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We develop machine learning approaches to predict context specific enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. Occupancy of estrogen receptor alpha (ER-alpha), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. Two Bayesian classifiers were developed, unsupervised and supervised. The supervised approach uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features and predicts interactions. The method was trained using experimentally determined interactions from the same system and achieves much higher precision than predictions based on the genomic proximity of nearest ER-alpha binding. We use the method to identify a confident set of ER-alpha target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data shows our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ER-alpha binding proximity alone. Accuracy of the predictions from the supervised model was compared against the second more complex unsupervised generative approach which uses proximity-based prior and temporal binding patterns at enhancers and promoters to infer protein-mediated regulatory complexes involving individual genes and their networks of multiple distant regulatory enhancers.

Chromatin insulators are short DNA sequences that, together with enhancers and silencers, orchestrate gene transcription through DNA-protein interactions in eukaryotic genomes. It has been proposed that insulators operate at the chromatin level by generating functionally independent higher-order chromatin domains. Insulators may maintain the integrity of such domains using two properties: blocking enhancer-promoter interactions and blocking heterochromatin spreading. The gypsy insulator of Drosophila was identified as a region of the gypsy retrovirus responsible for the production of tissue-specific mutations in many genes. The Suppressor of Hairy wing [Su(Hw)] protein contains 12 zinc fingers that specifically bind the gypsy insulator. Upon DNA binding, Su(Hw) recruits a second protein, Modifier of Mdg4 67.2 [Mod(mdg4) 67.2], and the interaction of both proteins is required for insulator function in vivo. We have found that three different arrays of gypsy retrovirus insertions in a yellow transgene result in unique yellow phenotypes, showing that the enhancer-blocking activity of the Drosophila gypsy insulators depends on the relative orientation of the gypsy retroviruses on the chromosome. We also observed from transgenic lines with gypsy retrovirus or insulator insertions that interaction of insulators may be regulated by active enhancers according to the relative positions of the insulators flanking the enhancers. Moreover, we show that gypsy insulators can positively modulate yellow activation and result in wild-type levels of expression when placed upstream of enhancers in yellow transgenes in which enhancers are placed out of context by &#:-DNA spacers and fail to reproduce the expression levels of yellow in wings and body cuticle. Our results provide evidence indicating that this phenomenon is independent of the boundary activity. Genetic analysis using mod(mdg4)67.2 mutant lines containing gypsy retrovirus insertions revealed that the gypsy insulator may be placed close to the yellow promoter region and be intimately involved in transcriptional activation and repression. Therefore, we suggest that insulators may also function by mediating long range interactions between enhancers and promoters.