2015.
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