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. 2017 Sep 25;7(1):12240.
doi: 10.1038/s41598-017-12501-5.

Ecosystem biomonitoring with eDNA: metabarcoding across the tree of life in a tropical marine environment

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Free PMC article

Ecosystem biomonitoring with eDNA: metabarcoding across the tree of life in a tropical marine environment

Michael Stat et al. Sci Rep. .
Free PMC article

Abstract

Effective marine management requires comprehensive data on the status of marine biodiversity. However, efficient methods that can document biodiversity in our oceans are currently lacking. Environmental DNA (eDNA) sourced from seawater offers a new avenue for investigating the biota in marine ecosystems. Here, we investigated the potential of eDNA to inform on the breadth of biodiversity present in a tropical marine environment. Directly sequencing eDNA from seawater using a shotgun approach resulted in only 0.34% of 22.3 million reads assigning to eukaryotes, highlighting the inefficiency of this method for assessing eukaryotic diversity. In contrast, using 'tree of life' (ToL) metabarcoding and 20-fold fewer sequencing reads, we could detect 287 families across the major divisions of eukaryotes. Our data also show that the best performing 'universal' PCR assay recovered only 44% of the eukaryotes identified across all assays, highlighting the need for multiple metabarcoding assays to catalogue biodiversity. Lastly, focusing on the fish genus Lethrinus, we recovered intra- and inter-specific haplotypes from seawater samples, illustrating that eDNA can be used to explore diversity beyond taxon identifications. Given the sensitivity and low cost of eDNA metabarcoding we advocate this approach be rapidly integrated into biomonitoring programs.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Assignment of sequences recovered from the shotgun library of eDNA collected from Coral Bay in west Australia. Pie chart segments represent the percentage of sequences that were assigned to taxa using the software MEGAN 5.11.3. Sequences that were assigned to fish were further mined for commonly used DNA barcodes (12S, 16S, 18S, 28S, COI, and cytb); the number of fish barcodes identified in the dataset is displayed in the box insert.
Figure 2
Figure 2
Taxonomic phylogram of eukaryotic diversity at Coral Bay in west Australia derived from ToL-metabarcoding. Bar graphs indicate the number of families in each phyla characterised at Coral Bay, and are coloured according to kingdom.
Figure 3
Figure 3
Hierarchical pie chart of prokaryotic diversity at Coral Bay in west Australia derived from ToL-metabarcoding. The inner pie chart represents the relative proportion of families identified in bacteria (blue) and archaea (red). Each segmented circle illustrates the number of taxa (phyla, classes and orders) characterised for both bacteria and archaea, and is scaled according to the number of families within each rank. Dotted lines partition the number of taxa within each phylum, which are named around the circumference of the chart.
Figure 4
Figure 4
Line graph representing the number of eukaryotic taxa recorded at Coral Bay in west Australia using eDNA. Coloured lines indicate the number of taxa identified for each taxonomic rank for the nine PCR assays that target eukaryotes.
Figure 5
Figure 5
Network of Lethrinus 16S rDNA haplotypes. Green circles represent haplotypes identified at Coral Bay in west Australia in this study using eDNA, blue circles represent Lethrinus haplotypes obtained from NCBI for additional species recorded at Coral Bay, and red circles represent all other Lethrinus haplotypes available from NCBI. Numerals in brackets indicate the number of samples the haplotype was detected in (out of a total of 9). Genbank accession numbers are also indicated in brackets.

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References

    1. Jennings S, Polunin NV. Impacts of fishing on tropical reef ecosystems. Ambio. 1996;25:44–49.
    1. Pauly D, Christensen V, Dalsgaard J, Froese R, Torres F. Fishing down marine food webs. Science. 1998;279:860–863. doi: 10.1126/science.279.5352.860. - DOI - PubMed
    1. Halpern BS, et al. A global map of human impact on marine ecosystems. Science. 2008;319:948–952. doi: 10.1126/science.1149345. - DOI - PubMed
    1. Hoegh-Guldberg O, Bruno JF. The impact of climate change on the world’s marine ecosystems. Science. 2010;328:1523–1528. doi: 10.1126/science.1189930. - DOI - PubMed
    1. Worm B, et al. Rebuilding global fisheries. Science. 2009;325:578–585. doi: 10.1126/science.1173146. - DOI - PubMed

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