Molecular identification and temporal genetic differentiation of Cyprinus carpio (Cypriniformes: Cyprinidae) eggs attached on artificial fish nests

Identifying fish eggs and larvae: from classic methodologies to DNA metabarcoding

Studies involving fish eggs and larvae date back to the end of the nineteenth century. Since then, studies with ichthyoplankton have proved to be an essential tool, generating information for the knowledge of the ichthyofauna and the environmental inventory. Most of these studies reveal the difficulty of obtaining a precise taxonomic identification of the collected materials, making research with ichthyoplankton extremely challenging. With the advent of molecular biology, the use of markers such as COI enabled greater taxonomic precision, helping to understand events involving ichthyofauna. Now we can observe the evolution of the molecular identification tool for ichthyoplankton via DNA barcoding, which has been increasingly used over the last few decades. From 2000 to 2010, we found six publications; from 2011 to 2021, 75 papers were published, and in 2022 four studies. Our survey also showed the accuracy of molecular identification when compared to the taxonomic identification of these. In this review, we show the state of the art of studies that used barcode and DNA metabarcoding to identify fish eggs and larvae in different environments and discuss their importance as the best practice for working with these organisms.

DNA barcoding reveals the temporal community composition of drifting fish eggs in the lower Hongshui River, China

Determining the temporal community composition of fish eggs in particular regions and understanding the reproductive times of regional fish taxa are key aspects of the management and regulation of regional fish stocks. However, it is extremely difficult to accurately identify fish eggs due to the absence of diagnostic morphological characters. We sampled fish eggs in the lower Hongshuihe River (an upper mainstem of the Pearl River) between May and September 2020. We then used DNA barcoding to determine the species composition of the egg pool and to predict the spawning periods of the identified species. A total of 641 eggs and 17 larvae were chosen for molecular identification; 397 eggs and 17 larvae yielded high-quality barcoding sequences. The high failure rate (~38%) was most likely due to long-term storage in low concentrations of ethanol prior to molecular analysis. We successfully classified 392 eggs into 10 species and 13 larvae into four species using public databases. Most of the species identified in the egg pool were small and/or benthic, and migratory species were rare. This may partially reflect the adverse effects of hydropower cascade development in this river section. We also found that spawning periods tended to be species-specific. Our study provides a reference for the conservation and management of regional fishery stocks.