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Record W2029091203 · doi:10.1073/pnas.0610902104

Evidence for mutation showers

2007· article· en· W2029091203 on OpenAlexaff
Jicheng Wang, Kelly Gonzalez, William A. Scaringe, Kimberly Tsai, Ning Liu, Dongqing Gu, Wenyan Li, Kathleen A. Hill, Steve S. Sommer

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsWestern University
FundersNational Institute on AgingNational Institutes of Health
KeywordsMutationMutantLac repressorGeneticsBiologyMutation rateMutation frequencyContext (archaeology)MutagenesisMolecular biologyGenePlasmidlac operon

Abstract

fetched live from OpenAlex

Mutants in the Big Blue transgenic mouse system show spontaneous clustered multiple mutations with unexpectedly high frequency, consistent with chronocoordinate events. We tested the prediction that the multiple mutations seen within the lacI mutation target sometimes occur in the context of chronocoordinate multiple mutations spanning multiple kilobases (mutation showers). Additional sequencing of mutants was performed in regions immediately flanking the lacI region (total of 10.7 kb). Nineteen additional mutations were found outside the lacI region ("ectomutations") from 10 mutants containing two or more lacI mutations, whereas only one ectomutation was found in 130 mutants with a single mutation (P < 0.0001). The mutation showers had an average of approximately one mutation per 3 kb. Four mutants showed closely spaced double mutations in the new sequence, and analysis of the spacing between these mutations revealed significant clustering (P = 0.0098). To determine the extent of the mutation showers, regions (8.5 kb total) remote from the lacI region (approximately 16-17 kb away) were sequenced. Only two additional ectomutations were found in these remote regions, consistent with mutation showers that generally do not extend more than approximately 30 kb. We conclude that mutation showers exist and that they constitute at least 0.2% and possibly 1% or more of mutational events observed in this system. The existence of mutation showers has implications for oncogenesis and evolution, raising the possibilities of "cancer in an instant" and "introns as sponges to reduce the deleterious impact of mutation showers."

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.148

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.068
GPT teacher head0.357
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2007
Admission routes1
Has abstractyes

Explore more

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