Modeling exon expression using histone modifications.

Histones undergo numerous covalent modifications that play important roles in regulating gene expression. Previous investigations have focused on the effects of histone modifications on gene promoters, whereas efforts to unravel their effects on transcribed regions have lagged behind. To elucidate the effects of histone modification on transcribed regions, we constructed a quantitative model, which we suggest can predict the variation of gene expression more faithfully than the model constructed on promoters. Moreover, motivated by the fact that exon spicing is functionally coupled to transcription, we also devised a quantitative model to predict alternative exon expression using histone modifications on exons. This model was found to be general across different exon types and even cell types. Furthermore, an interaction network linking histone modifications to alternative exon expression was constructed using partial correlations. The network indicated that gene expression and specific histone modifications (H3K36me3 and H4K20me1) could directly influence the exon expression, while other modifications could act in an additive way to account for the stability and robustness. In addition, our results suggest that combinations of histone modifications contribute to exon splicing in a redundant and cumulative fashion. To conclude, this study provides a better understanding of the effects of histone modifications on gene transcribed regions.