The Genetic Basis of Natural Variation in Algal Neutral Lipid Accumulation
Bibliographic record
Abstract
Neutral lipids are known to be involved in an algal adaptation to cold, light, and nutrient stress, but the extent of intraspecific variation and the mechanisms maintaining the variation in this economically important trait are unclear. I predict algal strains from different latitudes will vary in neutral lipid accumulation because many of the stressor associate with climate. Inducing neutral lipid accumulation using nitrogen (N) starvation in 26 natural isolates of Chlamydomonas reinhardtii revealed genetic variation but no latitudinal pattern in neutral lipid accumulation. A further experiment demonstrated latitudinal variation in neutral lipid accumulation induced by cold shock and light deprivation. By analyzing molecular evolution of 473 lipid-candidate genes, I inferred stronger purifying selection and higher rates of positive selection driving genetic divergence in the lipid-associated genes. From this, I suggest the possibility that neutral lipid accumulation is an adaptive trait in C. reinhardtii under positive selection.
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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 | 0.000 | 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) | 0.001 | 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".