| |
|
|
 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha : |
17/06/2022 |
|
Actualizado : |
17/06/2022 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
TONUSSI, R.L.; LONDOÑO-GIL, M.; DE OLIVEIRA SILVA, R.M.; MAGALHÃES, A.F.B.; AMORIM, S:T.; KLUSKA, S.; ESPIGOLAN, R.; PERIPOLLI, E.; PEREIRA, A.S.C.; LÔBO, R.B.; AGUILAR, I.; LOURENÇO, D.A.L.; BALDI, F. |
|
Afiliación : |
RAFAEL LARA TONUSSI,, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; MARISOL LONDOÑO-GIL, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; RAFAEL MEDEIROS DE OLIVEIRA SILVA, Zoetis, Kalamazoo, 49007, MI, United States; ANA FABRÍCIA BRAGA MAGALHÃES, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; SABRINA THAISE, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; SABRINA KLUSKA, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; RAFAEL ESPIGOLAN, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; ELISA PERIPOLLI, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil; ANGELICA SIMONE CRAVO PEREIRA, Faculdade de Medicina Veterinária E Zootecnia, Universidade de São Paulo, Pirassununga, CEP 13635-900, SP, Brazil; RAYSILDO BARBOSA LÔBO, Associação Nacional de Criadores E Pesquisadores (ANCP), Ribeirão Preto, CEP 14020-230, SP, Brazil; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIELA ANDRESSA LINO LOURENÇO, University of Georgia, Athens, 30602, GA, United States; FERNANDO BALDI, Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, CEP 14884-900, SP, Brazil. |
|
Título : |
Accuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information. |
|
Fecha de publicación : |
2021 |
|
Fuente / Imprenta : |
Tropical Animal Health and Production, 2021, Volume 53, Issue 4, Article number 432. doi: https://doi.org/10.1007/s11250-021-02879-w |
|
ISSN : |
0049-4747 |
|
DOI : |
10.1007/s11250-021-02879-w |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received 19 March 2021; Accepted 30 July 2021; Published online 10 August 2021.
Corresponding author: Londoño-Gil, M.; Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, SP, Brazil; email:londono.gil@unesp.br -- This work was funded by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant #2013/25910?0 and #2016/22751?6). |
|
Contenido : |
ABSTRACT - The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP effects are derived from ssGBLUP with a reference population with known sires. The ssGBLUP could be applied in situations of uncertain paternity, especially when selecting young animals. This methodology is shown to be accurate, mainly in scenarios with a high percentage of MS. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. MenosABSTRACT - The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP ... Presentar Todo |
|
Palabras claves : |
Age at first calving; Animals; Beef cattle; Genomic evaluation; Genomics; Uncertain paternity; Weight. |
|
Asunto categoría : |
L10 Genética y mejoramiento animal |
|
Marc : |
LEADER 03536naa a2200385 a 4500
001 1063326
005 2022-06-17
008 2021 bl uuuu u00u1 u #d
022 $a0049-4747
024 7 $a10.1007/s11250-021-02879-w$2DOI
100 1 $aTONUSSI, R.L.
245 $aAccuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 19 March 2021; Accepted 30 July 2021; Published online 10 August 2021. Corresponding author: Londoño-Gil, M.; Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, SP, Brazil; email:londono.gil@unesp.br -- This work was funded by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant #2013/25910?0 and #2016/22751?6).
520 $aABSTRACT - The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP effects are derived from ssGBLUP with a reference population with known sires. The ssGBLUP could be applied in situations of uncertain paternity, especially when selecting young animals. This methodology is shown to be accurate, mainly in scenarios with a high percentage of MS. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
653 $aAge at first calving
653 $aAnimals
653 $aBeef cattle
653 $aGenomic evaluation
653 $aGenomics
653 $aUncertain paternity
653 $aWeight
700 1 $aLONDOÑO-GIL, M.
700 1 $aDE OLIVEIRA SILVA, R.M.
700 1 $aMAGALHÃES, A.F.B.
700 1 $aAMORIM, S:T.
700 1 $aKLUSKA, S.
700 1 $aESPIGOLAN, R.
700 1 $aPERIPOLLI, E.
700 1 $aPEREIRA, A.S.C.
700 1 $aLÔBO, R.B.
700 1 $aAGUILAR, I.
700 1 $aLOURENÇO, D.A.L.
700 1 $aBALDI, F.
773 $tTropical Animal Health and Production, 2021, Volume 53, Issue 4, Article number 432. doi: https://doi.org/10.1007/s11250-021-02879-w
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha actual : |
09/11/2017 |
|
Actualizado : |
25/11/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
Autor : |
MASUDA, Y; MISZTAL, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; AGUILAR, I. |
|
Afiliación : |
Y. MASUDA, Department of Animal and Dairy Science, University of Georgia; I. MISZTAL, Department of Animal and Dairy Science, University of Georgia; A. LEGARRA, INRA (Institut National de la Recherche Agronomique); S. TSURUTA, Department of Animal and Dairy Science, University of Georgia; D.A.L. LOURENCO, Department of Animal and Dairy Science, University of Georgia; B.O. FRAGOMENI, Department of Animal and Dairy Science, University of Georgia; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
|
Título : |
Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. |
|
Fecha de publicación : |
2017 |
|
Fuente / Imprenta : |
Journal of Animal Science, 2017, v. 95(1): 49-52. |
|
DOI : |
10.2527/jas.2016.0699 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017.
This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and Food Research Initiative competitive grant 2015-67015-22936). |
|
Contenido : |
ABSTRACT.
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.
Copyright © 2016. American Society of Animal Science. MenosABSTRACT.
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When t... Presentar Todo |
|
Palabras claves : |
COMPUTATION; GENOMIC SELECTION; INVERSION; NUMERATOR RELATIONSHIP MATRIX; PRECONDITIONED CONJUGATE GRADIENT; SPARSE MATRIX. |
|
Asunto categoría : |
-- |
|
Marc : |
LEADER 02919naa a2200289 a 4500
001 1057743
005 2019-11-25
008 2017 bl uuuu u00u1 u #d
024 7 $a10.2527/jas.2016.0699$2DOI
100 1 $aMASUDA, Y
245 $aTechnical note$bAvoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.$h[electronic resource]
260 $c2017
500 $aArticle history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017. This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and Food Research Initiative competitive grant 2015-67015-22936).
520 $aABSTRACT. This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations. Copyright © 2016. American Society of Animal Science.
653 $aCOMPUTATION
653 $aGENOMIC SELECTION
653 $aINVERSION
653 $aNUMERATOR RELATIONSHIP MATRIX
653 $aPRECONDITIONED CONJUGATE GRADIENT
653 $aSPARSE MATRIX
700 1 $aMISZTAL, I.
700 1 $aLEGARRA, A.
700 1 $aTSURUTA, S.
700 1 $aLOURENCO, D.A.L.
700 1 $aFRAGOMENI, B.O.
700 1 $aAGUILAR, I.
773 $tJournal of Animal Science, 2017$gv. 95(1): 49-52.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
