Metabarcoding and Metagenomics (Mar 2018)
Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing
Abstract
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Effective ecosystem conservation and resource management require quantitative monitoring of biodiversity, including accurate descriptions of species composition and temporal variations of species abundance. Accordingly, quantitative monitoring of biodiversity has been performed for many ecosystems, but it is often time- and effort-consuming and costly. Recent studies have shown that environmental DNA (eDNA), which is released to the environment from macro-organisms living in a habitat, contains information about species identity and abundance. Thus, analysing eDNA would be a promising approach for more efficient biodiversity monitoring. In the present study, internal standard DNAs (i.e. known amounts of short DNA fragments from fish species that have never been observed in a sampling area) were added to eDNA samples, which were collected weekly from a coastal marine ecosystem in Maizuru Bay, Japan (from April 2015 to March 2016) and metabarcoding analysis was performed using Illumina MiSeq to simultaneously identify fish species and quantify fish eDNA copy numbers. A correction equation was obtained for each sample using the relationship between the number of sequence reads and the added amount of the standard DNAs and this equation was used to estimate the copy numbers from the sequence reads of non-standard fish eDNA. The calculated copy numbers showed significant positive correlations with those determined by quantitative PCR, suggesting that eDNA metabarcoding with standard DNA enabled useful quantification of eDNA. Furthermore, for samples that show a high level of PCR inhibition, this method might allow more accurate quantification than qPCR because the correction equations generated using internal standard DNAs would include the effect of PCR inhibition. A single run of Illumina MiSeq produced >70 quantitative fish eDNA time series in this study, showing that this method could contribute to more efficient and quantitative monitoring of biodiversity.