| Transcriptional regulation is a critical mediator of many normal cellular processes as well as disease progression. It involves a process by which different transcription factors bind to specific short DNA sequences termed cis-regulatory elements (CREs), such as promoters, enhancers, silencers and insulators, and thus control the transcription of different genes. Here we discuss both experimental and computational challenges in profiling Transcription Factor Binding Sites (TFBSs) using ChIP-based high throughput techniques. We then describe a method (w-ChIPeaks) for identifying TFBSs using such techniques.;The accessibility of CREs is often influenced by epigenetic modifications including DNA methylation, histone acetylation and methylation, which can be associated with the activation or repression of genes. Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. We generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to estimate the methylation level of individual CpG dinucleotides. Clonal bisulfite sequencing results showed that the methylation status of tested regions was accurately detected with high resolution using the proposed model. Using the predicated methylation score, genome wide analysis showed medium negative correlation between DNA methylation and DNase hypersensitivity, which is an indication of nucleosome depletion.;Transcription factors (TFs) often co-localize at CREs, form protein complexes, and collaboratively regulate gene expression. Machine learning and Bayesian approaches have been used to identify TF modules in a one-dimensional context. However, recent studies using high-throughput technologies have shown that TF interactions should also be considered in three-dimensional nuclear space. Taking K562 as a model cell line, we have analyzed publicly available Hi-C data, which enables genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model and a power-law decay background to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C results, including DNase-seq data and ChIP-seq data for 45 transcription factors and 9 histone modifications. Different interacting loci display distinct epigenetic status and relationships with TFBSs. As expected, many of the transcription factors show binding patterns specific to interacting loci that encompass promoters or enhancers. This work indicates that protein-protein interactions may serve as a driving force of chromatin dynamic reorganization. |
