Author
Skantar, Andrea | |
ROBERTSON, LEE - Consejo Superior De Investigaciones Cientificas (CSIC) | |
CASTAGNONE-SERENO, PHILIPPE - Institut National De La Recherche Agronomique (INRA) |
Submitted to: Genomics
Publication Type: Book / Chapter Publication Acceptance Date: 1/31/2011 Publication Date: 5/18/2011 Citation: Castagnone-Sereno, P., Skantar, A.M., Robertson, L. 2011. Molecular tools for diagnostics. In: Jones, J., Fenoll, C., Gheysen, G., editors. Genomics and Molecular Genetics of Plant-Nematode Interactions. New York, NY: Springer Science + Business Media B.V. p. 443-464. Interpretive Summary: Technical Abstract: About 25,000 species of nematodes have been described, among which more than 4,000 are parasites of plants. However, estimates of the total number of nematode species on the planet vary from 100,000 to several million, and thus the actual total number of plant-parasitic nematode (PPN) species is likely to be several-fold higher than is currently known. Due to morphological variation, nematodes are among the most difficult animals to identify. In addition, their small size and location below ground make most PPN species difficult to detect. Traditional diagnostics relies on the delineation of morphological features, but the intraspecific variability of these frequently obscure characters renders reliable identification a formidable task, even for well-qualified taxonomists. Nonetheless, correct identification to the species level is an absolute prerequisite for the implementation of successful management strategies against PPNs. DNA-based technologies, which are largely independent of phenotypic variation, have provided numerous avenues to overcome such limitations. In the past 25 years, plant nematologists have increasingly employed molecular techniques for diagnostic purposes. In the present chapter, we review the DNA technological approaches and advances made in the definition and use of molecular markers for the specific identification of PPNs and explore the fast-evolving methodologies that are being developed to provide diagnostics with greater robustness, precision and speed. |