Establishing a COI DNA barcoding reference database for Taiwanese coastal fish species from egg and larvae specimens

TL;DR

This study creates a DNA barcoding reference database for fish eggs and larvae in Taiwan's coastal waters to improve species identification and support marine conservation.

Contribution

The study provides a comprehensive DNA barcoding reference database for 844 fish species using egg and larval specimens from Taiwan's coastal waters.

Findings

DNA barcoding identified 844 fish species from 7602 egg and larval records collected between 2004 and 2023.

The database includes 24 orders, 158 families, and 500 genera of fish, enhancing species identification accuracy.

The database supports eDNA and DNA metabarcoding methods for studying marine biodiversity and fisheries.

Abstract

Fish eggs and larval stages are essential components of marine ecosystems and play important roles in sustaining marine food webs. However, the egg and larval stages often lack distinct diagnostic characteristics, making it challenging to identify species solely based on their morphology. In this study, we applied a DNA barcoding approach targeting the cytochrome c oxidase subunit I gene to establish a comprehensive reference for fish eggs and larval material in coastal waters off Taiwan. A total of 7602 records of fish eggs and larvae were collected from marine coastal waters surrounding Taiwan between 2004 and 2023 and identified using a DNA barcoding approach. By comparing our newly generated DNA barcoding sequences with records from public reference databases, we identified 1112 different fish taxa encompassing 24 orders, 158 families, 500 genera, and 844 fish species. This DNA barcoding referencing effort will facilitate future studies on the early life stages of Taiwanese coastal marine fish communities. In addition, it will also provide an important baseline for the development of new methods, such as eDNA and DNA metabarcoding diet analysis. This database provides comprehensive spatial and temporal distribution data of fish eggs and larvae in the waters surrounding Taiwan, contributing to a better understanding of fish spawning seasons, spawning grounds, and resource fluctuations. This database enhances the accuracy of species identification and serves as a scientific foundation for biodiversity conservation and fishery resource management.

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