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OPTIMIZING eDNA METABARCODING IN INDONESIAN FRESHWATERS: A SCOPING REVIEW OF BEST PRACTICES

Jul 2026 · BIOTROPIA · Vol 33, pp. 403-412 · 0 citations · 28 references

TL;DR

A standardized workflow combining coarse pre-filtration, taxa-specific primers (e.g., MiFish for fish), and manual validation against expanded local databases to strengthen eDNA-based biodiversity assessments in Indonesia is recommended.

Abstract

ARTICLE HIGLIGHTS- Environmental DNA studies in Indonesian freshwaters remain uneven.- Multi-step filtering improves species detection and reduces false findings in tropical condition.- Taxa-specific primers detect native species better than broad-range primers.- Local databases and manual plausibility checks reduce wrong species matches.ABSTRACTIndonesian freshwater ecosystems harbor immense biodiversity yet remain understudied due to logistical constraints of conventional methods. Environmental DNA (eDNA) metabarcoding offers a noninvasive, high-resolution alternative for biodiversity monitoring, but its uptake in Indonesia is still nascent and methodologically heterogeneous. We reviewed 106 peer-reviewed studies (of which 28 studies were eligible) published between 2015 and 2025 across Google Scholar, PubMed, DOAJ, and GARUDA, charting sampling designs, molecular workflows, and bioinformatics pipelines. Studies were heavily skewed toward Java and West Sumatra (86%) and overwhelmingly employed filtration-based sampling. Broad-range COI and 12S markers dominated (39% and 36% of studies, respectively), whereas fish-specific MiFish-U primers, demonstrating superior sensitivity and specificity, were only used in 14% of cases. Correspondingly, non-specific primer in shotgun metagenomics proven imprudent. Studies using 0.22 µm filters collected a lot of species as much as non-target amplification, while 0.45 µm filters performed inconsistently. Bioinformatics approaches (QIIME2, DADA2, mBRAVE) differed widely but showed no clear impact on detection outcomes. Key limitations included geographic and taxonomic biases, poor reference library coverage, and a lack of expert-driven plausibility checks. We recommend a standardized workflow combining coarse pre-filtration, taxa-specific primers (e.g., MiFish for fish), and manual validation against expanded local databases to strengthen eDNA-based biodiversity assessments in Indonesia.

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