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ZENODO
Dataset . 2014
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Data sources: ZENODO
DRYAD
Dataset . 2014
License: CC 0
Data sources: Datacite
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Data from: Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies

Authors: Zimmermann, Jonas; Glöckner, Gernot; Jahn, Regine; Enke, Neela; Gemeinholzer, Birgit;

Data from: Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies

Abstract

Environmental barcoding Lusatian Neisse/Odra RiverHWFN2LX01.sffRL6.1AmphoraTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_AmphNCBI_20130419.mtsRL6.1CocconeisTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_CoccoNCBI_20130423.mtsRL6.1_EncyonemaTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_EncyoNCBI_20130423.mtsRL6.1_EolimnaTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_EolimnaNCBI_20130423.mtsRL6.1_FragilariaTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_FragiNCBI_20130418.mtsRL6.1_NaviculaTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_NaviNCBI_20130420.mtsRL6.1_NitzschiaTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_NitzNCBI_20130422.mtsRL6.1_PlanothidiumAchnanthidiumTreeThis .mts file was generated in MEGA 5 and may be opened in MEGA 5. To open in MEGA 6, export the tree to a .nwk file in MEGA 5 and open the .nwk file in MEGA 6.RL6.1_thidiumNCBI_20130417.mts

Diatoms are frequently used for water quality assessments; however, identification to species level is difficult, time-consuming and needs in-depth knowledge of the organisms under investigation, as nonhomoplastic species-specific morphological characters are scarce. We here investigate how identification methods based on DNA (metabarcoding using NGS platforms) perform in comparison to morphological diatom identification and propose a workflow to optimize diatom fresh water quality assessments. Diatom diversity at seven different sites along the course of the river system Odra and Lusatian Neisse from the source to the mouth is analysed with DNA and morphological methods, which are compared. The NGS technology almost always leads to a higher number of identified taxa (270 via NGS vs. 103 by light microscopy LM), whose presence could subsequently be verified by LM. The sequence-based approach allows for a much more graduated insight into the taxonomic diversity of the environmental samples. Taxa retrieval varies considerably throughout the river system, depending on species occurrences and the taxonomic depth of the reference databases. Mostly rare taxa from oligotrophic parts of the river systems are less well represented in the reference database used. A workflow for DNA-based NGS diatom identification is presented. 28 000 diatom sequences were evaluated. Our findings provide evidence that metabarcoding of diatoms via NGS sequencing of the V4 region (18S) has a great potential for water quality assessments and could complement and maybe even improve the identification via light microscopy.

Keywords

DNA-based Species Identification, Environmental DNA Barcoding, Recent, Next Generation Sequencing, Water Monitoring

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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