Literature DB >> 25909325

Metabarcoding of benthic eukaryote communities predicts the ecological condition of estuaries.

Anthony A Chariton1, Sarah Stephenson2, Matthew J Morgan3, Andrew D L Steven4, Matthew J Colloff3, Leon N Court3, Christopher M Hardy3.   

Abstract

DNA-derived measurements of biological composition have the potential to produce data covering all of life, and provide a tantalizing proposition for researchers and managers. We used metabarcoding to compare benthic eukaryote composition from five estuaries of varying condition. In contrast to traditional studies, we found biotic richness was greatest in the most disturbed estuary, with this being due to the large volume of extraneous material (i.e. run-off from aquaculture, agriculture and other catchment activities) being deposited in the system. In addition, we found strong correlations between composition and a number of environmental variables, including nutrients, pH and turbidity. A wide range of taxa responded to these environmental gradients, providing new insights into their sensitivities to natural and anthropogenic stressors. Metabarcoding has the capacity to bolster current monitoring techniques, enabling the decisions regarding ecological condition to be based on a more holistic view of biodiversity. Crown
Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Keywords:  18S rRNA; Biomonitoring; DNA; Eukaryotes; High-throughput sequencing; Indicator taxa; Metabarcoding; Sediments; Threshold analysis

Mesh:

Substances:

Year:  2015        PMID: 25909325     DOI: 10.1016/j.envpol.2015.03.047

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  18 in total

1.  Environmental DNA metabarcoding reveals winners and losers of global change in coastal waters.

Authors:  Ramón Gallego; Emily Jacobs-Palmer; Kelly Cribari; Ryan P Kelly
Journal:  Proc Biol Sci       Date:  2020-12-09       Impact factor: 5.349

2.  The curious and neglected soft-bodied meiofauna: Rouphozoa (Gastrotricha and Platyhelminthes).

Authors:  Maria Balsamo; Tom Artois; Julian P S Smith; M Antonio Todaro; Loretta Guidi; Brian S Leander; Niels W L Van Steenkiste
Journal:  Hydrobiologia       Date:  2020-05-26       Impact factor: 2.694

3.  Environmental RNA as a Tool for Marine Community Biodiversity Assessments.

Authors:  Marissa S Giroux; Jay R Reichman; Troy Langknecht; Robert M Burgess; Kay T Ho
Journal:  Sci Rep       Date:  2022-10-22       Impact factor: 4.996

4.  Quantification of marine benthic communities with metabarcoding.

Authors:  Lise Klunder; Judith D L van Bleijswijk; Loran Kleine Schaars; Henk W van der Veer; Pieternella C Luttikhuizen; Allert I Bijleveld
Journal:  Mol Ecol Resour       Date:  2021-11-01       Impact factor: 8.678

5.  Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons.

Authors:  Magdalena Guardiola; María Jesús Uriz; Pierre Taberlet; Eric Coissac; Owen Simon Wangensteen; Xavier Turon
Journal:  PLoS One       Date:  2015-10-05       Impact factor: 3.240

6.  High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems.

Authors:  Franck Lejzerowicz; Philippe Esling; Loïc Pillet; Thomas A Wilding; Kenneth D Black; Jan Pawlowski
Journal:  Sci Rep       Date:  2015-09-10       Impact factor: 4.379

7.  Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA.

Authors:  Magdalena Guardiola; Owen S Wangensteen; Pierre Taberlet; Eric Coissac; María Jesús Uriz; Xavier Turon
Journal:  PeerJ       Date:  2016-12-21       Impact factor: 2.984

Review 8.  Censusing marine eukaryotic diversity in the twenty-first century.

Authors:  Matthieu Leray; Nancy Knowlton
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-09-05       Impact factor: 6.237

9.  The utility of DNA metabarcoding for studying the response of arthropod diversity and composition to land-use change in the tropics.

Authors:  Kingsly Chuo Beng; Kyle W Tomlinson; Xian Hui Shen; Yann Surget-Groba; Alice C Hughes; Richard T Corlett; J W Ferry Slik
Journal:  Sci Rep       Date:  2016-04-26       Impact factor: 4.379

10.  Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics.

Authors:  Hao-Yang Wu; Yan-Hui Wang; Qiang Xie; Yun-Ling Ke; Wen-Jun Bu
Journal:  Sci Rep       Date:  2016-06-17       Impact factor: 4.379

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