Description: Understanding the information encoded in the human genome requires deciphering two genetic codes. The first code specifies how mRNA sequence is converted into protein sequence, and the second code determines where and when the mRNAs are expressed. Although the proteins that read the second, regulatory code – transcription factors (TFs) – have been largely identified, the code is poorly understood as it is not known which sequences TFs can bind in the genome. To address this problem, 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 all human TFs, approximately doubling the coverage compared to existing systematic studies. Our results also reveal additional specificity determinants for a large number of factors for which a partial specificity was known before, including a commonly observed A- or T-rich stretch flanking core-binding 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 what has been previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Data type: Other

Sample scope: Monoisolate

Release date: 2013-01-17