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Comparing eDNA metabarcoding primers for assessing fish communities in a biodiverse estuary.

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  • 1Department of Biology, University of Central Florida, Genomics and Bioinformatics Cluster, Orlando, FL, United States of America.

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Comparing environmental DNA (eDNA) metabarcoding primers for fish surveys revealed the Riaz_12S primer set as most effective. This study highlights the importance of selecting appropriate primers for accurate aquatic biodiversity assessments.

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Area of Science:

  • Environmental DNA (eDNA) metabarcoding
  • Aquatic biodiversity assessment
  • Molecular ecology

Background:

  • Metabarcoding of environmental DNA is a powerful tool for assessing aquatic biodiversity.
  • Primer selection significantly impacts the efficiency and outcomes of eDNA metabarcoding studies.
  • Limited comparative studies exist for marine and estuarine fish metabarcoding primers.

Purpose of the Study:

  • To evaluate and compare the performance of five commonly used fish metabarcoding primer sets.
  • To identify the most effective primer set for eDNA-based fish surveys in estuarine systems.

Main Methods:

  • Collected water samples from estuarine sites in the Indian River Lagoon, Florida.
  • Amplified target genes (12S, 16S, 18S rRNA) using five different primer sets.
  • Analyzed metabarcoding reads to identify fish species and compare primer set efficacy.

Main Results:

  • The Riaz_12S and Berry_16S primer sets detected a comparable and higher number of fish species (55 and 49) than MiFish_12S and Valentini_12S (34 and 32).
  • The 18S primer set showed poor specificity, with most reads assigned to non-fish taxa.
  • The Riaz_12S primer set detected the most elasmobranch species (six) and was identified as the most effective overall for fish surveys.

Conclusions:

  • Primer choice critically influences the results of eDNA metabarcoding for fish biodiversity assessments.
  • The Riaz_12S primer set demonstrated superior performance for detecting fish diversity in this estuarine system.
  • Employing multiple primer sets targeting different genomic regions can enhance comprehensive biodiversity detection.