Duplex sequencing identifies unique characteristics of ENU-induced mutations in male mouse germ cells
Bibliographic record
Abstract
Germ cell mutagenicity testing is increasingly required for chemical risk assessment. Duplex sequencing is rapidly gaining acceptance as a method to assess in vivo mutagenesis, and as a valid alternative to transgenic rodent mutation models such as the MutaMouse. We used a duplex sequencing panel of 20 genomic targets and the transgenic rodent assay to measure mutations in the germ cells of MutaMouse males exposed to 0, 1, 2, or 5 mg/kg N-ethyl-N-nitrosourea for 28 days. Germ cells from the seminiferous tubules were collected 28 days post-exposure. The transgenic rodent assay showed a significant increase in mutant frequencies at the high (P < 0.001) and medium (P = 0.01) N-ethyl-N-nitrosourea doses relative to controls, while duplex sequencing revealed a significant increase (P < 0.001) in N-ethyl-N-nitrosourea-induced mutations only at the high dose. Duplex sequencing mutation frequencies were lower in genic than in intergenic targets, suggesting a protective role for transcription-coupled repair. Interestingly, we observed several unique germ cell characteristics with respect to duplex sequencing data from rodent somatic tissues: 1) larger inter-animal variability in clonally expanded mutations that affects the ability to detect significant increases in mutation frequency; 2) a target on chromosome 2 showing much higher susceptibility to spontaneous and chemical-induced mutagenesis than other targets; and 3) a mutation spectrum consistent with that observed in the offspring of N-ethyl-N-nitrosourea-treated males but not with the spectrum in bone marrow of directly-exposed males. These results suggest that duplex sequencing is a promising approach for characterizing germ cell mutagenesis and that mutagenic mechanisms operating in germ cells differ from those in somatic tissues.
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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".