MétaCan
Menu
← Back to cohort
Record W4404050293 · doi:10.1101/2024.11.01.621594

Modelling DNA replication fork stability and collapse using chromatin fiber analysis and the R-ODD-BLOBS program

2024· preprint· en· W4404050293 on OpenAlexafffund
Kazeera Aliar, Roozbeh Manshaei, Susan L. Forsburg, Ali Mazalek, Sarah Sabatinos

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFork (system call)Replication (statistics)ChromatinStability (learning theory)Computer scienceDNA replicationDNABiologyPhysicsGeneticsVirologyOperating system

Abstract

fetched live from OpenAlex

ABSTRACT We describe the anatomy of replication forks by comparing the lengths of synthesized BrdU-labelled DNA in wild type, mrc1Δ and cds1Δ Schizoasaccharomyces pombe . We correlated Rad51 and Cdc45 proteins relative to their positions on the fork, replicated tract, or unreplicated regions. We did this by using chromatin fiber images. These fibers track pixel intensity data, which is analyzed using our program: R-ODD-BLOBS. We compared the lengths of BrdU tracts and proteins, as well as the percentage of Rad51 and Cdc45 colocalization, and compared our results with literature findings. We measured average BrdU lengths consistent with current literature; cds1Δ was the longest at ∼2.9 kb (8.6 pixels, px), wild type was ∼ 2.5 kb (7.5 px), and mrc1Δ was the shortest at ∼1.7 kb (5.1 px). Intriguingly, Rad51 was found at 22% more replicated areas in mrc1Δ than in wild type. This suggests that homologous recombination repair may be more common at mrc1Δ forks. In this study, we summarize the usefulness of a computational modeling tool to assess large datasets of chromatin spread data. In turn, we find patterns of DNA replication length and protein components at replication forks, to describe the anatomy of a fork and how structures change with checkpoint loss. Abstract Figure GRAPHICAL ABSTRACT: R-ODD-BLOBS uses chromatin fiber data to rigorously model replication fork structures. DNA replication forks are multi-subunit structures that must pair and regulate DNA copying activity of the polymerases with unwinding activity of helicase. Chromatin fiber data retains proteins, and can be used to detect DNA synthesis (blue) and associated DNA replication fork proteins such as MCM4 helicase (MCM4) and replication protein A (RPA). In our work, we have used homologous recombination protein Rad51 and helicase factor Cdc45 to understand how DNA replication fork structures are destabilized during hydroxyurea treatment, and how they fail to recover because of Cdc45/helicase mis-localization.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.243
Teacher spread0.226 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicDNA Repair Mechanisms→French-language works237,207→