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Abstract Detail

Ecological Section

Gemeinholzer, Birgit [1], Zimmermann, Jonas [1], Jahn, Regine [1].

Establishing DNA-Barcoding Methods in Diatoms for Diversity Assessments.

Diatoms are single-celled eucaryotes, being responsible for ~20 % of the global carbon fixations through photosynthesis. They are important bio-indicators to monitor water quality being sensitive to pollution and contamination, trophies, as well as acidification, and salinisation. Diatoms are suited for water quality assessments as it is the only group of microscopic algae which is present in all water sources. Continuous screening of algal biodiversity can provide information about threatened ecosystems. Thus diatoms are an ideal model group to establish DNA-Barcoding methods to provide an easy to use, quick, efficient, standardised organism identification tool to serve routine water quality assessments. Method optimisation is the main task of this project. A pilot study was carried out by identifying diatoms via light microscope from a water sample (Tegeler See in Berlin/Germany). Total genomic DNA was isolated, the 18S region was amplified using diatom specific priming sites and the fragments were cloned, picked, and sequenced. The sequences were checked against a database (AlgaTerra). 62 different diatom species were identified by light microscopy and 62 species by DNA-Barcoding methods. However, results were not completely congruent; but most taxa identified by molecular means were potentially known to occur at the sample site which elucidates the potential of DNA-Barcoding for water quality assessments. In subsequent trials, we tested if other DNA regions are more suitable for species identification (cox1, rbcL, psbA, ITS, psaA, 16S nad5, rpoC1 cob, nad1, atp1, ycf5, 23S) and 2) and provide a standardized barcoding protocol. To test quality and quantity of diatom retrieval we created an artificial mix of DNA from cultured diatom clones to test if qualitative retrieval-rate is sufficient, and how far it is possible to quantify the taxa composition in mixed samples. At present retrieval-rates are up to 80 % in artificial samples but quantification is rather challenging.

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1 - Botanic Garden and Botanical Museum Berlin-Dahlem, Free University Berlin, Koenigin-Luise-Straße 6-8, Berlin, 14195, Germany

none specified

Presentation Type: Poster:Posters for Sections
Session: P
Location: Ball Room & Party Room/SUB
Date: Monday, July 28th, 2008
Time: 12:30 PM
Number: PEC005
Abstract ID:141

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