Dissecting Mechanisms of Epigenetic Memory Through Computational Modeling

被引:1
作者
Briffa, Amy [1 ,2 ]
Menon, Govind [1 ]
Miangolarra, Ander Movilla [1 ]
Howard, Martin [1 ]
机构
[1] John Innes Ctr, Dept Computat & Syst Biol, Res Pk, Norwich, England
[2] Babraham Inst, Epigenet Programme, Cambridge, England
基金
英国生物技术与生命科学研究理事会; 欧洲研究理事会; 英国工程与自然科学研究理事会;
关键词
epigenetic memory; computational modeling; gene regulatory networks; DNA methylation dynamics; histone modifications; stochastic simulations; DNA METHYLATION; TRANSPOSABLE ELEMENTS; HISTONE METHYLATION; DYNAMICS; CONSERVATION; INHERITANCE; GENOME; COLD;
D O I
10.1146/annurev-arplant-070523-041445
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Understanding the mechanistic basis of epigenetic memory has proven to be a difficult task due to the underlying complexity of the systems involved in its establishment and maintenance. Here, we review the role of computational modeling in helping to unlock this complexity, allowing the dissection of intricate feedback dynamics. We focus on three forms of epigenetic memory encoded in gene regulatory networks, DNA methylation, and histone modifications and discuss the important advantages offered by plant systems in their dissection. We summarize the main modeling approaches involved and highlight the principal conceptual advances that the modeling has enabled through iterative cycles of predictive modeling and experiments. Lastly, we discuss remaining gaps in our understanding and how intertwined theory and experimental approaches might help in their resolution.
引用
收藏
页码:265 / 290
页数:26
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