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1.
Phytopathology ; 107(9): 1000-1010, 2017 09.
Artigo em Inglês | MEDLINE | ID: mdl-28513284

RESUMO

Population genetic analysis is a powerful tool to understand how pathogens emerge and adapt. However, determining the genetic structure of populations requires complex knowledge on a range of subtle skills that are often not explicitly stated in book chapters or review articles on population genetics. What is a good sampling strategy? How many isolates should I sample? How do I include positive and negative controls in my molecular assays? What marker system should I use? This review will attempt to address many of these practical questions that are often not readily answered from reading books or reviews on the topic, but emerge from discussions with colleagues and from practical experience. A further complication for microbial or pathogen populations is the frequent observation of clonality or partial clonality. Clonality invariably makes analyses of population data difficult because many assumptions underlying the theory from which analysis methods were derived are often violated. This review provides practical guidance on how to navigate through the complex web of data analyses of pathogens that may violate typical population genetics assumptions. We also provide resources and examples for analysis in the R programming environment.


Assuntos
Genética Populacional/métodos , Marcadores Genéticos , Doenças das Plantas/microbiologia
2.
Phytopathology ; 105(4): 542-9, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-25317843

RESUMO

The purpose of this study was to determine the fine-scale genetic structure of populations of the brown rot pathogen Monilinia fructicola within individual peach tree canopies to better understand within-tree plant pathogen diversity and to complement previous work on spatiotemporal development of brown rot disease at the canopy level. Across 3 years in a total of six trees, we monitored disease development, collected isolates from every M. fructicola symptom during the course of the season, and created high-resolution three-dimensional maps of all symptom and isolate locations within individual canopies using an electromagnetic digitizer. Each canopy population (65 to 173 isolates per tree) was characterized using a set of 13 microsatellite markers and analyzed for evidence of spatial genetic autocorrelation among isolates during the epidemic phase of the disease. Results showed high genetic diversity (average uh=0.529) and high genotypic diversity (average D=0.928) within canopies. The percentage of unique multilocus genotypes within trees was greater for blossom blight isolates (78.2%) than for fruit rot isolates (51.3%), indicating a greater contribution of clonal reproduction during the preharvest epidemic. For fruit rot isolates, between 54.2 and 81.7% of isolates were contained in one to four dominant clonal genotypes per tree having at least 10 members. All six fruit rot populations showed positive and significant spatial genetic autocorrelation for distance classes between 0.37 and 1.48 m. Despite high levels of within-tree pathogen diversity, the contribution of locally available inoculum combined with short-distance dispersal is likely the main factor generating clonal population foci and associated spatial genetic clustering within trees.


Assuntos
Ascomicetos/genética , Variação Genética , Doenças das Plantas/microbiologia , Prunus/microbiologia , Ascomicetos/isolamento & purificação , Flores/microbiologia , Frutas/microbiologia , Genética Populacional , Genótipo , Repetições de Microssatélites/genética , Fenótipo , Doenças das Plantas/estatística & dados numéricos , Folhas de Planta/genética , Análise Espacial
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