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Record W3195232910 · doi:10.1101/2021.08.23.457454

DNA Replication-transcription conflicts do not significantly contribute to spontaneous mutations due to replication errors in <i>Escherichia coli</i> .

2021· preprint· en· W3195232910 on OpenAlexfundno aff
Patricia L. Foster, Brittany A. Niccum, Heewook Lee

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersInstitute of GeneticsArmy Research OfficeMultidisciplinary University Research InitiativeNational Institutes of Health
KeywordsGeneticsBiologyGeneDNA replicationIndelPoint mutationDNA mismatch repairTranscription (linguistics)Replication timingBase pairDNAMutationDNA repairSingle-nucleotide polymorphismGenotype

Abstract

fetched live from OpenAlex

ABSTRACT Encounters between DNA replication and transcription can cause genomic disruption, particularly when the two meet head-on. Whether these conflicts produce point mutations is debated. This paper presents detailed analyses of a large collection of mutations generated during mutation accumulation experiments with mismatch-repair (MMR) defective Escherichia coli . With MMR absent, mutations are primarily due to DNA replication errors. Overall, there were no differences in the frequencies of base-pair substitutions or small indels (insertion and deletions ≤ 4 bp) in the coding sequences or promoters of genes oriented codirectionally versus head-on to replication. Among a subset of highly expressed genes there was a 2- to 3-fold bias for indels in genes oriented head-on to replication, but this difference was almost entirely due to the asymmetrical genomic locations of tRNA genes containing mononucleotide runs, which are hotspots for indels. No additional orientation bias in mutation frequencies occurred when MMR − strains were also defective for transcription-coupled repair (TCR). However, in contrast to other reports, loss of TCR slightly increased the overall mutation rate, meaning that TCR is antimutagenic. There was no orientation bias in mutation frequencies among the stress-response genes that are regulated by RpoS or induced by DNA damage. Thus, biases in the locations of mutational targets can account for most, if not all, apparent biases in mutation frequencies between genes oriented head-on versus co-directional to replication. In addition, the data revealed a strong correlation of the frequency of base-pair substitutions with gene length, but no correlation with gene expression levels. IMPORTANCE Because DNA replication and transcription occur on the same DNA template, encounters between the two machines occur frequently. When these encounters are head-to-head, genomic disruption can occur. But, whether replication-transcription conflicts contribute to spontaneous mutations is debated. Analyzing in detail a large collection of mutations generated with mismatch repair defective Escherichia coli strains, we find that across the genome there are no significant differences in mutation frequencies between genes oriented co-directionally versus head-on to replication. Among a subset of highly expressed genes there was a 2- to 3-fold bias for small insertions and deletions in head-on oriented genes, but this difference was almost entirely due to the asymmetrical locations of tRNA genes containing mononucleotide runs, which are hotspots for these mutations. Thus, biases in the positions of mutational target sequences can account for most, if not all, apparent biases in mutation frequencies between genes oriented head-on and co-directionally to replication.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.235
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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