title: Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets.
abstract: BACKGROUND
  The global effort to annotate the non-coding portion of the human genome relies heavily on chromatin immunoprecipitation data generated with high-throughput DNA sequencing (ChIP-seq). ChIP-seq is generally successful in detailing the segments of the genome bound by the immunoprecipitated transcription factor (TF), however almost all datasets contain genomic regions devoid of the canonical motif for the TF. It remains to be determined if these regions are related to the immunoprecipitated TF or whether, despite the use of controls, there is a portion of peaks that can be attributed to other causes.
  
  
  RESULTS
  Analyses across hundreds of ChIP-seq datasets generated for sequence-specific DNA binding TFs reveal a small set of TF binding profiles for which predicted TF binding site motifs are repeatedly observed to be significantly enriched. Grouping related binding profiles, the set includes: CTCF-like, ETS-like, JUN-like, and THAP11 profiles. These frequently enriched profiles are termed 'zingers' to highlight their unanticipated enrichment in datasets for which they were not the targeted TF, and their potential impact on the interpretation and analysis of TF ChIP-seq data. Peaks with zinger motifs and lacking the ChIPped TF's motif are observed to compose up to 45% of a ChIP-seq dataset. There is substantial overlap of zinger motif containing regions between diverse TF datasets, suggesting a mechanism that is not TF-specific for the recovery of these regions.
  
  
  CONCLUSIONS
  Based on the zinger regions proximity to cohesin-bound segments, a loading station model is proposed. Further study of zingers will advance understanding of gene regulation.
authors: Rebecca
authors: R
authors: Worsley Hunt
authors: Wyeth W
authors: WW
authors: Wasserman
mesh_terms: D000818:Animals; D047369:Chromatin Immunoprecipitation; D019295:Computational Biology / Q000379:methods; D004247:DNA / Q000737:chemistry* / Q000378:metabolism; D030541:Databases, Genetic; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D058977:Molecular Sequence Annotation / Q000379:methods*; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000737:chemistry / Q000378:metabolism*
chemical_list: D014157:Transcription Factors; D004247:DNA