English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/25159
Compartir / Impacto:
Estadísticas
Add this article to your Mendeley library MendeleyBASE
Citado 50 veces en Web of Knowledge®  |  Pub MebCentral Ver citas en PubMed Central  |  Ver citas en Google académico
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Título

Molecular Taxonomy of Phytopathogenic Fungi: a Case Study in Peronospora

AutorGöker, M.; García Blázquez, Gema; Voglmayr, H.; Tellería, M. T.; Martín, María P.
Fecha de publicación2009
CitaciónPLoS ONE 4(7): e6319 (2009)
ResumenBackground: Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms. Methodology: Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews. Conclusions: A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence.
Versión del editorhttp://www.plosone.org/article/info:doi/10.1371/journal.pone.0006319
URIhttp://hdl.handle.net/10261/25159
DOI10.1371/journal.pone.0006319
ISSN1932-6203
Aparece en las colecciones: (RJB) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
2009_Martin_PlosOne_4(7).pdf747,21 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 



NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.