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      A MinION™-based pipeline for fast and cost-effective DNA barcoding

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          Abstract

          DNA barcodes are useful for species discovery and species identification, but obtaining barcodes currently requires a well-equipped molecular laboratory and is time-consuming, and/or expensive. We here address these issues by developing a barcoding pipeline for Oxford Nanopore MinION™ and demonstrating that one flow cell can generate barcodes for ~500 specimens despite the high basecall error rates of MinION™ reads. The pipeline overcomes these errors by first summarizing all reads for the same tagged amplicon as a consensus barcode. Consensus barcodes are overall mismatch-free but retain indel errors that are concentrated in homopolymeric regions. They are addressed with an optional error correction pipeline that is based on conserved amino acid motifs from publicly available barcodes. The effectiveness of this pipeline is documented by analysing reads from three MinION™ runs that represent three different stages of MinION™ development. They generated data for (i) 511 specimens of a mixed Diptera sample, (ii) 575 specimens of ants and (iii) 50 specimens of Chironomidae. The run based on the latest chemistry yielded MinION™ barcodes for 490 of the 511 specimens which were assessed against reference Sanger barcodes (N = 471). Overall, the MinION™ barcodes have an accuracy of 99.3%-100% with the number of ambiguous bases after correction ranging from <0.01% to 1.5% depending on which correction pipeline is used. We demonstrate that it requires ~2 hr of sequencing to gather all information needed for obtaining reliable barcodes for most specimens (>90%). We estimate that up to 1,000 barcodes can be generated in one flow cell and that the cost per barcode can be <USD 2.

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          Most cited references24

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          DNA barcoding and taxonomy in Diptera: a tale of high intraspecific variability and low identification success.

          DNA barcoding and DNA taxonomy have recently been proposed as solutions to the crisis of taxonomy and received significant attention from scientific journals, grant agencies, natural history museums, and mainstream media. Here, we test two key claims of molecular taxonomy using 1333 mitochondrial COI sequences for 449 species of Diptera. We investigate whether sequences can be used for species identification ("DNA barcoding") and find a relatively low success rate (< 70%) based on tree-based and newly proposed species identification criteria. Misidentifications are due to wide overlap between intra- and interspecific genetic variability, which causes 6.5% of all query sequences to have allospecific or a mixture of allo- and conspecific (3.6%) best-matching barcodes. Even when two COI sequences are identical, there is a 6% chance that they belong to different species. We also find that 21% of all species lack unique barcodes when consensus sequences of all conspecific sequences are used. Lastly, we test whether DNA sequences yield an unambiguous species-level taxonomy when sequence profiles are assembled based on pairwise distance thresholds. We find many sequence triplets for which two of the three pairwise distances remain below the threshold, whereas the third exceeds it; i.e., it is impossible to consistently delimit species based on pairwise distances. Furthermore, for species profiles based on a 3% threshold, only 47% of all profiles are consistent with currently accepted species limits, 20% contain more than one species, and 33% only some sequences from one species; i.e., adopting such a DNA taxonomy would require the redescription of a large proportion of the known species, thus worsening the taxonomic impediment. We conclude with an outlook on the prospects of obtaining complete barcode databases and the future use of DNA sequences in a modern integrative taxonomy.
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            A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents

            Introduction The PCR-based analysis of homologous genes has become one of the most powerful approaches for species detection and identification, particularly with the recent availability of Next Generation Sequencing platforms (NGS) making it possible to identify species composition from a broad range of environmental samples. Identifying species from these samples relies on the ability to match sequences with reference barcodes for taxonomic identification. Unfortunately, most studies of environmental samples have targeted ribosomal markers, despite the fact that the mitochondrial Cytochrome c Oxidase subunit I gene (COI) is by far the most widely available sequence region in public reference libraries. This is largely because the available versatile (“universal”) COI primers target the 658 barcoding region, whose size is considered too large for many NGS applications. Moreover, traditional barcoding primers are known to be poorly conserved across some taxonomic groups. Results We first design a new PCR primer within the highly variable mitochondrial COI region, the “mlCOIintF” primer. We then show that this newly designed forward primer combined with the “jgHCO2198” reverse primer to target a 313 bp fragment performs well across metazoan diversity, with higher success rates than versatile primer sets traditionally used for DNA barcoding (i.e. LCO1490/HCO2198). Finally, we demonstrate how the shorter COI fragment coupled with an efficient bioinformatics pipeline can be used to characterize species diversity from environmental samples by pyrosequencing. We examine the gut contents of three species of planktivorous and benthivorous coral reef fish (family: Apogonidae and Holocentridae). After the removal of dubious COI sequences, we obtained a total of 334 prey Operational Taxonomic Units (OTUs) belonging to 14 phyla from 16 fish guts. Of these, 52.5% matched a reference barcode (>98% sequence similarity) and an additional 32% could be assigned to a higher taxonomic level using Bayesian assignment. Conclusions The molecular analysis of gut contents targeting the 313 COI fragment using the newly designed mlCOIintF primer in combination with the jgHCO2198 primer offers enormous promise for metazoan metabarcoding studies. We believe that this primer set will be a valuable asset for a range of applications from large-scale biodiversity assessments to food web studies.
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              obitools: a unix-inspired software package for DNA metabarcoding.

              DNA metabarcoding offers new perspectives in biodiversity research. This recently developed approach to ecosystem study relies heavily on the use of next-generation sequencing (NGS) and thus calls upon the ability to deal with huge sequence data sets. The obitools package satisfies this requirement thanks to a set of programs specifically designed for analysing NGS data in a DNA metabarcoding context. Their capacity to filter and edit sequences while taking into account taxonomic annotation helps to set up tailor-made analysis pipelines for a broad range of DNA metabarcoding applications, including biodiversity surveys or diet analyses. The obitools package is distributed as an open source software available on the following website: http://metabarcoding.org/obitools. A Galaxy wrapper is available on the GenOuest core facility toolshed: http://toolshed.genouest.org.
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                Author and article information

                Contributors
                Journal
                Molecular Ecology Resources
                Mol Ecol Resour
                Wiley
                1755098X
                September 2018
                September 2018
                May 07 2018
                : 18
                : 5
                : 1035-1049
                Affiliations
                [1 ]Department of Biological Sciences; National University of Singapore; Singapore
                [2 ]Lee Kong Chian Natural History Museum; Singapore
                [3 ]Computational & Systems Biology; Genome Institute of Singapore; Singapore
                Article
                10.1111/1755-0998.12890
                29673082
                c6b02386-bbc9-49ba-8ab6-18bfb482764d
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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