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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
04/07/2019 |
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Actualizado : |
04/07/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
AGUILAR, I.; LEGARRA, A.; CARDOSO, F.; MASUDA, Y.; LOURENCO, D.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRÉS LEGARRA, INRA (Institut National de la Recherche Agronomique); FERNANDO CARDOSO, Department of Animal Science, Federal University of Pelotas, Brazil; Embrapa Pecuária Sul, Brazil; YUTAKA MASUDA, Department of Animal and Dairy Science, University of Georgia, United States; DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, United States; IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, United States. |
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Título : |
Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication) |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Genetics Selection Evolution, 20 June 2019, v. 51, Issue 1, Article number 28. OPEN ACCESS. |
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ISSN : |
0999-193X |
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DOI : |
10.1186/s12711-019-0469-3 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 3 January 2019 // Accepted: 27 May 2019 // Published Online: 20 June 2019.
Funding text: This study was partially funded by the American Angus Association (St. Joseph, MO) and by Agriculture and Food Research Initiative Competitive Grants No. 2015-67015-22936 from the US Department of Agriculture?s National Institute of Food and Agriculture.
Availability of data and materials: The data that support the fndings of this study were provided from the American Angus Association but restrictions apply to the availability of these data, which were used under license for the current study, and thus are not publicly available. The methods described here are included using ?OPTION snp_p_value? in the parameter fle in software blupf90 (factorization of the mixed model equations and solving of the SSGBLUP equations) and postGSf90
(backsolving of snp efects and computation of p-values), available at http://nce.ads.uga.edu/software/. |
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Contenido : |
ABSTRACT.
Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped.
© 2019 The Author(s). MenosABSTRACT.
Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of... Presentar Todo |
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Palabras claves : |
ANIMALIA. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12994/1/s12711-019-0469-3.pdf
https://gsejournal.biomedcentral.com/track/pdf/10.1186/s12711-019-0469-3
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Marc : |
LEADER 03268naa a2200229 a 4500
001 1059927
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008 2019 bl uuuu u00u1 u #d
022 $a0999-193X
024 7 $a10.1186/s12711-019-0469-3$2DOI
100 1 $aAGUILAR, I.
245 $aFrequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication)$h[electronic resource]
260 $c2019
500 $aArticle history: Received: 3 January 2019 // Accepted: 27 May 2019 // Published Online: 20 June 2019. Funding text: This study was partially funded by the American Angus Association (St. Joseph, MO) and by Agriculture and Food Research Initiative Competitive Grants No. 2015-67015-22936 from the US Department of Agriculture?s National Institute of Food and Agriculture. Availability of data and materials: The data that support the fndings of this study were provided from the American Angus Association but restrictions apply to the availability of these data, which were used under license for the current study, and thus are not publicly available. The methods described here are included using ?OPTION snp_p_value? in the parameter fle in software blupf90 (factorization of the mixed model equations and solving of the SSGBLUP equations) and postGSf90 (backsolving of snp efects and computation of p-values), available at http://nce.ads.uga.edu/software/.
520 $aABSTRACT. Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped. © 2019 The Author(s).
653 $aANIMALIA
700 1 $aLEGARRA, A.
700 1 $aCARDOSO, F.
700 1 $aMASUDA, Y.
700 1 $aLOURENCO, D.
700 1 $aMISZTAL, I.
773 $tGenetics Selection Evolution, 20 June 2019$gv. 51, Issue 1, Article number 28. OPEN ACCESS.
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
17/04/2020 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
JAURENA, M.; DE BARBIERI, I.; LEZAMA, F.; AYALA, W.; MONTOSSI, F.; RIVAS, M. |
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Afiliación : |
MARTIN ALEJANDRO JAURENA BARRIOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FELIPE LEZAMA HUERTA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WALTER FELIZARDO AYALA SILVERA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MERCEDES RIVAS, Universidad de la República (UdelaR)/ Facultad de Agronomía. |
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Título : |
Atributos de pasturas naturales sobre suelos superficiales de Basalto con cargas contrastantes de capones |
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Fecha de publicación : |
2008 |
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Fuente / Imprenta : |
ln: Reunión del grupo técnico en forrajeras del Cono Sur, 22., 2008, Minas, Uruguay Bioma campos: innovando para mantener su sustentabilidad y competitividad. Memorias. Minas (Uruguay): INIA; FAO; PROCISUR, 2008. |
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Páginas : |
p. 199 |
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Idioma : |
Español |
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Notas : |
Versión impresa y en CD ROM Instituto Nacional de Investigación Agropecuaria, Uruguay; FAO; PROCISUR |
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Contenido : |
Se presentan los resultados de un estudio sobre el impacto de diferentes cargas de capones en la evolución de una pastura natural sobre suelos superficiales de Basalto. Se encontraron efectos variables de la carga animal en la tasa de crecimiento y se generaron diferentes ofertas de forraje según el tipo de suelo y la estación del año considerada. El aumento de la carga animal disminuyó la riqueza de especies y cambió la composición de la vegetación principalmente en los suelos superficiales negros. |
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Palabras claves : |
CARGA ANIMAL. |
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Thesagro : |
BASALTO; CAMPO; CAMPO NATURAL; OVINOS; SUELO. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5347/1/Atributos-2008-campos-Jaurena.pdf
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Marc : |
LEADER 01485naa a2200277 a 4500
001 1008184
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008 2008 bl uuuu u00u1 u #d
100 1 $aJAURENA, M.
245 $aAtributos de pasturas naturales sobre suelos superficiales de Basalto con cargas contrastantes de capones
260 $c2008
300 $ap. 199
500 $aVersión impresa y en CD ROM Instituto Nacional de Investigación Agropecuaria, Uruguay; FAO; PROCISUR
520 $aSe presentan los resultados de un estudio sobre el impacto de diferentes cargas de capones en la evolución de una pastura natural sobre suelos superficiales de Basalto. Se encontraron efectos variables de la carga animal en la tasa de crecimiento y se generaron diferentes ofertas de forraje según el tipo de suelo y la estación del año considerada. El aumento de la carga animal disminuyó la riqueza de especies y cambió la composición de la vegetación principalmente en los suelos superficiales negros.
650 $aBASALTO
650 $aCAMPO
650 $aCAMPO NATURAL
650 $aOVINOS
650 $aSUELO
653 $aCARGA ANIMAL
700 1 $aDE BARBIERI, I.
700 1 $aLEZAMA, F.
700 1 $aAYALA, W.
700 1 $aMONTOSSI, F.
700 1 $aRIVAS, M.
773 $tln: Reunión del grupo técnico en forrajeras del Cono Sur, 22., 2008, Minas, Uruguay Bioma campos: innovando para mantener su sustentabilidad y competitividad. Memorias. Minas (Uruguay): INIA; FAO; PROCISUR, 2008.
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