This dataset contains 18s DNA sequences of planktonic animals that are potential prey of siphonophores. Siphonophores (Cnidaria: Hydrozoa) are abundant and diverse gelatinous predators in open-ocean ecosystems. This dataset expands the ability to study the feeding ecology of siphonophores and the structure of the open-ocean food web by facilitating the molecular identification of siphonophore gut contents. The new data presented here are for species that were underrepresented in existing sequence datasets.

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Related Publications
• Parameters
• Instruments
• Project Information
• Funding

Bioinformatic pipeline

Amplicon libraries were demultiplexed by primer sequence using custom bash code. Primer sequences were removed using cutadapt (Martin 2011). The forward and reverse reads were matched and repaired using bbtools (Bushnell 2017), then denoised and de-replicated using the DADA2 (Callahan 2016) plugin in QIIME2 (Bolyen 2019) with a truncation quality threshold of 28. We de novo clustered the unique features into operational taxonomic units (OTUs) using the VSEARCH (Rognes 2016) plugin in QIIME2 with a similarity threshold of 95%. To reduce computational load, only the top 100 most abundant features among the clustered OTUs were selected for taxonomic assignment. Taxonomic identities were assigned using the assignment software METAXA2 (Bengtsson‐Palme 2015) with a 70% reliability cutoff, comparing the sequences against the SILVA123.1 reference library (Quast 2012), and against our custom-built library built using SILVA138 as a foundation. The SILVA123.1 database contains 61383 eukaryotic reference sequences, while our custom database (built off SILVA138.1) contains 79044. Animals in the SILVA123.1 taxonomy are annotated to the ranks of superphylum, phylum, subphylum, class, subclass, order, family, genus, and species. However, the SILVA138.1 animal taxonomy was annotated at the levels of clade (e.g. Bilateria, Protostomia, Deuterostomia, Ecdysozoa, Lophotrochozoa), phylum, class, subclass, order, suborder, and species. All bioinformatics analyses were carried out in the Yale High Performance Computing Cluster. The taxonomic assignments and read count data were merged, then parsed to match the sample of origin and the DNA sequence they derived from. Sequence post-processing scripts can be found in the GitHub repository https://github.com/dunnlab/siphweb_metabarcoding/Scripts (Damian-Serrano, 2024).

Processed submitted files using the BCO-DMO tool named Laminar to create the primary data file named 935469_v1_gut_dna_seq_potential_prey_of_siphonophores.csv and the supplemental data file named 935469_supl_rrna_partial_seq_potential_prey_of_siphonophores.

- Created a SRA Run Info table which was downloaded from NCBI on page listing experiments https://www.ncbi.nlm.nih.gov/sra/?term=SRP321688

Added to this table to include information about Spots.
Additional metadata: spots bases spots_with_mates avgLength size_MB TaxID

The SRA Run Info table was named SraRunInfo.csv.

- Imported the submitted file named Example_Dunn_NCBI_SRA_RunTable.xlsx and the SRA Run Info file SraRunInfo.csv into Laminar.

- Renamed parameters in the file Example_Dunn_NCBI_SRA_RunTable.xlsx to follow BCO-DMO naming convention by replacing spaces with underscores.

- Removed two fields, geo_loc_name_country and geo_loc_name_country_continent, which contained the value of 'uncalculated' as it doesn't add any information to the dataset. The values for these two parameters was not entered in the NCBI submission, and that's why the value is 'uncalculated'. The location information of 'Water off California' is included on the dataset page.

- Joined the two submitted files into one table by joining on the parameter Run.

- Removed the parameter Bytes since the parameter size_MB is the same information with the size in MB which is easier to read.

- Converted the Collection_Date parameter format from %m-%d-%y to %Y-%m-%d to be in the ISO 8601 format.

- Renamed any parameters in the joined table that have spaces in their names with an underscore to follow BCO-DMO naming conventions.

- Split the column lat_lon which contained both latitude and longitude values into separate latitude and longitude columns. Then converted latitude values to positive or negative values following the convention of South is negative. And converted longitude values to positive or negative values following the convention of West is negative. Finally, deleted the lat_lon column since the information is now in separate columns.

- Renamed this table to 935469_supl_rrna_partial_seq_potential_prey_of_siphonophores.

- Imported the submitted file named Dunn_NCBI_MZ_data.xlsx into Laminar to process it. These are the steps performed for this file.

- Removed parameters with no values except for the Cruise_ID parameter which is filled in with information from the submitter.

- Removed the column Date because the submitter requested it in an email dated 10/15/2024. This is the comment from that email "Sorry about the double date columns. That is the result of a table join I did to integrate two different tables. Please disregard the Date column."

- Renamed parameters by replacing spaces with underscores according to BCO-DMO naming convention.

- Added a prefix of NCBI_ to the Accession parameter to make it clear where the Accession number comes from.

- Replaced Clade value for prey organism Calanus pacificus from Ctenophora to Copepoda. This change was performed from referencing the NCBI accession value and the taxonomy listed for the organism: Eukaryota; Metazoa; Ecdysozoa; Arthropoda; Crustacea; Multicrustacea; Hexanauplia; Copepoda; Calanoida; Calanidae; Calanus.

- Replaced Clade value for prey organism Parasagitta elegans from Ctenophora to Chaetognatha. This change was performed from referencing the NCBI accession value and the taxonomy listed for the organism: Eukaryota; Metazoa; Spiralia; Gnathifera; Chaetognatha; Sagittoidea; Aphragmophora; Ctenodontina; Sagittidae; Parasagitta.

- Replaced Clade value for prey organism Pleurobrachia bachei from Ostracoda to Ctenophora. This change was performed from referencing the NCBI accession value and the taxonomy listed for the organism: Eukaryota; Metazoa; Ctenophora; Tentaculata; Cydippida; Pleurobrachiidae; Pleurobrachia.

- Renamed this processed file to 935469_supl_rrna_partial_seq_potential_prey_of_siphonophores.

Created a taxonomy file named species_taxonomy_of_hosts_found_in_primary_file.csv that contains taxonomy information from the World Register of Marine Species (WoRMS) at https://www.marinespecies.org/index.php for the hosts listed in the primary dataset file 935469_v1_gut_dna_seq_potential_prey_of_siphonophores.csv.

Created a taxonomy file named species_taxonomy_of_prey_found_in_supplemental_file.csv that contains taxonomy information from the World Register of Marine Species (WoRMS) at https://www.marinespecies.org/index.php for the prey listed in the supplemental dataset file 935469_supl_rrna_partial_seq_potential_prey_of_siphonophores.csv.

Coverage: North Pacific

Food webs describe who eats whom, tracing the flow of energy from plants up to large animals. While many connections in food webs on land are quite familiar (lions eat antelope and antelope eat grass, for example), there are large gaps in our understanding of ocean food webs. Closing these gaps is critical to understanding how nutrients and energy move through ocean ecosystems, how organisms interact in the ocean, and how best to manage ocean resources. This project will study ocean food web structure with a focus on siphonophores, an abundant group of predators in the open ocean that range in length from less than an inch to more than one hundred feet. Siphonophores are closely related to corals and many jellyfish. They are known to be important predators within ocean food webs, but they are difficult to study because they live across great ocean depths and are gelatinous and fragile. The details of what they eat, as well as many other features of their biology, remain poorly known. This project will combine direct observations of feeding, genetic analysis of siphonophore gut contents, and stable isotope analyses to identify what different species of siphonophores eat. The team will also examine why they eat what they do. This will provide a new understanding of how the structure of food webs arise, aiding in our ability to predict future changes to food webs as the global climate shifts. Siphonophores feed in a very unique manner--they have highly specialized tentacles that are used solely for capturing prey--thus, the prey captured is determined largely by the anatomy and function of these tentacles. The project will describe these tentacles, reconstruct their evolutionary history, and investigate how evolutionary shifts in tentacle structure have led to changes in diet. This project will train one PhD student, one Master's student, a postdoc, and undergraduate students, including individuals of underrepresented groups. This project will support the production of scientifically rigorous yet engaging videos, foster the expansion of a citizen-science program, and create K-12 teaching modules. 

This project will advance three scientific aims: First, it will identify the diet of a diverse range of siphonophores using DNA metabarcoding of gut contents and prey field, remotely operated vehicle (ROV) video of prey encounters, and stable isotope analysis. These approaches are highly complementary and allow for extensive cross validation. Second, the project will characterize the selectivity of siphonophore diets by comparing them to the relative prey abundances in the habitats of each of these species. Third, the project will characterize the structure of the siphonophore prey capture apparatus across species through detailed morphological analysis of their tentacles and nematocysts. These data will be integrated in an ecological and evolutionary framework to identify predator features associated with prey specialization. In a larger context, addressing these questions will advance our understanding of oceanic predation by revealing how evolutionary changes in predator selectivity correspond to evolutionary changes in habitat and feeding apparatus and how these changes shape current food web structure in the open ocean. We will test and refine an integrated approach to describing the structure and origin of food web topology, and evaluate the potential for phylogenetic relationships to explain prey selectivity. 

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.