Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman

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 biogeo...

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Main Authors: DiBattista, Joseph, Berumen, Michael, Priest, Mark, De Brauwer, Maarten, Coker, Darren, Sinclair-Taylor, Tane, Hay, Amanda, Bruss, Gerd, Mansour, Shawky, Bunce, Michael, Goatley, Christopher, Power, Matthew, Marshell, Alyssa
Format: Dataset
Language:English
Published: Dryad 2020
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.tdz08kpxx
http://datadryad.org/stash/dataset/doi:10.5061/dryad.tdz08kpxx
id ftdatacite:10.5061/dryad.tdz08kpxx
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic FOS Biological sciences
spellingShingle FOS Biological sciences
DiBattista, Joseph
Berumen, Michael
Priest, Mark
De Brauwer, Maarten
Coker, Darren
Sinclair-Taylor, Tane
Hay, Amanda
Bruss, Gerd
Mansour, Shawky
Bunce, Michael
Goatley, Christopher
Power, Matthew
Marshell, Alyssa
Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
topic_facet FOS Biological sciences
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. : 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
format Dataset
author DiBattista, Joseph
Berumen, Michael
Priest, Mark
De Brauwer, Maarten
Coker, Darren
Sinclair-Taylor, Tane
Hay, Amanda
Bruss, Gerd
Mansour, Shawky
Bunce, Michael
Goatley, Christopher
Power, Matthew
Marshell, Alyssa
author_facet DiBattista, Joseph
Berumen, Michael
Priest, Mark
De Brauwer, Maarten
Coker, Darren
Sinclair-Taylor, Tane
Hay, Amanda
Bruss, Gerd
Mansour, Shawky
Bunce, Michael
Goatley, Christopher
Power, Matthew
Marshell, Alyssa
author_sort DiBattista, Joseph
title Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
title_short Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
title_full Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
title_fullStr Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
title_full_unstemmed Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman
title_sort environmental dna reveals a multi-taxa biogeographic break across the arabian sea and sea of oman
publisher Dryad
publishDate 2020
url https://dx.doi.org/10.5061/dryad.tdz08kpxx
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long_lat ENVELOPE(-86.200,-86.200,-77.800,-77.800)
ENVELOPE(-66.200,-66.200,-66.817,-66.817)
geographic Reimer
Wilkinson
geographic_facet Reimer
Wilkinson
genre Eudyptes chrysolophus
genre_facet Eudyptes chrysolophus
op_relation https://dx.doi.org/10.1002/edn3.252
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op_rightsnorm CC0
op_doi https://doi.org/10.5061/dryad.tdz08kpxx
https://doi.org/10.1002/edn3.252
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spelling ftdatacite:10.5061/dryad.tdz08kpxx 2023-05-15T16:08:23+02:00 Environmental DNA reveals a multi-taxa biogeographic break across the Arabian Sea and Sea of Oman DiBattista, Joseph Berumen, Michael Priest, Mark De Brauwer, Maarten Coker, Darren Sinclair-Taylor, Tane Hay, Amanda Bruss, Gerd Mansour, Shawky Bunce, Michael Goatley, Christopher Power, Matthew Marshell, Alyssa 2020 https://dx.doi.org/10.5061/dryad.tdz08kpxx http://datadryad.org/stash/dataset/doi:10.5061/dryad.tdz08kpxx en eng Dryad https://dx.doi.org/10.1002/edn3.252 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 CC0 FOS Biological sciences dataset Dataset 2020 ftdatacite https://doi.org/10.5061/dryad.tdz08kpxx https://doi.org/10.1002/edn3.252 2022-02-08T13:02:41Z 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 Dataset Eudyptes chrysolophus DataCite Metadata Store (German National Library of Science and Technology) Reimer ENVELOPE(-86.200,-86.200,-77.800,-77.800) Wilkinson ENVELOPE(-66.200,-66.200,-66.817,-66.817)