title: Chromatin computation: epigenetic inheritance as a pattern reconstruction problem.
abstract: Eukaryotic histones carry a diverse set of specific chemical modifications that accumulate over the life-time of a cell and have a crucial impact on the cell state in general and the transcriptional program in particular. Replication constitutes a dramatic disruption of the chromatin states that effectively amounts to partial erasure of stored information. To preserve its epigenetic state the cell reconstructs (at least part of) the histone modifications by means of processes that are still very poorly understood. A plausible hypothesis is that the different combinations of reader and writer domains in histone-modifying enzymes implement local rewriting rules that are capable of "recomputing" the desired parental modification patterns on the basis of the partial information contained in that half of the nucleosomes that predate replication. To test whether such a mechanism is theoretically feasible, we have developed a flexible stochastic simulation system (available at http://www.bioinf.uni-leipzig.de/Software/StoChDyn) for studying the dynamics of histone modification states. The implementation is based on Gillespie's approach, i.e., it models the master equation of a detailed chemical model. It is efficient enough to use an evolutionary algorithm to find patterns across multiple cell divisions with high accuracy. We found that it is easy to evolve a system of enzymes that can maintain a particular chromatin state roughly stable, even without explicit boundary elements separating differentially modified chromatin domains. However, the success of this task depends on several previously unanticipated factors, such as the length of the initial state, the specific pattern that should be maintained, the time between replications, and chemical parameters such as enzymatic binding and dissociation rates. All these factors also influence the accumulation of errors in the wake of cell divisions.
authors.affiliation: Computational EvoDevo Group, Department of Computer Science, Universität Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany; Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany; Harvard University, Department of Human Evolutionary Biology, 11 Divinity Avenue, Cambridge, MA 02138, USA. Electronic address: achristian@bioinf.uni-leipzig.de.
authors.forename: Christian
authors.initials: C
authors.lastname: Arnold
authors.forename: Peter F
authors.initials: PF
authors.lastname: Stadler
authors.forename: Sonja J
authors.initials: SJ
authors.lastname: Prohaska
mesh_terms: D000465:Algorithms; D002843:Chromatin / Q000235:genetics*; D003198:Computer Simulation; D044127:Epigenesis, Genetic; D019143:Evolution, Molecular; D056084:Genetic Fitness; D040582:Inheritance Patterns / Q000235:genetics*; D008954:Models, Biological; D009707:Nucleosomes / Q000378:metabolism; D013269:Stochastic Processes
chemical_list: D002843:Chromatin; D009707:Nucleosomes
keywords: Chromatin complexity; Chromatin computation; Epigenetic inheritance; Evolutionary algorithm; Gillespie algorithm; Histone modifications