Genome-wide analysis of transcription factor E2F1 mutant proteins reveals that N- and C-terminal protein interaction domains do not participate in targeting E2F1 to the human genome.

Previous studies of E2F family members have suggested that protein-protein interactions may be the mechanism by which E2F proteins are recruited to specific genomic regions. We have addressed this hypothesis on a genome-wide scale using ChIP-seq analysis of MCF7 cell lines that express tagged wild type and mutant E2F1 proteins. First, we performed ChIP-seq for tagged WT E2F1. Then, we analyzed E2F1 proteins that lacked the N-terminal SP1 and cyclin A binding domains, the C-terminal transactivation and pocket protein binding domains, and the internal marked box domain. Surprisingly, we found that the ChIP-seq patterns of the mutant proteins were identical to that of WT E2F1. However, mutation of the DNA binding domain abrogated all E2F1 binding to the genome. These results suggested that the interaction between the E2F1 DNA binding domain and a consensus motif may be the primary determinant of E2F1 recruitment. To address this possibility, we analyzed the in vivo binding sites for the in vitro-derived consensus E2F1 motif (TTTSSCGC) and also performed de novo motif analysis. We found that only 12% of the ChIP-seq peaks contained the TTTSSCGC motif. De novo motif analysis indicated that most of the in vivo sites lacked the 5' half of the in vitro-derived consensus, having instead the in vivo consensus of CGCGC. In summary, our findings do not provide support for the model that protein-protein interactions are involved in recruiting E2F1 to the genome, but rather suggest that recognition of a motif found at most human promoters is the critical determinant.

High resolution detection and analysis of CpG dinucleotides methylation using MBD-Seq technology.

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution.