DOI: 10.5061/dryad.7m0cfxprx
title: Bioinformatic pipeline from: Increasing confidence for discerning species and population compositions from metabarcoding assays of environmental samples: case studies of fishes in the Laurentian Great Lakes and Wabash River

description: Community composition data are essential for conservation management,
 facilitating identification of rare native and invasive species, along
 with abundant ones. However, traditional capture-based morphological
 surveys require considerable taxonomic expertise, are time consuming and
 expensive, can kill rare taxa and damage habitats, and often are prone to
 false negatives. Alternatively, metabarcode assays can be used to assess
 the genetic identity and compositions of entire communities from
 environmental samples, comprising a more sensitive, less damaging, and
 relatively time- and cost-efficient approach. However, there is a
 trade-off between the stringency of bioinformatic filtering needed to
 remove false positives and the potential for false negatives. The present
 investigation thus evaluated use of four mitochondrial (mt) DNA
 metabarcode assays and a customized bioinformatic pipeline to increase
 confidence in species identifications by removing false positives, while
 achieving high detection probability. Positive controls were used to
 calculate sequencing error, and results that fell below those cutoff
 values were removed, unless found with multiple assays. The performance of
 this approach was tested to discern and identify North American freshwater
 fishes using lab experiments (mock communities and aquarium experiments)
 and processing of a bulk ichthyoplankton sample. The method then was
 applied to field environmental (e)DNA water samples taken concomitant with
 electrofishing surveys and morphological identifications. This protocol
 detected 100% of species present in concomitant electrofishing surveys in
 the Wabash River and an additional 21 that were absent from traditional
 sampling. Using single 1 L water samples collected from just four
 locations, the metabarcoding assays discerned 73% of the total fish
 species that were discerned in comparison to four months of an extensive
 electrofishing river survey in the Maumee River, along with an additional
 nine species. In both rivers, total fish species diversity was best
 resolved when all four metabarcode assays were used together, which
 identified 35 additional species missed by electrofishing. Ecological
 distinction and diversity levels among the fish communities also were
 better resolved with the metabarcode assays than with morphological
 sampling and identifications, especially with the combined assays. At the
 population-level, metabarcode analyses targeting the invasive round goby
 Neogobius melanostomus and the silver carp Hypophthalmichthys molitrix
 identified all population haplotype variants found using Sanger sequencing
 of morphologically sampled fish, along with additional intra-specific
 diversity, meriting further investigation. Overall findings demonstrated
 that the use of multiple metabarcode assays and custom bioinformatics that
 filter potential error from true positive detections improves confidence
 in evaluating biodiversity.
description: These scripts were written and databases curated by Matthew
 Snyder during his PhD Dissertation research in Dr. Carol Stepien's
 Genetics and Genomics Group at the Pacific Marine Environmental
 Laboratory, National Oceanic and Atmospheric Administration, Seattle,
 WA.
description: <strong>Pipeline overview</strong>
 Demultiplexed raw reads returned from an Illumina HTS
 platform were trimmed with MetaTrim.py (see MetaTrim_README.md)
 Trimmed reads were merged in the R package Dada2 following
 Dada2Workflow.R The resulting sequence table was
 dmuxed into fastas by SeqTabToFasta.pl FASTAs were
 subjected to a BLAST search against multiple custom databases with
 BlastCycle500.pl BLAST results were summarized with
 SummarizeBlast.pl <b>Scripts and
 usage:</b> MetaTrim.py: See
 MetaTrim_README.md Dada2Workflow.R: workflow for
 Dada2 R package SeqTabToFasta.pl: Run in the
 directory with the sequence table returned from Dada2. Sequence table must
 be named SeqTab.txt. Creates a subdir called Dada2ASVs and places FASTA
 files for each sample in this dir. Sequence titles in these FASTAS have
 the format &gt; &lt;ASV #&gt; | &lt;# of
 reads&gt;. BlastCycle500.pl: Run in Dada2ASVs.
 Performs a BLAST search for each ASV in each FASTA against custom
 databases, returning the top 500 results per ASV. Results are saved as
 &lt;Sample name&gt;Res.txt SummarizeBlast.pl:
 Run in Dada2ASVs. Calculates the summarized species string: a list of
 species for each ASV that all had the lowest e value (best match) in the
 BLAST Results. Hits with &lt;90% identity or query cover are removed.
 Creates a tabular file with structure: Sample \t Summarized Species String
 \t N ASVs with identical Summarized Species String \t Number of reads
 corresponding to the ASV \t Proportion of reads in the sample
 corresponding to the ASV \t ASV sequence title from FASTA.
 <strong>BLAST
 Databases</strong> Each database is a tar.gz file
 containing the files required for a BLAST database. 
 Cytb_blast_db: Formatted database from all sequences returned
 from a GenBank search for "Actinopterygii AND Cyt b" and
 "Actinopterygii AND Cytochrome b"
 Cytb_GL_blast_db: Formatted database from all species present in
 the Laurentian Great Lakes from Cytb_blast_db
 12S_blast_db: Formatted database from all sequences returned
 from a GenBank search for "Actinopterygii AND 12S"
 12S_GL_blast_db: Formatted database from all species present in
 the Laurentian Great Lakes from 12S_blast_db