Identifying synergistic regulation involving c-Myc and sp1 in human tissues

Nucleic Acids Res. 2007;35(4):1098-107. doi: 10.1093/nar/gkl1157. Epub 2007 Jan 30.


Combinatorial gene regulation largely contributes to phenotypic versatility in higher eukaryotes. Genome-wide chromatin immuno-precipitation (ChIP) combined with expression profiling can dissect regulatory circuits around transcriptional regulators. Here, we integrate tiling array measurements of DNA-binding sites for c-Myc, sp1, TFIID and modified histones with a tissue expression atlas to establish the functional correspondence between physical binding, promoter activity and transcriptional regulation. For this we develop SLM, a methodology to map c-Myc and sp1-binding sites and then classify sites as sp1-only, c-Myc-only or dual. Dual sites show several distinct features compared to the single regulator sites: specifically, they exhibit overall higher degree of conservation between human and rodents, stronger correlation with TFIID-bound promoters, and preference for permissive chromatin state. By applying regression models to an expression atlas we identified a functionally distinct signature for strong dual c-Myc/sp1 sites. Namely, the correlation with c-Myc expression in promoters harboring dual-sites is increased for stronger sp1 sites by strong sp1 binding and the effect is largest in proliferating tissues. Our approach shows how integrated functional analyses can uncover tissue-specific and combinatorial regulatory dependencies in mammals.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Binding Sites
  • Chromatin / metabolism
  • Chromatin Immunoprecipitation
  • Evolution, Molecular
  • Gene Expression Profiling
  • Gene Regulatory Networks*
  • Humans
  • Mice
  • Promoter Regions, Genetic*
  • Proto-Oncogene Proteins c-myc / metabolism*
  • Rats
  • Sp1 Transcription Factor / metabolism*
  • Tissue Distribution


  • Chromatin
  • MYC protein, human
  • Proto-Oncogene Proteins c-myc
  • Sp1 Transcription Factor