Comparative Genomics of <i>Chloropicon primus</i> and <i>Chloropicon roscoffensis</i> Provide Insights into the Evolutionary Dynamics and Ecological Success of These Tiny Green Algae in Marine Environments
Bibliographic record
Abstract
The tiny green algae belonging to the class Chloropicophyceae play a key role in marine phytoplankton communities, especially in moderately oligotrophic water; yet, little is known about their biology, lifestyles, and what allows them to thrive in various oceanic environments. A single representative of this class (Chloropicon primus), comprising eight recognized species, has been previously subjected to genome analysis. To gain insight into the evolutionary changes that occurred during speciation in the Chloropicon genus and better understand the genes that distinguish Chloropicon species from other green algae traditionally designated as prasinophytes, we sequenced the genome of a second strain of C. primus and those of three strains of the closely related Chloropicon roscoffensis, the latter species representing the most dominant Chloropicon lineage in oceans. Our analyses highlighted substantial interspecific variations, including differences in chromosome number, gene content, gene arrangement, and ploidy state. Both C. primus genomes were predominantly diploid, while the C. roscoffensis genomes were either haploid or diploid. Specific proteins were identified for each species. Chloropicon roscoffensis possesses a biochemical C4-like inorganic carbon concentrating mechanism that potentially enables recycling of mitochondrial CO2 derived from photorespiration and respiration for carbon fixation in the chloroplast. In addition, it features specific proteins linked to the central carbon metabolism that suggest better coping mechanisms for abiotic stresses compared to C. primus. We also uncovered a previously undescribed eukaryotic recycling pathway for the micronutrient queuosine, a hypermodified nucleoside that is essential for post-transcriptional modification of several tRNAs at their anticodon wobble position.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".