High fidelity epigenetic inheritance: Information theoretic model predicts threshold filling of histone modifications post replication.
Nithya RamakrishnanSibi Raj B PillaiRanjith PadinhateeriPublished in: PLoS computational biology (2022)
During cell devision, maintaining the epigenetic information encoded in histone modification patterns is crucial for survival and identity of cells. The faithful inheritance of the histone marks from the parental to the daughter strands is a puzzle, given that each strand gets only half of the parental nucleosomes. Mapping DNA replication and reconstruction of modifications to equivalent problems in communication of information, we ask how well enzymes can recover the parental modifications, if they were ideal computing machines. Studying a parameter regime where realistic enzymes can function, our analysis predicts that enzymes may implement a critical threshold filling algorithm which fills unmodified regions of length at most k. This algorithm, motivated from communication theory, is derived from the maximum à posteriori probability (MAP) decoding which identifies the most probable modification sequence based on available observations. Simulations using our method produce modification patterns similar to what has been observed in recent experiments. We also show that our results can be naturally extended to explain inheritance of spatially distinct antagonistic modifications.
Keyphrases
- dna methylation
- mitochondrial dna
- genome wide
- gene expression
- machine learning
- health information
- induced apoptosis
- deep learning
- mental health
- single cell
- high resolution
- stem cells
- cell therapy
- oxidative stress
- healthcare
- signaling pathway
- cell death
- bone marrow
- mass spectrometry
- endoplasmic reticulum stress
- free survival
- social media
- mesenchymal stem cells
- pi k akt