Evidence map›Paper›PMID 24210825›Full record

ArticleCell reports2013

High-resolution replication profiles define the stochastic nature of genome replication initiation and termination.

Michelle Hawkins, Renata Retkute, Carolin A Müller, Nazan Saner, Tomoyuki U Tanaka, Alessandro P S de Moura, Conrad A Nieduszynski

Abstract read
In one paragraph

Article in Cell reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 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

7 authors.

Michelle HawkinsCentre for Genetics and Genomics, School of Life Sciences, Queen's Medical Centre, The University of Nottingham, Nottingham NG7 2UH, UK.
Renata Retkute
Carolin A Müller
Nazan Saner
Tomoyuki U Tanaka
Alessandro P S de Moura
Conrad A Nieduszynski

Funding

Biotechnology and Biological Sciences Research Council BB/E023754/1Biotechnology and Biological Sciences Research Council BB/F00513X/1Biotechnology and Biological Sciences Research Council BB/ G001596/1Biotechnology and Biological Sciences Research Council BB/G001596/1Biotechnology and Biological Sciences Research Council BB/K007211/1Wellcome Trust 080737Wellcome Trust 081918Wellcome Trust 083524Wellcome Trust 096535Wellcome Trust 097945
6 · The paper itself

Abstract

Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.

Indexed as

Base SequenceDNA ReplicationGenome, FungalGenomic InstabilityModels, TheoreticalReplication OriginSaccharomyces cerevisiaeSequence Analysis, DNAS Phase

Identifiers

PMID24210825
PMCPMC3898788

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.