Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M phase. These results suggest that cohesin-binding functions as a cellular memory that promotes re-establishment of TF clusters after DNA replication and chromatin condensation.

Genome-wide association studies have identified thousands of SNPs associated with predisposition to various diseases, including prostate cancer. However, the mechanistic roles of these SNPs remain poorly defined, particularly for noncoding polymorphisms. Here we find that the prostate cancer risk-associated SNP rs339331 at 6q22 lies within a functional HOXB13-binding site. The risk-associated T allele at rs339331 increases binding of HOXB13 to a transcriptional enhancer, conferring allele-specific upregulation of the rs339331-associated gene RFX6. Suppression of RFX6 diminishes prostate cancer cell proliferation, migration and invasion. Clinical data indicate that RFX6 upregulation in human prostate cancers correlates with tumor progression, metastasis and risk of biochemical relapse. Finally, we observe a significant association between the risk-associated T allele at rs339331 and increased RFX6 mRNA levels in human prostate tumors. Together, our results suggest that rs339331 affects prostate cancer risk by altering RFX6 expression through a functional interaction with the prostate cancer susceptibility gene HOXB13.