DOI: 10.5061/dryad.4b8gthtdb
title: DNA metabarcoding confirms primary targets and breadth of diet for coral reef butterflyfishes

description: Understanding species-specific resource requirements is paramount in
 managing and protecting biodiversity in a world where environmental
 quality is in decline. Dietary data can inform predator–prey relationships
 and how changes in prey availability impact different species. However,
 for many coral reef fishes, prey and predatory events can be difficult to
 observe and identify, both in situ and within examined stomach samples.
 Here we applied DNA metabarcoding of stomach content samples for eleven
 Red Sea butterflyfish species to identify the diversity of dietary
 components that these primarily benthic feeding fish consume across coral
 reefs. Detections based on 18S and COI sequences from partially digested
 stomach contents significantly increased the resolution and diversity of
 the known diet for this group of fish, which included cryptic prey that
 are difficult to visually document due to soft parts or morphological
 ambiguity. In addition to scleractinian corals and other Cnidaria, the
 obligate corallivore species fed on a wide range of benthic organisms,
 whereas facultative species displayed a broader diet with crustaceans,
 tunicates, and worms contributing to samples. While a number of
 individuals contained DNA that could not be confidently identified using
 this method, the proportion of unidentifiable sequences was relatively low
 across butterflyfish species. The COI marker identified the importance of
 soft corals in the diet for two hard coral specialists; Chaetodon
 melannotus and Chaetodon semilarvatus, with soft coral detected in over
 half of the individuals and contributing significantly to the number of
 DNA sequence reads within their gut. Notably, five prey items identified
 to the species level were detected that are currently not documented in
 the Red Sea. Our analysis revealed that the diet of different species of
 butterflyfish significantly overlaps, with all species deriving most of
 their diet from the phylum Cnidaria (hard and soft coral, anemones) and
 symbiotic Symbiodiniaceae algae. Furthermore, accumulation curves suggest
 that all study species may feed on an even greater fraction of the
 benthos, likely driven by the availability and diversity of each
 individual/pair’s associated territory. This approach increases the known
 dietary resolution and diversity of these key reef fishes and further
 enhances our understanding between butterflyfish and benthic organisms.
description: <em>Fusion-tag
 qPCR</em> A universal primer set targeting 18S
 rRNA (V1-3 hypervariable region; 18S_uni_1F: 5′-GCCAGTAGTCATATGCTTGTCT-3′;
 18S_uni_400R: 5′-GCCTGCTGCCTTCCTT-3′; Pochon et al. 2013) with an amplicon
 length of ~ 340–420 bp and COI (m1COIintF:
 5′-GGWACWGGWTGAACWGTWTAYCCYCC-3′; jgHCO2198: 5′-TAIACYTCIGGRTGICCRAAR
 AAYCA-3′; Leray et al. 2013) with an amplicon length of 313 bp was used to
 maximize the eukaryotic fraction of diversity detected from stomach
 content samples. 18S and COI primers were selected for this study because
 they have been shown to work well across a diversity of marine
 invertebrates, and the combination of these two assays provides a greater
 probability of prey detection for individual butterflyfish (Leray et al.
 2013; Casey et al. 2019, 2021). Samples from 126 individuals were analyzed
 using 18S and 67 samples were analyzed using COI (Table 1).
 Quantitative PCR (qPCR) experiments
 were set up in a dedicated ultra-clean laboratory at Curtin University
 (Perth, Western Australia) designed for ancient DNA work using a QIAgility
 robotics platform (Qiagen, Germany). Given that low copy number and PCR
 inhibition can severely impact metabarcoding data (Murray et al. 2015),
 template input concentrations were optimized using a dilution qPCR series
 based on the reaction conditions described below. To reduce the likelihood
 of cross-contamination, chimera production, and index-tag jumping,
 amplification of target DNA was performed in a single round of PCR using
 fusion-tag primers, custom sequencing primers, and index combinations
 unique to this study. All qPCR reactions for each replicate were run in
 duplicate to control for amplification stochasticity. PCR reagents
 included 1 × AmpliTaq Gold® Buffer (Life Technologies, CA), 2 mM MgCl2,
 0.25 μM dNTPs, 10 μg BSA, 5 pmol of each primer, 0.12 × SYBR® Green (Life
 Technologies, CA), 1 Unit AmpliTaq Gold DNA polymerase (Life Technologies,
 CA), 2 μl of DNA, and Ultrapure® Distilled Water (Life Technologies, CA)
 made up to 25 μl total volume. PCR was performed on a StepOnePlus
 Real-Time PCR System (Applied Biosystems, CA) under the following
 conditions: initial denaturation at 95 °C for 5 min, followed by 45 cycles
 of 30 s at 95 °C, 30 s at 52 °C (18S) or 51 °C (COI), and 45 s at 72 °C,
 with a final extension for 10 min at 72 °C. All extraction controls were
 combined into a single PCR reaction run in duplicate for each assay,
 hereafter referred to as “GutNC”. Libraries for sequencing were
 prepared by pooling amplicons, separated by assay, into equimolar ratios
 based on the endpoint of qPCR amplification curves. Amplicons in each
 pooled library were size selected (160–600 bp) using a Pippin Prep (Sage
 Science, MA) and purified using the Qiaquick PCR Purification Kit (Qiagen,
 Germany). The volume of purified library added to the sequencing run was
 determined against DNA standards of known molarity on a LabChip GX Touch
 (PerkinElmer Health Sciences, MA). Final libraries were sequenced
 paired-end using 500 cycle MiSeq® V2 Reagent Kits on an Illumina MiSeq
 platform (Illumina, CA) located in the Trace and Environmental DNA (TrEnD)
 Laboratory at Curtin University (Perth, Western Australia).
 <strong>References:</strong> Casey, J. M., Meyer, C. P., Morat, F., Brandl, S. J., Planes, S. & Parravicini, V. Reconstructing hyperdiverse food webs: gut content metabarcoding as a tool to disentangle trophic interactions on coral reefs. <em>Methods in Ecology and Evolution</em> <strong>10</strong>, 1157–1170 (2019). Casey, J. M., Ransome, E., Collins, A. G., Mahardini, A., Kurniasih, E. M., Sembiring, A., Schiettekatte, N. M., Cahyani, N. K., Wahyu Anggoro, A., Moore, M., Uehling, A. DNA metabarcoding marker choice skews perception of marine eukaryotic biodiversity. <em>Environmental DNA</em> <strong>6</strong>, 1229–1246 (2021). Leray, M.<em> et al.</em> 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. <em>Frontiers in Zoology</em> <strong>10</strong>, 34 (2013). Murray, D. C., Coghlan, M. L. & Bunce, M. From benchtop to desktop: important considerations when designing amplicon sequencing workflows. <em>PLoS One</em> <strong>10</strong>, e0124671 (2015). Pochon, X., Bott, N. J., Smith, K. F. & Wood, S. A. Evaluating detection limits of next-generation sequencing for the surveillance and monitoring of international marine pests. <em>PloS one</em> <strong>8</strong>, e73935 (2013).
description: We here provide raw Illumina MiSeq sequencing runs (read 1 and
 read 2) in .fastq.gz format. 
 MSRun125_FTP85_S1_L001_R1_001.fastq.gz paired with
 MSRun125_FTP85_S1_L001_R2_001.fastq.gz
 MSRun131_FTP89_S1_L001_R1_001.fastq.gz paired with
 MSRun131_FTP89_S1_L001_R2_001.fastq.gz
 MSRun142_FTP100_S1_L001_R1_001.fastq.gz paired with
 MSRun142_FTP100_S1_L001_R2_001.fastq.gz We additionally
 provide a text file ("Table_Sequence_Tags_Primers.txt") listing
 the type of run (i.e., paired end), paired sequence file names, run date,
 individual sample ID, TrEnD lab sample ID, primer pair, forward tag
 number, forward tag sequence, reverse tag number, reverse tag sequence,
 forward primer sequence, and reverse primer sequence for
 demultiplexing.  All data quality filtering steps that
 we used are outlined in the Coral Reefs publication: 
 https://link.springer.com/article/10.1007/s00338-022-02302-2