Inducible chromosomal rearrangement reveals nonlinear polygenic dosage effects in driving aneuploid yeast traits
Bibliographic record
Abstract
Aneuploidy induces chromosomal scale alterations in gene dosage, impacting organismal proliferation yet serving as a driver for adaptive evolution. The complexity of gene dosage effects makes it challenging to elucidate the causal genetic basis of aneuploid consequence. Here, using loss-of-function screening with Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) in synthetic aneuploid yeast, in conjunction with gain-of-function testing in euploid yeast, we established a sufficient and necessary framework and discovered cases of nonlinear polygenic dosage effects in driving aneuploid phenotypes. We identified an emergent effect resulting from copy number alterations in a locus of five genes, which enhance trehalose biosynthesis and confer heat tolerance in aneuploid yeast with additional chromosome III. Additionally, a gene dosage-dependent antagonistic epistasis effect of two genes YCL039W and YCL037C determines rapamycin resistance in aneuploid yeast by regulating the Ras signaling pathway. Moreover, several cases of sufficiency-necessity asymmetries were found for other aneuploid traits. Together, our findings provide direct evidence of various dosage-dependent nonlinear polygenic interactions in shaping aneuploid phenotypes and advance understanding of the genetic basis of cellular adaptive evolution. Elucidating the genetic basis of aneuploid phenotypes has posed a challenge. Here, the authors use loss-of-function screening in synthetic aneuploid yeast and gain-of-function testing in euploid yeast to identify various dosage-dependent nonlinear polygenic interactions driving aneuploid traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".