Evaluation of Fish Species Detection in the Northwestern Pacific using eDNA Metabarcoding: A Mock Community Approach DOI Creative Commons
Sergei V. Turanov, Olesia A. Rutenko

Frontiers in Bioscience-Scholar, Journal Year: 2025, Volume and Issue: 17(1)

Published: March 24, 2025

Background: Metabarcoding of environmental DNA (eDNA), a technique using high-throughput sequencing, has transformed biodiversity monitoring by identifying organisms from fragments present in the environment. This method, particularly useful for aquatic ecosystems, allows non-invasive species monitoring, helping to provide insight into ecosystem composition and taxonomic diversity. The objective this study was assess efficacy eDNA metabarcoding fish identification model community northeast Pacific Ocean 12S ribosomal RNA (12S rRNA) marker. Methods: Water samples were collected tank Primorsky Aquarium, which contains Sea Japan, Okhotsk, Bering Sea. extracted syringe filters enriched with polymerase chain reaction (PCR) mitochondrial rRNA fragment, followed sequencing on Illumina platform. resulting reads processed bayesian generalized uncertainty modeling (BEGUM) pipeline their diversity assessed basic local alignment search tool (BLAST) search. Using silico PCR, we also possible association detection failures some presence primer-to-target sequence mismatches. Results: From only 20 tank, identified 56 operational units (OTUs) corresponding 28 genera. Among these OTUs, unambiguously classified BLAST-based analysis, though 9 them corresponded actually tank. Significant problems included inconsistent reference data marker biases that affected accuracy identification. In addition contamination feed, water source may have introduced extraneous samples. Also, PCR analysis small number available sequences, demonstrated significantly higher primer mismatches not identified. Conclusions: highlights relative identification, but need improve databases minimise contamination, searching references primers accuracy. Further research should focus optimising selection controlling methodological bias ensure robust estimates.

Language: Английский

Evaluation of Fish Species Detection in the Northwestern Pacific using eDNA Metabarcoding: A Mock Community Approach DOI Creative Commons
Sergei V. Turanov, Olesia A. Rutenko

Frontiers in Bioscience-Scholar, Journal Year: 2025, Volume and Issue: 17(1)

Published: March 24, 2025

Background: Metabarcoding of environmental DNA (eDNA), a technique using high-throughput sequencing, has transformed biodiversity monitoring by identifying organisms from fragments present in the environment. This method, particularly useful for aquatic ecosystems, allows non-invasive species monitoring, helping to provide insight into ecosystem composition and taxonomic diversity. The objective this study was assess efficacy eDNA metabarcoding fish identification model community northeast Pacific Ocean 12S ribosomal RNA (12S rRNA) marker. Methods: Water samples were collected tank Primorsky Aquarium, which contains Sea Japan, Okhotsk, Bering Sea. extracted syringe filters enriched with polymerase chain reaction (PCR) mitochondrial rRNA fragment, followed sequencing on Illumina platform. resulting reads processed bayesian generalized uncertainty modeling (BEGUM) pipeline their diversity assessed basic local alignment search tool (BLAST) search. Using silico PCR, we also possible association detection failures some presence primer-to-target sequence mismatches. Results: From only 20 tank, identified 56 operational units (OTUs) corresponding 28 genera. Among these OTUs, unambiguously classified BLAST-based analysis, though 9 them corresponded actually tank. Significant problems included inconsistent reference data marker biases that affected accuracy identification. In addition contamination feed, water source may have introduced extraneous samples. Also, PCR analysis small number available sequences, demonstrated significantly higher primer mismatches not identified. Conclusions: highlights relative identification, but need improve databases minimise contamination, searching references primers accuracy. Further research should focus optimising selection controlling methodological bias ensure robust estimates.

Language: Английский

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