Elevated Coding Mutation Rate During the Reprogramming of Human Somatic Cells into Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Mutations in human induced pluripotent stem cells (iPSCs) pose a risk for their clinical use due to preferential reprogramming of mutated founder cell and selection of mutations during maintenance of iPSCs in cell culture. It is unknown, however, if mutations in iPSCs are due to stress associated with oncogene expression during reprogramming. We performed whole exome sequencing of human foreskin fibroblasts and their derived iPSCs at two different passages. We found that in vitro passaging contributed 7% to the iPSC coding point mutation load, and ultradeep amplicon sequencing revealed that 19% of the mutations preexist as rare mutations in the parental fibroblasts suggesting that the remaining 74% of the mutations were acquired during cellular reprogramming. Simulation suggests that the mutation intensity during reprogramming is ninefold higher than the background mutation rate in culture. Thus the factor induced reprogramming stress contributes to a significant proportion of the mutation load of iPSCs.
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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 | 0.001 |
| 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) | 0.001 | 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".