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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
18/03/2022 |
Actualizado : |
02/09/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
SILVA, P.; EVERS, B.; KIEFFABER, A.; WANG, X.; BROWN, R.; GAO, L.; FRITZ, A.; CRAIN, J.; POLAND, J. |
Afiliación : |
MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./ Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; BYRON EVERS, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, USA.; ALEXANDRIA KIEFFABER, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, USA.; XU WANG, Department of Agricultural and Biological Engineering, University of Florida, IFAS Gulf Coast , Research and Education Center, Wimauma, Florida,USA.; RICHARD BROWN, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; LIANGLIANG GAO, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, USA.; ALLAN FRITZ, Department of Agronomy, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA.; JARED CRAIN, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA.; JESSE POLAND, Department of Plant Pathology, College of Agriculture, Kansas State University, Manhattan, Kansas, 66506, USA. |
Título : |
Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
G3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064 |
DOI : |
10.1093/g3journal/jkac064 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 22 December 2021/Accepted: 12 March 2022/Published: 30 March 2022.
The Author(s) (2022) . Published by Oxford University Press on behalf of the Genetics Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Contenido : |
Abstract:
Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive model had a large effect for predicting BYD but almost no effect for PTHTM and GY. This study was the first attempt to characterize BYD using field-HTP and apply GS to predict the disease severity. These methods have the potential to improve BYD characterization and identifying new sources of resistance will be crucial for delivering BYD resistant germplasm. MenosAbstract:
Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive mo... Presentar Todo |
Palabras claves : |
Barley yellow dwarf (BYD); Genomic Selection (GS); High-throughput Phenotyping (HTP); Resistance; Tolerance; Triticum aestivum; Virus. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16662/1/Applied-phenomics-and-genomics-for-improving-barley-yellow-dwarf-resistance-in-winter.-2022.Silva.pdf
https://academic.oup.com/g3journal/article-pdf/12/7/jkac064/44473353/jkac064.pdf
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Marc : |
LEADER 03303naa a2200325 a 4500 001 1062870 005 2022-09-02 008 2022 bl uuuu u00u1 u #d 024 7 $a10.1093/g3journal/jkac064$2DOI 100 1 $aSILVA, P. 245 $aApplied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat.$h[electronic resource] 260 $c2022 500 $aArticle history: Received: 22 December 2021/Accepted: 12 March 2022/Published: 30 March 2022. The Author(s) (2022) . Published by Oxford University Press on behalf of the Genetics Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 520 $aAbstract: Barley yellow dwarf (BYD) is one of the major viral diseases of cereals. Phenotyping BYD in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to, i) evaluate the use of high-throughput phenotyping (HTP) from unmanned aerial systems to improve BYD assessment and selection, ii) identify genomic regions associated with BYD resistance, and iii) evaluate genomic prediction models ability to predict BYD resistance. Up to 107 wheat lines were phenotyped during each of five field seasons under both insecticide treated and untreated plots. Across all seasons, BYD severity was lower with the insecticide treatment and plant height (PTHTM) and grain yield (GY) showed increased values relative to untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying resistance gene Bdv2 on chromosome 7DL. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for resistance on chromosome 5AS. Given the variable heritability of the trait (0.211 ? 0.806), we obtained relatively good predictive ability for BYD severity ranging between 0.06 ? 0.26. Including Bdv2 on the predictive model had a large effect for predicting BYD but almost no effect for PTHTM and GY. This study was the first attempt to characterize BYD using field-HTP and apply GS to predict the disease severity. These methods have the potential to improve BYD characterization and identifying new sources of resistance will be crucial for delivering BYD resistant germplasm. 653 $aBarley yellow dwarf (BYD) 653 $aGenomic Selection (GS) 653 $aHigh-throughput Phenotyping (HTP) 653 $aResistance 653 $aTolerance 653 $aTriticum aestivum 653 $aVirus 700 1 $aEVERS, B. 700 1 $aKIEFFABER, A. 700 1 $aWANG, X. 700 1 $aBROWN, R. 700 1 $aGAO, L. 700 1 $aFRITZ, A. 700 1 $aCRAIN, J. 700 1 $aPOLAND, J. 773 $tG3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
20/06/2015 |
Actualizado : |
20/06/2015 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
GIMENEZ, A.; CASTAÑO, J.; CAL, A.; TISCORNIA, G.; SCHIAVI, C. |
Afiliación : |
AGUSTIN EDUARDO GIMENEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE PEDRO CASTAÑO SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS IGNACIO SCHIAVI RAMPELBERG, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe Agroclimático 2014 - Situación a Setiembre. |
Fecha de publicación : |
2014 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2014. |
Páginas : |
4 p. |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4739/1/Inf.Agr.-setiembre-2014.pdf
http://www.inia.uy/Publicaciones/Paginas/Informe-agroclimatico-2014---Situacion-Setiembre.aspx
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Marc : |
LEADER 02068nam a2200793 a 4500 001 1052895 005 2015-06-20 008 2014 bl uuuu u0uu1 u #d 100 1 $aGIMENEZ, A. 245 $aInforme Agroclimático 2014 - Situación a Setiembre.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2014 300 $a4 p. 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aCASTAÑO, J. 700 1 $aCAL, A. 700 1 $aTISCORNIA, G. 700 1 $aSCHIAVI, C.
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