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Title: Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea
Authors: Yamamoto, Satoshi  kyouindb  KAKEN_id
Masuda, Reiji  kyouindb  KAKEN_id
Sato, Yukuto
Sado, Tetsuya
Araki, Hitoshi
Kondoh, Michio
Minamoto, Toshifumi
Miya, Masaki
Author's alias: 山本, 哲史
益田, 玲爾
荒木, 仁志
近藤, 倫生
源, 利文
宮, 正樹
Issue Date: 12-Jan-2017
Publisher: Springer Nature
Journal title: Scientific Reports
Volume: 7
Thesis number: 40368
Abstract: Environmental DNA (eDNA) metabarcoding has emerged as a potentially powerful tool to assess aquatic community structures. However, the method has hitherto lacked field tests that evaluate its effectiveness and practical properties as a biodiversity monitoring tool. Here, we evaluated the ability of eDNA metabarcoding to reveal fish community structures in species-rich coastal waters. High-performance fish-universal primers and systematic spatial water sampling at 47 stations covering ~11 km2 revealed the fish community structure at a species resolution. The eDNA metabarcoding based on a 6-h collection of water samples detected 128 fish species, of which 62.5% (40 species) were also observed by underwater visual censuses conducted over a 14-year period. This method also detected other local fishes (≥23 species) that were not observed by the visual censuses. These eDNA metabarcoding features will enhance marine ecosystem-related research, and the method will potentially become a standard tool for surveying fish communities.
Description: わずか1日の調査で魚種の8割を検出 : 海水からのDNA解析法で. 京都大学プレスリリース. 2017-01-13.
Rights: © The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
URI: http://hdl.handle.net/2433/217791
DOI(Published Version): 10.1038/srep40368
Related Link: https://www.kyoto-u.ac.jp/ja/research-news/2017-01-13-1
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