Legarreta, L. | Search bioRxiv

bioRxiv2026

Quantifying the Information Capacity of DNA Methylation as an Epigenetic Memory System

The information content of the genome has been extensively analyzed. However, a comparable quantitative framework for DNA methylation is still lacking. Without such quantification, the magnitude of this regulatory and dynamic epigenetic structure remains conceptually imprecise, even though methylation dysregulation is strongly linked to disease-related phenotypes and altered cellular identity. Here we address this gap by applying Shannon information theory to DNA methylation. We first consider methylation marks as binary or probabilistic regulatory states and estimate the theoretical upper-bound information capacity of the human methylome under simplifying assumptions. We then progressively refine this estimate by incorporating biologically relevant constraints, including methylation bias, bimodal methylation distributions, local CpG correlation, genomic regulatory class, and cell-type-discriminative methylation patterns. This approach allows us to distinguish between theoretical methylation capacity, statistical methylation entropy, and biologically interpretable regulatory information. Finally, we consider methylation information from a discriminative perspective, analyzing its contribution to distinguishing cell types and regulatory cellular states. Within this framework, mutual information between methylation patterns and cell identity provides a biologically constrained estimate of methylations role as an epigenetic identity code. Our layered analysis reconciles megabit-scale methylome capacity with compact, biologically interpretable identity signatures. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/735086v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@44dc66org.highwire.dtl.DTLVardef@e1ba03org.highwire.dtl.DTLVardef@17b2acborg.highwire.dtl.DTLVardef@136b1ae_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2026

Multi-timescale PTM architecture in human RNA polymerase II

Human RNA Polymerase II (Pol II) is characterized by a dense layer of over 775 post-translational modifications (PTMs) that form a dynamic, rewritable regulatory architecture integrating large numbers of cellular signals to coordinate transcription initiation, elongation, termination, and co-transcriptional RNA processing. While genomic information has been extensively catalogued, the potential information capacity associated with Pol II PTM patterns has remained largely unquantified. Here, we analyze the PTM sites across the human Pol II complex (Rpb1-Rpb12) and estimate the state-space information capacity using Shannon entropy theory. We first provide a theoretical upper bound of ~707.98 bits per Pol II molecule (~88.50 bytes) corresponding to ~5.68 x 107 bits per nucleus (~7.10 MB), assuming ~80,200 Pol II molecules per cell. We distinguish this maximal capacity from a conservative, kinetically addressable estimate of ~114.88 bits per molecule (~1.15 MB per nucleus), reflecting physiological kinetic constraints and site coupling that restrict the simultaneously addressable PTM state space in vivo. Finally, we show that major PTM classes (phosphorylation, proline isomerization, O-GlcNAcylation and ubiquitination) operate over distinct lifetimes, from seconds to minutes and hours-scale processes, supporting a multi-timescale biochemical architecture of this enzyme. Together, these results provide a quantitative information framework that distinguishes maximal PTM state-space capacity from kinetically addressable physiological regulatory capacity, supporting a view of Pol II PTM patterning as a high-dimensional, dynamically reconfigurable, multi-timescale regulatory information layer. HighlightsA systems-level framework quantifies regulatory information in Pol II PTMs Known PTM modification sites provide 707.98 bits per Pol II as a regulatory upper bound Physiological kinetic constraints reduce accessible regulatory capacity to 114.88 bits Distinct PTM modification classes define fast, intermediate, and slow regulatory layers Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/734958v1_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@1101c1borg.highwire.dtl.DTLVardef@a551fcorg.highwire.dtl.DTLVardef@1a97bd3org.highwire.dtl.DTLVardef@68db_HPS_FORMAT_FIGEXP M_FIG C_FIG

Systems Biology↗