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Indigenous species barcode database improves the identification of zooplankton
Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here m...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627919/ https://www.ncbi.nlm.nih.gov/pubmed/28977035 http://dx.doi.org/10.1371/journal.pone.0185697 |
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author | Yang, Jianghua Zhang, Xiaowei Zhang, Wanwan Sun, Jingying Xie, Yuwei Zhang, Yimin Burton, G. Allen Yu, Hongxia |
author_facet | Yang, Jianghua Zhang, Xiaowei Zhang, Wanwan Sun, Jingying Xie, Yuwei Zhang, Yimin Burton, G. Allen Yu, Hongxia |
author_sort | Yang, Jianghua |
collection | PubMed |
description | Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton. |
format | Online Article Text |
id | pubmed-5627919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56279192017-10-20 Indigenous species barcode database improves the identification of zooplankton Yang, Jianghua Zhang, Xiaowei Zhang, Wanwan Sun, Jingying Xie, Yuwei Zhang, Yimin Burton, G. Allen Yu, Hongxia PLoS One Research Article Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton. Public Library of Science 2017-10-04 /pmc/articles/PMC5627919/ /pubmed/28977035 http://dx.doi.org/10.1371/journal.pone.0185697 Text en © 2017 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Yang, Jianghua Zhang, Xiaowei Zhang, Wanwan Sun, Jingying Xie, Yuwei Zhang, Yimin Burton, G. Allen Yu, Hongxia Indigenous species barcode database improves the identification of zooplankton |
title | Indigenous species barcode database improves the identification of zooplankton |
title_full | Indigenous species barcode database improves the identification of zooplankton |
title_fullStr | Indigenous species barcode database improves the identification of zooplankton |
title_full_unstemmed | Indigenous species barcode database improves the identification of zooplankton |
title_short | Indigenous species barcode database improves the identification of zooplankton |
title_sort | indigenous species barcode database improves the identification of zooplankton |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627919/ https://www.ncbi.nlm.nih.gov/pubmed/28977035 http://dx.doi.org/10.1371/journal.pone.0185697 |
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