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.

2.3 Fusion-tag qPCR 

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 MgCl₂, 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. Coral Reefs, 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 (Neophoca cinerea). Ecology and Evolution, 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. Coral Reefs, 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 (Eudyptes chrysolophus). PLoS One, 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. PeerJ, 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. PloS One, 8(9), e73935. https://doi.org/10.1371/journal.pone.0073935

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:
 

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