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Comparing eDNA metabarcoding primers for assessing fish communities in a biodiverse estuary
Girish Kumar1, Ashley M Reaume1, Emily Farrell1
1Department of Biology, University of Central Florida, Genomics and Bioinformatics Cluster, Orlando, FL, United States of America.
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.
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.
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