Identificação e validação de marcadores microssatélites ligados ao gene Rpp5 de resistência à ferrugem-asiática-da-soja

Morceli, Thaiza Galhardo Silva; Trevisoli, Sandra Helena Unêda; Morceli, Antonio Ayrton; Kiihl, Romeu Afonso de Souza; Calvo, Éberson Sanches; Mauro, Antônio Orlando Di; Garcia, Alexandre

doi:10.1590/s0100-204x2008001100011

Cited by 17 publications

(13 citation statements)

References 23 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Recentemente, no Brasil, diversos trabalhos têm sido realizados para se conhecer os mecanismos de resistência à ferrugem-asiática-da-soja, sejam estes qualitativos (Santos et al, 2007;Silva et al, 2007;Costa et al, 2008;Laperuta et al, 2008;Morceli et al, 2008) ou quantitativos (Koga et al, 2008;Ribeiro et al, 2009aRibeiro et al, , 2009bCruz et al, 2011). A associação de mecanismos qualitativos, por meio da piramidação de genes de resistência, e de mecanismos quantitativos, de resistência horizontal, deve ser utilizada como estratégia dos programas de melhoramento de soja, para que se possa obter resistência mais duradoura.…”

Section: Iniciadorunclassified

Variabilidade genética de Phakopsora pachyrhizi avaliada por meio de marcadores microssatélites

Tschurtschenthaler

Vieira

Nora³

et al. 2012

Pesq. agropec. bras.

View full text Add to dashboard Cite

Resumo -O objetivo deste trabalho foi avaliar a variabilidade genética da ferrugem-asiática-da-soja no Brasil, com uso de marcadores microssatélites. Populações de esporos de Phakopsora pachyrhizi coletadas nas regiões Sul, Sudeste e Centro Oeste do país foram submetidas à análise de variabilidade genética, avaliada por meio de marcadores microssatélites específicos para o fungo. Foram coletadas, também, populações de fungo em diversas variedades de soja em uma mesma localidade, incluindo populações com lesão "reddish-brown" (RB). Entre essas populações, não houve variabilidade. Tecidos com lesões RB não apresentaram esporos do fungo e não amplificaram com os marcadores específicos para P. pachyrhizi. A variabilidade genética entre as populações coletadas nas três regiões variou de 0 a 0,36. Observou-se tendência de agrupamento das populações da região Sul e Centro Oeste do Brasil em grupos diferentes. A existência de variabilidade genética em populações de P. pachyrhizi é um indicativo de que a resistência genética vertical, conferida por genes únicos, é uma estratégia de risco para os programas de melhoramento genético que visam a resistência à ferrugem-asiática-da-soja no Brasil.Termos para indexação: Glycine max, diversidade genética, ferrugem-asiática-da-soja, resistência genética, resistência vertical, SSR. Genetic variability of Phakopsora pachyrhizi accessed by microsatellite markersAbstract -The objective of this work was to evaluate the genetic variability of Asian soybean rust in Brazil using microsatellite markers. Samples of Phakopsora pachyrhizi spores collected in the Southern, Southeastern, and Central West regions of Brazil were subjected to analysis of genetic variability, accessed with microsatellite markers specific for the fungus. Spores of the fungus were also collected in several soybean varieties in a same locality, including samples with reddish-brown (RB) lesions. Among these samples, there was no variability. Tissues with RB lesions did not contain spores of the fungus and did not amplify with the specific markers for P. pachyrhizi. Genetic variability among samples collected in the three regions ranged from 0 to 0.36. A tendency to cluster samples of the Southern and Central West regions of Brazil in different groups was observed. The existence of genetic variability in P. pachyrhizi spore populations indicates that vertical genetic resistance, provided by single genes, is a risky strategy for soybean breeding programs that aim resistance to Asian soybean rust.

show abstract

Section: Iniciadorunclassified

Variabilidade genética de Phakopsora pachyrhizi avaliada por meio de marcadores microssatélites

Tschurtschenthaler

Vieira

Nora³

et al. 2012

Pesq. agropec. bras.

View full text Add to dashboard Cite

show abstract

“…One way to minimize the damage caused by this disease is to use resistant varieties, obtained in breeding programs (Alvarenga et al, 2011). In this context, plant genome sequencing and identification of molecular markers associated with resistance have been used to assist breeding programs (Morceli et al, 2008;Alvarenga et al, 2011). Among the statistical methods based on molecular markers, genome wide selection (GWS) is a technique that has been widely used for selecting materials with higher performance based on information from molecular markers.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee

Silva

Nascimento

Sant’Anna³

et al. 2017

Pesq. agropec. bras.

View full text Add to dashboard Cite

-The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F 2 population derived from the self-fertilization of the F 1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped, while the Bayesian generalized model identified only two markers belonging to these groups. Lower prediction error rates (1.60%) were observed for predicting leaf rust resistance in Arabica coffee when artificial neural networks were used instead of Bayesian generalized linear regression (2.4%). The results showed that artificial neural networks are a promising approach for predicting leaf rust resistance in Arabica coffee.Index terms: Coffea arabica, Hemileia vastatrix, artificial intelligence, molecular markers, prediction. Redes neurais artificiais comparadas com modelos lineares generalizados sob o enfoque bayesiano para predição de resistência à ferrugem em café arábicaResumo -O objetivo deste trabalho foi avaliar o uso de redes neurais artificiais em comparação à modelagem por meio de modelos lineares generalizados na predição de resistência à ferrugem em café arábica (Coffea arabica). Foram utilizados 245 indivíduos provenientes de uma população F 2 , oriundos da autofecundação do híbrido F 1 H511-1, resultante do cruzamento da cultivar suscetível Catuaí Amarelo IAC 64 (UFV 2148-57) e do genitor resistente Híbrido de Timor (UFV 443-03). Os 245 indivíduos foram genotipados com 137 marcadores. Realizaram-se análises com redes neurais artificiais e com modelos lineares generalizados sob o enfoque bayesiano. As redes neurais identificaram quatro marcadores importantes pertencentes a grupos de ligação que foram recentemente mapeados, enquanto o modelo generalizado bayesiano identificou somente dois marcadores pertencentes a esses grupos. Foram observadas taxas de erro de predição inferiores (1,60%) para predizer a resistência à ferrugem em café arábica, quando foram utilizadas as redes neurais artificiais em vez de modelos lineares generalizados sob o enfoque bayesiano (2,4%). Os resultados mostraram que as redes neurais artificiais são uma abordagem promissora para predizer a resistência à ferrugem em café arábica.Termos para indexação: Coffea arabica, Hemileia vastatrix, inteligência artificial, marcadores moleculares, predição.

show abstract

“…Five genes for ASR resistance have already been identified, as Rpp1 -PI 200492 (McLean and Byth 1980), Rpp2 -PI 230970 (Bromfield and Hartwig 1980), Rpp3 -PI 462312 Hartwig 1980, 1983), Rpp4 -PI 459025 (Hartwig 1986) and Rpp5 (Parker et al 1993, Grant et al 2000, Hayes et al 2000, Graham et al 2002, Morceli et al 2008. All these genes confer vertical resistance for only some races of P. pachyrhizi and the resistance conferred by these genes has already been broken in most soybean crop regions in Brazil.…”

Section: Introductionmentioning

confidence: 99%

“…All these genes confer vertical resistance for only some races of P. pachyrhizi and the resistance conferred by these genes has already been broken in most soybean crop regions in Brazil. However, it was shown that the markers linked to gene Rpp5 are useful in the assisted selection, in early stages of plant development and pathogen absence, which streamlines the most promising genotypes selection (Morceli et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Characterization of soybean genotypes for Asian soybean rust reaction

Araujo

Vello²

2010

Crop Breed. Appl. Biotechnol.

View full text Add to dashboard Cite

Our objective was to characterize soybean experimental lines for Asian soybean rust reaction. In the 2004/2005 growing season, three experiments were conducted with middle-cycle and three with late-cycle genotypes, designed in randomized blocks with four replications. Twelve experimental lines and two cultivars of each cycle were used. In each experiment the plant management differs as follows: three applications of carbendazim or three of flutriafol or without applications. The experimental lines with high yield, low notes to the symptoms and resistance to lodging, were selected and tested again in the 2005/2006 growing season. Genotypes with high severity and yield were considered tolerant to rust and the low severity and high yield ones as moderately resistant. Among the medium-cycle genotypes, there was moderate resistance to rust in one line and tolerance in five. Among the late-cycle genotypes, the six lines showed moderate resistance. The line USP 97-08135 is more tolerant to rust.

show abstract

Identificação e validação de marcadores microssatélites ligados ao gene Rpp5 de resistência à ferrugem-asiática-da-soja

Cited by 17 publications

References 23 publications

Variabilidade genética de Phakopsora pachyrhizi avaliada por meio de marcadores microssatélites

Variabilidade genética de Phakopsora pachyrhizi avaliada por meio de marcadores microssatélites

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee

Characterization of soybean genotypes for Asian soybean rust reaction

Contact Info

Product

Resources

About