Evidence map›Paper›PMID 39556945›Full record

ArticlePhysical biology2024

Theory of epigenetic switching due to stochastic histone mark loss during DNA replication.

Ander Movilla Miangolarra, Martin Howard

Abstract read
In one paragraph

Article in Physical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Consensus Formation and Change are Enhanced by Neutrality.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. Review
  5. A Model of Epigenetic Inheritance Accounts for Unexpected Adaptation to Unforeseen Challenges.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  6. Review
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

2 authors.

Ander Movilla MiangolarraDepartment of Computational and Systems Biology, John Innes Centre, Norwich NR4 7UH, United Kingdom.ORCID 0000-0002-1064-7647
Martin HowardDepartment of Computational and Systems Biology, John Innes Centre, Norwich NR4 7UH, United Kingdom.

Funding

BBSRC BB/P013511/1Wellcome Trust
6 · The paper itself

Abstract

How much information does a cell inherit from its ancestors beyond its genetic sequence? What are the epigenetic mechanisms that allow this? Despite the rise in available epigenetic data, how such information is inherited through the cell cycle is still not fully understood. Often, epigenetic marks can display bistable behaviour and their bistable state is transmitted to daughter cells through the cell cycle, providing the cell with a form of memory. However, loss-of-memory events also take place, where a daughter cell switches epigenetic state (with respect to the mother cell). Here, we develop a framework to compute these epigenetic switching rates, for the case when they are driven by DNA replication, i.e. the frequency of loss-of-memory events due to replication. We consider the dynamics of histone modifications during the cell cycle deterministically, except at DNA replication, where nucleosomes are randomly distributed between the two daughter DNA strands, which is therefore implemented stochastically. This hybrid stochastic-deterministic approach enables an analytic derivation of the replication-driven switching rate. While retaining great simplicity, this framework can explain experimental switching rate data, establishing its biological importance as a framework to quantitatively study epigenetic inheritance.

Indexed as

DNA ReplicationEpigenesis, GeneticStochastic ProcessesCell CycleHistone CodeHistonesModels, GeneticNucleosomesHistonesNucleosomesepigenetic inheritancemathematical modellingsystems biology

Identifiers

PMID39556945
PMCPMC11605279

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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.