Comprehensive analysis of meiosis-derived cDNA libraries reveals gene isoforms and mitochondrial proteins important for competitive fitness
Bibliographic record
Abstract
ABSTRACT Gametogenesis is a highly regulated and dynamic developmental program where a diploid progenitor cell differentiates into haploid gametes, the precursors for sexual reproduction. During meiosis, several pathways converge to initiate ploidy reduction and organelle remodelling to render gametes competent for zygote formation and subsequent organismal development. Additionally, meiosis inherently rejuvenates the newly formed gametes resulting in lifespan resetting. Here, we construct five stage-specific, inducible meiotic cDNA libraries that represent over 84% of the yeast genome. We employ computational strategies to detect stage-specific meiotic transcript isoforms in each library and develop a robust screening pipeline to test the effect of each cDNA on competitive fitness. Our multi-day proof-of-principle time course reveals gene isoforms that are important for competitive fitness as well as mitochondrial proteins that cause dose-dependent disruption of respiration. Together, these novel meiotic cDNA libraries provide an important resource for systematically studying meiotic genes and gene isoforms in future studies. HIGHLIGHTS Construction of five stage-specific, inducible meiotic cDNA libraries in budding yeast that collectively represent 5563 genes, which is over 84% of the genome Analysis of the cDNA libraries reveal the presence of meiosis-specific transcript isoforms that are largely uncharacterized Development of a robust gain-of-function screening pipeline identifies previously characterized genes and novel gene isoforms important for competitive fitness Multi-day proof-of-principle screen reveals mitochondrial proteins that cause dosage-specific respiration defects
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".