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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
21/02/2014 |
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Actualizado : |
05/12/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
BRANDARIZ , S.; GONZÁLEZ RAYMÚNDEZ, A.; LADO, B.; MALOSETTI, M.; FRANCO GARCIA, A.; QUINCKE, M.; VON ZITZEWITZ, J.; CASTRO, M.; MATUS,I.; DEL POZO, A.; CASTRO, A.J.; GUTIÉRREZ, L. |
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Afiliación : |
SOFÍA P. BRANDARIZ, Universidad de la República (UdelaR); Facultad de Agronomía, Uruguay.; AGUSTÍN GONZÁLEZ REYMÚNDEZ; BETTINA LADO; MARCOS MALOSETTI; ANTONIO AUGUSTO FRANCO GARCIA; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JARISLAV RAMON VON ZITZEWITZ VON SALVIATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IVÁN MATUS; ALEJANDRO DEL POZO; ARIEL J. CASTRO; LUCÍA GUTIÉRREZ. |
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Título : |
Ascertainment bias from imputation methods evaluation in wheat. |
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Fecha de publicación : |
2016 |
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Fuente / Imprenta : |
BMC Genomics, 2016, v. 17, p.773. |
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DOI : |
10.1186/s12864-016-3120-5 |
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Idioma : |
Inglés |
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Notas : |
OPEN ACCESS. Article history: Received 2016 Feb 24 // Accepted 2016 Sep 23. |
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Contenido : |
Abstract
BACKGROUND:
Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel.
RESULTS:
In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available.
CONCLUSIONS:
Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel. MenosAbstract
BACKGROUND:
Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel.
RESULTS:
In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between ... Presentar Todo |
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Palabras claves : |
FALSE POSITIVE; FALSO POSITIVO; GBS; GWAS; POWER; QTLs. |
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Thesagro : |
MEJORAMIENTO DE TRIGO. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12122/1/s12864-016-3120-5.pdf
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-3120-5
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Marc : |
LEADER 02972nam a2200349 a 4500
001 1047336
005 2018-12-05
008 2016 bl uuuu u0uu1 u #d
024 7 $a10.1186/s12864-016-3120-5$2DOI
100 1 $aBRANDARIZ , S.
245 $aAscertainment bias from imputation methods evaluation in wheat.$h[electronic resource]
260 $aBMC Genomics, 2016, v. 17, p.773.$c2016
500 $aOPEN ACCESS. Article history: Received 2016 Feb 24 // Accepted 2016 Sep 23.
520 $aAbstract BACKGROUND: Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel. RESULTS: In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available. CONCLUSIONS: Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel.
650 $aMEJORAMIENTO DE TRIGO
653 $aFALSE POSITIVE
653 $aFALSO POSITIVO
653 $aGBS
653 $aGWAS
653 $aPOWER
653 $aQTLs
700 1 $aGONZÁLEZ RAYMÚNDEZ, A.
700 1 $aLADO, B.
700 1 $aMALOSETTI, M.
700 1 $aFRANCO GARCIA, A.
700 1 $aQUINCKE, M.
700 1 $aVON ZITZEWITZ, J.
700 1 $aCASTRO, M.
700 1 $aMATUS,I.
700 1 $aDEL POZO, A.
700 1 $aCASTRO, A.J.
700 1 $aGUTIÉRREZ, L.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó; INIA Treinta y Tres. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
10/09/2018 |
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Tipo de producción científica : |
Artículos en Revistas Agropecuarias |
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Autor : |
GILSANZ, J. |
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Afiliación : |
JUAN CARLOS GILSANZ MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Abonos verdes en la producción hortícola. |
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Fecha de publicación : |
2008 |
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Fuente / Imprenta : |
Suplemento Tecnológico INIA, 2008, p. 26-27. |
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Idioma : |
Español |
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Notas : |
Suplemento tecnológico Expo Prado 2008. |
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Contenido : |
La producción de hortalizas se basa normalmente en el uso intensivo del suelo, de rotaciones cortas y con pequeños períodos de descanso entre cultivos. En muchos
casos no se logra tener toda el área disponible en cultivo en una misma estación existiendo superficies en barbecho que se pueden enmalezar. El excesivo laboreo
incluye el uso de implementos que causan un gran deterioro del suelo favoreciendo la disminución en la infiltración, y aumento del encostramiento. En áreas de fuerte
pendiente se incrementa la erosión y el lavado de los nutrientes. En este escenario es que se inicia el espiral descendente en los niveles de rendimiento y calidad del suelo. El cultivo de hortalizas en suelos deteriorados produce un menor desarrollo y vigor de las mismas, estando más expuestas al ataque de plagas y de enfermedades.
Para mantener el nivel productivo de esos predios es necesario un mayor uso de agroquímicos, en desmedro del medio ambiente, en una pérdida en la sustentabilidad
de la producción y un incremento en los costos. |
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Palabras claves : |
PRODUCCIÓN HORTÍCOLA. |
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Thesagro : |
ABONOS; ABONOS VERDES; CALIDAD DEL SUELO; HORTALIZAS; SUELO. |
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Asunto categoría : |
--
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4435/1/inia-2008-suplemento-tecnologico.pdf
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Marc : |
LEADER 01573nam a2200193 a 4500
001 1028149
005 2018-09-10
008 2008 bl uuuu u0uu1 u #d
100 1 $aGILSANZ, J.
245 $aAbonos verdes en la producción hortícola.
260 $aSuplemento Tecnológico INIA, 2008, p. 26-27.$c2008
500 $aSuplemento tecnológico Expo Prado 2008.
520 $aLa producción de hortalizas se basa normalmente en el uso intensivo del suelo, de rotaciones cortas y con pequeños períodos de descanso entre cultivos. En muchos casos no se logra tener toda el área disponible en cultivo en una misma estación existiendo superficies en barbecho que se pueden enmalezar. El excesivo laboreo incluye el uso de implementos que causan un gran deterioro del suelo favoreciendo la disminución en la infiltración, y aumento del encostramiento. En áreas de fuerte pendiente se incrementa la erosión y el lavado de los nutrientes. En este escenario es que se inicia el espiral descendente en los niveles de rendimiento y calidad del suelo. El cultivo de hortalizas en suelos deteriorados produce un menor desarrollo y vigor de las mismas, estando más expuestas al ataque de plagas y de enfermedades. Para mantener el nivel productivo de esos predios es necesario un mayor uso de agroquímicos, en desmedro del medio ambiente, en una pérdida en la sustentabilidad de la producción y un incremento en los costos.
650 $aABONOS
650 $aABONOS VERDES
650 $aCALIDAD DEL SUELO
650 $aHORTALIZAS
650 $aSUELO
653 $aPRODUCCIÓN HORTÍCOLA
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INIA Tacuarembó (TBO) |
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