Suresh Cuddapah

Insulators are DNA elements that prevent inappropriate interactions between the neighboring regions of the genome. They can be functionally classified as either enhancer blockers or domain barriers. CTCF (CCCTC-binding factor) is the only known major insulator-binding protein in the vertebrates and has been shown to bind many enhancer-blocking elements. However, it is not clear whether it plays a role in chromatin domain barriers between active and repressive domains. Here, we used ChIP-seq to map the genome-wide binding sites of CTCF in three cell types and identified significant binding of CTCF to the boundaries of repressive chromatin domains marked by H3K27me3. Although we find an extensive overlapping of CTCF-binding sites across the three cell types, its association with the domain boundaries is cell-type-specific. We further show that the nucleosomes flanking CTCF-binding sites are well positioned. Interestingly, we found a complementary pattern between the repressive H3K27me3 and the active H2AK5ac regions, which are separated by CTCF. Our data indicate that CTCF may play important roles in the barrier activity of insulators, and this study provides a resource for further investigation of the CTCF function in organizing chromatin in the human genome.

ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with ultra high-throughput massively parallel sequencing, is increasingly being used for mapping protein-DNA interactions in-vivo on a genome scale. Typically, short sequence reads from ChIP-Seq are mapped to a reference genome for further analysis. Although genomic regions enriched with mapped reads could be inferred as approximate binding regions, short read lengths (approximately 25-50 nt) pose challenges for determining the exact binding sites within these regions. Here, we present SISSRs (Site Identification from Short Sequence Reads), a novel algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments. The sensitivity and specificity of SISSRs are demonstrated by applying it on ChIP-Seq data for three widely studied and well-characterized human transcription factors: CTCF (CCCTC-binding factor), NRSF (neuron-restrictive silencer factor) and STAT1 (signal transducer and activator of transcription protein 1). We identified 26 814, 5813 and 73 956 binding sites for CTCF, NRSF and STAT1 proteins, respectively, which is 32, 299 and 78% more than that inferred previously for the respective proteins. Motif analysis revealed that an overwhelming majority of the identified binding sites contained the previously established consensus binding sequence for the respective proteins, thus attesting for SISSRs' accuracy. SISSRs' sensitivity and precision facilitated further analyses of ChIP-Seq data revealing interesting insights, which we believe will serve as guidance for designing ChIP-Seq experiments to map in vivo protein-DNA interactions. We also show that tag densities at the binding sites are a good indicator of protein-DNA binding affinity, which could be used to distinguish and characterize strong and weak binding sites. Using tag density as an indicator of DNA-binding affinity, we have identified core residues within the NRSF and CTCF binding sites that are critical for a stronger DNA binding.