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Gigascience. 2015 Oct 6;4:46. doi: 10.1186/s13742-015-0086-1. eCollection 2015.

Evaluating a multigene environmental DNA approach for biodiversity assessment.

Author information

1
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; Department of Computer Science, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand.
2
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand ; The Institute for Plant and Food Research, Private Bag 92169, Auckland, 1142 New Zealand.
3
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand ; Landcare Research, Private Bag 92170, Auckland, 1142 New Zealand.
4
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand.
5
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; The Institute for Plant and Food Research, Private Bag 92169, Auckland, 1142 New Zealand.
6
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; Landcare Research, Private Bag 92170, Auckland, 1142 New Zealand.
7
Landcare Research, Private Bag 92170, Auckland, 1142 New Zealand.
8
Department of Biological Sciences, University of Waikato, Private Bag 3105, Hamilton, 3240 New Zealand.
9
South Australian Museum, North Terrace, Adelaide, SA 5000 Australia ; School of Pharmacy and Medical Sciences, University of South Australia, GPO Box 2471, Adelaide, SA 5001 Australia.
10
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand ; Department of Statistics, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand.
11
School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand.
12
Allan Wilson Centre, University of Auckland, Auckland, New Zealand ; School of Biological Sciences, Victoria University of Wellington, PO Box 600, Wellington, 6140 New Zealand.

Abstract

BACKGROUND:

There is an increasing demand for rapid biodiversity assessment tools that have a broad taxonomic coverage. Here we evaluate a suite of environmental DNA (eDNA) markers coupled with next generation sequencing (NGS) that span the tree of life, comparing them with traditional biodiversity monitoring tools within ten 20×20 meter plots along a 700 meter elevational gradient.

RESULTS:

From six eDNA datasets (one from each of 16S, 18S, ITS, trnL and two from COI) we identified sequences from 109 NCBI taxonomy-defined phyla or equivalent, ranging from 31 to 60 for a given eDNA marker. Estimates of alpha and gamma diversity were sensitive to the number of sequence reads, whereas beta diversity estimates were less sensitive. The average within-plot beta diversity was lower than between plots for all markers. The soil beta diversity of COI and 18S markers showed the strongest response to the elevational variation of the eDNA markers (COI: r=0.49, p<0.001; 18S: r=0.48, p<0.001). Furthermore pairwise beta diversities for these two markers were strongly correlated with those calculated from traditional vegetation and invertebrate biodiversity measures.

CONCLUSIONS:

Using a soil-based eDNA approach, we demonstrate that standard phylogenetic markers are capable of recovering sequences from a broad diversity of eukaryotes, in addition to prokaryotes by 16S. The COI and 18S eDNA markers are the best proxies for aboveground biodiversity based on the high correlation between the pairwise beta diversities of these markers and those obtained using traditional methods.

KEYWORDS:

Biodiversity assessment; Environmental DNA; Genomic observatory; Metabarcoding

PMID:
26445670
PMCID:
PMC4595072
DOI:
10.1186/s13742-015-0086-1
[Indexed for MEDLINE]
Free PMC Article

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