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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
26/09/2014 |
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Actualizado : |
06/11/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LADO, B.; MATUS, I.; RODRIGUEZ, A.; INOSTROZA, L.; POLAND, J.; BELZILE ,F.; DEL POZO, A.; QUINCKE, M.; CASTRO, M.; VON ZITZEWITZ, J. |
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Afiliación : |
BETTINA LADO LINDNER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JARISLAV RAMON VON ZITZEWITZ VON SALVIATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Increased genomic prediction accuracy in wheat breeding through spatial adjustment of field trial data. |
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Fecha de publicación : |
2013 |
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Fuente / Imprenta : |
G3: Genes, Genomes, Genetics (Bethesda), v. 3, n,12, p. 2105-2114, 2013.OPEN ACCESS. |
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ISSN : |
2160-1836. |
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DOI : |
10.1534/g3.113.007807 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 2013 Aug 26 // Accepted 2013 Sep 18. |
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Contenido : |
Abstract:
In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confirm that genotyping-by-sequencing is an effective tool to obtain genome-wide information for crops with complex genomes, that these data are efficient for predicting traits, and that correction of spatial variation is a crucial ingredient to increase prediction accuracy in genomic selection models. MenosAbstract:
In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confir... Presentar Todo |
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Palabras claves : |
GBLUP; GENOMIC SELECTION; GENOTIPADO POR SECUENCIACIÓN; GENOTYPING BY SEQUENCING; GENPRED; LOCUS DE UN CARÁCTER CUANTITATIVO; MEJOR PREDICTOR LINEAR INSESGADO; POLIMORFISMO DE NUCLEÓTICO SIMPLE; QTL; QUANTITATIVE TRAIT LOCUS; SELECCIÓN GENÓMICA; SHARED DATA RESOURCES; SINGLE NUCLEOTIDE POLYMORPHISM; SPATIAL CORRECTION; WHEAT. |
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Thesagro : |
TRIGO; TRITICUM AESTIVUM. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13756/1/G3Bethesda-v.-3-n12-p.-2105-2114-2013.pdf
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Marc : |
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022 $a2160-1836.
024 7 $a10.1534/g3.113.007807$2DOI
100 1 $aLADO, B.
245 $aIncreased genomic prediction accuracy in wheat breeding through spatial adjustment of field trial data.$h[electronic resource]
260 $c2013
500 $aArticle history: Received 2013 Aug 26 // Accepted 2013 Sep 18.
520 $aAbstract: In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confirm that genotyping-by-sequencing is an effective tool to obtain genome-wide information for crops with complex genomes, that these data are efficient for predicting traits, and that correction of spatial variation is a crucial ingredient to increase prediction accuracy in genomic selection models.
650 $aTRIGO
650 $aTRITICUM AESTIVUM
653 $aGBLUP
653 $aGENOMIC SELECTION
653 $aGENOTIPADO POR SECUENCIACIÓN
653 $aGENOTYPING BY SEQUENCING
653 $aGENPRED
653 $aLOCUS DE UN CARÁCTER CUANTITATIVO
653 $aMEJOR PREDICTOR LINEAR INSESGADO
653 $aPOLIMORFISMO DE NUCLEÓTICO SIMPLE
653 $aQTL
653 $aQUANTITATIVE TRAIT LOCUS
653 $aSELECCIÓN GENÓMICA
653 $aSHARED DATA RESOURCES
653 $aSINGLE NUCLEOTIDE POLYMORPHISM
653 $aSPATIAL CORRECTION
653 $aWHEAT
700 1 $aMATUS, I.
700 1 $aRODRIGUEZ, A.
700 1 $aINOSTROZA, L.
700 1 $aPOLAND, J.
700 1 $aBELZILE ,F.
700 1 $aDEL POZO, A.
700 1 $aQUINCKE, M.
700 1 $aCASTRO, M.
700 1 $aVON ZITZEWITZ, J.
773 $tG3: Genes, Genomes, Genetics (Bethesda)$gv. 3, n,12, p. 2105-2114, 2013.OPEN ACCESS.
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Registro original : |
INIA La Estanzuela (LE) |
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| Registros recuperados : 11 | |
| 1. |  | LADO,B.; BATTENFIELD, S.; POLAND, J.; QUINCKE, M.; SILVA, P.; GUTIÉRREZ, L. Comparación de metodologías de predicción de cruzamientos para rendimiento en trigo. MV 14 - COMUNICACIONES LIBRES - MV. MEJORAMIENTO VEGETAL In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016 p. 287.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 2. | | LADO, B.; MATUS, I.; BELZILE, F.; POLAND, J.; QUINCKE, M.; CASTRO, M.; VON ZITZEWITZ, J. Genotipado por secuenciación en trigo (Triticum aestivum). In: JORNADAS DE LA SOCIEDAD DE BIOQUÍMICA Y BIOLOGÍA MOLECULAR , 8., SIMPOSIO BIOLOGÍA Y BIOTECNOLOGÍA VEGETAL, 11., 2013. Resumen. Montevideo: SBBM, SUB, 2013.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 3. | | WANG, X.; SILVA, P.; BELLO, N.M.; SINGH, D.; EVERS, B.; SINGH, R.P.; POLAND, J. Improved accuracy of high-throughput phenotyping from unmanned aerial systems by extracting traits directly from orthorectified images. Frontiers in Plant Science, 21 October 2020, Volume 11, Article number 587093. Open Access. Doi: https://doi.org/10.3389/fpls.2020.587093 Article history: Received: 27 July 2020/ Accepted: 30 September 2020/Published: 21 October 2020.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 4. | | SILVA, P.; EVERS, B.; KIEFFABER, A.; WANG, X.; BROWN, R.; GAO, L.; FRITZ, A.; CRAIN, J.; POLAND, J. Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat. G3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 5. | | MORA, F.; CASTILLO, D.; LADO, B.; MATUS, I.; POLAND, J.; BELZILE, F.; VON ZITZEWITZ, J.; DEL POZO, A. Genome-wide association mapping of agronomic traits and carbon isotope discrimination in a worldwide germplasm collection of spring wheat using SNP markers. Molecular Breeding, 2015, v,35, no.2, 12 p.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
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| 6. | | LADO, B.; BATTENFIELD, S.; SILVA, P.; QUINCKE, M.; GUZMAN, C.; SINGH, R.P.; DREISIGACKER, S.; PEÑA, J.; FRITZ, A.; POLAND, J.; GUTIERREZ, L. Comparing strategies to select crosses using genomic prediction in two wheat breeding programs. In: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria. p.88-90.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 7. | | LADO, B.; POLAND, J.; BELZILE, F.; DEL POZO, A.; MATUS, I.; RODRÍGUEZ, A.; INOSTROZA, L.; LOBOS, G.A.; CASTRO, M.; QUINCKE, M.; LANDECHEA, L.; VON ZITZEWITZ, J. Genotipado por secuenciación del genoma de 384 genotipos de T. aestivum para selección genómica. BAG. Journal of Basic and Applied Genetics ,Ciudad Autónoma de Buenos Aires, v.23, supl.1, p. 267, 2012.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : B - 3 |
| Biblioteca(s): INIA La Estanzuela. |
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| 8. | | LADO, B.; MATUS, I.; RODRIGUEZ, A.; INOSTROZA, L.; POLAND, J.; BELZILE ,F.; DEL POZO, A.; QUINCKE, M.; CASTRO, M.; VON ZITZEWITZ, J. Increased genomic prediction accuracy in wheat breeding through spatial adjustment of field trial data. G3: Genes, Genomes, Genetics (Bethesda), v. 3, n,12, p. 2105-2114, 2013.OPEN ACCESS. Article history: Received 2013 Aug 26 // Accepted 2013 Sep 18.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : B - 5 |
| Biblioteca(s): INIA La Estanzuela. |
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| 9. | | LADO, B.; BATTENFIELD, S. D.; GUZMÁN, C.; QUINCKE, M.; SINGH, R. P.; DREISIGACKER, S.; PEÑA, R. J.; FRITZ, AL.; SILVA, P.; POLAND, J.; GUTIÉRREZ, L. Strategies for selecting crosses using genomic prediction in two wheat breeding programs. The Plant Genome, 2017, v.10, Issue 2, 12p. OPEN ACCESS Article history: Received: Dec 14, 2016 // Accepted: Mar 18, 2017 // Published: July 6, 2017.
B. Lado and S. Battenfield contributed equally.Assigned to Associate Editor Nicholas Tinker.
This is an open access article distributed under...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 10. | | GAO, L.; KOO, D.H.; JULIANA, P.; RIFE, T.; SINGH, D.; CRISTIANO LEMES DA SILVA; LUX, T.; DORN, K.M.; CLINESMITH, M.; SILVA, P.; WANG, X.; SPANNAGL, M.; MONAT, C.; FRIEBE, B.; STEUERNAGEL, B.; MUEHLBAUER, G.J.; WALKOWIAK, S.; POZNIAK, C.; SINGH, R.; STEIN, N.; MASCHER, M.; FRITZ, A.; POLAND, J. The Aegilops ventricosa 2N v S segment in bread wheat: cytology, genomics and breeding. Theoretical and Applied Genetics, volume 134, pag. 529?542, feb 2021. Open Access. Doi: https://doi.org/10.1007/s00122-020-03712-y Article history:Received: 22 June 2020 / Accepted: 17 October 2020/ Published:12 November 2020/ Issue Date:February 2021| Biblioteca(s): INIA La Estanzuela. |
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| 11. | | GAURAV, K.; ARORA, S.; SILVA, P.; SÁNCHEZ-MARTÍN, J.; HORSNELL,R.; GAO, L.; BRAR ,G.S.; WIDRIG,V.; JOHN RAUPP,W.; SINGH, N.; WU, S.; KALE, S.M.; CHINOY, C.; NICHOLSON, P.; QUIROZ-CHÁVEZ, J.; SIMMONDS, J.; HAYTA, S.; SMEDLEY, M. A; HARWOOD, W.; PEARCE, S.; GILBERT, D.; KANGARA, N.; GARDENER, C.; FORNER-MARTÍNEZ, M.; LIU, J.; YU, G.; BODEN, S.A.; PASCUCCI, A.; GHOSH, S.; HAFEEZ, A.N.; O'HARA, T.; WAITES, J.; CHEEMA, J.; STEUERNAGEL, B.; PATPOUR, M.; JUSTESEN, A.F.; LIU, S.; RUDD, J. C.; AVNI, R.; SHARON, A.R; STEINER, B.; KIRANA, R.P.; BUERSTMAYR, H.; MEHRABI, A.A.; NASYROVA, F.Y.; CHAYUT, N.; MATNY, O.; STEFFENSON, B. J.; SANDHU, N.; CHHUNEJA, P.; LAGUDAH, E.; ELKOT, A.F.; TYRRELL, S.; BIAN, X.; DAVEY, R.P.; SIMONSEN, M.; SCHAUSER, L.; TIWARI, V.K.; RANDY KUTCHER, H.; HUCL, P.; LI, A.; LIU, D.C.; MAO, L.; XU, S.; BROWN-GUEDIRA, G.; FARIS, J.; DVORAK, J.; LUO, M.CH.; KRASILEVA, K.; LUX, T.; ARTMEIER, S.; MAYER, K. F. X.; UAUY, C.; MASCHER, M.; BENTLEY, A.R.; KELLER, B.; POLAND, J.; WULFF, B. B. H. Population genomic analysis of Aegilops tauschii identifies targets for bread wheat improvement. Nature Biotechnology, Volume 40, Pages 422-431, March 2022. Open Access. doi: https://doi.org/10.1038/s41587-021-01058-4| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| Registros recuperados : 11 | |
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