Communities of zooplankton can be adversely affected by contamination resulting from human activities. Yet understanding the influence of water quality on zooplankton under field-conditions is hindered by traditional labor-intensive approaches that are prone to incomplete or uncertain taxonomic determinations. Here, for the first time, an eco-genomic approach, based on genetic diversity in the mitochondrial cytochrome c oxidase I (COI) region of DNA of zooplankton was used to develop a site-specific, water quality criterion (WQC) for ammonia (NH). Ammonia has been recognized as a primary stressor in the catchment of the large, eutrophic Tai Lake, China. Nutrients, especially NH and nitrite (NO) had more significant effects on structure of the zooplankton community than did other environmental factors. Abundances of rotifers increased along a gradient of increasing concentrations of total ammonia nitrogen (TAN), while abundances of copepods and cladocera decreased. A novel, rapid, species sensitivity distribution (SSD) approach based on operational taxonomic units (OTUs) was established to develop a WQC for NH. The WQC based on OTUs was consistent with the WQC based on the traditional morphology taxonomy approach. This genetics-based SSD approach could be a useful tool for monitoring for status and trends in species composition and deriving ecological criteria and an efficient biomonitoring tool to protect local aquatic ecosystems in virtually any aquatic ecosystem.
Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton.
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