2017
DOI: 10.1101/215897
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Needle in a haystack? A comparison of eDNA metabarcoding and targeted qPCR for detection of the great crested newt (Triturus cristatus)

Abstract: SummaryEnvironmental DNA (eDNA) analysis is a rapid, cost-effective, non-invasive biodiversity monitoring tool which utilises DNA left behind in the environment by organisms for species detection. The method is used as a species specific survey tool for rare or invasive species across a broad range of ecosystems. Recently, eDNA and ‘metabarcoding’ have been combined to describe whole communities rather than focusing on single target species. However, whether metabarcoding is as sensitive as targeted approaches… Show more

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Cited by 44 publications
(77 citation statements)
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“…Finally, as a holistic approach to surveying marine biodiversity, previous studies have established that metabarcoding of eDNA from filtered seawater remains unmatched in terms of its cost‐effectiveness and sensitivity (Bakker et al, ; Boussarie et al, ; Port et al, ; Stat et al, ; Valentini et al, ; Yamamoto et al, ). However, the results from this study indicate that metabarcoding can also be used under some circumstances as a rapid alternative to qPCR in determining abundance of multiple taxa (Hänfling et al, ; Harper et al, ; Piñol et al, ; Pont et al, ; Stoeckle et al, ; Thomsen et al, ; Ushio et al, ). Additionally, this technique may be applicable not only to tracking changes in coral cover, but also to track changes in community composition, as well as to detect cryptic taxa, or new recruits, on coral reefs that may otherwise be missed by traditional visual‐based survey methods.…”
Section: Discussionmentioning
confidence: 89%
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“…Finally, as a holistic approach to surveying marine biodiversity, previous studies have established that metabarcoding of eDNA from filtered seawater remains unmatched in terms of its cost‐effectiveness and sensitivity (Bakker et al, ; Boussarie et al, ; Port et al, ; Stat et al, ; Valentini et al, ; Yamamoto et al, ). However, the results from this study indicate that metabarcoding can also be used under some circumstances as a rapid alternative to qPCR in determining abundance of multiple taxa (Hänfling et al, ; Harper et al, ; Piñol et al, ; Pont et al, ; Stoeckle et al, ; Thomsen et al, ; Ushio et al, ). Additionally, this technique may be applicable not only to tracking changes in coral cover, but also to track changes in community composition, as well as to detect cryptic taxa, or new recruits, on coral reefs that may otherwise be missed by traditional visual‐based survey methods.…”
Section: Discussionmentioning
confidence: 89%
“…Regardless of the reason why, our study suggests that target sequence length must be carefully considered when designing eDNA metabarcoding assays of community abundance, yet sequence length has received little attention in eDNA study design (Goldberg et al, ; Taberlet et al, ; Wilcox et al, ). eDNA metabarcoding approaches have primarily focused on amplifying short (~100 bp) sequences (Hänfling et al, ; Harper et al, ; Pont et al, ; Port et al, ; Stoeckle et al, ; Thomsen et al, ; Valentini et al, ) to increase detection rates in systems with (presumably) highly degraded eDNA (Taberlet et al, ). While estimates of coral cover are more precise with a particular pair of short sequence primers (16S in our case), assays designed to measure diversity may require different tools than those designed for abundance estimates.…”
Section: Discussionmentioning
confidence: 99%
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“…One well‐recognized bias in metabarcoding analyses is preferential amplification of a few target sequences, that is, those that are relatively abundant or have few primer‐template mismatches (Bylemans, Gleeson, Hardy, & Furlan, ; Elbrecht & Leese, ). Amplification biases can increase the chance of false‐negative detections (failure to detect a species even when it is present) compared to a targeted approach (Harper et al, ; Lacoursière‐Roussel, Dubois, Normandeau, Bernatchez, & Adamowicz, ; Schneider et al, ). Concerns also remain as to whether eDNA metabarcoding data can be interpreted in a quantitative manner.…”
Section: Introductionmentioning
confidence: 99%