In silico identification of transcriptional regulators associated with c-Myc

Abstract

The development of powerful experimental strategies for functional genomics and accompanying computational tools has brought major advances in the delineation of transcriptional networks in organisms ranging from yeast to human. Regulation of transcription of eukaryotic genes is to a large extent combinatorial. Here, we used an in silico approach to identify transcription factors (TFs) that form recurring regulatory modules with c-Myc, a protein encoded by an oncogene that is frequently disregulated in human malignancies. A recent study identified, on a genomic scale, human genes whose promoters are bound by c-Myc and its heterodimer partner Max in Burkitt's lymphoma cells. Using computational methods, we identified nine TFs whose binding-site signatures are highly overrepresented in this promoter set of c-Myc targets, pointing to possible functional links between these TFs and c-Myc. Binding sites of most of these TFs are also enriched on the set of mouse homolog promoters, suggesting functional conservation. Among the enriched TFs, there are several regulators known to control cell cycle progression. Another TF in this set, EGR-1, is rapidly activated by numerous stress challenges and plays a central role in angiogenesis. Experimental investigation confirmed that c-Myc and EGR-1 bind together on several target promoters. The approach applied here is general and demonstrates how computational analysis of functional genomics experiments can identify novel modules in complex networks of transcriptional regulation.

Figure 1

Location distribution of hits for c-Myc/Max target set and EGR-1 on promoters of the c-Myc/Max target set. The promoter region spanning 1000 bp upstream to 200 bp downstream of the TSS was divided into 10 bins of 120 bp. The graph represents the relative frequency of hits over the bins for c-Myc/Max (M00322), EGR-1 (M00243) and for a random PWM derived from the EGR-1 PWM as explained in the text. The number of hits in each bin was normalized by the effective sequence length scanned in the bin (effective lengths can be different in different bins due to masking of repetitive elements in promoters). Multiple hits in promoters were counted as such.

Figure 2

ChIP of c-Myc and EGR-1 targets in K562 cells. Each graph represents real-time PCR amplification of the promoter and control regions of each gene using anti-Myc, anti-EGR-1, anti-HGF and no antibody precipitated chromatin as template. Bars represent the percentage of total input DNA for each ChIP sample averaged over three PCRs. Error bars represent 1 SD. The horizontal solid line represents 0.02% total input DNA, the background signal for this assay. The signals obtained for the binding of c-Myc and EGR-1 to the promoter regions of all six genes examined (RAP2B, KHSRP, PolH, PTPN1, PP and KPNA3), but not for the negative control, MCCC2, were above the background level (P < 0.025, one-tailed t-test). Primer sequences and positions, and locations of the putative hits for c-Myc and EGR-1 on the examined promoters are given in Supplementary Table D.