Microarray Analyses of Gene Expression during the Tetrahymena thermophila Life Cycle
Bibliographic record
Abstract
BACKGROUND: The model eukaryote, Tetrahymena thermophila, is the first ciliated protozoan whose genome has been sequenced, enabling genome-wide analysis of gene expression. METHODOLOGY/PRINCIPAL FINDINGS: A genome-wide microarray platform containing the predicted coding sequences (putative genes) for T. thermophila is described, validated and used to study gene expression during the three major stages of the organism's life cycle: growth, starvation and conjugation. CONCLUSIONS/SIGNIFICANCE: Of the approximately 27,000 predicted open reading frames, transcripts homologous to only approximately 5900 are not detectable in any of these life cycle stages, indicating that this single-celled organism does indeed contain a large number of functional genes. Transcripts from over 5000 predicted genes are expressed at levels >5x corrected background and 95 genes are expressed at >250x corrected background in all stages. Transcripts homologous to 91 predicted genes are specifically expressed and 155 more are highly up-regulated in growing cells, while 90 are specifically expressed and 616 are up-regulated during starvation. Strikingly, transcripts homologous to 1068 predicted genes are specifically expressed and 1753 are significantly up-regulated during conjugation. The patterns of gene expression during conjugation correlate well with the developmental stages of meiosis, nuclear differentiation and DNA elimination. The relationship between gene expression and chromosome fragmentation is analyzed. Genes encoding proteins known to interact or to function in complexes show similar expression patterns, indicating that co-ordinate expression with putative genes of known function can identify genes with related functions. New candidate genes associated with the RNAi-like process of DNA elimination and with meiosis are identified and the late stages of conjugation are shown to be characterized by specific expression of an unexpectedly large and diverse number of genes not involved in nuclear functions.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".