Positive Selection within a Diatom Species Acts on Putative Protein Interactions and Transcriptional Regulation
Bibliographic record
Abstract
Diatoms are the most species-rich group of microalgae, and their contribution to marine primary production is important on a global scale. Diatoms can form dense blooms through rapid asexual reproduction; mutations acquired and propagated during blooms likely provide the genetic, and thus phenotypic, variability upon which natural selection may act. Positive selection was tested using genome and transcriptome-wide pair-wise comparisons of homologs in three genera of diatoms (Pseudo-nitzschia, Ditylum, and Thalassiosira) that represent decreasing phylogenetic distances. The signal of positive selection was greatest between two strains of Thalassiosira pseudonana. Further testing among seven strains of T. pseudonana yielded 809 candidate genes of positive selection, which are 7% of the protein-coding genes. Orphan genes and genes encoding protein-binding domains and transcriptional regulators were enriched within the set of positively selected genes relative to the genome as a whole. Positively selected genes were linked to the potential selective pressures of nutrient limitation and sea surface temperature based on analysis of gene expression profiles and identification of positively selected genes in subsets of strains from locations with similar environmental conditions. The identification of positively selected genes presents an opportunity to test new hypotheses in natural populations and the laboratory that integrate selected genotypes in T. pseudonana with their associated phenotypes and selective forces.
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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) | 0.000 | 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 teacher head, 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".