Abstract
The European Marine Omics Biodiversity Observation Network (EMO BON) is a long-term genomic observatory run by the European Research Infrastructure European Marine Biological Resource Centre (EMBRC). It was established in 2021 to support the challenges of biodiversity observation and unsystematic management of biodiversity data in the European seas. EMO BON introduced and coordinated the systematic and harmonised observation of biodiversity amongst more than fourteen marine stations in the European coastline. Here, we report the next release (Release 2) of shotgun metagenomic data from seawater and sediment microbial communities.
Keywords: metagenomics, marine biodiversity, ocean observation, water column, soft substrate, microorganisms
Introduction
The advancement of marine biological observation needs to be built on long-term initiatives, able to produce data tackling not only the spatial, but also the temporal component of the dynamic biodiversity. The coordination across different entities and countries has always presented a challenge and a prerequisite for expanded observation capacity in space and time. Research Infrastructures (RIs), as part of the pan-European scientific landscape, can play a substantial role in this by adding value for their members in providing services and resources, such as management and coordination of marine biological observation.
The EMBRC RI consolidated the marine genomics experience in its community and, therefore, established and coordinated the EMO BON network (Santi et al. 2023). The network widens the distribution of the observatories along the entire European coastline and includes a unique and broad coverage of habitats and longitudes, from the Arctic to the Red Sea. The different observatory stations are coordinated at the RI-level and act as nodes of one integrated network. In 2025, EMO BON is running its fifth year in operation, all the while sample collection and processing, data generation and management and network coordination progress continuously. The aspiration is to maintain the network for at least 10 years of systematic biodiversity observation.
Value of the dataset
This work is the second set of genomic datasets of the EMO BON long-term observation network. It follows up from the first dataset that was realised in this journal in March 2025 (Pavloudi et al. 2025) and will be followed by future releases. All data releases are accompanied by a data publication describing the (meta)data and their online location and allowing for maximum data re-usability and openness, exhibiting the value and potential impact in biodiversity observation research. This release includes raw shotgun metagenomic sequencing data from the seawater and the marine sediment collected between October and December 2021 from 13 observatories, across the European coast and in the Red Sea. The raw sequence data are deposited in and accessible through the European Nucleotide Archive (ENA) (O’Cathail et al. 2024), together with metadata associated with the sampling event, sample preparation, processing and sequencing procedures and a diverse set of measured environmental variables available, such as temperature, salinity and nutrient concentrations in the associated BioSamples (Courtot et al. 2021). Follow-up publications related to the EMO BON macro- and meio-benthos metabarcoding data are upcoming. In addition, it connects with the recent data release from the marine genetic monitoring programme ARMS-MBON (Autonomous Reef Monitoring Structure Marine Biodiversity Observation Network) (Daraghmeh et al. 2025) that was merged into EMO BON and the ARMS data releases that are in preparation (Pagnier et al. 2025).
The present dataset is part of a larger biodiversity time series dataset that is progressively being released in ENA and published in this journal. The impact of the whole dataset is predicted to appear after at least 5 years of data releases, as the value increases with the extension of the data's temporal range. The existence of a marine biodiversity dataset of this depth and quality, spanning at least 5 years and multiple coastal areas in Europe is expected to have a broad appeal, hence increasing the data users and applications.
In addition, this dataset aligns with the mission of the Ocean Biodiversity Information System (OBIS), to facilitate free and open access to biodiversity data and information on marine life. Data products generated after the bioinformatics analyses of this dataset will include taxonomical and functional information and will be submitted in OBIS and in the Global Biodiversity Information Facility (GBIF), using the DNA extension of the Darwin Core standards. Following the data availability in OBIS and GBIF, the data products will be incorporated in the European Marine Observation and Data Network (EMODnet) and the European Digital Twin of the Ocean (EU DTO). This FAIR data flow into the EU DTO will allow, on one hand, to fill gaps in the current knowledge on biodiversity of the world's oceans and, on the other hand, to model and simulate the ‘what if’ scenarios, further advancing ocean knowledge and providing information for evidence-based policy-making.
The potential arising from the incorporation of genomic methodologies into marine observation is enormous. Out of many arguments outlining the added value of including genomics to the study of biodiversity in scientific publications (for example, Cordier et al. (2020), Pawlowski et al. (2022), Theissinger et al. (2023)), the most relevant and influential to the EMO BON initiative are the ability to early detect non-indigenous species, the identification of cryptic species and early life stages (e.g. larvae), the interaction amongst species, the study of evolutionary ecology and events shaping species diversity, the access to communities difficult to identify morphologically such as microorganisms and meiofauna, the exploration and explanation of biodiversity patterns across time and space including different communities, from microorganisms to macrobenthos and the response of biodiversity to ecosystem changes (for example, climate change and pollution). Furthermore, the metagenomic analyses of samples allow us to access data and, subsequently, information on function. This leads to additional scientific directions like bioprospecting and biotechnology research, community functioning across time and space and connection of communities functioning to ecosystem changes.
In this dataset, each material sample is represented by identical technical replicates, two of which are processed and sequenced using the exact same methodologies and workflow. The duplicate data can increase the quality of the whole sequencing dataset by allowing the assessment of the processing and sequencing procedures and providing an additional level of quality assurance.
The field of DNA-based environmental research is rapidly evolving and, thus, anticipating the future need for biodiversity re-assessments, another two technical replicates for each material sample are stored in the long-term. The long-term stored replicates can be processed in the future using new technologies or targeted scientific questions. Using the long-term stored samples will open a window in time and allow potential re-sequencing or usage of other omics technologies and combining with the data produced in the present.
Methods
The sampling, sample and data processing methodologies are described in the first EMO BON dataset publication (Pavloudi et al. 2025). The procedures are also briefly described in the following subsections.
Sampling
Seawater sampling was performed by following the Standard Operating Procedures (SOPs) included in the EMO BON Handbook (Santi et al. 2021) and in particular “WaSOP 1 (basic)”. Subsurface seawater was collected using Niskin bottles, pre-filtered using 200 μm mesh to exclude particles > 200 μm. The pre-filtered seawater was sequentially filtered through 3 μm and 0.2 μm polycarbonate filter membranes; this produced two seawater samples including particles of different size fractions: 3-200 μm and 0.2-3 μm. Each of the membranes was subsequently cut into two equal pieces using a sterile scalpel; each cut membrane was considered to represent one technical replicate. The sequential filtration took place two separate times producing 2 X the 3-200 μm and 0.2-3 μm membranes, which were then cut into two pieces of equal size, finally generating four technical replicates [First sequential filtration: 3-200 μm membrane cut in half to generate 3-200 μm replicates (1) and (2); and 0.2-3 μm membrane cut in half to generate 0.2-3 μm replicates (1) and (2). Second sequential filtration: 3-200 μm membrane cut in half to generate 3-200 μm replicates (3) and (4); and 0.2-3 μm membrane cut in half to generate 0.2-3 μm replicates (3) and (4)]. Replicates (1) and (2) were preserved in individual tubes using the DNA/RNA shield preservative (Zymo Research) and stored at -80oC until shipment to the sequencing facility. Replicates (3) and (4) were preserved in cryotubes without the addition of DNA/RNA Shield and stored at -80oC for long-term storage.
Sediment was collected by following the Standard Operating Procedures (SOPs) included in the EMO BON Handbook (Santi et al. 2021). In particular, “SoSOP 1 (intertidal sediments)" was followed by the observatories NRMCB and RFormosa, “SoSOP 2 (coastal sediments by diving)" was followed by the observatories ROSKOGO and OOB, “SoSOP 3 (coastal sediments by research vessel)" was followed by the observatory BPNS. In all SOPs, sediment was sampled (or subsampled from the sediment grab in SoSOP 3) using sediment corers. The top 5 cm were sliced, gently homogenised and subsamples were placed in individual tubes to represent four technical replicates. Similarly to the seawater approach, replicates (1) and (2) were preserved in DNA/RNA Shield and stored at -80oC until shipment to the sequencing facility; replicates (3) and (4) were preserved in cryotubes without the addition of DNA/RNA Shield and stored at -80oC for long-term storage.
Geographic range
EMO BON observatories are operating in each of the EMBRC member countries in the EU. This dataset includes data from Norway, Belgium, UK (former EMBRC member), France, Spain, Portugal, Italy and Israel. The geographic range of the dataset includes 14 locations across eight marine ecoregions, based on the Marine Ecoregions of the World (MEOW) (Spalding et al. 2007) (Table 1, Fig. 1). The locality of the observatories is also described using standardised georeferenced terms from the Marine Regions (Flanders Marine Institute 2025), from the broader (ocean/sea) to the regional and the local level (Table 1, Fig. 1). This dataset includes data from the observatory IUIEilat located in the Gulf of Eilat, Indian Ocean, which falls outside the primary European focus of this study.
Table 1.
Coordinates, locality, sampling type (seawater and/or sediment) and number of samples for the operational observatories sampling sites.
| Observatory | Coordinates | Ocean/Sea | Region | Location | Marine Ecoregion of the World (MEOW) | Seawater sampling | Sediment sampling | Total Number of samples in this batch | Number of successfully sequenced samples |
| AAOT | 45.31417N; 12.508333E | Mediterranean Sea - Eastern Basin | Adriatic Sea | Gulf of Venice | Adriatic Sea | Yes | 8 | 8 | |
| BPNS | 51.43333N; 2.808331E | North Atlantic Ocean | North Sea | Belgian part of the North Sea | North Sea | Yes | Yes | 12 | 12 |
| EMT21 | 42.20194N; -8.798500W | Atlantic Ocean | North Atlantic Ocean | Vigo Seamount | South European Atlantic Shelf | Yes | 8 | 8 | |
| ESC68N | 68.92589N; 17.125619E | Arctic Ocean | Norwegian Sea | Norwegian part of the Norwegian Sea | Northern Norway and Finnmark | Yes | 8 | 2 | |
| IUIEilat | 29.50000N; 34.916667E | Indian Ocean | Gulf of Eilat | Gulf of Eilat | Northern and Central Red Sea | Yes | 8 | 8 | |
| NRMCB | 40.80014N; 14.250000E | Mediterranean Sea - Western Basin | Tyrrhenian Sea | Naples Gulf | Western Mediterranean | Yes | Yes | 8 | 12 |
| OOB | 42.489N; 3.143E | Mediterranean Sea - Western Basin | Gulf of Lion | Bay of Banyuls-sur-Mer | Western Mediterranean | Yes | 4 | 2 | |
| OSD74 | 41.14653N; -8.666639W | Atlantic Ocean | North Atlantic Ocean | Porto Valley | South European Atlantic Shelf | Yes | 8 | 8 | |
| PiEGetxo | 43.33858N; -3.014639W | North Atlantic Ocean | Bay of Biscay | Abra de Bilbao | South European Atlantic Shelf | Yes | 8 | 8 | |
| RFormosa | 37.00564N; -7.969250W | Atlantic Ocean | North Atlantic Ocean | Ria Formosa | South European Atlantic Shelf | Yes | Yes | 12 | 12 |
| ROSKOGO | 48.70833N; -3.866000W | North Atlantic Ocean | English Channel | French part of the English Channel | Celtic Seas | Yes | 4 | 4 | |
| ROSKOGO | 48.77167N; -3.968333W | North Atlantic Ocean | English Channel | French part of the English Channel | Celtic Seas | Yes | 8 | 8 | |
| VB | 43.68300N; 7.317000E | Mediterranean Sea - Western Basin | Villefranche Bay | Villefranche Bay - Point B | Western Mediterranean | Yes | 8 | 8 | |
| MBAL4 | 50.25N; -4.217W | North Atlantic Ocean | English Channel | Western Channel | Celtic Seas | Yes | 8 | 8 |
Figure 1.
Map of EMO BON observatory sampling sites for sediment (triangle ▲), seawater (circle ●) and both seawater and sediment (square ◼), included in this dataset. Observatory IUIEilat located in the Gulf of Eilat, Indian Ocean, falls outside the primary European focus of this study.
Temporal range
This dataset includes samples collected from October to December 2021.
Sample processing
DNA extraction, library preparation and sequencing
DNA extraction, library preparation and sequencing were collectively performed at the Genoscope French National Sequencing Centre and are described in detail in the first EMO BON dataset publication (Pavloudi et al. 2025). Brief description of sample processing are included here. The water column samples were extracted according to Alberti et al. (2017): manual cell disruption by cryogenic grinding of membrane filters followed by chemical lysis and nucleic acid purification using NucleoSpin RNA Kits, combined with the NucleoSpin RNA/DNA buffer set (Macherey-Nagel, Düren, Germany). The sediment samples were extracted using the DNeasy PowerSoil Pro Kit (Qiagen) with slight modifications.
Fragments of ~ 350 bp were obtained by sonication. After freebarcodes adapters were added, ligation products were purified using beads and Illumina specific adapters were added by PCR amplifications (2 PCR reactions, 14 cycles). Libraries were quantified and their size profiles analysed prior to sequencing.
Sequencing was performed using 151-bp pairwise read chemistry on an Illumina NovaSeq6000 sequencer, using S4 Flowcells (Illumina, San Diego, CA, USA). A minimum of 40,000 million useful paired-end reads were obtained per sample. Short Illumina reads were bioinformatically post-processed sensu Alberti et al. (2017) to filter out low-quality data. Finally, read pairs mapping to the phage phiX genome were identified and discarded using SOAP aligner (Li et al. (2008), default parameters) and the Enterobacteria phage PhiX174 reference sequence (GenBank: NC_001422.1)
Biodiversity scope
Target
Microbial Prokaryotic and Eukaryotic biodiversity in the marine environment.
Taxonomic range
Archaea, Bacteria, Eukaryota
Data Resources
Details for the samples can be found in Suppl. material 1. All the raw sequence files of this study were submitted to ENA (O’Cathail et al. 2024) with the umbrella study accession number PRJEB51688. The accession numbers of the component projects under the umbrella study are PRJEB51656, PRJEB51652, PRJEB51653, PRJEB51657, PRJEB50566, PRJEB51664, PRJEB51662, PRJEB51654, PRJEB51660, PRJEB51661, PRJEB51658, PRJEB51665 and PRJEB51659. All sampling events and environmental data, linked to the respective accession numbers, are also available to browse and download from EMO BON’s data landing page.
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Data format : FASTQ
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Resource 41
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Resource identifier: ERR14888801
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/001/ERR14888801/ERR14888801_2.fastq.gz
Resource 42
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Data format : FASTQ
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Resource 43
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Resource identifier: ERR14888803
Data format : FASTQ
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Resource 44
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Resource identifier: ERR14888804
Data format : FASTQ
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Resource 45
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Resource identifier: ERR14888805
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/005/ERR14888805/ERR14888805_2.fastq.gz
Resource 46
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Data format : FASTQ
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Resource 47
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Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/007/ERR14888807/ERR14888807_2.fastq.gz
Resource 48
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Resource identifier: ERR14888808
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/008/ERR14888808/ERR14888808_2.fastq.gz
Resource 49
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Resource identifier: ERR14888809
Data format : FASTQ
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Resource 50
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Resource identifier: ERR14888810
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/010/ERR14888810/ERR14888810_2.fastq.gz
Resource 51
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Resource identifier: ERR14888811
Data format : FASTQ
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Resource 52
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Resource identifier: ERR14888897
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/097/ERR14888897/ERR14888897_2.fastq.gz
Resource 53
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Resource identifier: ERR14888898
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/098/ERR14888898/ERR14888898_2.fastq.gz
Resource 54
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Resource identifier: ERR14888899
Data format : FASTQ
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Resource 55
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Data format : FASTQ
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Resource 56
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Data format : FASTQ
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Data format : FASTQ
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Resource 58
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Data format : FASTQ
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Resource 59
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Data format : FASTQ
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Resource 60
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Data format : FASTQ
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Resource 61
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Data format : FASTQ
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Resource 62
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Data format : FASTQ
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Resource 63
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Data format : FASTQ
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Data format : FASTQ
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Resource 65
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Resource identifier: ERR14888601
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/001/ERR14888601/ERR14888601_2.fastq.gz
Resource 66
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Data format : FASTQ
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Resource 67
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Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/080/ERR14888780/ERR14888780_2.fastq.gz
Resource 68
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Resource identifier: ERR14888781
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/081/ERR14888781/ERR14888781_2.fastq.gz
Resource 69
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Resource identifier: ERR14888782
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/082/ERR14888782/ERR14888782_2.fastq.gz
Resource 70
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Data format : FASTQ
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Resource 71
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Resource identifier: ERR14888784
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/084/ERR14888784/ERR14888784_2.fastq.gz
Resource 72
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Resource identifier: ERR14888785
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/085/ERR14888785/ERR14888785_2.fastq.gz
Resource 73
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Resource identifier: ERR14888786
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/086/ERR14888786/ERR14888786_2.fastq.gz
Resource 74
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Resource identifier: ERR14888970
Data format : FASTQ
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Resource 75
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Resource identifier: ERR14888972
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/072/ERR14888972/ERR14888972_2.fastq.gz
Resource 76
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Resource identifier: ERR14888973
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/073/ERR14888973/ERR14888973_2.fastq.gz
Resource 77
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Resource identifier: ERR14888974
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/074/ERR14888974/ERR14888974_2.fastq.gz
Resource 78
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Resource identifier: ERR14888975
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/075/ERR14888975/ERR14888975_2.fastq.gz
Resource 79
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Resource identifier: ERR14888976
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/076/ERR14888976/ERR14888976_2.fastq.gz
Resource 80
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Resource identifier: ERR14888977
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/077/ERR14888977/ERR14888977_2.fastq.gz
Resource 81
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Resource identifier: ERR14888978
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/078/ERR14888978/ERR14888978_2.fastq.gz
Resource 82
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Resource identifier: ERR14888979
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/079/ERR14888979/ERR14888979_2.fastq.gz
Resource 83
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Resource identifier: ERR14888980
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/080/ERR14888980/ERR14888980_2.fastq.gz
Resource 84
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Resource identifier: ERR14888981
Data format : FASTQ
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Resource 85
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Resource identifier: ERR14888982
Data format : FASTQ
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Resource 86
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Data format : FASTQ
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Resource 87
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Data format : FASTQ
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Resource 88
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Resource identifier: ERR14888960
Data format : FASTQ
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Resource 89
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Resource identifier: ERR14888961
Data format : FASTQ
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Resource 90
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Resource identifier: ERR14888962
Data format : FASTQ
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Resource 91
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Data format : FASTQ
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Resource 92
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Data format : FASTQ
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Resource 93
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Resource identifier: ERR14888965
Data format : FASTQ
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Resource 94
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Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/066/ERR14888966/ERR14888966_2.fastq.gz
Resource 95
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Data format : FASTQ
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Resource 96
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Resource identifier: ERR14888968
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/068/ERR14888968/ERR14888968_2.fastq.gz
Resource 97
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Resource identifier: ERR14888969
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/069/ERR14888969/ERR14888969_2.fastq.gz
Resource 98
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Data format : FASTQ
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Resource 99
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Resource identifier: ERR14888715
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/015/ERR14888715/ERR14888715_2.fastq.gz
Resource 100
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Resource identifier: ERR14888849
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/049/ERR14888849/ERR14888849_2.fastq.gz
Resource 101
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Resource identifier: ERR14888850
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/050/ERR14888850/ERR14888850_2.fastq.gz
Resource 102
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Resource identifier: ERR14888851
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/051/ERR14888851/ERR14888851_2.fastq.gz
Resource 103
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Resource identifier: ERR14888852
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/052/ERR14888852/ERR14888852_.fastq.gz
Resource 104
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Resource identifier: ERR14888853
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/053/ERR14888853/ERR14888853_2.fastq.gz
Resource 105
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Resource identifier: ERR14888854
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/054/ERR14888854/ERR14888854_.fastq.gz
Resource 106
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Resource identifier: ERR14888855
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/055/ERR14888855/ERR14888855_2.fastq.gz
Resource 107
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Resource identifier: ERR14888856
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/056/ERR14888856/ERR14888856_2.fastq.gz
Resource 108
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/079/ERR14888679/ERR14888679_1.fastq.gz
Resource identifier: ERR14888679
Data format : FASTQ
Download URL: ftp.sra.ebi.ac.uk/vol1/fastq/ERR148/079/ERR14888679/ERR14888679_2.fastq.gz
Usage Rights
CC BY 4.0
Usage Rights
Supplementary Material
ENA accession numbers
Christina Pavloudi
Data type
metadata
Brief description
ENA accession numbers (sample, experiment, run, project and umbrella project) for the EMO BON shotgun metagenomics data release from seawater and sediment samples (batch_2, second release).
File: oo_1460327.csv
Acknowledgements
This work used resources provided by the European Marine Omics Biodiversity Observation Network (EMO BON) project, coordinated by the European Marine Biological Resource Centre - European Research Infrastructure Consortium (EMBRC-ERIC). For the SZN observatory (NRMCB), the captain and crew of RV Vettoria, Carmen Minucci and the NEREA Team (www.nerea-observatory.org) are acknowledged for support to sampling. For the BPNS observatory, captain and crew of RV Simon Stevin are acknowledged for operational support and FWO I002021N and I001621N for funding. For the CCMAR observatory (RFormosa), this study received Portuguese national funds from FCT - Foundation for Science and Technology through UID/04326/2025, UID/PRR/04326/2025 and LA/P/0101/2020 (DOI: 10.54499/LA/P/0101/2020) and from the operational programmes CRESC Algarve 2020 and COMPETE 2020 through contracts EMBRC.PT ALG-01-0145-FEDER-022121 and BIODATA.PT ALG-01-0145-FEDER-022231. For the PiE-UPV/EHU observatory (PiEGetxo), we acknowledge the Grant to consolidated research projects of the Basque Government (IT1743-22; IT1657-22 and IT1471-22). For the Station Biologique de Roscoff (SBR) observatory (ROSKOGO), the captain and crew of RV Neomysis, Stéphanie Cabioch, Noël Guidal, Arnaud Perrey and the Service Mer et Plongée Team are acknowledged for operational support to sampling. This work was also supported by Genoscope, the Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), funded as part of the «Investissements d’Avenir» programme managed by the Agence Nationale pour la Recherche (contract ANR-10-INBS-09).
Conflicts of interest
No conflict of interest to declare
Disclaimer: This article is (co-)authored by any of the Editors-in-Chief, Managing Editors or their deputies in this journal.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
ENA accession numbers
Christina Pavloudi
Data type
metadata
Brief description
ENA accession numbers (sample, experiment, run, project and umbrella project) for the EMO BON shotgun metagenomics data release from seawater and sediment samples (batch_2, second release).
File: oo_1460327.csv