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1.
Plant Dis ; 104(1): 137-146, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31730415

RESUMO

Mango anthracnose, caused by Colletotrichum spp., is the most significant disease of mango (Mangifera indica L.) in almost all production areas around the world. In Mexico, mango anthracnose has only been attributed to C. asianum and C. gloeosporioides. The aims of this study were to identify the Colletotrichum species associated with mango anthracnose symptoms in Mexico by phylogenetic inference using the ApMat marker, to determine the distribution of these species, and to test their pathogenicity and virulence on mango fruits. Surveys were carried out from 2010 to 2012 in 59 commercial orchards in the major mango growing states of Mexico, and a total of 118 isolates were obtained from leaves, twigs, and fruits with typical anthracnose symptoms. All isolates were tentatively identified in the C. gloeosporioides species complex based on morphological and cultural characteristics. The Bayesian inference phylogenetic tree generated with Apn2/MAT intergenic spacer sequences of 59 isolates (one per orchard) revealed that C. alienum, C. asianum, C. fructicola, C. siamense, and C. tropicale were associated with symptoms of mango anthracnose. In this study, C. alienum, C. fructicola, C. siamense, and C. tropicale are reported for the first time in association with mango tissues in Mexico. This study represents the first report of C. alienum causing mango anthracnose worldwide. The distribution of Colletotrichum species varied among the mango growing states from Mexico. Chiapas was the only state in which all five species were found. Pathogenicity tests on mango fruit cultivar Manila showed that all Colletotrichum species from this study could induce anthracnose lesions. However, differences in virulence were evident among species. C. siamense and C. asianum were the most virulent, whereas C. alienum and C. fructicola were considered the least virulent species.


Assuntos
Colletotrichum , Mangifera , Filogenia , Teorema de Bayes , Colletotrichum/classificação , Colletotrichum/genética , Colletotrichum/patogenicidade , Colletotrichum/fisiologia , DNA Fúngico/genética , Mangifera/microbiologia , México , Filipinas , Doenças das Plantas/microbiologia , Virulência
2.
Theor Appl Genet ; 111(7): 1260-70, 2005 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-16179997

RESUMO

The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n = 409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods-resampling, selective genotyping, and selective phenotyping-to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.


Assuntos
Basidiomycota , Mapeamento Cromossômico/métodos , Hordeum/genética , Imunidade Inata/genética , Doenças das Plantas/microbiologia , Densidade Demográfica , Locos de Características Quantitativas , Análise de Variância , Cruzamento/métodos , Cruzamentos Genéticos , México , Doenças das Plantas/genética , Washington
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