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Evaluating a multigene environmental DNA approach for biodiversity assessment.

Authors :
Drummond, Alexei J.
Newcomb, Richard D.
Buckley, Thomas R.
Dong Xie
Dopheide, Andrew
Potter, Benjamin C. M.
Heled, Joseph
Ross, Howard A.
Tooman, Leah
Grosser, Stefanie
Park, Duckchul
Demetras, Nicholas J.
Stevens, Mark I.
Russell, James C.
Anderson, Sandra H.
Carter, Anna
Nelson, Nicola
Source :
GigaScience; 10/7/2015, Vol. 4 Issue 1, preceding p1-19, 20p
Publication Year :
2015

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2047217X
Volume :
4
Issue :
1
Database :
Complementary Index
Journal :
GigaScience
Publication Type :
Academic Journal
Accession number :
110261813
Full Text :
https://doi.org/10.1186/s13742-015-0086-1