Literature DB >> 36070298

Comparison of species-specific qPCR and metabarcoding methods to detect small pelagic fish distribution from open ocean environmental DNA.

Zeshu Yu1,2, Shin-Ichi Ito1, Marty Kwok-Shing Wong1, Susumu Yoshizawa1, Jun Inoue1, Sachihiko Itoh1, Ryuji Yukami3, Kazuo Ishikawa1,2, Chenying Guo1,4, Minoru Ijichi1,5, Susumu Hyodo1.   

Abstract

Environmental DNA (eDNA) is increasingly used to noninvasively monitor aquatic animals in freshwater and coastal areas. However, the use of eDNA in the open ocean (hereafter referred to OceanDNA) is still limited because of the sparse distribution of eDNA in the open ocean. Small pelagic fish have a large biomass and are widely distributed in the open ocean. We tested the performance of two OceanDNA analysis methods-species-specific qPCR (quantitative polymerase chain reaction) and MiFish metabarcoding using universal primers-to determine the distribution of small pelagic fish in the open ocean. We focused on six small pelagic fish species (Sardinops melanostictus, Engraulis japonicus, Scomber japonicus, Scomber australasicus, Trachurus japonicus, and Cololabis saira) and selected the Kuroshio Extension area as a testbed, because distribution of the selected species is known to be influenced by the strong frontal structure. The results from OceanDNA methods were compared to those of net sampling to test for consistency. Then, we compared the detection performance in each target fish between the using of qPCR and MiFish methods. A positive correlation was evident between the qPCR and MiFish detection results. In the ranking of the species detection rates and spatial distribution estimations, comparable similarity was observed between results derived from the qPCR and MiFish methods. In contrast, the detection rate using the qPCR method was always higher than that of the MiFish method. Amplification bias on non-target DNA and low sample DNA quantity seemed to partially result in a lower detection rate for the MiFish method; the reason is still unclear. Considering the ability of MiFish to detect large numbers of species and the quantitative nature of qPCR, the combined usage of the two methods to monitor quantitative distribution of small pelagic fish species with information of fish community structures was recommended.

Entities:  

Mesh:

Substances:

Year:  2022        PMID: 36070298      PMCID: PMC9451083          DOI: 10.1371/journal.pone.0273670

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


  41 in total

1.  DNA metabarcoding of insects and allies: an evaluation of primers and pipelines.

Authors:  G-J Brandon-Mong; H-M Gan; K-W Sing; P-S Lee; P-E Lim; J-J Wilson
Journal:  Bull Entomol Res       Date:  2015-09-07       Impact factor: 1.750

2.  Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding.

Authors:  Alice Valentini; Pierre Taberlet; Claude Miaud; Raphaël Civade; Jelger Herder; Philip Francis Thomsen; Eva Bellemain; Aurélien Besnard; Eric Coissac; Frédéric Boyer; Coline Gaboriaud; Pauline Jean; Nicolas Poulet; Nicolas Roset; Gordon H Copp; Philippe Geniez; Didier Pont; Christine Argillier; Jean-Marc Baudoin; Tiphaine Peroux; Alain J Crivelli; Anthony Olivier; Manon Acqueberge; Matthieu Le Brun; Peter R Møller; Eske Willerslev; Tony Dejean
Journal:  Mol Ecol       Date:  2016-01-18       Impact factor: 6.185

3.  A comparison of droplet digital polymerase chain reaction (PCR), quantitative PCR and metabarcoding for species-specific detection in environmental DNA.

Authors:  Susanna A Wood; Xavier Pochon; Olivier Laroche; Ulla von Ammon; Janet Adamson; Anastasija Zaiko
Journal:  Mol Ecol Resour       Date:  2019-08-07       Impact factor: 7.090

4.  eDNA metabarcoding survey reveals fine-scale coral reef community variation across a remote, tropical island ecosystem.

Authors:  Katrina M West; Michael Stat; Euan S Harvey; Craig L Skepper; Joseph D DiBattista; Zoe T Richards; Michael J Travers; Stephen J Newman; Michael Bunce
Journal:  Mol Ecol       Date:  2020-03-02       Impact factor: 6.185

5.  Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea.

Authors:  Satoshi Yamamoto; Reiji Masuda; Yukuto Sato; Tetsuya Sado; Hitoshi Araki; Michio Kondoh; Toshifumi Minamoto; Masaki Miya
Journal:  Sci Rep       Date:  2017-01-12       Impact factor: 4.379

6.  eDNA metabarcoding of small plankton samples to detect fish larvae and their preys from Atlantic and Pacific waters.

Authors:  Eva Garcia-Vazquez; Oriane Georges; Sara Fernandez; Alba Ardura
Journal:  Sci Rep       Date:  2021-03-31       Impact factor: 4.379

7.  Rapid and reliable extraction of genomic DNA from various wild-type and transgenic plants.

Authors:  Tae-Jin Kang; Moon-Sik Yang
Journal:  BMC Biotechnol       Date:  2004-09-02       Impact factor: 2.563

8.  Detection of Invasive Mosquito Vectors Using Environmental DNA (eDNA) from Water Samples.

Authors:  Judith Schneider; Alice Valentini; Tony Dejean; Fabrizio Montarsi; Pierre Taberlet; Olivier Glaizot; Luca Fumagalli
Journal:  PLoS One       Date:  2016-09-14       Impact factor: 3.240

9.  Environmental DNA analysis of river herring in Chesapeake Bay: A powerful tool for monitoring threatened keystone species.

Authors:  Louis V Plough; Matthew B Ogburn; Catherine L Fitzgerald; Rose Geranio; Gabriella A Marafino; Kimberly D Richie
Journal:  PLoS One       Date:  2018-11-01       Impact factor: 3.240

10.  eDNA metabarcoding as a biomonitoring tool for marine protected areas.

Authors:  Zachary Gold; Joshua Sprague; David J Kushner; Erick Zerecero Marin; Paul H Barber
Journal:  PLoS One       Date:  2021-02-24       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.