Testing the Mutation Accumulation Theory of Aging through Epistasis in Drosophila
Bibliographic record
Abstract
The mutation accumulation (MA) theory of aging stands today as one of the leading theories of senescence, or age-related physiological decline, in the fields of evolutionary biology and gerontology. This theory postulates that senescence is the result of mutations with late-age effects accumulating relatively unchecked by selection over evolutionary time. This is the result of the force of natural selection primarily acting during the reproductive period of an organism's life. Epistasis is a term referring to the biological phenomenon describing the complex and non-additive interactions mutations can have depending on their genetic background. The original theory of epistasis predicts additive interactions among mutations affecting aging within the genome. However, recent theoretical work suggests non-additive interactions can occur between accumulated mutations impacting aging. The current literature displaying non-additive epistatic interactions on aging is limited, mainly due to the inability to experimentally assess this theory. The invertebrate model organism, Drosophila melanogaster, is ideal for examining mutation accumulation because of its short generation time, well-mapped genome, and ability to maintain controlled breeding lines over many generations. Using lines of D.melanogaster we aim to examine the effects of MA as potential evidence of non-additive epistasis and its role in aging. Through our MA protocol, we have accumulated mutations on the D.melanogaster genome for 30 successive generations. Sex- and age-specific impacts of accumulated autosomal mutations will be assessed by measuring reproductive fitness at both early and late-age across various combinations of these mutations in both males and females. The results of this project will offer key experimental insights to refine the MA model through the exploration of epistasis, as well as age- and sex-specificity, ultimately advancing the understanding of the evolutionary biology of aging.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".