CHIME: Multimodal Prediction of Histone Modification Profiles across Adult Mouse Brain Cell Types

Comprehensive profiling of histone modifications across the adult mouse brain remains experimentally costly. A recent integrative single-cell epigenomic atlas profiles over 2.5 million nuclei yet covers only nine brain regions, leaving the cerebellum, olfactory bulb, and additional midbrain areas unprofiled. Completing histone modification maps therefore requires predicting active and repressive chromatin features for cell types lacking histone measurements. We introduce CHIME, which integrates chromatin accessibility, DNA methylation, RNA expression, and DNA sequence features to predict four continuous histone modification signals at 200-bp resolution. CHIME leverages a distance-aware representation to integrate local and broader genomic context, paired with a position-preserving decoder that predicts cell-type-specific deviations from a shared histone profile. Evaluated via five-fold cross-validation across 118 cell types with test targets completely withheld, CHIME achieves a mean positional correlation of 0.737 and surpasses all evaluated baselines on every metric across all folds. Matched removals show complementary contributions from chromatin accessibility, DNA methylation, and gene expression. With reference profiles from training cell types available on each chromosome, models trained on chromosome 19 transfer without parameter updates to 18 additional autosomes, achieving a mean correlation across genomic positions of 0.734. These results support computational extension of brain epigenetic maps to cell populations lacking histone measurements.