Differential contribution to gene expression prediction of histone modifications at enhancers or promoters

The ChIP-seq signal of histone modifications at promoters is a good predictor of gene expression in different cellular contexts, but whether this is also true at enhancers is not clear. To address this issue, we develop quantitative models to characterize the relationship of gene expression with histone modifications at enhancers or promoters. We use embryonic stem cells (ESCs), which contain a full spectrum of active and repressed (poised) enhancers, to train predictive models. As many poised enhancers in ESCs switch towards an active state during differentiation, predictive models can also be trained on poised enhancers throughout differentiation and in development. Remarkably, we determine that histone modifications at enhancers, as well as promoters, are predictive of gene expression in ESCs and throughout differentiation and development. Importantly, we demonstrate that their contribution to the predictive models varies depending on their location in enhancers or promoters. Moreover, we use a local regression (LOESS) to normalize sequencing data from different sources, which allows us to apply predictive models trained in a specific cellular context to a different one. We conclude that the relationship between gene expression and histone modifications at enhancers is universal and different from promoters. Our study provides new insight into how histone modifications relate to gene expression based on their location in enhancers or promoters.Author summary: Gene expression can be properly predicted by the ChIP-seq signal of histone modifications at promoters, but whether this is also true at enhancers is unclear. In this study we develop predictive models of gene expression that demonstrate the predictive power of histone modifications at enhancers in the context of mouse embryonic stem cells, during differentiation, and in animal development. Moreover, by assessing the contribution of each histone modification, we found that enhancer predictive models and promoter predictive models have different histone modification requirement. Therefore, different histone modifications relate better to enhancer or promoter function(s). Finally, by applying predictive models trained in a specific cellular context to a different one, we concluded that the relationship between gene expression and histone modifications at enhancers is universal.