OceanWiki - User contributions [en]

Data Types

2026-09-24T13:29:25Z

Michiel Perneel:

Oceanographers measuring bulk rates of carbon fixation and respiration as well as elemental composition, i.e. how much particulate carbon, nitrogen, or phosphorus is present in a given volume of water, provide foundational information about ocean biogeochemical cycles. These bulk measurements can be coupled with targeted methods to further assess rates of transformation<ref name="Levine et al. 2025">Naomi M. Levine, Harriet Alexander, Erin M. Bertrand, Victoria J. Coles, Stephanie Dutkiewicz, Suzana G. Leles and Emily J. Zakem. 2025. Microbial Ecology to Ocean Carbon Cycling: From Genomes to Numerical Models.Annual Review of Earth and Planetary Science, Vol. 53:595-624, https://doi.org/10.1146/annurev-earth-040523-020630</ref>. More recently, new tools in analytical chemistry, molecular microbiology, and bioinformatics are enhancing our ability to integrate process-based mechanisms and biomass estimates of functional groups of interest into the study of ocean biogeochemistry<ref> Moran MA, Kujawinski EB, Stubbins A, Fatland R, Aluwihare LI, et al. 2016. Deciphering ocean carbon in a changing world. PNAS 113:(12):3143–51, https://doi.org/10.1073/pnas.1514645113</ref>. <br>
In addition, advances in sequencing and mass spectrometry technologies over the last decades have accelerated the study of microbial communities. These high-throughput, data-rich approaches enable assessment of community taxonomic and functional composition, metabolic potential and diversity, and phylogeny and evolutionary history across the global oceans<ref name="Levine et al. 2025"/>.

This literature review, initiated by [https://www.primoscorwg.org PRIMO], covers well-established physiological metrics routinely used in biological oceanography, as well as novel metrics being developed to determine physiological rates at both the cellular and community level. The entries include information about the methods (currencies, units, assumptions, uncertainties). We also provide key references to facilitate discovery.<br>
We have divided the inventory into four sections: Primary Production, Secondary Production, Nutrient Fluxes, and Interactions.

If you would like to add a data type page, please use the [[Data wiki template | Data wiki template]].

== Data Type Sections ==

''Expand a section below to browse methods by type.''


<div id="Primary_Production" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#d5e8d4; padding:8px 14px; font-weight:bold; font-size:1.1em;">Primary Production</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Photoautotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Incubation | Discrete
* [[14-Carbon uptake (NPP)]]
* [[18O-labelled water (GOP)]]
* [[Winkler light-dark dissolved O2 bottle]]
* [[Phytoplankton carbon biomass (Cphyto) x growth rate (µ)]]
* [[13-Carbon uptake]]
* [[Gross Primary Production (GPP) - triple oxygen]]
* [[Net community production (NCP)]]
; ''In situ | Continuous''
* [[Net community production (NCP) - O₂/Ar]]
* [[Continuous dissolved oxygen (DO) optodes]]
; Optics-based
* [[Single Turnover Chlorophyll Fluorescence]]
* [[Remote Sensing NPP]]
* [[BGC-Argo NPP]]
; Omics-based
* [[RT-qPCR/ddPCR]]
* [[rcbL gene expression/quant]]
* [[psbA]]
* [[Rubisco protein]]
* [[PSII/PSI quantification]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Nitrogen Fixation]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Bulk uptake 15N2]]
* [[Single cell uptake (SIP-SIMS/nanoSIMS; CHIP-SIMS; CARD-FISH paired with nanoSIMS)|Single cell uptake techniques]]
* [[Acetylene Reduction Assays (ARA)]]
* [[NifH detection/quantification (qPCR, RT-qPCR; nifH database)|nifH detection/quantification]]
* [[nifH amplicon sequence]]
* [[H2 supersaturation]]
* [[Nitrogenase quantification]]
* [[Other diazotroph marker genes: nifD, nifK|Other diazotroph marker genes]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Phytoplankton C/N-Based Growth Rates]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Carbon content]]
* [[Nitrogen content]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Chemoautotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Mass balance approach]]
* [[Dark 14C-bicarbonate fixation]]
* [[Nano SIP]]
* [[Black smoker]]
</div>
</div>

</div>
</div>


<div id="Secondary_Production" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#fff2cc; padding:8px 14px; font-weight:bold; font-size:1.1em;">Secondary Production</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Enzyme Activity]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Enzyme assay with fluoresceinamine labeled biopolymers]]
* [[Enzyme assay with RBB labeled polysaccharides]]
* [[Enzyme assay with DNS]]
* [[Enzyme assay/alkaline phosphatase with fluorescently labeled substrate]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Growth Rate]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Growth rate from biomass observation]]
* [[Radiolabeled tracer method]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Respiration]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Respiration from BGC-Argo floats and AOU]]
* [[Respiration from oxygen consumption: optodes]]
* [[Respiration from activity of respiratory chain: enzymatic assays]]
* [[Respiration from activity of respiratory chain: redoxsensor green]]
* [[Respiration from oxygen consumption]]
</div>
</div>

</div>
</div>


<div id="Nutrient_Fluxes" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#ddeeff; padding:8px 14px; font-weight:bold; font-size:1.1em;">Nutrient Fluxes</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Nitrogen]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Nitrogen Uptake
* [[(15N-ρNO3-) uptake New Production]]
* [[Size-fractionated (15N-ρNO3-) uptake New Production]]
* [[15N-ρNO3/chl a (N assimilation rate)]]
* [[Size-fractionated 15N-ρNO3/chl a (N assimilation rate)]]
* [[(15N-ρNH4+) uptake Regenerated Production]]
* [[Size-fractionated (15N-ρNH4+) uptake Regenerated Production]]
* [[(15N-ρurea) uptake Regenerated Production]]
* [[Size-fractionated (15N-ρurea) uptake Regenerated Production]]
; Nitrogen Assimilation
* [[Eukaryotic Assimilatory nitrate reductase, NAD(P)H dependent, Nitrate -> Nitrite, Nitrate (NR)]]
; Nitrification
* [[DIN inventory with inhibitors]]
* [[Inhibitors with 14 or 13CO2 uptake]]
* [[Nitrite oxidation (Nxr)]]
* [[amoA gene or transcript abundance]]
* [[Natural abundance of N and O isotopes in nitrate, nitrite and ammonium]]
* [[15N tracers]]
; Denitrification
* [[Acetylene-block proxy for denitrifcation enzyme activity]]
* [[15N tracer-based method]]
* [[N2:Ar ratio quantification]]
* [[Mass Balance]]
* [[Stoichiometric approach]]
* [[Natural Abundances of 15N and 18O]]
; Other Processes (DNRA, Anammox, DON)
* [[Isotopic measurements---15N-labeled ammonium (15NH4+) accumulation rate in 15NO3- added incubation|Isotopic measurements of 15NH4+ accumulation (DNRA)]]
* [[15N tracers (15N labeled gases upon addition of 15NO3, 15NO2, or 15NH4)|15N tracers for anaerobic ammonium oxidation]]
* [[Functional gene quantification (hzs, hzo)]]
* [[FISH staining of anammox bacteria]]
* [[13C- and 15N-labeled algal exudates (isotope tracing & nanoSIMS)|13C- and 15N-labeled algal exudates with nanoSIMS]]
* [[Degradation of dissolved organic nitrogen: Leucine-aminopeptidase activity|Leucine-aminopeptidase activity measurement]]
* [[Degradation of dissolved organic nitrogen: Endopeptidase activity|Endopeptidase activity measurement]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Phosphorus]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Degradation of dissolved organic phosphorus
* [[Degradation of dissolved organic phosphorus (P-monoesters): Alkaline phosphatase activity (APA)|Alkaline phosphatase activity (APA)]]
* [[Degradation of dissolved organic phosphorus (P-diesters): Phosphodiesterase activity (PDE)|Phosphodiesterase activity (PDE)]]
* [[Degradation of dissolved organic phosphorus (phosphonates): C-P lyase activity (CLA)|C-P lyase activity (CLA)]]
* [[Cleavage of phosphate from 5'-nucleotides: 5'NT/5PN activity|5'NT/5PN activity]]
; P nutrition
* [[Reduction of phosphite to phosphate for growth (ptxABCD)|ptxABCD]]
* [[32-P incorporation]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Sulfur]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[DMS/P/O cycling]]
* [[Rates of DMSO reduction to DMS]]
* [[Rates of DMS and DMSP oxidation to DMSO]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Trace Metals]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[55-Iron uptake]]
* [[54-Manganese uptake]]
* [[67-Copper (half-life 62 h; incubation) & 64-Cu (half-life 12.7 h; lab) uptake|67-Copper & 64-Cu uptake]]
* [[Cobalamin uptake with 57Cobalt-B12]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Biomineralization]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Silicon
* [[Silicon uptake]]
* [[Kinetics of silicon uptake]]
* [[Silica production]]
* [[Silica production - PDMPO]]
* [[Biogenic silica accumulation]]
; Calcification
* [[Calcification (13-Carbon uptake)]]
</div>
</div>

</div>
</div>


<div id="Interactions" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#ffe6cc; padding:8px 14px; font-weight:bold; font-size:1.1em;">Interactions</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Grazing]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Microzooplankton on Phytoplankton
* [[Incubation dilution experiments]]
* [[Size-fractionated incubation dilution experiments]]
* [[Cell abundance]]
; Mesozooplankton
* [[Gut-fluorescence]]
; Bacterivory & Mixotrophy
* [[Fluorescently labeled prey surrogates]]
* [[Radioactively labeled prey surrogates]]
* [[Pulse-chase labeling of bacterial prey]]
* [[Stable isotope-labelled prey]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Mixotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[LysoTracker Green Incorporation]]
* [[15N/13C-labelled DOM/cells]]
* [[Bead consumption rates by cells with chloroplasts]]
* [[BrdU-labeled prey incorporation into things with chloroplasts]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Viruses]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Electron microscopy of cells]]
* [[Quantification of virus particles]]
* [[Dilution incubation experiments]]
* [[Bulk RNA marker-gene PCR analysis]]
* [[Bulk RNA-sequencing (whole transcriptome)]]
* [[Single-cell RNA-sequencing (population)]]
* [[Single-cell RNA-sequencing (community)]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Allelopathy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Filtrate cross-culturing]]
* [[Size-fractionated extract spiking]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Life cycles]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Light or electron microscopic counts of life cycle stages/transitions]]
* [[Fluorescent in situ hybridization microscope counts]]
* [[Bulk RNA marker-gene PCR analysis]]
* [[Bulk RNA-sequencing (whole transcriptome)]]
</div>
</div>

</div>
</div>

== References ==
<references />

Bulk RNA-sequencing (whole transcriptome)

2026-09-24T13:24:39Z

Michiel Perneel:

* [[Page authors|Page authors]]: [[Michiel Perneel]], [[PRIMO]]
* [[Responsible curator|Responsible curator]]: [[User:Kate Evans|Kate Evans]]
----
__TOC__
<div class="model-box">
{| class="model-ib"
| '''Definition:''' High-throughput sequencing of RNA transcribed by an individual or population of a given organism, or a community of species.
|-
| '''Approach:''' filtering, RNA extraction, sequencing, bioinformatics
|-
| '''Context:''' ''in situ'', culturing, incubations
|-
| '''Spatial scale:''' L
|-
| '''Temporal scale:''' hours, days, weeks, seasons, events of interest
|-
| '''Units:''' gene expression, e.g. TPM
|-
| '''Community captured:''' size-fractioned, e.g. 0.2 - 250 µm, cultured or target species (both prokaryotic and eukaryotic)
|-
| '''Co-measurements:''' Other measurements required for interpretation of in-situ samples e.g., temperature, salinity, nutrients, physiological data
|}
</div>
<div style="clear:both"></div>

== Method Overview ==

(Meta)transcriptomics sequences the pool of RNA recovered from a single-species culture up to a whole microbial assemblage. In the latter case it can provide a semi-quantitative snapshot of which genes were being transcribed by which organisms at the moment of sampling.
Where (meta)genomics describes ''metabolic potential'' (i.e. the genes that are present), (meta)transcriptomics describes ''metabolic expression'' (i.e. the genes that are being transcribed), and is therefore the molecular measurement most often used as a proxy for ''in situ'' physiological state and for the activity of specific biogeochemical pathways.

The method is sensitive to how the sample is handled. Prokaryotic mRNA has a half-life of roughly 5 minutes, and as little as ~2.4 minutes in marine cyanobacteria.<ref name="Moran2013">Moran, M. A., Satinsky, B., Gifford, S. M., Luo, H., Rivers, A., Chan, L.-K., Meng, J., Durham, B. P., Shen, C., Varaljay, V. A., Smith, C. B., Yager, P. L., & Hopkinson, B. M. (2013). Sizing up metatranscriptomics. ''The ISME Journal'', 7(2), 237–243. doi:10.1038/ismej.2012.94</ref>
Protocol choices at every step during the generation of bulk RNA-Seq data such as filtration, preservation, enrichment (e.g. for mRNA in poly(A) selection to target microeukaryotic material), sequencing depth, assembly and annotation, affect the final expression matrix<ref name="Cohen2022">Cohen, N. R., Alexander, H., Krinos, A. I., Hu, S. K., & Lampe, R. H. (2022). Marine microeukaryote metatranscriptomics: sample processing and bioinformatic workflow recommendations for ecological applications. ''Frontiers in Marine Science'', 9, 867007. doi:10.3389/fmars.2022.867007</ref>

=== Sample collection and filtration ===

Seawater can be collected by Niskin bottles, underway pump, manually, or ''in situ'' pump, and biomass is concentrated onto filters. Culture samples can be taken directly from the culture vessel (potentially with upconcentration).
Because the transcriptome degrades and responds to handling stress within minutes, the interval between sampling and freezing should be minimised<ref name="Cohen2022" />.

* '''Volume.''' Can be several mL from cultures, 1.5-3.5 L in productive coastal waters, and ≥10 L in oligotrophic offshore waters for microeukaryote work; 1–10 L is common for prokaryote-targeted sampling on 0.22 µm Sterivex cartridges. Volume is constrained by filter clogging and by the requirement to complete filtration quickly. More volume can be filtered and later subsampled.
* '''Size fractionation.''' Serial or stacked filters partition the assemblage, e.g. 0.2–3 µm (prokaryote-enriched), 3–20 µm and 20–250 µm (nano- and microplankton), or a single 0.8–250 µm protistan fraction. Fractionation aids interpretation but introduces cell breakage and incomplete separation, and the chosen cut-offs must accompany any downstream comparison.
* '''Preservation, extraction and quality control.''' Filters or filtrate can be flash-frozen in liquid nitrogen and stored at −80 °C; RNA-stabilising buffers (e.g. RNA''later'') can be added to safeguard RNA integrity<ref name="Cohen2022" />

=== RNA extraction & library preparation ===
'''Internal standards:''' Adding a known number of synthetic RNA molecules at the start of extraction converts an otherwise compositional (relative) dataset into an absolute one. Standards may be commercial spike-in sets (ERCC, ArrayControl, Sequins) or ''in vitro'' transcripts from custom plasmids, and are typically dosed at ~1% of the expected mRNA pool.<ref name="Cohen2022" /><ref name="Satinsky2013">Satinsky, B. M., Gifford, S. M., Crump, B. C., & Moran, M. A. (2013). Use of internal standards for quantitative metatranscriptome and metagenome analysis. ''Methods in Enzymology'', 531, 237–250. doi:10.1016/B978-0-12-407863-5.00012-5</ref> The ratio of standard molecules added to standard reads recovered yields transcript inventories per litre of seawater (see [[#Common calculations/conversions|Common calculations]]), and also diagnoses extraction and library-prep losses. Quantitative metatranscriptomics of this kind is the form most directly comparable to rate measurements and to model state variables.<ref name="Gifford2011">Gifford, S. M., Sharma, S., Rinta-Kanto, J. M., & Moran, M. A. (2011). Quantitative analysis of a deeply sequenced marine microbial metatranscriptome. ''The ISME Journal'', 5(3), 461–472. doi:10.1038/ismej.2010.141</ref>
'''RNA extraction''' Total RNA is extracted from the sample often using commercial kits (e.g. Qiagen RNeasy, Invitrogen TRIzol, ToTALLY RNA), usually with bead-beating in silica or zirconia beads to break silicified, armoured or thick-walled cells, followed by DNase treatment to remove co-extracted DNA. Yield and integrity are checked by fluorometry (Qubit) and capillary electrophoresis (Bioanalyzer/TapeStation)<ref name="Cohen2022" />.

For eukaryotes, ribosomal RNA dominates total RNA (usually >80%), so libraries are enriched for mRNA by one of two routes:
* '''Poly-A selection''' captures polyadenylated eukaryotic mRNA on oligo-dT beads. It delivers the most protein-coding reads per sequencing dollar, but excludes bacteria and archaea, discriminates against plastid and mitochondrial transcripts, and biases against transcripts with short or absent poly-A tails. Standard kits (e.g. TruSeq Stranded mRNA) need 0.1–1 µg total RNA; low-input chemistries (e.g. SMART-Seq v4) work from ~250 pg via linear amplification, at the cost of amplification bias.<ref name="Cohen2022" />
* '''rRNA depletion''' (Ribo-Zero, riboPOOLs and equivalents) removes rRNA by probe hybridisation and retains prokaryotic, eukaryotic and organellar mRNA together. It is the choice for whole-community and prokaryote-focused work and for organelle transcripts, but leaves a larger residual rRNA fraction and so requires greater sequencing depth per unit of usable signal.<ref name="Cohen2022" />

Residual rRNA is removed ''in silico'' after sequencing with SortMeRNA, BBDuk or riboPicker.
Libraries are further prepared according to the sequencing platform.

=== Sequencing ===

Short-read Illumina sequencing (NextSeq, NovaSeq; typically 2×150 to 2×250 bp) is the most popular platform.

=== Bioinformatic processing ===

# '''Quality control.''' Adapter and quality trimming (fastp, Trimmomatic, cutadapt) with inspection via FastQC/MultiQC; ''in silico'' rRNA removal.
# '''Direct mapping or ''de novo'' assembly.''' Reads may be mapped directly to a reference genome or database (e.g. MMETSP, EukProt, MarFERReT, OM-RGC) or assembled ''de novo'' (Trinity, rnaSPAdes, MEGAHIT). rnaSPAdes and Trinity perform well on marine microeukaryote communities. Multi-assembler approaches or assemblies from multiple samples can be followed by clustering at 95-100% identity (CD-HIT, MMseqs2)<ref name="Cohen2022" />.
# '''Quantification.''' Trimmed reads are mapped back to the assembly with Bowtie2/BWA or quasi-mapped with Salmon/kallisto to produce per-contig counts.
# '''Protein prediction and annotation.''' Open reading frames are called (TransDecoder, GeneMarkS-T; Prodigal for prokaryote-dominated assemblies), then annotated functionally against KEGG/KOfam, eggNOG, Pfam (HMMER), KOG and Gene Ontology, and taxonomically by DIAMOND/MMseqs2 alignment (with a last-common-ancestor algorithm)<ref name="Cohen2022" />.
# '''Aggregation and statistics.''' Quantified matrics are integrated with environmental metadata, and annotation information to tackle questions of interest.

'''Workflow examples:''' Reproducible pipelines include eukrhythmic, SqueezeMeta and nf-core/metatdenovo,<ref name="DiLeo2025">Di Leo, ''et al.'' (2025). The Nextflow nf-core/metatdenovo pipeline for reproducible annotation of metatranscriptomes, and more. ''PeerJ'', 13, e20328. doi:10.7717/peerj.20328</ref><ref name="Krinos2023">Krinos, A. I., Cohen, N. R., Follows, M. J., & Alexander, H. (2023). Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly. ''BMC Bioinformatics'', 24, 74. doi:10.1186/s12859-022-05121-y</ref> and require high-performance computing resources for large datasets.

=== Output & normalisation ===

Sequencing produces compositional data: read counts describe proportions of a fixed-size library. Reads should be normalised:

* '''Within-sample relative expression''' (TPM, RPKM/FPKM) — comparable across genes within a sample, and the pragmatic choice for large spatial or temporal surveys, but composition-dependent and without a statistical test of differential expression.<ref name="Cohen2022" />
* '''Model-based differential expression''' (DESeq2, edgeR) — negative-binomial generalised linear models with FDR control, appropriate for replicated designs and ideally applied after binning to taxon-specific transcript sets.<ref name="Cohen2022" />
* '''Absolute estimates''' (transcripts L<sup>-1</sup>, transcripts cell<sup>-1</sup>) — requires internal standards(and logging of processed volumes, optionally with cell counts or a paired metagenome), and is the form best suited to comparison with rates and with model fluxes.<ref name="Gifford2011" /><ref name="Satinsky2013" /><ref name="Perneel2025">Perneel, M., Alexander, H., Hablützel, P. I., & Maere, S. (2025). A case for absolute gene expression estimates in microbiome studies using metatranscriptomics. ''The ISME Journal'', 19(1), wraf188. doi:10.1093/ismejo/wraf188</ref>

=== Scale of measurement ===
Next to culture-based approaches, in-situ sampling of bulk RNA-Seq depends on the study design. A single sample is a point measurement in space: one sample integrates the litres of seawater it collected (typically 1–10 L, more offshore), at one depth and station.
These can then be aggregated across the research cruise, mooring or autonomous platform, individual snapshots resolve diel cycles, bloom development, mesoscale features and seasonal transitions; global-scale synthesis is possible if protocols are harmonised.<ref name="Salazar2019">Salazar, G., Paoli, L., Alberti, A., ''et al.'' (2019). Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. ''Cell'', 179(5), 1068–1083.e21. doi:10.1016/j.cell.2019.10.014</ref><ref name="Peoples2026">Peoples, L. M., Eppley, J. M., Barone, B., Hobson, B. W., Karl, D. M., Kieft, B., Marin, R. III, Preston, C. M., Romano, A. E., Ryan, J. P., Scholin, C. A., Wilson, S. T., Zhang, Y., Church, M. J., & DeLong, E. F. (2026). Diel and eddy driven changes in microbial gene expression and biogeochemistry in the oceanic chlorophyll maximum. ''Nature Communications'', 17, 3636.</ref>

=== Data generated ===

* Raw paired-end sequence reads (FASTQ), with library and sample metadata.
* Assembled contigs or a mapped reference catalogue (FASTA), and predicted proteins.
* A count matrix of contigs/genes × samples, plus taxonomic and functional annotation tables.
* Derived products: normalised expression matrices (TPM), differential-expression tables, transcript inventories per litre, ordinations, co-expression networks, and pathway- or taxon-level expression profiles.
* Where internal standards were used, standard recovery statistics documenting extraction and library efficiency.
* Environmental or study metadata

=== Repositories & databases ===

'''Raw and processed data'''
* [https://www.ncbi.nlm.nih.gov/sra NCBI Sequence Read Archive (SRA)] and [https://www.ebi.ac.uk/ena ENA] — raw reads; the expected archive for publication.
* [https://zenodo.org Zenodo] and GitHub for processed data ( assemblies, count matrices, metadata, etc) and analysis code<ref name="Cohen2022" />.

'''Reference libraries for annotation'''
* MMETSP (Marine Microbial Eukaryote Transcriptome Sequencing Project): 678 transcriptomes from 405 microbial eukaryote strains.<ref name="Keeling2014">Keeling, P. J., ''et al.'' (2014). The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. ''PLoS Biology'', 12(6), e1001889. doi:10.1371/journal.pbio.1001889</ref>
* [https://github.com/armbrustlab/marferret MarFERReT]: version-controlled reference library of marine microbial eukaryote functional genes.<ref name="Groussman2023">Groussman, R. D., Blaskowski, S., Coesel, S. N., & Armbrust, E. V. (2023). MarFERReT, an open-source, version-controlled reference library of marine microbial eukaryote functional genes. ''Scientific Data'', 10, 926. doi:10.1038/s41597-023-02842-4</ref>
* EukProt, EukZoo and PhyloDB: complementary eukaryote protein references; MarRef and OM-RGC for prokaryotes.
* [https://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/ Ocean Gene Atlas]: online query of ''Tara'' Oceans gene abundance and expression biogeography.<ref name="Vernette2022">Vernette, C., Lecubin, J., Sánchez, P., ''Tara'' Oceans Coordinators, Sunagawa, S., Delmont, T. O., Acinas, S. G., Pelletier, E., Hingamp, P., & Lescot, M. (2022). The Ocean Gene Atlas v2.0: online exploration of the biogeography and phylogeny of plankton genes. ''Nucleic Acids Research'', 50(W1), W516–W526. doi:10.1093/nar/gkac420</ref>
* [https://github.com/armbrustlab/NPac_euk_gene_catalog North Pacific Eukaryotic Gene Catalog]: assembled and annotated metatranscriptomes for the North Pacific.<ref name="Groussman2024">Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. ''Scientific Data'', 11, 1161. doi:10.1038/s41597-024-04005-5</ref>
* Functional references: KEGG/KOfam, eggNOG, Pfam, KOG, Gene Ontology.

== Limitations ==

'''Sampling and handling'''
* mRNA half-lives of minutes mean the measurement is easily perturbed. Time from collection to preservation, bottle confinement, light and temperature change, and filtration pressure all induce stress responses that are indistinguishable from ''in situ'' signal unless handling is standardised.<ref name="Moran2013" /><ref name="Cohen2022" />
* Strong diel periodicity in transcription means samples are only comparable when time of day is matched or explicitly modelled<ref name="Peoples2026" /><ref name="Ottesen2014">Ottesen, E. A., Young, C. R., Gifford, S. M., Eppley, J. M., Marin, R. III, Schuster, S. C., Scholin, C. A., & DeLong, E. F. (2014). Multispecies diel transcriptional oscillations in open ocean heterotrophic bacterial assemblages. ''Science'', 345(6193), 207–212. doi:10.1126/science.1252476</ref>
* Size fractionation is imperfect: cells break, fractions overlap, and filters clog, biasing which taxa are represented.

'''Library chemistry'''
* Poly-A selection excludes prokaryotes and discriminates against organellar and non-polyadenylated transcripts; rRNA depletion retains more rRNA and needs deeper sequencing. Neither is bias-free, and libraries prepared by the two routes are not directly comparable.<ref name="Cohen2022" />

'''Quantification and statistics'''
* Without internal standards the data are compositional: an apparent increase in one transcript can reflect a decrease elsewhere.<ref name="Satinsky2013" /><ref name="Perneel2025" />
* Sequencing captures a minute fraction of the mRNA pool, so many functionally important genes fall below detection; roughly half the functional categories in early quantitative work had too few counts for robust comparison.<ref name="Gifford2011" />
* Limited biological replication constrains formal differential-expression testing.<ref name="Cohen2022" />

'''Reference and assembly'''
* Reference libraries under-represent rare lineages, deep-sea taxa and uncultured groups and often contain contamination; a large share of contigs and predicted proteins remain taxonomically or functionally unannotated.<ref name="Cohen2022" />
* ''De novo'' assembly of mixed communities generates chimeric and spurious contigs where close relatives co-occur, and results depend on assembler and ''k''-mer choice.<ref name="Cohen2022" />
* Choosing a taxonomic resolution is a trade-off: species-level assignment is confident for fewer sequences, while class-level aggregation can mask opposing physiological responses within a group. The use of reference databases suffer from different biases.<ref name="Cohen2022" /><ref name="Krinos2024">Krinos, A.I., Mars Brisbin, M., Hu, S.K. et al. Missing microbial eukaryotes and misleading meta-omic conclusions. Nat Commun 15, 9873 (2024). https://doi.org/10.1038/s41467-024-52212-w</ref>

'''Interpretation'''
* Transcript abundance is not protein abundance and not a rate.
* Expression change can arise from a shift in community composition rather than in per-cell regulation<ref name="Salazar2019" />.
* Converting expression into a flux requires independent calibration (rate measurements, physiological data, or a model).

== Specific use cases ==
=== Viruses ===
=== Life cycles ===
== Example studies ==
https://doi.org/10.1073/pnas.0708897105

https://doi.org/10.1111/j.1462-2920.2008.01863.x

https://doi.org/10.1073/pnas.1118408109

https://doi.org/10.1073/pnas.1421993112

https://doi.org/10.1038/s41467-017-02342-1

https://doi.org/10.1016/j.cell.2019.10.014

== References ==
<references/>

[[Category:Main Pages|Model types]]

Data Types

2026-09-24T13:10:08Z

Michiel Perneel:

Oceanographers measuring bulk rates of carbon fixation and respiration as well as elemental composition, i.e. how much particulate carbon, nitrogen, or phosphorus is present in a given volume of water, provide foundational information about ocean biogeochemical cycles. These bulk measurements can be coupled with targeted methods to further assess rates of transformation<ref name="Levine et al. 2025">Naomi M. Levine, Harriet Alexander, Erin M. Bertrand, Victoria J. Coles, Stephanie Dutkiewicz, Suzana G. Leles and Emily J. Zakem. 2025. Microbial Ecology to Ocean Carbon Cycling: From Genomes to Numerical Models.Annual Review of Earth and Planetary Science, Vol. 53:595-624, https://doi.org/10.1146/annurev-earth-040523-020630</ref>. More recently, new tools in analytical chemistry, molecular microbiology, and bioinformatics are enhancing our ability to integrate process-based mechanisms and biomass estimates of functional groups of interest into the study of ocean biogeochemistry<ref> Moran MA, Kujawinski EB, Stubbins A, Fatland R, Aluwihare LI, et al. 2016. Deciphering ocean carbon in a changing world. PNAS 113:(12):3143–51, https://doi.org/10.1073/pnas.1514645113</ref>. <br>
In addition, advances in sequencing and mass spectrometry technologies over the last decades have accelerated the study of microbial communities. These high-throughput, data-rich approaches enable assessment of community taxonomic and functional composition, metabolic potential and diversity, and phylogeny and evolutionary history across the global oceans<ref name="Levine et al. 2025"/>.

This literature review, initiated by [https://www.primoscorwg.org PRIMO], covers well-established physiological metrics routinely used in biological oceanography, as well as novel metrics being developed to determine physiological rates at both the cellular and community level. The entries include information about the methods (currencies, units, assumptions, uncertainties). We also provide key references to facilitate discovery.<br>
We have divided the inventory into four sections: Primary Production, Secondary Production, Nutrient Fluxes, and Interactions.

If you would like to add a data type page, please use the [[Data wiki template | Data wiki template]].

== Data Type Sections ==

''Expand a section below to browse methods by type.''


<div id="Primary_Production" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#d5e8d4; padding:8px 14px; font-weight:bold; font-size:1.1em;">Primary Production</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Photoautotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Incubation | Discrete
* [[14-Carbon uptake (NPP)]]
* [[18O-labelled water (GOP)]]
* [[Winkler light-dark dissolved O2 bottle]]
* [[Phytoplankton carbon biomass (Cphyto) x growth rate (µ)]]
* [[13-Carbon uptake]]
* [[Gross Primary Production (GPP) - triple oxygen]]
* [[Net community production (NCP)]]
; ''In situ | Continuous''
* [[Net community production (NCP) - O₂/Ar]]
* [[Continuous dissolved oxygen (DO) optodes]]
; Optics-based
* [[Single Turnover Chlorophyll Fluorescence]]
* [[Remote Sensing NPP]]
* [[BGC-Argo NPP]]
; Omics-based
* [[RT-qPCR/ddPCR]]
* [[rcbL gene expression/quant]]
* [[psbA]]
* [[Rubisco protein]]
* [[PSII/PSI quantification]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Nitrogen Fixation]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Bulk uptake 15N2]]
* [[Single cell uptake (SIP-SIMS/nanoSIMS; CHIP-SIMS; CARD-FISH paired with nanoSIMS)|Single cell uptake techniques]]
* [[Acetylene Reduction Assays (ARA)]]
* [[NifH detection/quantification (qPCR, RT-qPCR; nifH database)|nifH detection/quantification]]
* [[nifH amplicon sequence]]
* [[H2 supersaturation]]
* [[Nitrogenase quantification]]
* [[Other diazotroph marker genes: nifD, nifK|Other diazotroph marker genes]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Phytoplankton C/N-Based Growth Rates]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Carbon content]]
* [[Nitrogen content]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #b0d0ae; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f2faf1;">[[Chemoautotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Mass balance approach]]
* [[Dark 14C-bicarbonate fixation]]
* [[Nano SIP]]
* [[Black smoker]]
</div>
</div>

</div>
</div>


<div id="Secondary_Production" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#fff2cc; padding:8px 14px; font-weight:bold; font-size:1.1em;">Secondary Production</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Enzyme Activity]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Enzyme assay with fluoresceinamine labeled biopolymers]]
* [[Enzyme assay with RBB labeled polysaccharides]]
* [[Enzyme assay with DNS]]
* [[Enzyme assay/alkaline phosphatase with fluorescently labeled substrate]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Growth Rate]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Growth rate from biomass observation]]
* [[Radiolabeled tracer method]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #e0c86a; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fffbe6;">[[Respiration]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Respiration from BGC-Argo floats and AOU]]
* [[Respiration from oxygen consumption: optodes]]
* [[Respiration from activity of respiratory chain: enzymatic assays]]
* [[Respiration from activity of respiratory chain: redoxsensor green]]
* [[Respiration from oxygen consumption]]
</div>
</div>

</div>
</div>


<div id="Nutrient_Fluxes" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#ddeeff; padding:8px 14px; font-weight:bold; font-size:1.1em;">Nutrient Fluxes</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Nitrogen]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Nitrogen Uptake
* [[(15N-ρNO3-) uptake New Production]]
* [[Size-fractionated (15N-ρNO3-) uptake New Production]]
* [[15N-ρNO3/chl a (N assimilation rate)]]
* [[Size-fractionated 15N-ρNO3/chl a (N assimilation rate)]]
* [[(15N-ρNH4+) uptake Regenerated Production]]
* [[Size-fractionated (15N-ρNH4+) uptake Regenerated Production]]
* [[(15N-ρurea) uptake Regenerated Production]]
* [[Size-fractionated (15N-ρurea) uptake Regenerated Production]]
; Nitrogen Assimilation
* [[Eukaryotic Assimilatory nitrate reductase, NAD(P)H dependent, Nitrate -> Nitrite, Nitrate (NR)]]
; Nitrification
* [[DIN inventory with inhibitors]]
* [[Inhibitors with 14 or 13CO2 uptake]]
* [[Nitrite oxidation (Nxr)]]
* [[amoA gene or transcript abundance]]
* [[Natural abundance of N and O isotopes in nitrate, nitrite and ammonium]]
* [[15N tracers]]
; Denitrification
* [[Acetylene-block proxy for denitrifcation enzyme activity]]
* [[15N tracer-based method]]
* [[N2:Ar ratio quantification]]
* [[Mass Balance]]
* [[Stoichiometric approach]]
* [[Natural Abundances of 15N and 18O]]
; Other Processes (DNRA, Anammox, DON)
* [[Isotopic measurements---15N-labeled ammonium (15NH4+) accumulation rate in 15NO3- added incubation|Isotopic measurements of 15NH4+ accumulation (DNRA)]]
* [[15N tracers (15N labeled gases upon addition of 15NO3, 15NO2, or 15NH4)|15N tracers for anaerobic ammonium oxidation]]
* [[Functional gene quantification (hzs, hzo)]]
* [[FISH staining of anammox bacteria]]
* [[13C- and 15N-labeled algal exudates (isotope tracing & nanoSIMS)|13C- and 15N-labeled algal exudates with nanoSIMS]]
* [[Degradation of dissolved organic nitrogen: Leucine-aminopeptidase activity|Leucine-aminopeptidase activity measurement]]
* [[Degradation of dissolved organic nitrogen: Endopeptidase activity|Endopeptidase activity measurement]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Phosphorus]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Degradation of dissolved organic phosphorus
* [[Degradation of dissolved organic phosphorus (P-monoesters): Alkaline phosphatase activity (APA)|Alkaline phosphatase activity (APA)]]
* [[Degradation of dissolved organic phosphorus (P-diesters): Phosphodiesterase activity (PDE)|Phosphodiesterase activity (PDE)]]
* [[Degradation of dissolved organic phosphorus (phosphonates): C-P lyase activity (CLA)|C-P lyase activity (CLA)]]
* [[Cleavage of phosphate from 5'-nucleotides: 5'NT/5PN activity|5'NT/5PN activity]]
; P nutrition
* [[Reduction of phosphite to phosphate for growth (ptxABCD)|ptxABCD]]
* [[32-P incorporation]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Sulfur]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[DMS/P/O cycling]]
* [[Rates of DMSO reduction to DMS]]
* [[Rates of DMS and DMSP oxidation to DMSO]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Trace Metals]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[55-Iron uptake]]
* [[54-Manganese uptake]]
* [[67-Copper (half-life 62 h; incubation) & 64-Cu (half-life 12.7 h; lab) uptake|67-Copper & 64-Cu uptake]]
* [[Cobalamin uptake with 57Cobalt-B12]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #cee0f2; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#f0f7ff;">[[Biomineralization]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Silicon
* [[Silicon uptake]]
* [[Kinetics of silicon uptake]]
* [[Silica production]]
* [[Silica production - PDMPO]]
* [[Biogenic silica accumulation]]
; Calcification
* [[Calcification (13-Carbon uptake)]]
</div>
</div>

</div>
</div>


<div id="Interactions" class="mw-collapsible mw-collapsed" style="border:1px solid #a2a9b1; margin:0.5em 0;">
<div style="background:#ffe6cc; padding:8px 14px; font-weight:bold; font-size:1.1em;">Interactions</div>
<div class="mw-collapsible-content" style="padding:8px 14px;">

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Grazing]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
; Microzooplankton on Phytoplankton
* [[Incubation dilution experiments]]
* [[Size-fractionated incubation dilution experiments]]
* [[Cell abundance]]
* [[Gut-fluorescence]]
; Bacterivory & Mixotrophy
* [[Fluorescently labeled prey surrogates]]
* [[Radioactively labeled prey surrogates]]
* [[Pulse-chase labeling of bacterial prey]]
* [[Stable isotope-labelled prey]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Mixotrophy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[LysoTracker Green Incorporation]]
* [[15N/13C-labelled DOM/cells]]
* [[Bead consumption rates by cells with chloroplasts]]
* [[BrdU-labeled prey incorporation into things with chloroplasts]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Viruses]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Electron microscopy of cells]]
* [[Quantification of virus particles]]
* [[Dilution incubation experiments]]
* [[Bulk RNA marker-gene PCR analysis]]
* [[Bulk RNA-sequencing (whole transcriptome)]]
* [[Single-cell RNA-sequencing (population)]]
* [[Single-cell RNA-sequencing (community)]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Allelopathy]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Filtrate cross-culturing]]
* [[Size-fractionated extract spiking]]
</div>
</div>

<div class="mw-collapsible mw-collapsed" style="border:1px solid #f0c080; margin:4px 0;">
<div style="padding:5px 10px; font-weight:bold; background:#fff8f0;">[[Life cycles]]</div>
<div class="mw-collapsible-content" style="padding:4px 10px 6px 24px;">
* [[Light or electron microscopic counts of life cycle stages/transitions]]
* [[Fluorescent in situ hybridization microscope counts]]
* [[Bulk RNA marker-gene PCR analysis]]
* [[Bulk RNA-sequencing (whole transcriptome)]]
</div>
</div>

</div>
</div>

== References ==
<references />

Bulk RNA-sequencing (whole transcriptome)

2026-09-24T13:00:14Z

Michiel Perneel:

* [[Page authors|Page authors]]: [[Michiel Perneel]], [[PRIMO]]
* [[Responsible curator|Responsible curator]]: [[User:Kate Evans|Kate Evans]]
----
__TOC__
<div class="model-box">
{| class="model-ib"
| '''Definition:''' High-throughput sequencing of RNA transcribed by an individual or population of a given organism, or a community of species.
|-
| '''Approach:''' filtering, RNA extraction, sequencing, bioinformatics
|-
| '''Context:''' ''in situ'', culturing, incubations
|-
| '''Spatial scale:''' L
|-
| '''Temporal scale:''' hours, days, weeks, seasons, events of interest
|-
| '''Units:''' gene expression, e.g. TPM
|-
| '''Community captured:''' size-fractioned, e.g. 0.2 - 250 µm, cultured or target species (both prokaryotic and eukaryotic)
|-
| '''Co-measurements:''' Other measurements required for interpretation of in-situ samples e.g., temperature, salinity, nutrients, physiological data
|}
</div>
<div style="clear:both"></div>

== Method Overview ==

(Meta)transcriptomics sequences the pool of RNA recovered from a single-species culture up to a whole microbial assemblage. In the latter case it can provide a semi-quantitative snapshot of which genes were being transcribed by which organisms at the moment of sampling.
Where (meta)genomics describes ''metabolic potential'' (i.e. the genes that are present), (meta)transcriptomics describes ''metabolic expression'' (i.e. the genes that are being transcribed), and is therefore the molecular measurement most often used as a proxy for ''in situ'' physiological state and for the activity of specific biogeochemical pathways.

The method is sensitive to how the sample is handled. Prokaryotic mRNA has a half-life of roughly 5 minutes, and as little as ~2.4 minutes in marine cyanobacteria.<ref name="Moran2013">Moran, M. A., Satinsky, B., Gifford, S. M., Luo, H., Rivers, A., Chan, L.-K., Meng, J., Durham, B. P., Shen, C., Varaljay, V. A., Smith, C. B., Yager, P. L., & Hopkinson, B. M. (2013). Sizing up metatranscriptomics. ''The ISME Journal'', 7(2), 237–243. doi:10.1038/ismej.2012.94</ref>
Protocol choices at every step during the generation of bulk RNA-Seq data such as filtration, preservation, enrichment (e.g. for mRNA in poly(A) selection to target microeukaryotic material), sequencing depth, assembly and annotation, affect the final expression matrix<ref name="Cohen2022">Cohen, N. R., Alexander, H., Krinos, A. I., Hu, S. K., & Lampe, R. H. (2022). Marine microeukaryote metatranscriptomics: sample processing and bioinformatic workflow recommendations for ecological applications. ''Frontiers in Marine Science'', 9, 867007. doi:10.3389/fmars.2022.867007</ref>

== Specific use cases ==

=== Sample collection and filtration ===

Seawater can be collected by Niskin bottles, underway pump, manually, or ''in situ'' pump, and biomass is concentrated onto filters. Culture samples can be taken directly from the culture vessel (potentially with upconcentration).
Because the transcriptome degrades and responds to handling stress within minutes, the interval between sampling and freezing should be minimised<ref name="Cohen2022" />.

* '''Volume.''' Can be several mL from cultures, 1.5-3.5 L in productive coastal waters, and ≥10 L in oligotrophic offshore waters for microeukaryote work; 1–10 L is common for prokaryote-targeted sampling on 0.22 µm Sterivex cartridges. Volume is constrained by filter clogging and by the requirement to complete filtration quickly. More volume can be filtered and later subsampled.
* '''Size fractionation.''' Serial or stacked filters partition the assemblage, e.g. 0.2–3 µm (prokaryote-enriched), 3–20 µm and 20–250 µm (nano- and microplankton), or a single 0.8–250 µm protistan fraction. Fractionation aids interpretation but introduces cell breakage and incomplete separation, and the chosen cut-offs must accompany any downstream comparison.
* '''Preservation, extraction and quality control.''' Filters or filtrate can be flash-frozen in liquid nitrogen and stored at −80 °C; RNA-stabilising buffers (e.g. RNA''later'') can be added to safeguard RNA integrity<ref name="Cohen2022" />

=== RNA extraction & library preparation ===
'''Internal standards:''' Adding a known number of synthetic RNA molecules at the start of extraction converts an otherwise compositional (relative) dataset into an absolute one. Standards may be commercial spike-in sets (ERCC, ArrayControl, Sequins) or ''in vitro'' transcripts from custom plasmids, and are typically dosed at ~1% of the expected mRNA pool.<ref name="Cohen2022" /><ref name="Satinsky2013">Satinsky, B. M., Gifford, S. M., Crump, B. C., & Moran, M. A. (2013). Use of internal standards for quantitative metatranscriptome and metagenome analysis. ''Methods in Enzymology'', 531, 237–250. doi:10.1016/B978-0-12-407863-5.00012-5</ref> The ratio of standard molecules added to standard reads recovered yields transcript inventories per litre of seawater (see [[#Common calculations/conversions|Common calculations]]), and also diagnoses extraction and library-prep losses. Quantitative metatranscriptomics of this kind is the form most directly comparable to rate measurements and to model state variables.<ref name="Gifford2011">Gifford, S. M., Sharma, S., Rinta-Kanto, J. M., & Moran, M. A. (2011). Quantitative analysis of a deeply sequenced marine microbial metatranscriptome. ''The ISME Journal'', 5(3), 461–472. doi:10.1038/ismej.2010.141</ref>
'''RNA extraction''' Total RNA is extracted from the sample often using commercial kits (e.g. Qiagen RNeasy, Invitrogen TRIzol, ToTALLY RNA), usually with bead-beating in silica or zirconia beads to break silicified, armoured or thick-walled cells, followed by DNase treatment to remove co-extracted DNA. Yield and integrity are checked by fluorometry (Qubit) and capillary electrophoresis (Bioanalyzer/TapeStation)<ref name="Cohen2022" />.

For eukaryotes, ribosomal RNA dominates total RNA (usually >80%), so libraries are enriched for mRNA by one of two routes:
* '''Poly-A selection''' captures polyadenylated eukaryotic mRNA on oligo-dT beads. It delivers the most protein-coding reads per sequencing dollar, but excludes bacteria and archaea, discriminates against plastid and mitochondrial transcripts, and biases against transcripts with short or absent poly-A tails. Standard kits (e.g. TruSeq Stranded mRNA) need 0.1–1 µg total RNA; low-input chemistries (e.g. SMART-Seq v4) work from ~250 pg via linear amplification, at the cost of amplification bias.<ref name="Cohen2022" />
* '''rRNA depletion''' (Ribo-Zero, riboPOOLs and equivalents) removes rRNA by probe hybridisation and retains prokaryotic, eukaryotic and organellar mRNA together. It is the choice for whole-community and prokaryote-focused work and for organelle transcripts, but leaves a larger residual rRNA fraction and so requires greater sequencing depth per unit of usable signal.<ref name="Cohen2022" />

Residual rRNA is removed ''in silico'' after sequencing with SortMeRNA, BBDuk or riboPicker.
Libraries are further prepared according to the sequencing platform.

=== Sequencing ===

Short-read Illumina sequencing (NextSeq, NovaSeq; typically 2×150 to 2×250 bp) is the most popular platform.

=== Bioinformatic processing ===

# '''Quality control.''' Adapter and quality trimming (fastp, Trimmomatic, cutadapt) with inspection via FastQC/MultiQC; ''in silico'' rRNA removal.
# '''Direct mapping or ''de novo'' assembly.''' Reads may be mapped directly to a reference genome or database (e.g. MMETSP, EukProt, MarFERReT, OM-RGC) or assembled ''de novo'' (Trinity, rnaSPAdes, MEGAHIT). rnaSPAdes and Trinity perform well on marine microeukaryote communities. Multi-assembler approaches or assemblies from multiple samples can be followed by clustering at 95-100% identity (CD-HIT, MMseqs2)<ref name="Cohen2022" />.
# '''Quantification.''' Trimmed reads are mapped back to the assembly with Bowtie2/BWA or quasi-mapped with Salmon/kallisto to produce per-contig counts.
# '''Protein prediction and annotation.''' Open reading frames are called (TransDecoder, GeneMarkS-T; Prodigal for prokaryote-dominated assemblies), then annotated functionally against KEGG/KOfam, eggNOG, Pfam (HMMER), KOG and Gene Ontology, and taxonomically by DIAMOND/MMseqs2 alignment (with a last-common-ancestor algorithm)<ref name="Cohen2022" />.
# '''Aggregation and statistics.''' Quantified matrics are integrated with environmental metadata, and annotation information to tackle questions of interest.

'''Workflow examples:''' Reproducible pipelines include eukrhythmic, SqueezeMeta and nf-core/metatdenovo,<ref name="DiLeo2025">Di Leo, ''et al.'' (2025). The Nextflow nf-core/metatdenovo pipeline for reproducible annotation of metatranscriptomes, and more. ''PeerJ'', 13, e20328. doi:10.7717/peerj.20328</ref><ref name="Krinos2023">Krinos, A. I., Cohen, N. R., Follows, M. J., & Alexander, H. (2023). Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly. ''BMC Bioinformatics'', 24, 74. doi:10.1186/s12859-022-05121-y</ref> and require high-performance computing resources for large datasets.

=== Output & normalisation ===

Sequencing produces compositional data: read counts describe proportions of a fixed-size library. Reads should be normalised:

* '''Within-sample relative expression''' (TPM, RPKM/FPKM) — comparable across genes within a sample, and the pragmatic choice for large spatial or temporal surveys, but composition-dependent and without a statistical test of differential expression.<ref name="Cohen2022" />
* '''Model-based differential expression''' (DESeq2, edgeR) — negative-binomial generalised linear models with FDR control, appropriate for replicated designs and ideally applied after binning to taxon-specific transcript sets.<ref name="Cohen2022" />
* '''Absolute estimates''' (transcripts L<sup>-1</sup>, transcripts cell<sup>-1</sup>) — requires internal standards(and logging of processed volumes, optionally with cell counts or a paired metagenome), and is the form best suited to comparison with rates and with model fluxes.<ref name="Gifford2011" /><ref name="Satinsky2013" /><ref name="Perneel2025">Perneel, M., Alexander, H., Hablützel, P. I., & Maere, S. (2025). A case for absolute gene expression estimates in microbiome studies using metatranscriptomics. ''The ISME Journal'', 19(1), wraf188. doi:10.1093/ismejo/wraf188</ref>

=== Scale of measurement ===
Next to culture-based approaches, in-situ sampling of bulk RNA-Seq depends on the study design. A single sample is a point measurement in space: one sample integrates the litres of seawater it collected (typically 1–10 L, more offshore), at one depth and station.
These can then be aggregated across the research cruise, mooring or autonomous platform, individual snapshots resolve diel cycles, bloom development, mesoscale features and seasonal transitions; global-scale synthesis is possible if protocols are harmonised.<ref name="Salazar2019">Salazar, G., Paoli, L., Alberti, A., ''et al.'' (2019). Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. ''Cell'', 179(5), 1068–1083.e21. doi:10.1016/j.cell.2019.10.014</ref><ref name="Peoples2026">Peoples, L. M., Eppley, J. M., Barone, B., Hobson, B. W., Karl, D. M., Kieft, B., Marin, R. III, Preston, C. M., Romano, A. E., Ryan, J. P., Scholin, C. A., Wilson, S. T., Zhang, Y., Church, M. J., & DeLong, E. F. (2026). Diel and eddy driven changes in microbial gene expression and biogeochemistry in the oceanic chlorophyll maximum. ''Nature Communications'', 17, 3636.</ref>

=== Data generated ===

* Raw paired-end sequence reads (FASTQ), with library and sample metadata.
* Assembled contigs or a mapped reference catalogue (FASTA), and predicted proteins.
* A count matrix of contigs/genes × samples, plus taxonomic and functional annotation tables.
* Derived products: normalised expression matrices (TPM), differential-expression tables, transcript inventories per litre, ordinations, co-expression networks, and pathway- or taxon-level expression profiles.
* Where internal standards were used, standard recovery statistics documenting extraction and library efficiency.
* Environmental or study metadata

=== Repositories & databases ===

'''Raw and processed data'''
* [https://www.ncbi.nlm.nih.gov/sra NCBI Sequence Read Archive (SRA)] and [https://www.ebi.ac.uk/ena ENA] — raw reads; the expected archive for publication.
* [https://zenodo.org Zenodo] and GitHub for processed data ( assemblies, count matrices, metadata, etc) and analysis code<ref name="Cohen2022" />.

'''Reference libraries for annotation'''
* MMETSP (Marine Microbial Eukaryote Transcriptome Sequencing Project): 678 transcriptomes from 405 microbial eukaryote strains.<ref name="Keeling2014">Keeling, P. J., ''et al.'' (2014). The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. ''PLoS Biology'', 12(6), e1001889. doi:10.1371/journal.pbio.1001889</ref>
* [https://github.com/armbrustlab/marferret MarFERReT]: version-controlled reference library of marine microbial eukaryote functional genes.<ref name="Groussman2023">Groussman, R. D., Blaskowski, S., Coesel, S. N., & Armbrust, E. V. (2023). MarFERReT, an open-source, version-controlled reference library of marine microbial eukaryote functional genes. ''Scientific Data'', 10, 926. doi:10.1038/s41597-023-02842-4</ref>
* EukProt, EukZoo and PhyloDB: complementary eukaryote protein references; MarRef and OM-RGC for prokaryotes.
* [https://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/ Ocean Gene Atlas]: online query of ''Tara'' Oceans gene abundance and expression biogeography.<ref name="Vernette2022">Vernette, C., Lecubin, J., Sánchez, P., ''Tara'' Oceans Coordinators, Sunagawa, S., Delmont, T. O., Acinas, S. G., Pelletier, E., Hingamp, P., & Lescot, M. (2022). The Ocean Gene Atlas v2.0: online exploration of the biogeography and phylogeny of plankton genes. ''Nucleic Acids Research'', 50(W1), W516–W526. doi:10.1093/nar/gkac420</ref>
* [https://github.com/armbrustlab/NPac_euk_gene_catalog North Pacific Eukaryotic Gene Catalog]: assembled and annotated metatranscriptomes for the North Pacific.<ref name="Groussman2024">Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. ''Scientific Data'', 11, 1161. doi:10.1038/s41597-024-04005-5</ref>
* Functional references: KEGG/KOfam, eggNOG, Pfam, KOG, Gene Ontology.

== Limitations ==

'''Sampling and handling'''
* mRNA half-lives of minutes mean the measurement is easily perturbed. Time from collection to preservation, bottle confinement, light and temperature change, and filtration pressure all induce stress responses that are indistinguishable from ''in situ'' signal unless handling is standardised.<ref name="Moran2013" /><ref name="Cohen2022" />
* Strong diel periodicity in transcription means samples are only comparable when time of day is matched or explicitly modelled<ref name="Peoples2026" /><ref name="Ottesen2014">Ottesen, E. A., Young, C. R., Gifford, S. M., Eppley, J. M., Marin, R. III, Schuster, S. C., Scholin, C. A., & DeLong, E. F. (2014). Multispecies diel transcriptional oscillations in open ocean heterotrophic bacterial assemblages. ''Science'', 345(6193), 207–212. doi:10.1126/science.1252476</ref>
* Size fractionation is imperfect: cells break, fractions overlap, and filters clog, biasing which taxa are represented.

'''Library chemistry'''
* Poly-A selection excludes prokaryotes and discriminates against organellar and non-polyadenylated transcripts; rRNA depletion retains more rRNA and needs deeper sequencing. Neither is bias-free, and libraries prepared by the two routes are not directly comparable.<ref name="Cohen2022" />

'''Quantification and statistics'''
* Without internal standards the data are compositional: an apparent increase in one transcript can reflect a decrease elsewhere.<ref name="Satinsky2013" /><ref name="Perneel2025" />
* Sequencing captures a minute fraction of the mRNA pool, so many functionally important genes fall below detection; roughly half the functional categories in early quantitative work had too few counts for robust comparison.<ref name="Gifford2011" />
* Limited biological replication constrains formal differential-expression testing.<ref name="Cohen2022" />

'''Reference and assembly'''
* Reference libraries under-represent rare lineages, deep-sea taxa and uncultured groups and often contain contamination; a large share of contigs and predicted proteins remain taxonomically or functionally unannotated.<ref name="Cohen2022" />
* ''De novo'' assembly of mixed communities generates chimeric and spurious contigs where close relatives co-occur, and results depend on assembler and ''k''-mer choice.<ref name="Cohen2022" />
* Choosing a taxonomic resolution is a trade-off: species-level assignment is confident for fewer sequences, while class-level aggregation can mask opposing physiological responses within a group. The use of reference databases suffer from different biases.<ref name="Cohen2022" /><ref name="Krinos2024">Krinos, A.I., Mars Brisbin, M., Hu, S.K. et al. Missing microbial eukaryotes and misleading meta-omic conclusions. Nat Commun 15, 9873 (2024). https://doi.org/10.1038/s41467-024-52212-w</ref>

'''Interpretation'''
* Transcript abundance is not protein abundance and not a rate.
* Expression change can arise from a shift in community composition rather than in per-cell regulation<ref name="Salazar2019" />.
* Converting expression into a flux requires independent calibration (rate measurements, physiological data, or a model).

== Example studies ==
https://doi.org/10.1073/pnas.0708897105

https://doi.org/10.1111/j.1462-2920.2008.01863.x

https://doi.org/10.1073/pnas.1118408109

https://doi.org/10.1073/pnas.1421993112

https://doi.org/10.1038/s41467-017-02342-1

https://doi.org/10.1016/j.cell.2019.10.014

== References ==
<references/>

[[Category:Main Pages|Model types]]

Bulk RNA-sequencing (whole transcriptome)

2026-08-27T14:39:20Z

Michiel Perneel: first draft of the Wiki, mainly based on Cohen et al., (2022)

* [[Page authors|Page authors]]: [[Michiel Perneel]], [[PRIMO]]
* [[Responsible curator|Responsible curator]]: [[User:Kate Evans|Kate Evans]]
----
__TOC__
<div class="model-box">
{| class="model-ib"
| '''Definition:''' High-throughput sequencing of RNA transcribed by an individual or population of a given organism, or a community of species.
|-
| '''Approach:''' filtering, RNA extraction, sequencing, bioinformatics
|-
| '''Context:''' ''in situ'', culturing, incubations
|-
| '''Spatial scale:''' L
|-
| '''Temporal scale:''' hours, days, weeks, seasons, events of interest
|-
| '''Units:''' gene expression, e.g. TPM
|-
| '''Community captured:''' size-fractioned, e.g. 0.2 - 250 µm, cultured or target species (both prokaryotic and eukaryotic)
|-
| '''Co-measurements:''' Other measurements required for interpretation of in-situ samples e.g., temperature, salinity, nutrients, physiological data
|}
</div>
<div style="clear:both"></div>

== Method Overview ==

(Meta)transcriptomics sequences the pool of RNA recovered from a single-species culture up to a whole microbial assemblage. In the latter case it can provide a semi-quantitative snapshot of which genes were being transcribed by which organisms at the moment of sampling.
Where (meta)genomics describes ''metabolic potential'' (i.e. the genes that are present), (meta)transcriptomics describes ''metabolic expression'' (i.e. the genes that are being transcribed), and is therefore the molecular measurement most often used as a proxy for ''in situ'' physiological state and for the activity of specific biogeochemical pathways.

The method is sensitive to how the sample is handled. Prokaryotic mRNA has a half-life of roughly 5 minutes, and as little as ~2.4 minutes in marine cyanobacteria.<ref name="Moran2013">Moran, M. A., Satinsky, B., Gifford, S. M., Luo, H., Rivers, A., Chan, L.-K., Meng, J., Durham, B. P., Shen, C., Varaljay, V. A., Smith, C. B., Yager, P. L., & Hopkinson, B. M. (2013). Sizing up metatranscriptomics. ''The ISME Journal'', 7(2), 237–243. doi:10.1038/ismej.2012.94</ref>
Protocol choices at every step during the generation of bulk RNA-Seq data such as filtration, preservation, enrichment (e.g. for mRNA in poly(A) selection to target microeukaryotic material), sequencing depth, assembly and annotation, affect the final expression matrix<ref name="Cohen2022">Cohen, N. R., Alexander, H., Krinos, A. I., Hu, S. K., & Lampe, R. H. (2022). Marine microeukaryote metatranscriptomics: sample processing and bioinformatic workflow recommendations for ecological applications. ''Frontiers in Marine Science'', 9, 867007. doi:10.3389/fmars.2022.867007</ref>

=== Sample collection and filtration ===

Seawater can be collected by Niskin bottles, underway pump, manually, or ''in situ'' pump, and biomass is concentrated onto filters. Culture samples can be taken directly from the culture vessel (potentially with upconcentration).
Because the transcriptome degrades and responds to handling stress within minutes, the interval between sampling and freezing should be minimised<ref name="Cohen2022" />.

* '''Volume.''' Can be several mL from cultures, 1.5-3.5 L in productive coastal waters, and ≥10 L in oligotrophic offshore waters for microeukaryote work; 1–10 L is common for prokaryote-targeted sampling on 0.22 µm Sterivex cartridges. Volume is constrained by filter clogging and by the requirement to complete filtration quickly. More volume can be filtered and later subsampled.
* '''Size fractionation.''' Serial or stacked filters partition the assemblage, e.g. 0.2–3 µm (prokaryote-enriched), 3–20 µm and 20–250 µm (nano- and microplankton), or a single 0.8–250 µm protistan fraction. Fractionation aids interpretation but introduces cell breakage and incomplete separation, and the chosen cut-offs must accompany any downstream comparison.
* '''Preservation, extraction and quality control.''' Filters or filtrate can be flash-frozen in liquid nitrogen and stored at −80 °C; RNA-stabilising buffers (e.g. RNA''later'') can be added to safeguard RNA integrity<ref name="Cohen2022" />

=== RNA extraction & library preparation ===
'''Internal standards:''' Adding a known number of synthetic RNA molecules at the start of extraction converts an otherwise compositional (relative) dataset into an absolute one. Standards may be commercial spike-in sets (ERCC, ArrayControl, Sequins) or ''in vitro'' transcripts from custom plasmids, and are typically dosed at ~1% of the expected mRNA pool.<ref name="Cohen2022" /><ref name="Satinsky2013">Satinsky, B. M., Gifford, S. M., Crump, B. C., & Moran, M. A. (2013). Use of internal standards for quantitative metatranscriptome and metagenome analysis. ''Methods in Enzymology'', 531, 237–250. doi:10.1016/B978-0-12-407863-5.00012-5</ref> The ratio of standard molecules added to standard reads recovered yields transcript inventories per litre of seawater (see [[#Common calculations/conversions|Common calculations]]), and also diagnoses extraction and library-prep losses. Quantitative metatranscriptomics of this kind is the form most directly comparable to rate measurements and to model state variables.<ref name="Gifford2011">Gifford, S. M., Sharma, S., Rinta-Kanto, J. M., & Moran, M. A. (2011). Quantitative analysis of a deeply sequenced marine microbial metatranscriptome. ''The ISME Journal'', 5(3), 461–472. doi:10.1038/ismej.2010.141</ref>
'''RNA extraction''' Total RNA is extracted from the sample often using commercial kits (e.g. Qiagen RNeasy, Invitrogen TRIzol, ToTALLY RNA), usually with bead-beating in silica or zirconia beads to break silicified, armoured or thick-walled cells, followed by DNase treatment to remove co-extracted DNA. Yield and integrity are checked by fluorometry (Qubit) and capillary electrophoresis (Bioanalyzer/TapeStation)<ref name="Cohen2022" />.

For eukaryotes, ribosomal RNA dominates total RNA (usually >80%), so libraries are enriched for mRNA by one of two routes:
* '''Poly-A selection''' captures polyadenylated eukaryotic mRNA on oligo-dT beads. It delivers the most protein-coding reads per sequencing dollar, but excludes bacteria and archaea, discriminates against plastid and mitochondrial transcripts, and biases against transcripts with short or absent poly-A tails. Standard kits (e.g. TruSeq Stranded mRNA) need 0.1–1 µg total RNA; low-input chemistries (e.g. SMART-Seq v4) work from ~250 pg via linear amplification, at the cost of amplification bias.<ref name="Cohen2022" />
* '''rRNA depletion''' (Ribo-Zero, riboPOOLs and equivalents) removes rRNA by probe hybridisation and retains prokaryotic, eukaryotic and organellar mRNA together. It is the choice for whole-community and prokaryote-focused work and for organelle transcripts, but leaves a larger residual rRNA fraction and so requires greater sequencing depth per unit of usable signal.<ref name="Cohen2022" />

Residual rRNA is removed ''in silico'' after sequencing with SortMeRNA, BBDuk or riboPicker.
Libraries are further prepared according to the sequencing platform.

=== Sequencing ===

Short-read Illumina sequencing (NextSeq, NovaSeq; typically 2×150 to 2×250 bp) is the most popular platform.

=== Bioinformatic processing ===

# '''Quality control.''' Adapter and quality trimming (fastp, Trimmomatic, cutadapt) with inspection via FastQC/MultiQC; ''in silico'' rRNA removal.
# '''Direct mapping or ''de novo'' assembly.''' Reads may be mapped directly to a reference genome or database (e.g. MMETSP, EukProt, MarFERReT, OM-RGC) or assembled ''de novo'' (Trinity, rnaSPAdes, MEGAHIT). rnaSPAdes and Trinity perform well on marine microeukaryote communities. Multi-assembler approaches or assemblies from multiple samples can be followed by clustering at 95-100% identity (CD-HIT, MMseqs2)<ref name="Cohen2022" />.
# '''Quantification.''' Trimmed reads are mapped back to the assembly with Bowtie2/BWA or quasi-mapped with Salmon/kallisto to produce per-contig counts.
# '''Protein prediction and annotation.''' Open reading frames are called (TransDecoder, GeneMarkS-T; Prodigal for prokaryote-dominated assemblies), then annotated functionally against KEGG/KOfam, eggNOG, Pfam (HMMER), KOG and Gene Ontology, and taxonomically by DIAMOND/MMseqs2 alignment (with a last-common-ancestor algorithm)<ref name="Cohen2022" />.
# '''Aggregation and statistics.''' Quantified matrics are integrated with environmental metadata, and annotation information to tackle questions of interest.

'''Workflow examples:''' Reproducible pipelines include eukrhythmic, SqueezeMeta and nf-core/metatdenovo,<ref name="DiLeo2025">Di Leo, ''et al.'' (2025). The Nextflow nf-core/metatdenovo pipeline for reproducible annotation of metatranscriptomes, and more. ''PeerJ'', 13, e20328. doi:10.7717/peerj.20328</ref><ref name="Krinos2023">Krinos, A. I., Cohen, N. R., Follows, M. J., & Alexander, H. (2023). Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly. ''BMC Bioinformatics'', 24, 74. doi:10.1186/s12859-022-05121-y</ref> and require high-performance computing resources for large datasets.

=== Output & normalisation ===

Sequencing produces compositional data: read counts describe proportions of a fixed-size library. Reads should be normalised:

* '''Within-sample relative expression''' (TPM, RPKM/FPKM) — comparable across genes within a sample, and the pragmatic choice for large spatial or temporal surveys, but composition-dependent and without a statistical test of differential expression.<ref name="Cohen2022" />
* '''Model-based differential expression''' (DESeq2, edgeR) — negative-binomial generalised linear models with FDR control, appropriate for replicated designs and ideally applied after binning to taxon-specific transcript sets.<ref name="Cohen2022" />
* '''Absolute estimates''' (transcripts L<sup>-1</sup>, transcripts cell<sup>-1</sup>) — requires internal standards(and logging of processed volumes, optionally with cell counts or a paired metagenome), and is the form best suited to comparison with rates and with model fluxes.<ref name="Gifford2011" /><ref name="Satinsky2013" /><ref name="Perneel2025">Perneel, M., Alexander, H., Hablützel, P. I., & Maere, S. (2025). A case for absolute gene expression estimates in microbiome studies using metatranscriptomics. ''The ISME Journal'', 19(1), wraf188. doi:10.1093/ismejo/wraf188</ref>

=== Scale of measurement ===
Next to culture-based approaches, in-situ sampling of bulk RNA-Seq depends on the study design. A single sample is a point measurement in space: one sample integrates the litres of seawater it collected (typically 1–10 L, more offshore), at one depth and station.
These can then be aggregated across the research cruise, mooring or autonomous platform, individual snapshots resolve diel cycles, bloom development, mesoscale features and seasonal transitions; global-scale synthesis is possible if protocols are harmonised.<ref name="Salazar2019">Salazar, G., Paoli, L., Alberti, A., ''et al.'' (2019). Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. ''Cell'', 179(5), 1068–1083.e21. doi:10.1016/j.cell.2019.10.014</ref><ref name="Peoples2026">Peoples, L. M., Eppley, J. M., Barone, B., Hobson, B. W., Karl, D. M., Kieft, B., Marin, R. III, Preston, C. M., Romano, A. E., Ryan, J. P., Scholin, C. A., Wilson, S. T., Zhang, Y., Church, M. J., & DeLong, E. F. (2026). Diel and eddy driven changes in microbial gene expression and biogeochemistry in the oceanic chlorophyll maximum. ''Nature Communications'', 17, 3636.</ref>

=== Data generated ===

* Raw paired-end sequence reads (FASTQ), with library and sample metadata.
* Assembled contigs or a mapped reference catalogue (FASTA), and predicted proteins.
* A count matrix of contigs/genes × samples, plus taxonomic and functional annotation tables.
* Derived products: normalised expression matrices (TPM), differential-expression tables, transcript inventories per litre, ordinations, co-expression networks, and pathway- or taxon-level expression profiles.
* Where internal standards were used, standard recovery statistics documenting extraction and library efficiency.
* Environmental or study metadata

=== Repositories & databases ===

'''Raw and processed data'''
* [https://www.ncbi.nlm.nih.gov/sra NCBI Sequence Read Archive (SRA)] and [https://www.ebi.ac.uk/ena ENA] — raw reads; the expected archive for publication.
* [https://zenodo.org Zenodo] and GitHub for processed data ( assemblies, count matrices, metadata, etc) and analysis code<ref name="Cohen2022" />.

'''Reference libraries for annotation'''
* MMETSP (Marine Microbial Eukaryote Transcriptome Sequencing Project): 678 transcriptomes from 405 microbial eukaryote strains.<ref name="Keeling2014">Keeling, P. J., ''et al.'' (2014). The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. ''PLoS Biology'', 12(6), e1001889. doi:10.1371/journal.pbio.1001889</ref>
* [https://github.com/armbrustlab/marferret MarFERReT]: version-controlled reference library of marine microbial eukaryote functional genes.<ref name="Groussman2023">Groussman, R. D., Blaskowski, S., Coesel, S. N., & Armbrust, E. V. (2023). MarFERReT, an open-source, version-controlled reference library of marine microbial eukaryote functional genes. ''Scientific Data'', 10, 926. doi:10.1038/s41597-023-02842-4</ref>
* EukProt, EukZoo and PhyloDB: complementary eukaryote protein references; MarRef and OM-RGC for prokaryotes.
* [https://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/ Ocean Gene Atlas]: online query of ''Tara'' Oceans gene abundance and expression biogeography.<ref name="Vernette2022">Vernette, C., Lecubin, J., Sánchez, P., ''Tara'' Oceans Coordinators, Sunagawa, S., Delmont, T. O., Acinas, S. G., Pelletier, E., Hingamp, P., & Lescot, M. (2022). The Ocean Gene Atlas v2.0: online exploration of the biogeography and phylogeny of plankton genes. ''Nucleic Acids Research'', 50(W1), W516–W526. doi:10.1093/nar/gkac420</ref>
* [https://github.com/armbrustlab/NPac_euk_gene_catalog North Pacific Eukaryotic Gene Catalog]: assembled and annotated metatranscriptomes for the North Pacific.<ref name="Groussman2024">Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. ''Scientific Data'', 11, 1161. doi:10.1038/s41597-024-04005-5</ref>
* Functional references: KEGG/KOfam, eggNOG, Pfam, KOG, Gene Ontology.

== Limitations ==

'''Sampling and handling'''
* mRNA half-lives of minutes mean the measurement is easily perturbed. Time from collection to preservation, bottle confinement, light and temperature change, and filtration pressure all induce stress responses that are indistinguishable from ''in situ'' signal unless handling is standardised.<ref name="Moran2013" /><ref name="Cohen2022" />
* Strong diel periodicity in transcription means samples are only comparable when time of day is matched or explicitly modelled<ref name="Peoples2026" /><ref name="Ottesen2014">Ottesen, E. A., Young, C. R., Gifford, S. M., Eppley, J. M., Marin, R. III, Schuster, S. C., Scholin, C. A., & DeLong, E. F. (2014). Multispecies diel transcriptional oscillations in open ocean heterotrophic bacterial assemblages. ''Science'', 345(6193), 207–212. doi:10.1126/science.1252476</ref>
* Size fractionation is imperfect: cells break, fractions overlap, and filters clog, biasing which taxa are represented.

'''Library chemistry'''
* Poly-A selection excludes prokaryotes and discriminates against organellar and non-polyadenylated transcripts; rRNA depletion retains more rRNA and needs deeper sequencing. Neither is bias-free, and libraries prepared by the two routes are not directly comparable.<ref name="Cohen2022" />

'''Quantification and statistics'''
* Without internal standards the data are compositional: an apparent increase in one transcript can reflect a decrease elsewhere.<ref name="Satinsky2013" /><ref name="Perneel2025" />
* Sequencing captures a minute fraction of the mRNA pool, so many functionally important genes fall below detection; roughly half the functional categories in early quantitative work had too few counts for robust comparison.<ref name="Gifford2011" />
* Limited biological replication constrains formal differential-expression testing.<ref name="Cohen2022" />

'''Reference and assembly'''
* Reference libraries under-represent rare lineages, deep-sea taxa and uncultured groups and often contain contamination; a large share of contigs and predicted proteins remain taxonomically or functionally unannotated.<ref name="Cohen2022" />
* ''De novo'' assembly of mixed communities generates chimeric and spurious contigs where close relatives co-occur, and results depend on assembler and ''k''-mer choice.<ref name="Cohen2022" />
* Choosing a taxonomic resolution is a trade-off: species-level assignment is confident for fewer sequences, while class-level aggregation can mask opposing physiological responses within a group. The use of reference databases suffer from different biases.<ref name="Cohen2022" /><ref name="Krinos2024">Krinos, A.I., Mars Brisbin, M., Hu, S.K. et al. Missing microbial eukaryotes and misleading meta-omic conclusions. Nat Commun 15, 9873 (2024). https://doi.org/10.1038/s41467-024-52212-w</ref>

'''Interpretation'''
* Transcript abundance is not protein abundance and not a rate.
* Expression change can arise from a shift in community composition rather than in per-cell regulation<ref name="Salazar2019" />.
* Converting expression into a flux requires independent calibration (rate measurements, physiological data, or a model).

== Example studies ==
https://doi.org/10.1073/pnas.0708897105

https://doi.org/10.1111/j.1462-2920.2008.01863.x

https://doi.org/10.1073/pnas.1118408109

https://doi.org/10.1073/pnas.1421993112

https://doi.org/10.1038/s41467-017-02342-1

https://doi.org/10.1016/j.cell.2019.10.014

== References ==
<references/>

[[Category:Main Pages|Model types]]

Single Turnover Chlorophyll Fluorescence

2026-02-21T10:43:32Z

Michiel Perneel: Created page with "{{BreadcrumbsPhotoautotrophy}} * Page authors: Michiel Perneel, PRIMO * Responsible curator: Kate Evans ---- Photosynthetic primary productivity is the light-driven process of extracting reducing power from water to drive CO<sub>2</sub> reduction to carbohydrates (i.e. CO<sub>2</sub> ‘fixation’). Global primary productivity is a critical source of O<sub>2</sub> for the atmosphere and oceans. Marin..."

{{BreadcrumbsPhotoautotrophy}}

* [[Page authors|Page authors]]: [[Michiel Perneel]], [[PRIMO]]
* [[Responsible curator|Responsible curator]]: [[User:Kate Evans|Kate Evans]]
----
Photosynthetic primary productivity is the light-driven process of extracting reducing power from water to drive CO<sub>2</sub> reduction to carbohydrates (i.e. CO<sub>2</sub> ‘fixation’). Global primary productivity is a critical source of O<sub>2</sub> for the atmosphere and oceans. Marine primary productivity also plays an important role in carbon sequestration to the deep ocean through the biological pump, while providing a critical source of organic matter to support aquatic food webs and metabolism.

__TOC__
<div class="model-box">
{| class="model-ib"
! What is being measured in 1 - 3 words
|-
| '''Photosynthetic electron transport'''
|-
| '''Approach:''' active chlorophyll fluorescence (single turnover), optical photophysiology
|-
| '''Context:''' ''in situ'', underway, incubation, autonomous platforms
|-
| '''Spatial scale:''' mL to km<sup>2</sup> (point measurements to transects)
|-
| '''Temporal scale:''' milliseconds to seasons (instantaneous to long-term monitoring)
|-
| '''Units:''' electrons m<sup>-3</sup> s<sup>-1</sup>, e<sup>-</sup> PSII<sup>-1</sup> s<sup>-1</sup>, derived C or O<sub>2</sub> units
|-
| '''Community captured:''' target species culture experiments, bulk phytoplankton community; taxon-weighted signal
|-
| '''Co-measurements:''' irradiance, temperature, salinity, nutrient concentrations, chlorophyll a, light history
|}
</div>
<div style="clear:both"></div>

== Method Overview ==
Single Turnover Active Chlorophyll Fluorescence (ST-ChlF) is an optical technique used to quantify photosynthetic activity in aquatic primary producers by resolving rapid fluorescence induction and relaxation transients following short excitation flashes. These transients reflect the opening and closure of Photosystem II (PSII) reaction centres and downstream electron transport processes.

By fitting photophysiological models to fluorescence transients, ST-ChlF enables estimation of photosynthetic electron transfer rates (ETR), which scale stoichiometrically with gross oxygen evolution and are closely linked to primary productivity. The method provides rapid, non-invasive measurements and can be applied across laboratory, ship-based, and autonomous observing platforms.

== Output ==

=== Scale of measurement ===
*Cellular to community-integrated photosynthesis
*Short- and long temporal scales

=== Data generated ===
*Raw fluorescence induction-relaxation transients
*Primary photophysiological parameters (e.g. Fo, Fm, σPSII, τ)
*Electron transfer rates (ETR)
*Light-response (ETR–E) curves and derived parameters (α, Ek, ETRmax)
*Ancillary stress and efficiency metrics (e.g. NPQ-related indices)

=== Units & currency ===
*ETR reported as electrons per unit volume or per PSII reaction centre per second
*Can be converted to O<sub>2</sub> or carbon-based primary productivity using stoichiometric or empirical relationships
*Represents gross photosynthetic activity on instantaneous time scales

=== Sample size ===
*Typically mL per measurement
*Not necessarily needing sample destruction
*Compatible with continuous flow-through systems

=== Repositories & databases ===

== Limitations ==
*ETR is not a direct measure of carbon fixation and requires conversion assumptions
*Relationships between ETR, O<sub>2</sub>, and carbon vary with taxonomy and environmental conditions
*Sensitive to non-photochemical quenching (NPQ) and light history
*Requires careful calibration, spectral correction, and baseline fluorescence treatment
*Community-weighted signal may mask taxon-specific responses

== Example Applications & Protocols ==

=== Classic examples ===

=== Recent applications ===

=== Common calculations/conversions ===
*Conversion of ETR to gross O<sub>2</sub> production (4 e- per O<sub>2</sub>)
*Empirical ETR–C relationships calibrated against 14C incubations
*Light-response curve fitting (ETR vs irradiance)

== References ==
SCOR Working Group 156 (2021). A User Guide for the Application of Single Turnover Active Chlorophyll Fluorescence for Phytoplankton Productivity Measurements. Version 1.0.

[[Category:Main Pages|Model types]]

Bulk RNA-sequencing (whole transcriptome)

2026-02-21T10:24:04Z

Michiel Perneel: Created page with "* Page authors: Michiel Perneel, PRIMO * Responsible curator: Kate Evans ---- __TOC__ <div class="model-box"> {| class="model-ib" High-throughput sequencing of RNA transcribed by an individual or population of a given organism, or a community of species. |- | '''Approach:''' filtering, RNA extraction, sequencing, bioinformatics |- | '''Context:''' ''in situ'', culturing, incubations |- | '''Spatial s..."

Grazing

2026-02-21T10:07:33Z

Michiel Perneel:

===Microzooplankton on phyto loss process===
*[[Incubation dilution experiments]]
*[[Incubation dilution experiments]]
*[[Cell abundance]]
*[[Gut-fluorescence]]

===Bacterivory & Mixotrophy===
*[[Fluorescently labeled prey surrogates]]
*[[Radioactively labeled prey surrogates]]
*[[Pulse-chase labeling of bacterial prey]]
*[[Stable isotope-labelled prey]]

===Life Cycles===
*[[Bulk RNA-sequencing (whole transcriptome)]]