Divergent gene expression among phytoplankton taxa in response to upwelling
Bibliographic record
Abstract
Frequent blooms of phytoplankton occur in coastal upwelling zones creating hotspots of biological productivity in the ocean. As cold, nutrient-rich water is brought up to sunlit layers from depth, phytoplankton are also transported upwards to seed surface blooms that are often dominated by diatoms. The physiological response of phytoplankton to this process, commonly referred to as shift-up, is characterized by increases in nitrate assimilation and rapid growth rates. To examine the molecular underpinnings behind this phenomenon, metatranscriptomics was applied to a simulated upwelling experiment using natural phytoplankton communities from the California Upwelling Zone. An increase in diatom growth following 5 days of incubation was attributed to the genera Chaetoceros and Pseudo-nitzschia. Here, we show that certain bloom-forming diatoms exhibit a distinct transcriptional response that coordinates shift-up where diatoms exhibited the greatest transcriptional change following upwelling; however, comparison of co-expressed genes exposed overrepresentation of distinct sets within each of the dominant phytoplankton groups. The analysis revealed that diatoms frontload genes involved in nitrogen assimilation likely in order to outcompete other groups for available nitrogen during upwelling events. We speculate that the evolutionary success of diatoms may be due, in part, to this proactive response to frequently encountered changes in their environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".