High fidelity epigenetic inheritance: Information theoretic model predicts $k$-threshold filling of histone modifications post replication
Beyond the genetic code, there is another layer of information encoded as chemical modifications on histone proteins positioned along the DNA. Maintaining these modifications is crucial for survival and identity of cells. How the information encoded in the histone marks gets inherited, given that only half the parental nucleosomes are transferred to each daughter chromatin, is a puzzle. We address this problem using ideas from Information theory and understanding from recent biological experiments. Mapping the replication and reconstruction of modifications to equivalent problems in communication, we ask how well an enzyme-machinery can recover information, if they were ideal computing machines. Studying a parameter regime where realistic enzymes can function, our analysis predicts that, pragmatically, enzymes may implement a threshold$-k$ filling algorithm which derives from maximum \`a posteriori probability decoding. Simulations using our method produce modification patterns similar to what is observed in recent experiments.
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