Environmental DNA metabarcoding of intertidal meiofauna sheds light on its potential for habitat discovery

Meng Wang, Timur Yergaliyev, Changhai Sun, Joey Genevieve Martinez, Beixin Wang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Benthic meiofauna is a fundamental component of food webs and nutrient exchange of marine ecosystems. However, its diversity pattern and ecology of intertidal meiofauna remain poorly understood because the studies are often constrained by morphology-based species identification. Environmental DNA metabarcoding is a powerful tool to overcome this limitation. In the present study, we assessed the intertidal meiofauna diversity and their correlations with environmental variables using eDNA metabarcoding approach with both 18S rRNA and two COI markers. The 18S rRNA marker suggested Nematoda (32.1%), Arthropoda (10.5%), and Cercozoa (8.0%) were the three most abundant phyla while COI primers show strong biased towards either Arthropoda or Nematoda and generated inconsistent results when using different reference databases. The correlation analysis showed that most examined environmental factors were strongly associated with community separation, but only salinity, the content of clay, and pheophorbide were found to be significant. The eDNA metabarcoding recovered a terrestrial nematode belonging to the genus Acrobeloides in a marine-related environment. Further resampling and laboratory experiments confirmed this species is tolerant to high salinity concentrations, suggesting eDNA metabarcoding recovery is consistent with the laboratory experiment. This result demonstrated eDNA metabarcoding can be a promising tool for high-throughput new habitat discovery in meiofauna.

Original languageEnglish
Article number110223
JournalEcological Indicators
Volume150
DOIs
StatePublished - 1 Jun 2023
Externally publishedYes

Keywords

  • Acrobeloides
  • Environmental variables
  • Marine biodiversity
  • Nematoda
  • Sediment DNA

ASJC Scopus subject areas

  • General Decision Sciences
  • Ecology, Evolution, Behavior and Systematics
  • Ecology

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