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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
12/11/2015 |
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Actualizado : |
28/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
BENÍTEZ-GALEANO, M.J.; RUBIO, L.; BERTALMIO, A.; MAESO, D.; RIVAS, F.; COLINA, R. |
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Afiliación : |
MARÍA JOSÉ BENÍTEZ-GALEANO, Universidad de la República (UdelaR)/ Centro Universitario Regional Noroeste, Salto (CENUR); LETICIA PAOLA RUBIO CATTANI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANA MARIA BERTALMIO CASARIEGO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO CESAR MAESO TOZZI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS FERNANDO RIVAS GRELA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RODNEY COLINA, Universidad de la República (UdelaR)/ Centro Universitario Regional Noroeste, Salto (CENUR). |
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Título : |
Phylogenetic studies of the three RNA silencing suppressor genes of south american ctv isolates reveal the circulation of a novel genetic lineage. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Viruses, 2015, v.7, no.7, p.4152-4168. OPEN ACCESS. |
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ISSN : |
1999-4915 |
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DOI : |
10.3390/v7072814 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 26 May 2015 / Accepted: 17 July 2015 / Published: 22 July 2015. |
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Contenido : |
ABSTRACT.
Citrus Tristeza Virus (CTV) is the most economically important virus of citrus worldwide. Genetic diversity and population structure of CTV isolates from all citrus growing areas from Uruguay were analyzed by RT-PCR and cloning of the three RNA silencing suppressor genes (p25, p20 and p23). Bayesian phylogenetic analysis revealed the circulation of three known genotypes (VT, T3, T36) in the country, and the presence of a new genetic lineage composed by isolates from around the world, mainly from South America. Nucleotide and amino acid identity values for this new genetic lineage were both higher than 97% for the three analyzed regions. Due to incongruent phylogenetic relationships, recombination analysis was performed using Genetic Algorithms for Recombination Detection (GARD) and SimPlot software. Recombination events between previously described CTV isolates were detected. High intra-sample variation was found, confirming the co-existence of different genotypes into the same plant. This is the first report describing: (1) the genetic diversity of Uruguayan CTV isolates circulating in the country and (2) the circulation of a novel CTV genetic lineage, highly present in the South American region. This information may provide assistance to develop an effective cross-protection program. |
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Palabras claves : |
CITRUS TRISTEZA VIRUS; RT-PCR. |
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Thesagro : |
CITRUS; CRUZAMIENTO INTERCROMOSOMICO; FILOGENIA; RECOMBINACION; URUGUAY. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5167/1/Rivas-F.-Maeso-D.-2015.-Viruses.pdf
http://www.mdpi.com/1999-4915/7/7/2814
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Marc : |
LEADER 02270nam a2200289 a 4500
001 1053851
005 2019-10-28
008 2015 bl uuuu u0uu1 u #d
022 $a1999-4915
024 7 $a10.3390/v7072814$2DOI
100 1 $aBENÍTEZ-GALEANO, M.J.
245 $aPhylogenetic studies of the three RNA silencing suppressor genes of south american ctv isolates reveal the circulation of a novel genetic lineage.$h[electronic resource]
260 $aViruses, 2015, v.7, no.7, p.4152-4168. OPEN ACCESS.$c4168
500 $aArticle history: Received: 26 May 2015 / Accepted: 17 July 2015 / Published: 22 July 2015.
520 $aABSTRACT. Citrus Tristeza Virus (CTV) is the most economically important virus of citrus worldwide. Genetic diversity and population structure of CTV isolates from all citrus growing areas from Uruguay were analyzed by RT-PCR and cloning of the three RNA silencing suppressor genes (p25, p20 and p23). Bayesian phylogenetic analysis revealed the circulation of three known genotypes (VT, T3, T36) in the country, and the presence of a new genetic lineage composed by isolates from around the world, mainly from South America. Nucleotide and amino acid identity values for this new genetic lineage were both higher than 97% for the three analyzed regions. Due to incongruent phylogenetic relationships, recombination analysis was performed using Genetic Algorithms for Recombination Detection (GARD) and SimPlot software. Recombination events between previously described CTV isolates were detected. High intra-sample variation was found, confirming the co-existence of different genotypes into the same plant. This is the first report describing: (1) the genetic diversity of Uruguayan CTV isolates circulating in the country and (2) the circulation of a novel CTV genetic lineage, highly present in the South American region. This information may provide assistance to develop an effective cross-protection program.
650 $aCITRUS
650 $aCRUZAMIENTO INTERCROMOSOMICO
650 $aFILOGENIA
650 $aRECOMBINACION
650 $aURUGUAY
653 $aCITRUS TRISTEZA VIRUS
653 $aRT-PCR
700 1 $aRUBIO, L.
700 1 $aBERTALMIO, A.
700 1 $aMAESO, D.
700 1 $aRIVAS, F.
700 1 $aCOLINA, R.
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Registro original : |
INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
04/01/2018 |
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Actualizado : |
30/01/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
GONZALEZ-BARRIOS, P.; CASTRO, M.; PÉREZ, O.; VILARÓ, D.; GUTIÉRREZ, G. |
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Afiliación : |
PABLO GONZALEZ-BARRIOS,; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSVALDO MARTIN PÉREZ GONZÁLEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO VILARÓ; LUCÍA GUTIÉRREZ. |
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Título : |
Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Spanish Journal of Agricultural Research, v.15. n.4, e0705, 2017. |
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DOI : |
10.5424/sjar/2017154-11016 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 06 Jan 2017, Accepted: 01 Dec 2017. |
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Contenido : |
Abstract:
Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars. MenosAbstract:
Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and f... Presentar Todo |
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Palabras claves : |
GENOTYPE BY ENVIRONMENT INTERACTION; MULTI-ENVIRONMENT TRIALS; NETWORK EFFICIENCY; SUNFLOWER; YIELD STABILITY. |
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Thesagro : |
GIRASOL; INTERACCIÓN GENOTIPO AMBIENTE. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/8628/1/SJAR.2017.v.15.n.4.pdf
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Marc : |
LEADER 02709naa a2200277 a 4500
001 1057950
005 2020-01-30
008 2017 bl uuuu u00u1 u #d
024 7 $a10.5424/sjar/2017154-11016$2DOI
100 1 $aGONZALEZ-BARRIOS, P.
245 $aGenotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency.$h[electronic resource]
260 $c2017
500 $aArticle history: Received: 06 Jan 2017, Accepted: 01 Dec 2017.
520 $aAbstract: Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars.
650 $aGIRASOL
650 $aINTERACCIÓN GENOTIPO AMBIENTE
653 $aGENOTYPE BY ENVIRONMENT INTERACTION
653 $aMULTI-ENVIRONMENT TRIALS
653 $aNETWORK EFFICIENCY
653 $aSUNFLOWER
653 $aYIELD STABILITY
700 1 $aCASTRO, M.
700 1 $aPÉREZ, O.
700 1 $aVILARÓ, D.
700 1 $aGUTIÉRREZ, G.
773 $tSpanish Journal of Agricultural Research$gv.15. n.4, e0705, 2017.
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