eDNA 분석을 위한 황해 주요 수산자원의 CO1 염기서열 분석.

Autor: 사공현, 박주면, 이연정, 양원석, 이수정, 김맹진, 최동한
Předmět:
Zdroj: Ocean & Polar Research; Sep2024, Vol. 46 Issue 3, p131-142, 12p
Abstrakt: Ocean change due to anthropogenic activities and climate change are causing a decline in coldwater fish species and emergence of subtropical fish species in Korean waters. Therefore, environmental change-dependent time-space distribution of fishery resources in Korea, which has a big fisheries industry, needs to be investigated. Environmental DNA (eDNA) metabarcoding is an environmentally noninvasive method for understanding the spatiotemporal distribution of marine organisms at high spatial resolution. The highly variable cytochrome oxidase-1 (CO1) gene is used in eDNA studies for species identification across diverse taxa. However, it exhibits genetic differences depending on geographical distribution. For improving the accuracy of eDNA research, the CO1 database should be expanded by incorporating sequence information for individuals inhabiting the Korean seas. Here, 106 biological samples from the Yellow Sea were identified morphologically and their nucleotide sequences were compared with those in the GenBank. Most sequences were 100% identical with those in the GenBank. In most samples, the morphological and molecular identification results were consistent, indicating the utility of CO1. However, some nucleotide sequences differed from those in the database. Amino acid sequences translated from nucleotide sequences with less than 97% similarity showed high similarity to the amino acid database, indicating intraspecies variation due to "silent mutations". These results highlight the need for a sequence database of fishery resources in Korean coastal waters to improve the reliability of eDNA studies using CO1. However, because of the same CO1 sequences in several species, genetic markers need to be developed and the database should be supplemented with more sequences for reliable high-resolution eDNA studies. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index