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Record W4296792091 · doi:10.1093/genetics/iyac144

Intrinsic base substitution patterns in diverse species reveal links to cancer and metabolism

2022· article· en· W4296792091 on OpenAlexafffund
Suzana P. Gelova, Kassidy N. Doherty, Salma Alasmar, Kin Chan

Bibliographic record

VenueGenetics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsBiologyGeneticsMutagenesisSaccharomyces cerevisiaeMutationGeneComputational biologyNucleotideEvolutionary biology

Abstract

fetched live from OpenAlex

Analyses of large-scale cancer sequencing data have revealed that mutagenic processes can create distinctive patterns of base substitutions, called mutational signatures. Interestingly, mutational patterns resembling some of these signatures can also be observed in normal cells. To determine whether similar patterns exist more generally, we analyzed large data sets of genetic variation, including mutations from 7 model species and single nucleotide polymorphisms in 42 species, totaling >1.9 billion variants. We found that base substitution patterns for most species closely match single base substitution (SBS) mutational signature 5 in the Catalog of Somatic Mutations in Cancer (COSMIC) database. SBS5 is ubiquitous in cancers and also present in normal human cells, suggesting that similar patterns of genetic variation across so many species are likely due to conserved biochemistry. We investigated the mechanistic origins of the SBS5-like mutational pattern in Saccharomyces cerevisiae, and show that translesion DNA synthesis and sugar metabolism are directly linked to this form of mutagenesis. We propose that conserved metabolic processes in cells are coupled to continuous generation of genetic variants, which can be acted upon by selection to drive the evolution of biological entities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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 designObservational
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

Citations16
Published2022
Admission routes2
Has abstractyes

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