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Environmental DNAEcologyPeer-reviewed journal article

An efficient early-pooling protocol for environmental DNA metabarcoding

M. Ushio, S. Furukawa, H. Murakami, R. Masuda, A. J. Nagano

PDFDOIPreprint

Abstract

Environmental DNA (eDNA) metabarcoding, a method that applies high-throughput sequencing and universal primer sets to eDNA analysis, has been a promising approach for efficient, comprehensive biodiversity monitoring. However, significant money-, labor-, and time-costs are still required for performing eDNA metabarcoding. In the present study, we assessed the performance of an "early-pooling" protocol (a protocol based on the 1st PCR indexing) to reduce the experimental costs of the library preparation for eDNA metabarcoding. Specifically, we performed three experiments to test the effects of 1st PCR and 2nd PCR indexing protocols on the community composition revealed by eDNA metabarcoding, of post-1st-PCR exonuclease purification on index-hopping, and of the number of PCR replicates and eDNA template volume on the number of detected OTUs. By analyzing 204 eDNA libraries from 3 natural aquatic ecosystems and 1 mock eDNA sample, we show that (i) the 1st PCR indexing does not cause clear biases in the outcomes of eDNA metabarcoding, (ii) post-1st-PCR exonuclease purification reduces the risk of index-hopping, and (iii) increasing the eDNA template volume can increase the number of detected OTUs and reduce the variations in detected community compositions, as can increasing the number of the 1st PCR replicates. Our results show that an early-pooling protocol with post-1st-PCR exonuclease purification and an increased amount of DNA template will reduce the risk of index-hopping, the costs for consumables and reagents, and the handling time in the library preparation, and that it produces comparable results to a 2nd-PCR-indexing protocol. Therefore, once a target metabarcoding region is determined and a set of indexed-1st-PCR primers is prepared, the early-pooling protocol provides a cost-, labor-, and time-efficient way to process a large number of samples.

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