DOI: 10.5061/dryad.tdz08kpxx
title: Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman

description: Environmental DNA (eDNA) is increasingly being used to assess community
 composition in marine ecosystems. Applying eDNA approaches across broad
 spatial scales now provide the potential to inform biogeographic analyses.
 However, to date, few studies have employed this technique to assess broad
 biogeographic patterns across multiple taxonomic groups. Here, we compare
 eDNA-derived communities of bony fishes and invertebrates, including
 corals and sponges, from 15 locations spanning the entire length of the
 Omani coast. This survey includes a variety of habitats, including coral
 and rocky reefs, and covers three distinct marine ecoregions. Our data
 support a known biogeographic break in fish communities between the north
 and the south of Oman; however, the eDNA data highlight that this faunal
 break is mostly reflected in schooling baitfish species (e.g., sardines
 and anchovies), whereas reef-associated fish communities appear more
 homogeneous along this coastline. Furthermore, our data provide
 indications that these biogeographic breaks also affect invertebrate
 communities, which includes corals, sponges, and broader eukaryotic
 groups. The observed community shifts were correlated with local
 environmental and anthropogenic differences characteristic of this
 coastline, particularly for the eDNA-derived bony fish communities.
 Overall, this study provides compelling support that eDNA sequencing and
 associated analyses may serve as powerful tools to detect community
 differences across biogeographic breaks and ecoregions, particularly in
 places where there is significant variation in oceanographic conditions or
 anthropogenic impacts.
description: <i>2.3 Fusion-tag qPCR  </i> In
 this study, we used previously published primers to amplify DNA from bony
 fish, corals, and sponges, as well as most other marine eukaryotes from
 mixed environmental samples. The four applied assays are hereafter
 referred to as "18Suni" targeting 18S rRNA in most eukaryotes
 (V1-3 hypervariable region; 18S_uni_1F: 5' – GCCAGTAGTCATATGCTTGTCT –
 3'; 18S_uni_400R: 5' – GCCTGCTGCCTTCCTT – 3'; Pochon, Bott,
 Smith, & Wood, 2013 ), "16SFish" targeting 16S rRNA in
 mostly bony fish (16SF/D: 5' – GACCCTATGGAGCTTTAGAC – 3';
 16S2R-degenerate: 5' – CGCTGTTATCCCTADRGTAACT – 3'; Berry et
 al., 2017; Deagle et al., 2007), "CP1" targeting ITS2 in basal
 metazoans such as corals and sponges (SCL5.8S_F: 5' –
 GARTCTTTGAACGCAAATGGC – 3'; SCL28S_R: 5' –
 GCTTATTAATATGCTTAAATTCAGCG – 3'; Brian, Davy, & Wilkinson,
 2019), and "CP2" targeting a modified fragment of ITS2 more
 appropriate for the additional detection of Acroporid corals (SCL5.8S_F:
 5' – GARTCTTTGAACGCAAATGGC – 3'; Acro874_R: 5' –
 TCGCCGTTACTGAGGGAATC – 3'; Alexander et al., 2020).
 Quantitative PCR (qPCR) experiments were set up in a separate
 ultra-clean laboratory at Curtin University designed for trace DNA work
 using a QIAgility robotics platform (Qiagen Inc.). All qPCR reactions were
 performed in duplicate on a StepOnePlus Real-Time PCR System (Applied
 Biosystems, CA, USA). PCR reagents included 10X AmpliTaq Gold PCR Buffer
 (Applied Biosystems), 2 mM MgCl<sub>2</sub>, 0.25 mM dNTPs,
 0.4 mg/ml BSA (Fisher Biotec, Australia), 0.4 µmol/l of each primer
 (Integrated DNA Technologies, Australia), 0.12X SYBR Green (Life
 Technologies), one Unit AmpliTaq Gold DNA polymerase (Applied Biosystems),
 2 µl of DNA, and Ultrapure Distilled Water (Life Technologies) to make the
 solution to 25 µl total volume. Assay-specific annealing temperatures and
 cycle number are as follows: 18Suni, 52˚C for 45 cycles; 16SFish, 54˚C for
 45 cycles; CP1, 55˚C for 50 cycles; CP2, 55˚C for 50 cycles (for more
 details see DiBattista et al., 2019). To check for contamination,
 non-template control (labelled as NTC) PCR reactions were run alongside
 the template PCR reactions, which only contained master mix including the
 assay primers. Duplicate PCRs for each assay amplified
 from the same eDNA template were combined to control for amplification
 stochasticity and then pooled into a library with all amplicons at
 equimolar ratios based on amplification CT and DRn
 values. Each library was size selected using a Pippin Prep (Sage Science,
 Beverly, USA), retaining amplicons between 160-600 bp for 18Suni, CP1, and
 CP2, and between 160-400 bp for 16SFish, which were then purified using a
 Qiaquick PCR Purification Kit (Qiagen Inc.). Final libraries were
 quantified using a Qubit 4.0 Fluorometer (Invitrogen, Carlsbad, USA) and
 if necessary, diluted to 2nM, prior to loading on either a 300 cycle (for
 unidirectional sequencing; 16SFish) or 500 cycles (for paired-end
 sequencing; 18Suni, CP1, and CP2) MiSeq V2 Standard Flow Cell on an
 Illumina MiSeq platform (Illumina, San Diego, USA).
   References: Alexander, J.
 B., Bunce, M., White, N., Wilkinson, S. P., Adam, A. A., Berry, T., …
 Richards Z.T. (2020). Development of a multi-assay approach for monitoring
 coral diversity using eDNA metabarcoding. <i>Coral Reefs</i>,
 39(1), 159-171. https://doi.org/10.1007/s00338-019-01875-9
 Berry, T. E., Osterrieder, S. K., Murray, D. C., Coghlan, M. L.,
 Richardson, A. J., Grealy, A. K., … Bunce, M. (2017). DNA metabarcoding
 for diet analysis and biodiversity: A case study using the endangered
 Australian sea lion (<i>Neophoca cinerea</i>).
 <i>Ecology and Evolution</i>, 7(14), 5435-5453.
 https://doi.org/10.1002/ece3.3123 Brian, J. I., Davy,
 S. K., & Wilkinson, S. P. (2019). Elevated Symbiodiniaceae
 richness at Atauro Island (Timor-Leste): a highly biodiverse reef system.
 <i>Coral Reefs</i>, 38(1), 123-136.
 https://doi.org/10.1007/s00338-018-01762-9 Deagle, B.
 E., Gales, N. J., Evans, K., Jarman, S. N., Robinson, S., Trebilco, R.,
 Hindell, M. A. (2007). Studying seabird diet through genetic analysis of
 faeces: a case study on macaroni penguins (<i>Eudyptes
 chrysolophus</i>). <i>PLoS One</i>, 2(9), e831.
 https://doi.org/10.1371/journal.pone.0000831
 DiBattista, J. D., Reimer, J. D., Stat, M., Masucci, G. D.,
 Biondi, P., De Brauwer, M., Bunce, M. (2019). Digging for DNA at depth:
 rapid universal metabarcoding surveys (RUMS) as a tool to detect coral
 reef biodiversity across a depth gradient. <i>PeerJ</i>, 7,
 e6379. https://doi.org/10.7717/peerj.6379 Pochon, X.,
 Bott, N. J., Smith, K. F., Wood, S. A. (2013). Evaluating detection limits
 of next-generation sequencing for the surveillance and monitoring of
 international marine pests. <i>PloS One</i>, 8(9), e73935.
 https://doi.org/10.1371/journal.pone.0073935
description: We have provided all raw, compressed Illumina MiSeq sequence read
 1 and read 2 files, where applicable, as well as a tab delimited text file
 entitled "Table, Sequence Tags and Primers" that includes all of
 the sequence tags and primers needed to demultiplex these runs and quality
 filter as required. These MiSeq runs are listed here:<br>
   EFMSRun20_Elib18_R1.fastq.gz
 EFMSRun20_Elib18_R2.fastq.gz
 EFMSRun29_Elib23_R1.fastq
 EFMSRun29_Elib23_R2.fastq
 EFMSRun39_Elib33_R1.fastq.gz
 EFMSRun42_ELib35_R1.fastq.gz
 EFMSRun42_ELib35_R2.fastq.gz Note that for the
 following three Illumina MiSeq runs, demultiplexed .fastq files are
 provided instead: FTP203_Oman_Water.tar.gz
 FTP204_Oman_Water.tar.gz
 FTP209_Oman_Water.tar.gz