Nonclassical Regulation of Transcription: Interchromosomal Interactions at the <i>Malic enzyme</i> Locus of <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Regulation of transcription can be a complex process in which many cis- and trans-interactions determine the final pattern of expression. Among these interactions are trans-interactions mediated by the pairing of homologous chromosomes. These trans-effects are wide ranging, affecting gene regulation in many species and creating complex possibilities in gene regulation. Here we describe a novel case of trans-interaction between alleles of the Malic enzyme (Men) locus in Drosophila melanogaster that results in allele-specific, non-additive gene expression. Using both empirical biochemical and predictive bioinformatic approaches, we show that the regulatory elements of one allele are capable of interacting in trans with, and modifying the expression of, the second allele. Furthermore, we show that nonlocal factors--different genetic backgrounds--are capable of significant interactions with individual Men alleles, suggesting that these trans-effects can be modified by both locally and distantly acting elements. In sum, these results emphasize the complexity of gene regulation and the need to understand both small- and large-scale interactions as more complete models of the role of trans-interactions in gene regulation are developed.
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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) | 0.002 | 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".