High‐throughput identification of non‐marine Ostracoda from the Tibetan Plateau: Evaluating the success of various primers on sedimentary DNA samples

Autor: Paula Echeverría‐Galindo, Sten Anslan, Peter Frenzel, Sven Künzel, Miguel Vences, Liseth Pérez, Nicole Börner, Wengang Kang, Anja Schwarz, Junbo Wang, Ping Peng, Liping Zhu, Antje Schwalb
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Environmental DNA, Vol 3, Iss 5, Pp 982-996 (2021)
Druh dokumentu: article
ISSN: 2637-4943
DOI: 10.1002/edn3.222
Popis: Abstract Dwelling in a variety of aquatic habitats, one of the most abundant groups of microcrustaceans, ostracodes, are widely used indicator organisms in paleolimnological research. Typically, they are identified via traditional methods using morphological features but this may be excessively time‐consuming and prone to inter‐investigator variation. DNA barcoding and metabarcoding have become important tools for specimen identification, with a great impact in the field of taxonomy, (paleo‐)ecology and evolution. Despite its potential, metabarcoding has been rarely used to analyze the community structure of ostracodes. Here, we evaluate the performance of a metabarcoding approach for ostracode identification in surface sediment samples collected from Lake Nam Co on the Tibetan Plateau. We tested six different primer pairs amplifying fragments of three different genes, and compared their success in inferring ostracode communities, coupled with morphological identification of ostracodes from the same sediment samples. In total, depending on the primer pair used, seven to nineteen ostracode amplicon sequence variants (ASVs) were identified. Via microscopy, eight morphospecies were identified. We found considerable differences between primer pairs in yielding ostracode sequences via metabarcoding. In general, the highest proportions of ostracode reads and ASVs were found with primers amplifying fragments of the 18S rRNA gene, whereas primers for COI gene had the highest in silico amplification success and highest sequencing depth per sample but only contained
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