论文标题
高保真表观遗传遗传：信息理论模型预测复制后组蛋白修饰的$ k $阈值填充
High fidelity epigenetic inheritance: Information theoretic model predicts $k$-threshold filling of histone modifications post replication
论文作者
论文摘要
除了遗传密码之外，还有另一层信息编码为对沿着DNA的组蛋白的化学修饰。维持这些修饰对于细胞的存活和身份至关重要。鉴于只有一半的亲本核小体被转移到每个女儿染色质的一半是一个难题，因此在组蛋白标记中编码的信息是如何遗传的。我们使用信息理论和最新生物学实验的理解中的思想解决了这个问题。将修改的复制和重建映射到交流中的等效问题时，我们询问酶计算机如何恢复信息，如果它们是理想的计算机。我们的分析研究了现实酶可以起作用的参数状态，务实地预测，酶可以实现阈值$ -K填充算法，该算法源自最大后验概率解码。使用我们的方法的仿真产生的修饰模式类似于最近实验中观察到的。
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 à posteriori probability decoding. Simulations using our method produce modification patterns similar to what is observed in recent experiments.
