The Identification of Fish Eggs From Four Economically Important Species in Guanghai Bay (China)

By far, very few studies have dealt with the ichthyoplankton diversity in Guanghai Bay (China), which is a potential spawning ground for many important fish species. In this study, fish eggs collected in Guanghai Bay were identified through molecular method combined with visual taxonomic method. We employed two mitochondrial gene regions of cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (16S rRNA) as genetic markers for species identification. Through sequence identification at NCBI, 121 eggs with overlapping size range and easy to be confused were discriminated as four economically important species: seven as silver sillago Sillago sihama, 48 as black-banded sillago Sillago nigrofasciata, 38 as yellow drum Nibea albiflora, and 28 as Pacific seabream Acanthopagrus pacificus. Phylogenetic analyses showed that these 121 eggs clustered in four groups with strong support. To testify the validity of these identification results, species identification through five BarcodingR package methods was also carried out using sequences of 33 fish specimens as a reference library covering four target species. Finally, a highly consensus of species assignment results was achieved across different methods. Morphological characteristics and detailed photographs for eggs from these four species were supplied here. Eggs of each species are pelagic, round, have a smooth chorion and one single oil globule. Embryonic pigment patterns vary as eggs develop and can be used for species distinguishing. Eggs from S. nigrofasciata and A. pacificus were described for the first time in this study. One simple and accurate method for identifying N. albiflora eggs was additionally provided. Moreover, the morphological differences between two Sillago eggs offered supportive evidence for the recent separation of S. nigrofasciata as a new species from S. sihama. All these results would be critical for the discrimination of eggs from these four species and the estimation for their spawning areas. Meanwhile, our study would contribute to the stock assessment and fishery management in Guanghai Bay.