English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/113209
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


Identification and quantification of two species of oyster larvae using real time PCR

AuthorsSánchez, Ana Cristina ; Quinteiro, Javier; Rey Méndez, Manuel; Pérez Martín, Ricardo Isaac ; González Sotelo, Carmen
KeywordsReal-time PCR
Oyster larvae identification
Species identification
16S rRNA
Issue Date2014
PublisherEDP Sciences
CitationAquatic Living Resources 27(3-4): 35-145 (2014)
AbstractA real-time polymerase chain reaction (PCR) assay was developed for the identification and quantification of two oyster species: Ostrea edulis and Crassostrea gigas. Two sets of primers and TaqMan-MGB probes were designed, based on partial sequences of the 16S rRNA gene. An amplification positive control system was also located in the 18S rRNA gene sequences. Closely related species of oysters and other bivalves, known to co-occur with the target species in European waters, were used to test the assay for cross-reactivity. The assay designed was specific for the target species and no signal or no significant signal was detected for all non-target species tested. The high sensitivity of this method was demonstrated since it is possible to detect just one larva (150–200 μm size) of each species even when it is present with others. Furthermore, this assay provided an acceptable quantification of the number of spiked larvae (1, 10 and 100 larvae) in plankton samples employing a standard curve for larvae
Description13 páginas, 3 figuras
Publisher version (URL)http://dx.doi.org/10.1051/alr/2014012
Appears in Collections:(IIM) Artículos
Files in This Item:
File Description SizeFormat 
Identification_quantification_oyster.doc115 kBMicrosoft WordView/Open
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.