DOI: 10.5061/dryad.ncjsxksrc
title: Biodiversity Soup II: A bulk‐sample metabarcoding pipeline emphasizing error reduction

description: 1. Despite widespread recognition of its great promise to aid
 decision-making in environmental management, the applied use of
 metabarcoding requires improvements to reduce the multiple errors that
 arise during PCR amplification, sequencing, and library generation. We
 present a co-designed wet-lab and bioinformatic workflow for metabarcoding
 bulk samples that removes both false-positive (tag jumps, chimeras,
 erroneous sequences) and false-negative (‘dropout’) errors. However, we
 find that it is not possible to recover relative-abundance information
 from amplicon data, due to persistent species-specific biases. 
 2. To present and validate our workflow, we created eight mock
 arthropod soups, all containing the same 248 arthropod morphospecies but
 differing in absolute and relative DNA
 concentrations, and we ran them under five different PCR
 conditions. Our pipeline includes qPCR-optimized PCR annealing temperature
 and cycle number, twin-tagging, multiple independent PCR replicates per
 sample, and negative and positive controls. In the bioinformatic portion,
 we introduce Begum, which is a new version
 of DAMe (Zepeda-Mendoza et al.
 2016. BMC Res. Notes 9:255) that ignores
 heterogeneity spacers, allows primer mismatches when demultiplexing
 samples, and is more efficient.
 Like DAMe, Begum removes tag-jumped reads and
 removes sequence errors by keeping only sequences that appear in more than
 one PCR above a minimum copy number per PCR. The filtering thresholds are
 user-configurable.  3.  We report that OTU
 dropout frequency and taxonomic amplification bias are both reduced by
 using a PCR annealing temperature and cycle number on the low ends of the
 ranges currently used for the Leray-FolDegenRev primers.
 We also report that tag jumps and erroneous sequences can be nearly
 eliminated with Begum filtering, at the cost of only a
 small rise in dropouts. We replicate published findings that uneven size
 distribution of input biomasses leads to greater dropout frequency and
 that OTU size is a poor predictor of species input biomass. Finally, we
 find no evidence for ‘tag-biased’ PCR amplification. 4. To aid
 learning, reproducibility, and the design and testing of alternative
 metabarcoding pipelines, we provide our Illumina and input-species
 sequence datasets, scripts, a spreadsheet for designing primer tags, and a
 tutorial.
description: In this study, we tested the <i>Begum</i> pipeline
 with eight mock soups that differed in their absolute and relative DNA
 concentrations of 248 arthropod species. We metabarcoded the soups under
 five different PCR conditions that varied annealing temperatures
 (T<sub>a</sub>) and PCR cycles, and we filtered the OTUs under
 different stringencies. 
description: We have archived a tutorial with a reduced sequence dataset and
 simplified scripts (PCR B only, 253 MB), and we
 have archived the full dataset (~9.75 GB) with reference files, folder structure, output files, and scripts. To run the scripts, remove the included output files listed in the README file.  The scripts are kept updated at https://github.com/dougwyu/BiodiversitySoupII