TITLE:
Community Characteristics Analysis of Eukaryotic Microplankton via ITS Gene Metabarcoding Based on Environmental DNA in Lower Reaches of Qiantang River, China
AUTHORS:
Aiju Zhang, Jun Wang, Yabin Hao, Shanshi Xiao, Wei Luo, Ganxiang Wang, Zhiming Zhou
KEYWORDS:
Microplankton, eDNA, Metabarcoding, ITS, Diversity, Qiantang River
JOURNAL NAME:
Open Journal of Animal Sciences,
Vol.11 No.2,
April
2,
2021
ABSTRACT: Eukaryotic microplankton plays an important role in water biotic community
and in maintaining the stability of water ecosystems. Environmental DNA metabarcoding
provides the opportunity to integrate traditional and emerging approaches to discover
more new species, and develop molecular biotic indices that can be more rapidly,
frequently, and robustly used in water quality assessments. In order to examine
assemblages of eukaryotic microplankton in lower reaches of Qiantang River, ITS
gene metabarcoding technology based on environmental DNA was carried out. As a result,
various species of phytoplankton, fungi and zooplankton were annotated on. More
phylum, classes and specieses of eukaryotic phytoplankton and zooplankton were found
after compared communities taxa based on metabarcoding with that obtained from morphological
examination. Nevertheless, Chlorophyceae was the most common assemblage both identified
by using these two methods, also Mesocyclops
leuckarti and Acanthocyclops
bicuspidatus were both found to be the dominant species of Cyclopoida
in the river. Additionally, the reads proportions of phytoplankton and zooplankton
at the three freshwater sampling sites (Tonglu, Fuyang and Wenyan) decreased as temperature
drop. Meanwhile, twenty classes of fungi were annotated on, of which the community
characteristic was first researched in the river. There were significant spatial differences in values of Chao1
index for eukaryotic microplankton. Cluster analysis and Non-metric multidimensional
scaling ordination further confirmed that the community composition of eukaryotic
microplankton at class level for Jiashao-September sample had the most dissimilarity
with the others.