| |
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha : |
31/03/2021 |
|
Actualizado : |
31/03/2021 |
|
Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
|
Autor : |
MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. |
|
Afiliación : |
YATUKA MASUDA, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHOGO TSURUTA; IGNACY MISZTAL, University of Georgia, Athens, USA. |
|
Título : |
Acceleration of computations in AI REML for single-step GBLUP models. |
|
Complemento del título : |
Volume Methods and Tools: Statistical methods - linear and nonlinear models (Posters), 703. |
|
Fecha de publicación : |
2014 |
|
Fuente / Imprenta : |
In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703. |
|
Idioma : |
Inglés |
|
Contenido : |
ABSTRACT.
The objective of this study was to evaluate the advantage of the YAMS package over the FSPAK package in average-information (AI) REML for single-step GBLUP models. Data sets from broiler and Holsteins were used in this study. (Co)variance components were estimated with the AIREMLF90 program which could switch YAMS and FSPAK for sparse operations. The YAMS package used the BLAS and LAPACK libraries using all the 16 cores on CPU. For a single-trait model applied to the data contained over 15,000 genotyped animals, FSPAK took over 4 hours to finish the first 5 rounds while YAMS took 20 minutes. For a 4-trait model applied to the same data set, FSPAK failed in the sparse factorization while YAMS took 5 hours to finish the first 5 rounds. The use of YAMS can dramatically increase speed and stability of AIREMLF90 for single-step GBLUP models. |
|
Palabras claves : |
Single step GBLUP; Supernodal methods; Variance component estimation. |
|
Asunto categoría : |
L10 Genética y mejoramiento animal |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15447/1/Masuda-et-al.-2014.-WCGALP.pdf
|
|
Marc : |
LEADER 01492nam a2200181 a 4500
001 1061923
005 2021-03-31
008 2014 bl uuuu u01u1 u #d
100 1 $aMASUDA, Y.
245 $aAcceleration of computations in AI REML for single-step GBLUP models.$h[electronic resource]
260 $aIn: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703.$c2014
520 $aABSTRACT. The objective of this study was to evaluate the advantage of the YAMS package over the FSPAK package in average-information (AI) REML for single-step GBLUP models. Data sets from broiler and Holsteins were used in this study. (Co)variance components were estimated with the AIREMLF90 program which could switch YAMS and FSPAK for sparse operations. The YAMS package used the BLAS and LAPACK libraries using all the 16 cores on CPU. For a single-trait model applied to the data contained over 15,000 genotyped animals, FSPAK took over 4 hours to finish the first 5 rounds while YAMS took 20 minutes. For a 4-trait model applied to the same data set, FSPAK failed in the sparse factorization while YAMS took 5 hours to finish the first 5 rounds. The use of YAMS can dramatically increase speed and stability of AIREMLF90 for single-step GBLUP models.
653 $aSingle step GBLUP
653 $aSupernodal methods
653 $aVariance component estimation
700 1 $aAGUILAR, I.
700 1 $aTSURUTA, S.
700 1 $aMISZTAL, I.
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 : |
27/04/2021 |
|
Actualizado : |
27/04/2021 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
Autor : |
SIMEONE, M.; GÓMEZ, C.; BERTALMIO, A.; RUIZ, E.; HAUTEVILLE, C.; GODOY, L.; TITO, B.; GARCÍA, M.L. |
|
Afiliación : |
MELINA SIMEONE, Instituto de Biotecnología y Biología Molecular, CCT-La Plata CONICET-UNLP Facultad de Ciencias Exactas, UNLP, La Plata, Argentina; CLAUDIO GÓMEZ, Estación Experimental Agropecuaria Concordia, Instituto Nacional de Tecnología Agropecuaria (INTA), Entre Ríos, Argentina; ANA MARIA BERTALMIO CASARIEGO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ESPERANZA RUIZ, Laboratorio de Investigación y Desarrollo de Bioactivos, Facultad de Ciencias Exactas, UNLP, La Plata, Argentina; CLAUDIA HAUTEVILLE, Estación Experimental Agropecuaria Concordia, Instituto Nacional de Tecnología Agropecuaria (INTA), Entre Ríos, Argentina; LAURA GODOY SUÁREZ, Estación Experimental Agropecuaria Concordia, Instituto Nacional de Tecnología Agropecuaria (INTA), Entre Ríos, Argentina; BLAS TITO, Estación Experimental Agropecuaria Concordia, Instituto Nacional de Tecnología Agropecuaria (INTA), Entre Ríos, Argentina; MARÍA L. GARCÍA, Instituto de Biotecnología y Biología Molecular, CCT?La Plata CONICET?UNLP Facultad de Ciencias Exactas, UNLP, La Plata, Argentina. |
|
Título : |
Detection of citrus psorosis virus by RT‐qPCR validated by diagnostic parameters. |
|
Fecha de publicación : |
2021 |
|
Fuente / Imprenta : |
Plant Pathology, May 2021, Volume 70, Issue 4, Pages 980-986. Doi: https://doi.org/10.1111/ppa.13341 |
|
ISSN : |
0032-0862 |
|
DOI : |
10.1111/ppa.13341 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received, 8 September 2020; Accepted, 28 December 2020, First published, 18 January 2021.
This work was supported by Agencia Nacional de Promoción Científica y Tecnológica (ANPCYT) PICT 2014‐1007 and PICT Start UP 2014‐3762, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Proyectos de Investigación de Unidades Ejecutoras?(IBBM), Universidad Nacional de La Plata (UNLP) X‐692, and Instituto Nacional de Tecnología Agropecuaria (INTA) (PNFRU‐1172; 11721; ERIOS‐630081, PD I081 and RIST I091). M.S. was supported by ANPCyT and CONICET. M.L.G. belongs to CONICET and Departamento de Ciencias Biológicas, Facultad de Ciencias Exactas, UNLP. We thank Beatriz Stein and Julia Figueroa from the Estación Experimental Agroindustrial Obispo Colombres (EEOC), Tucumán, for providing samples from their collection and Magalí Gabrielli for technical assistance in the total RNA extractions. We thank Pedro Moreno for helpful discussion and critical reading of the manuscript. |
|
Contenido : |
ABSTRACT.
Citrus psorosis virus (CPsV) is the causal agent of psorosis, an important disease of citrus. Sanitary and certification programmes helped reduce disease damage caused by psorosis and other graft‐transmissible diseases in many citrus‐growing regions. For quarantine and certification programmes, most of these diseases are currently diagnosed using biological indexing (BI) on sensitive indicator plants. In the case of citrus psorosis, CPsV can be detected by molecular methods such as quantitative reverse transcription PCR (RT‐qPCR), which is cheaper and faster than BI, but sensitivity, reliability, and reproducibility of both procedures have not been compared so far. In this work, 128 plants from Argentina and Uruguay were analysed using BI and CPsV detection by the RT‐qPCR assay. Almost perfect agreement between both diagnostic procedures and sensitivity, specificity, and estimated likelihood ratios indicate that RT‐qPCR is equivalent to BI for citrus psorosis diagnosis, thus providing confidence in the quick diagnostic procedure to monitor the sanitary status of citrus trees.
© 2021 British Society for Plant Pathology |
|
Palabras claves : |
Citrus psorosis virus; Diagnostic parameters; RT-qPCR. |
|
Asunto categoría : |
H20 Enfermedades de las plantas |
|
Marc : |
LEADER 03027naa a2200277 a 4500
001 1061995
005 2021-04-27
008 2021 bl uuuu u00u1 u #d
022 $a0032-0862
024 7 $a10.1111/ppa.13341$2DOI
100 1 $aSIMEONE, M.
245 $aDetection of citrus psorosis virus by RT‐qPCR validated by diagnostic parameters.$h[electronic resource]
260 $c2021
500 $aArticle history: Received, 8 September 2020; Accepted, 28 December 2020, First published, 18 January 2021. This work was supported by Agencia Nacional de Promoción Científica y Tecnológica (ANPCYT) PICT 2014‐1007 and PICT Start UP 2014‐3762, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Proyectos de Investigación de Unidades Ejecutoras?(IBBM), Universidad Nacional de La Plata (UNLP) X‐692, and Instituto Nacional de Tecnología Agropecuaria (INTA) (PNFRU‐1172; 11721; ERIOS‐630081, PD I081 and RIST I091). M.S. was supported by ANPCyT and CONICET. M.L.G. belongs to CONICET and Departamento de Ciencias Biológicas, Facultad de Ciencias Exactas, UNLP. We thank Beatriz Stein and Julia Figueroa from the Estación Experimental Agroindustrial Obispo Colombres (EEOC), Tucumán, for providing samples from their collection and Magalí Gabrielli for technical assistance in the total RNA extractions. We thank Pedro Moreno for helpful discussion and critical reading of the manuscript.
520 $aABSTRACT. Citrus psorosis virus (CPsV) is the causal agent of psorosis, an important disease of citrus. Sanitary and certification programmes helped reduce disease damage caused by psorosis and other graft‐transmissible diseases in many citrus‐growing regions. For quarantine and certification programmes, most of these diseases are currently diagnosed using biological indexing (BI) on sensitive indicator plants. In the case of citrus psorosis, CPsV can be detected by molecular methods such as quantitative reverse transcription PCR (RT‐qPCR), which is cheaper and faster than BI, but sensitivity, reliability, and reproducibility of both procedures have not been compared so far. In this work, 128 plants from Argentina and Uruguay were analysed using BI and CPsV detection by the RT‐qPCR assay. Almost perfect agreement between both diagnostic procedures and sensitivity, specificity, and estimated likelihood ratios indicate that RT‐qPCR is equivalent to BI for citrus psorosis diagnosis, thus providing confidence in the quick diagnostic procedure to monitor the sanitary status of citrus trees. © 2021 British Society for Plant Pathology
653 $aCitrus psorosis virus
653 $aDiagnostic parameters
653 $aRT-qPCR
700 1 $aGÓMEZ, C.
700 1 $aBERTALMIO, A.
700 1 $aRUIZ, E.
700 1 $aHAUTEVILLE, C.
700 1 $aGODOY, L.
700 1 $aTITO, B.
700 1 $aGARCÍA, M.L.
773 $tPlant Pathology, May 2021, Volume 70, Issue 4, Pages 980-986. Doi: https://doi.org/10.1111/ppa.13341
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! |
|
|
