This dataset includes RNA-seq differential expression results of KEGG genes within mixotrophs and diatoms from an iron incubation experiment using upwelled waters sampled in the California Current System (CCS) during the PUPCYCLE II cruise with Chief Scientist Adrian Marchetti. PUPCYCLE II (Phytoplankton response to the UPwelling CYCLE) took place onboard the R/V Sally Ride from May 29th to June 10th, 2023. Freshly upwelled seawater for the incubation experiment was collected within the northern CCS and placed into designated 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 FeCl2 (+Fe), and nine were amended with 200 nM Desferrioxamine B, a strong iron chelator (DFB). 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. Approximately 2.5 to 4 liters of each sample was harvested for RNA-seq of the natural phytoplankton community, or metatranscriptomics. This dataset provides differential expression results of KEGG genes within mixotrophs and diatoms, specifically comparing expression levels between +Fe and DFB at T1 and T2. This data includes genes that significantly differ in expression between treatments in both taxa groups, and results were used to understand gene expression trends behind trophic mode selection based on iron bioavailability in strict phototrophs (diatoms) versus mixotrophs.

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Curation Notes
  • Problem Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

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.

Analyses include:

• Physiology (dataset 994607)
  • Dissolved inorganic nutrients (nitrate, phosphate, silicic acid)
  • Size-fractionated chlorophyll a
  • Size-fractionated isotope uptake rates (nitrate and DIC)
  • Flow cytometry
  • FlowCAM analysis
  • FLP experiments for mixotroph cell-specific grazing rates
• RNA taxonomy data for normalized reads (dataset 1003525)
• Differential expression for +Fe versus DFB treatments at T1 and T2: Pfam
  • Mixotroph Pfam (dataset 1004659)
  • Diatom Pfam (dataset 1004674)
• Differential expression for +Fe versus DFB treatments at T1 and T2 for mixotrophs and diatoms: KEGG gene (this dataset 1004689)
• Differential expression for +Fe versus DFB treatments at T1 and T2 for mixotrophs and diatoms: KEGG pathways (dataset 1004704)
• Dissolved iron concentrations (dataset 1004007)

See Related Datasets section below for links to above mentioned datasets.

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 meters – 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 FeCl₂ (+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 irradiance. The incubator was 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.

RNA Collection and Metatranscriptomics. 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, according to the manufacturer's instructions with a 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. 

Raw reads were trimmed using Trim Galore v0.6.10 (Krueger, 2015), which uses Cutadapt (Martin, 2011), and quality control was assessed through FastQC (Andrews, 2010). A de novo 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 & Godzik, 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 < 1e^-06) (Groussman et al., 2023) for NCBI taxonomies (Federhen, 2011), PR² 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 < 1e^-06) (Krinos et al., 2020). Any ORF with a higher bitscore for a bacteria or virus compared to its MarFERReT annotation was removed (resulting in < 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). Reads not mapping to a protist group as defined by MarFERReT annotations were removed before downstream analysis. 

DESeq2 was used to conduct differential expression analyses (Love et al., 2014). Differential expression analyses for KEGG genes were performed for reads mapping to mixotroph genera and reads mapping to the lineage Bacillariophyta (henceforth referred to as diatoms). Reads not mapping to the taxa group being analyzed were removed prior to normalization and statistical testing. Mixotrophs were identified based on constitutive mixotroph genera within the Mixoplankton Database (MDB) (Mitra et al., 2023 ). Reads were summed based on annotation ID prior to entering DESeq2 analysis; if a contig annotated to multiple IDs, its reads were evenly distributed between the mapped annotations. The differential expression analyses only focused on comparing +Fe vs DFB at T1 and T2. 

 

Differential expression analysis was conducted through DESeq2’s “DESeq()” function in which significance is determined by estimating size factors (using median-of-ratios method), estimating dispersion, fitting a negative binomial generalized linear model, then hypothesis testing. For hypothesis testing, the Wald test is used followed by the Benjamini-Hochberg procedure for false discovery rate (which gives the p-adjusted value). A pathway was considered differentially expressed if the absolute value of log2FoldChange > 1 and p-adjusted < 0.05.

The metatranscriptomic pipeline code used for this project is publicly available at https://github.com/emilyspeciale/Speciale-Metatranscriptomics. 

Software: Trim Galore v0.6.10; FastQC v0.12.1; rnaSPAdes v3.15.5; CD-HIT v4.8.1; TransDecoder v5.7.1; EUKulele v2.0.9; eggNOG-mapper v2.1.12; Salmon v1.10.3;  tximport v1.3.9; DESeq2.

Databases/reference resources: MarFERReT v1.1.1; NCBI Taxonomy; PR2; Pfam 34.0; PhyloDB v1076; Kyoto Encyclopedia of Genes and Genomes (KEGG); Mixoplankton Database (MDB).

• 1. Raw reads were trimmed with Trim Galore v0.6.10 (Krueger, 2015)
• 2. Read quality was assessed with FastQC v0.12.1 (Andrews, 2010)
• 3. De novo metatranscriptome assemblies were generated using rnaSPAdes v3.15.5 (Bushmanova et al., 2019) for individual assemblies and CD-HIT v4.8.1 (Li & Godzik, 2006) for the grand assembly
• 4. ORFs were identified with TransDecoder v5.7.1 (Haas, 2023). 
• 5. Taxonomy and functional annotation via Marine Functional Eukaryotic Reference Taxa (MarFERReT) database v1.1.1 (Groussman et al., 2023); includes NCBI taxonomies (Federhen, 2011), PR2 taxonomies (Guillou et al., 2012), and Pfam 34.0 functions (Mistry et al., 2021). 
• 6. PhyloDB v1076 filtering using EUKulele v2.0.9 (Krinos et al., 2020). 
• 7. eggNOG-mapper v2.1.12 (Cantalapiedra et al., 2021) / KEGG annotation (Kanehisa, 2000)
• 8. Reads were quantified with Salmon v1.10.3 (Patro et al., 2017) 
• 9. Reads were imported with tximport v1.3.9 (Soneson et al., 2016)
• 10. Taxonomic filtering where reads outside the target taxonomic group were removed
• 11. Annotation-ID read summation
• 12. DESeq2 v1.42.1 (Love et al., 2014) was used to compare +Fe versus DFB at T1 and T2

 

CURATION ACTIONS PERFORMED ON DATA
- Loaded source file " BCO_DMO_PUPCYCLEII_KEGGgeneDE.csv" into the BCO-DMO system converting missing data identifier NA to empty cell.
- Added columns for latitude and longitude of water sampling station
- Set data types for first 6 columns to string, and all others to numeric, with p-values in scientific notation.
- Exported the final file as "1004689_v1_kegg_genes_diffexp.csv"

CURATION ACTIONS PERFORMED ON METADATA
- Added summary for broader study showing connections between related datasets
- Changed in-line citations to have format of (author, year) replacing number references.
- Corrected the FastQC citation to Andrews et al. (2010)

ISSUES POTENTIALLY IMPACTING REUSE
- N/A

Analyses focused on +Fe vs. DFB treatments from T0 to T2 to compare an iron-replete versus iron-limited environment; Ctrl and T3 were excluded due to large variability among biological replicates, possibly caused by low read and annotation mappings.

Coverage: California Upwelling Zone

NSF Award Abstract:
Upwelling zones are hotspots of photosynthesis that are very dynamic in space and time. Microscopic 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.

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.