Natural selection in a population of Drosophila melanogaster explained by changes in gene expression caused by sequence variation in core promoter regions
Bibliographic record
Abstract
BACKGROUND: Understanding the evolutionary forces that influence variation in gene regulatory regions in natural populations is an important challenge for evolutionary biology because natural selection for such variations could promote adaptive phenotypic evolution. Recently, whole-genome sequence analyses have identified regulatory regions subject to natural selection. However, these studies could not identify the relationship between sequence variation in the detected regions and change in gene expression levels. We analyzed sequence variations in core promoter regions, which are critical regions for gene regulation in higher eukaryotes, in a natural population of Drosophila melanogaster, and identified core promoter sequence variations associated with differences in gene expression levels subjected to natural selection. RESULTS: Among the core promoter regions whose sequence variation could change transcription factor binding sites and explain differences in expression levels, three core promoter regions were detected as candidates associated with purifying selection or selective sweep and seven as candidates associated with balancing selection, excluding the possibility of linkage between these regions and core promoter regions. CHKov1, which confers resistance to the sigma virus and related insecticides, was identified as core promoter regions that has been subject to selective sweep, although it could not be denied that selection for variation in core promoter regions was due to linked single nucleotide polymorphisms in the regulatory region outside core promoter regions. Nucleotide changes in core promoter regions of CHKov1 caused the loss of two basal transcription factor binding sites and acquisition of one transcription factor binding site, resulting in decreased gene expression levels. Of nine core promoter regions regions associated with balancing selection, brat, and CG9044 are associated with neuromuscular junction development, and Nmda1 are associated with learning, behavioral plasticity, and memory. Diversity of neural and behavioral traits may have been maintained by balancing selection. CONCLUSIONS: Our results revealed the evolutionary process occurring by natural selection for differences in gene expression levels caused by sequence variation in core promoter regions in a natural population. The sequences of core promoter regions were diverse even within the population, possibly providing a source for natural selection.
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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".