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Cited by 291

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification

Open access
Zhou, Xin, Li, Yiyuan, Liu, Shanlin, Yang, Qing, Su, Xu, Zhou, Lili, Tang, Min, Fu, Ribei, Li, Jiguang, Huang, Quanfei·2013·GigaScience

Abstract

BACKGROUND: Next-generation-sequencing (NGS) technologies combined with a classic DNA barcoding approach have enabled fast and credible measurement for biodiversity of mixed environmental samples. However, the PCR amplification involved in nearly all existing NGS protocols inevitably introduces taxonomic biases. In the present study, we developed new Illumina pipelines without PCR amplifications to analyze terrestrial arthropod communities. RESULTS: Mitochondrial enrichment directly followed by Illumina shotgun sequencing, at an ultra-high sequence volume, enabled the recovery of Cytochrome c Oxidase subunit 1 (COI) barcode sequences, which allowed for the estimation of species composition at high fidelity for a terrestrial insect community. With 15.5 Gbp Illumina data, approximately 97% and 92% were detected out of the 37 input Operational Taxonomic Units (OTUs), whether the reference barcode library was used or not, respectively, while only 1 novel OTU was found for the latter. Additionally, relatively strong correlation between the sequencing volume and the total biomass was observed for species from the bulk sample, suggesting a potential solution to reveal relative abundance. CONCLUSIONS: The ability of the new Illumina PCR-free pipeline for DNA metabarcoding to detect small arthropod specimens and its tendency to avoid most, if not all, false positives suggests its great potential in biodiversity-related surveillance, such as in biomonitoring programs. However, further improvement for mitochondrial enrichment is likely needed for the application of the new pipeline in analyzing arthropod communities at higher diversity.

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Metadata

Authors
Zhou, X., Li, Y., Liu, S., Yang, Q., Su, X., Zhou, L., Tang, M., Fu, R., Li, J., & Huang, Q.
Venue
GigaScience
Published
2013-03-27
Volume
2
Issue
1
Pages
4-4
ISSN
2047-217X (ISSN-L)
OpenAlex
W2112732800
Cited by
291
References
3
FWCI
27.05
Type
journal article
Language
en
Open access
gold

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