Evidence map›Paper›PMID 28854733›Full record

ArticleNucleic acids research2017

Cell-to-cell variability and robustness in S-phase duration from genome replication kinetics.

Qing Zhang, Federico Bassetti, Marco Gherardi, Marco Cosentino Lagomarsino

Abstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qing ZhangSorbonne Universités, UPMC Univ Paris 06, UMR 7238, Computational and Quantitative Biology, 4 Place Jussieu, Paris, France.
Federico BassettiDipartimento di Matematica, Università di Pavia, Pavia, Italy.
Marco GherardiSorbonne Universités, UPMC Univ Paris 06, UMR 7238, Computational and Quantitative Biology, 4 Place Jussieu, Paris, France.
Marco Cosentino LagomarsinoSorbonne Universités, UPMC Univ Paris 06, UMR 7238, Computational and Quantitative Biology, 4 Place Jussieu, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome replication, a key process for a cell, relies on stochastic initiation by replication origins, causing a variability of replication timing from cell to cell. While stochastic models of eukaryotic replication are widely available, the link between the key parameters and overall replication timing has not been addressed systematically. We use a combined analytical and computational approach to calculate how positions and strength of many origins lead to a given cell-to-cell variability of total duration of the replication of a large region, a chromosome or the entire genome. Specifically, the total replication timing can be framed as an extreme-value problem, since it is due to the last region that replicates in each cell. Our calculations identify two regimes based on the spread between characteristic completion times of all inter-origin regions of a genome. For widely different completion times, timing is set by the single specific region that is typically the last to replicate in all cells. Conversely, when the completion time of all regions are comparable, an extreme-value estimate shows that the cell-to-cell variability of genome replication timing has universal properties. Comparison with available data shows that the replication program of three yeast species falls in this extreme-value regime.

Indexed as

AlgorithmsModels, GeneticChromosomes, FungalComputational BiologyDNA Replication TimingGenomeKineticsReplication OriginSaccharomyces cerevisiaeSaccharomycetalesSchizosaccharomycesSpecies SpecificityS PhaseStochastic Processes

Identifiers

PMID28854733
PMCPMC5737480

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.