http://lod.bco-dmo.org/id/dataset/1003525
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2026-08-04
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
RNA taxonomy data from an iron incubation experiment during the PUPCYCLE II cruise (R/V Sally Ride) within the California Current System in May and June of 2023
2026-08-12
publication
2026-08-12
revision
BCO-DMO Linked Data URI
2026-08-12
creation
http://lod.bco-dmo.org/id/dataset/1003525
Adrian Marchetti
University of North Carolina at Chapel Hill
principalInvestigator
Natalie Cohen
University of Georgia
principalInvestigator
Astrid Schnetzer
North Carolina State University
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Speciale, E., Marchetti, A., Lim, P., Jeong, Y., Cook, C., Cohen, N., McClure, W., Schnetzer, A. (2026) RNA taxonomy data from an iron incubation experiment during the PUPCYCLE II cruise (R/V Sally Ride) within the California Current System in May and June of 2023. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-08-12 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/1003525 [access date]
RNA taxonomy from iron incubation experiments PUPCYCLE II Dataset Description: <p>This dataset is one of many generated from an iron incubation experiment conducted as part of the PUPCYCLE II cruise in May and June 2023. The different analyses are listed here, with links to other datasets from this study in the Related Datasets section.</p>
<p>Analyses&nbsp;include:</p>
<ul>
<li>Physiology (dataset 994607)
<ul>
<li>Dissolved inorganic nutrients</li>
<li>Size-fractionated chlorophyll a</li>
<li>Size-fractionated isotope uptake rates</li>
<li>Flow cytometry</li>
<li>FlowCAM analysis</li>
<li>FLP experiments for mixotroph grazing</li>
</ul>
</li>
<li><strong>RNA taxonomy data (this dataset 1003525)</strong></li>
<li>Differential expression: Pfam
<ul>
<li>Mixotroph Pfam (dataset 1004659)</li>
<li>Diatom Pfam (dataset 1004674)</li>
</ul>
</li>
<li>Differential expression: KEGG gene&nbsp;(dataset 1004689)</li>
<li>Differential expression: KEGG pathways (dataset1004704)</li>
<li>Dissolved iron concentrations (dataset 1004007)</li>
</ul>
<p>See Related Datasets section below for links to above mentioned datasets.</p> Methods and Sampling: <p>Data collection took place on the R/V Sally Ride from May 29th to June 10th, 2023. To simulate upwelling conditions under different iron treatments, an onboard incubation experiment was conducted. Seawater for the incubation experiment was collected within the northern CCS, off the southern coast of Oregon at 43°02'42.7"N, 124°33'07.2"W. The collected seawater was deemed as freshly upwelled water and taken from a depth of 55 m – which corresponds to a depth slightly below the euphotic zone receiving less than 1% irradiance – using trace-metal clean techniques on May 30th, 2023, 13:30 GMT. The seawater was pumped and homogenized using trace metal clean techniques, then transferred into a total of thirty 20 L low-density polyethylene cubitainers. Three cubitainers were immediately harvested for the initial timepoint (T0). The remaining twenty-seven cubitainers were assigned treatments: nine were unamended (Ctrl), nine were amended with 5 nM FeCl<sub>2</sub> (+Fe), and nine were amended with 200 nM desferrioxamine B, a strong iron chelator that inhibits dissolved iron uptake (DFB). The cubitainers were placed in an on-deck incubator covered with two layers of neutral density screening to simulate 26% of incident&nbsp;irradiance supplied with flow-through surface seawater to maintain ambient surface temperature. Three cubitainers from each treatment were harvested for each of the three subsequent timepoints: 48 hours (T1), 168 hours (T2), and 264 hours (T3) after incubation.</p>
<p><strong>RNA Collection and Metatranscriptomics. </strong>Cubitainers were harvested for RNA by collecting and filtering approximately 2.5 to 4 L of each sample onto 0.8 μm Pall Supor filters (142 mm) using a peristaltic pump; samples were then immediately flash frozen in liquid nitrogen and stored at -80°C. RNA was extracted using the RNAqueous-4PCR kit, per instructions from the manufacturer with few modifications – filters were cut up due to their large size, 200 μL of glass beads were added, and 3 mL of lysis buffer was added. RNA samples were sent to GENEWIZ for library preparation and sequencing with PolyA tail selection. Sequencing was performed on an Illumina HiSeq 4000 with a 2x150 bp configuration. GENEWIZ provided raw paired-end read sequences for each sample.&nbsp;</p>
<p>Raw reads were trimmed using Trim Galore v0.6.10 (Krueger, 2015)&nbsp;and quality control was assessed through FastQC (Andrews, 2010). A <em>de novo </em>metatranscriptome assembly was conducted using rnaSPAdes v3.15.5 for individual assemblies (Bushmanova et al., 2019) and CD-HIT v4.8.1 for a grand assembly (Li &amp; Godzick, 2006). TransDecoder v5.7.1 was used to determine the most likely open reading frame (ORF) for each contig (Haas, 2023). ORFs were annotated using the Marine Functional Eukaryotic Reference Taxa (MarFERReT) database v1.1.1 (e-value &lt; 1e<sup>-06</sup>) (Groussman et al., 2023) for NCBI taxonomies (Federhen, 2012), PR<sup>2</sup> taxonomies (Guillou et al., 2012) and Pfam 34.0 functions (Mistry et al., 2021). To remove any potential bacterial contamination, ORFs were also annotated against the PhyloDB v1076 database using EUKulele (e-value &lt; 1e<sup>-06</sup>) (Krinos et al., 2020). Any ORF with a higher bitscore for a bacteria or virus compared to its MarFERReT annotation was removed (resulting in &lt; 3% of ORFs removed). To maximize functional annotation coverage, ORFs were annotated using eggNOG-mapper v2.1.12 (Cantalapiedra et al., 2021) to obtain annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa, 2000). Trimmed samples were then aligned to the grand assembly using Salmon v1.10.3 (Patro et al., 2017) and exported into a comprehensive counts table using tximport (Soneson et al., 2016).&nbsp;Reads not mapping to a protist group as defined by MarFERReT annotations were removed before downstream analysis.&nbsp;</p>
<p>For taxonomic composition, all protist reads were normalized using DESeq2’s median of ratios methods (Love et al., 2014). The mean and standard deviation for the number of reads mapping to each protist group and the proportion of reads mapping to each protist group were calculated for each timepoint/treatment. Mean/standard deviation for number and proportion of protist reads specifically mapping to mixotroph genera and diatom genera were also calculated. Mixotrophs were identified based on constitutive mixotroph genera within the Mixoplankton Database (MDB) (Mitra et al., 2023) and diatom&nbsp;genera were identified based on mapping to the lineage Bacillariophyta.&nbsp;</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1751805 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1751805
onGoing
Adrian Marchetti
University of North Carolina at Chapel Hill
919-843-3473
123 South Rd.
Chapel Hill
NC
27514
USA
amarchet@email.unc.edu
pointOfContact
Natalie Cohen
University of Georgia
919-519-8297
10 Ocean Science Circle
Savannah
GA
31411
USA
cohen@uga.edu
pointOfContact
Astrid Schnetzer
North Carolina State University
919-515-7837
2800 Faucette Drive 4148 Jordan Hall
Raleigh
NC
27695
USA
aschnet@ncsu.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Timepoint
Treatment
Protist_Group
Mixotroph_Genera
Diatom_Genera
Mean_Num_Reads
SD_Num_Reads
Mean_Percent_Reads
SD_Percent_Reads
Latitude
Longitude
Illumina HiSeq 4000
Sea Bird SBE 9 plus CTD
theme
None, User defined
time_point
treatment
taxon
genus
mean
standard deviation
latitude
longitude
featureType
BCO-DMO Standard Parameters
Automated DNA Sequencer
Sea-Bird SBE 9plus CTD
instrument
BCO-DMO Standard Instruments
SR2311
service
Deployment Activity
California Current System
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
CAREER: An integrated molecular and physiological approach to examining the dynamics of upwelled phytoplankton in current and changing oceans
https://osprey.bco-dmo.org/project/768006
CAREER: An integrated molecular and physiological approach to examining the dynamics of upwelled phytoplankton in current and changing oceans
<p><em>NSF Award Abstract:</em><br />
Upwelling zones are hotspots of photosynthesis that are very dynamic in space and time. Microsocopic algae, known as phytoplankton, bloom when deep, nutrient-rich waters are upwelled into sunlit surface layers of the ocean, providing nourishment that supports productive food webs and draws down carbon dioxide (CO2) from the atmosphere to the deep ocean. Photosynthetic microbes in these regions must constantly adapt to changes in their chemical and physical environments. For example, subsurface populations respond to changes in light as they approach the surface. When upwelled waters move offshore, cells sink out of the illuminated zone, establishing seed populations that remain inactive until the next upwelling event. This process is called the upwelling conveyor belt cycle (UCBC). How phytoplankton respond to these changes in environmental conditions and how they may influence their nutrient requirements remains unknown. With future ocean changes predicted to alter seawater chemistry, including ocean acidification and decreased iron availability, some phytoplankton groups may be more vulnerable than others. Accompanying educational activities provide learning experiences to enhance understanding and awareness of marine microbes. The development of a research hub at UNC aims to provide infrastructure and support for scientists and students conducting research on environmental genomics. A laboratory component for an upper-level undergraduate course focused on marine phytoplankton is being developed. Educational outreach activities to broader communities include creation of a lesson plan on phytoplankton in upwelling zones and a virtual research cruise experience for middle-school students, as well as a hands-on lab activity for a local museum focused on marine phytoplankton and the important roles they play in shaping our planet.</p>
<p>The project examines how phytoplankton respond at the molecular and physiological level to the different UCBC stages, which seed populations (i.e., surface versus subsurface) contribute most to phytoplankton blooms during upwelling events of varying intensity, how phytoplankton elemental compositions are altered throughout UCBC stages, and how future predicted ocean conditions will affect the phytoplankton responses to UCBC conditions. This project contains both laboratory and fieldwork. In the laboratory, phytoplankton isolates recently obtained from upwelling regions are exposed to simulated UCBC conditions to examine changes in gene expression, growth and photosynthetic characteristics and elemental composition. Cultures are subjected to both current and future ocean conditions, including reduced iron availability and higher CO2. In the field, research cruises within upwelling regions study the dynamics of natural phytoplankton communities (both surface and subsurface) experiencing upwelling and relaxation and within simulated upwelling incubation experiments. Knowledge of how phytoplankton are affected by UCBC conditions at an integrated molecular, physiological and elemental level under both current and future scenarios is imperative for the proper conservation and management of these critically important ecosystems.</p>
Upwelled Phytoplankton Dynamics
largerWorkCitation
project
eng; USA
biota
oceans
California Current System
-124.552
-124.552
43.045194
43.045194
2023-05-29
2023-06-10
California Upwelling Zone
0
BCO-DMO catalogue of parameters from RNA taxonomy data from an iron incubation experiment during the PUPCYCLE II cruise (R/V Sally Ride) within the California Current System in May and June of 2023
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/1004913.rdf
Name: Timepoint
Units: unitless
Description: <p>Timepoint identification (T0, T1, T2, or T3)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004914.rdf
Name: Treatment
Units: unitless
Description: <p>Treatment identification (Ctrl, +Fe, or DFB)</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004915.rdf
Name: Protist_Group
Units: unitless
Description: <p>Classified general protist groups based on MarFERReT. Resulted in nine protist groups, any non-protist reads were excluded.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004916.rdf
Name: Mixotroph_Genera
Units: unitless
Description: <p>Classified constitutive mixotroph genera based on Mixoplankton Database. Only includes 8 named genera, the rest are grouped into Other_mixotroph, or if not mapping to a mixotroph, Nonmixotroph.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004917.rdf
Name: Diatom_Genera
Units: unitless
Description: <p>Classified diatom genera based on MarFERReT. Only includes 8 named genera, the rest are grouped into Other_diatom, or if not mapping to a diatom, NonDiatom.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004918.rdf
Name: Mean_Num_Reads
Units: number of normalized reads
Description: <p>Mean number of normalized reads mapping to the identified protist group, mixotroph genera, or diatom genera for triplicates within each treatment/timepoint.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004919.rdf
Name: SD_Num_Reads
Units: number of normalized reads
Description: <p>Standard deviation of number of normalized reads mapping to the identified protist group, mixotroph genera, or diatom genera for triplicates within each treatment/timepoint.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004920.rdf
Name: Mean_Percent_Reads
Units: percentage
Description: <p>Mean proportion of normalized reads mapping to the identified protist group, mixotroph genera, or diatom genera for triplicates within each treatment/timepoint.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1004921.rdf
Name: SD_Percent_Reads
Units: percentage
Description: <p>Standard deviation of proportion of normalized reads mapping to the identified protist group, mixotroph genera, or diatom genera for triplicates within each treatment/timepoint.</p>
http://lod.bco-dmo.org/id/dataset-parameter/1005004.rdf
Name: Latitude
Units: decimal degrees
Description: <p>Latitude of sampling station</p>
http://lod.bco-dmo.org/id/dataset-parameter/1005006.rdf
Name: Longitude
Units: decimal degrees
Description: <p>Longitude of sampling station</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
https://osprey.bco-dmo.org/dataset/1003525/data/download
download
onLine
dataset
<p>Data collection took place on the R/V Sally Ride from May 29th to June 10th, 2023. To simulate upwelling conditions under different iron treatments, an onboard incubation experiment was conducted. Seawater for the incubation experiment was collected within the northern CCS, off the southern coast of Oregon at 43°02'42.7"N, 124°33'07.2"W. The collected seawater was deemed as freshly upwelled water and taken from a depth of 55 m – which corresponds to a depth slightly below the euphotic zone receiving less than 1% irradiance – using trace-metal clean techniques on May 30th, 2023, 13:30 GMT. The seawater was pumped and homogenized using trace metal clean techniques, then transferred into a total of thirty 20 L low-density polyethylene cubitainers. Three cubitainers were immediately harvested for the initial timepoint (T0). The remaining twenty-seven cubitainers were assigned treatments: nine were unamended (Ctrl), nine were amended with 5 nM FeCl<sub>2</sub> (+Fe), and nine were amended with 200 nM desferrioxamine B, a strong iron chelator that inhibits dissolved iron uptake (DFB). The cubitainers were placed in an on-deck incubator covered with two layers of neutral density screening to simulate 26% of incident&nbsp;irradiance supplied with flow-through surface seawater to maintain ambient surface temperature. Three cubitainers from each treatment were harvested for each of the three subsequent timepoints: 48 hours (T1), 168 hours (T2), and 264 hours (T3) after incubation.</p>
<p><strong>RNA Collection and Metatranscriptomics. </strong>Cubitainers were harvested for RNA by collecting and filtering approximately 2.5 to 4 L of each sample onto 0.8 μm Pall Supor filters (142 mm) using a peristaltic pump; samples were then immediately flash frozen in liquid nitrogen and stored at -80°C. RNA was extracted using the RNAqueous-4PCR kit, per instructions from the manufacturer with few modifications – filters were cut up due to their large size, 200 μL of glass beads were added, and 3 mL of lysis buffer was added. RNA samples were sent to GENEWIZ for library preparation and sequencing with PolyA tail selection. Sequencing was performed on an Illumina HiSeq 4000 with a 2x150 bp configuration. GENEWIZ provided raw paired-end read sequences for each sample.&nbsp;</p>
<p>Raw reads were trimmed using Trim Galore v0.6.10 (Krueger, 2015)&nbsp;and quality control was assessed through FastQC (Andrews, 2010). A <em>de novo </em>metatranscriptome assembly was conducted using rnaSPAdes v3.15.5 for individual assemblies (Bushmanova et al., 2019) and CD-HIT v4.8.1 for a grand assembly (Li &amp; Godzick, 2006). TransDecoder v5.7.1 was used to determine the most likely open reading frame (ORF) for each contig (Haas, 2023). ORFs were annotated using the Marine Functional Eukaryotic Reference Taxa (MarFERReT) database v1.1.1 (e-value &lt; 1e<sup>-06</sup>) (Groussman et al., 2023) for NCBI taxonomies (Federhen, 2012), PR<sup>2</sup> taxonomies (Guillou et al., 2012) and Pfam 34.0 functions (Mistry et al., 2021). To remove any potential bacterial contamination, ORFs were also annotated against the PhyloDB v1076 database using EUKulele (e-value &lt; 1e<sup>-06</sup>) (Krinos et al., 2020). Any ORF with a higher bitscore for a bacteria or virus compared to its MarFERReT annotation was removed (resulting in &lt; 3% of ORFs removed). To maximize functional annotation coverage, ORFs were annotated using eggNOG-mapper v2.1.12 (Cantalapiedra et al., 2021) to obtain annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa, 2000). Trimmed samples were then aligned to the grand assembly using Salmon v1.10.3 (Patro et al., 2017) and exported into a comprehensive counts table using tximport (Soneson et al., 2016).&nbsp;Reads not mapping to a protist group as defined by MarFERReT annotations were removed before downstream analysis.&nbsp;</p>
<p>For taxonomic composition, all protist reads were normalized using DESeq2’s median of ratios methods (Love et al., 2014). The mean and standard deviation for the number of reads mapping to each protist group and the proportion of reads mapping to each protist group were calculated for each timepoint/treatment. Mean/standard deviation for number and proportion of protist reads specifically mapping to mixotroph genera and diatom genera were also calculated. Mixotrophs were identified based on constitutive mixotroph genera within the Mixoplankton Database (MDB) (Mitra et al., 2023) and diatom&nbsp;genera were identified based on mapping to the lineage Bacillariophyta.&nbsp;</p>
Specified by the Principal Investigator(s)
<p>The metatranscriptomic pipeline code used for this project is publicly available at https://github.com/emilyspeciale/Speciale-Metatranscriptomics.</p>
<ul>
<li>CD-HIT v4.8.1&nbsp;</li>
<li>DESeq2</li>
<li>eggNOG-mapper v2.1.12&nbsp;</li>
<li>FastQC</li>
<li>Marine Functional Eukaryotic Reference Taxa (MarFERReT) database v1.1.1&nbsp;</li>
<li>PhyloDB v1076 database using EUKulele&nbsp;</li>
<li>rnaSPAdes v3.15.5&nbsp;</li>
<li>Salmon v1.10.3&nbsp;</li>
<li>TransDecoder v5.7.1&nbsp;</li>
<li>Trim Galore v0.6.10</li>
<li>tximport&nbsp;</li>
</ul>
Specified by the Principal Investigator(s)
- Imported source file "BCO_DMO_PUPCYCLEII_RNATaxonomy.csv" with NA as missing data identifier replaced with empty cells.
- Added columns for latitude and longitude of sampling station
- Set data types as string or numeric
- Exported the final file as "1003525_v1_rna_taxonomy.csv"
Specified by BCO-DMO Data Managers
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Illumina HiSeq 4000
Illumina HiSeq 4000
PI Supplied Instrument Name: Illumina HiSeq 4000 PI Supplied Instrument Description:Sequencing was performed on an Illumina HiSeq 4000 with a 2x150 bp configuration. Instrument Name: Automated DNA Sequencer Instrument Short Name:Automated Sequencer Instrument Description: A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences.
Sea Bird SBE 9 plus CTD
Sea Bird SBE 9 plus CTD
PI Supplied Instrument Name: Sea Bird SBE 9 plus CTD Instrument Name: Sea-Bird SBE 9plus CTD Instrument Short Name:Seabird SBE 9plus Instrument Description: High precision and accuracy CTD comprising an SBE 9plus underwater unit (SBE 3plus temperature, SBE 4C conductivity, and Paroscientific Digiquartz pressure sensors, and an SBE 5T submersible pump). Can be used for either real-time data acquisition or for autonomous operations at a sampling speed of up to 24 Hz. The instrument package also includes a TC duct, to reduce salinity spiking caused by ship heave for improved resolution of water column features, and to ensure that temperature and conductivity measurements are made on the same parcel of water. Supplied with both an aluminium and titanium main housing, allowing for use up to 6800 and 10,500 metre depths respectively. Also capable of measuring from eight auxiliary sensors.
Cruise: SR2311
SR2311
R/V Sally Ride
Community Standard Description
International Council for the Exploration of the Sea
R/V Sally Ride
vessel
SR2311
Adrian Marchetti
University of North Carolina at Chapel Hill
R/V Sally Ride
Community Standard Description
International Council for the Exploration of the Sea
R/V Sally Ride
vessel