Wellington-bootstrap : differential DNase-seq footprinting identifies cell-type determining transcription factors

Article English OPEN
Piper, Jason ; Assi, Salam A. ; Cauchy, Pierre ; Ladroue, Christophe ; Cockerill, Peter N. ; Bonifer, Constanze ; Ott, Sascha (2015)

Background The analysis of differential gene expression is a fundamental tool to relate gene regulation with specific biological processes. Differential binding of transcription factors (TFs) can drive differential gene expression. While DNase-seq data can provide global snapshots of TF binding, tools for detecting differential binding from pairs of DNase-seq data sets are lacking. Results In order to link expression changes with changes in TF binding we introduce the concept of differential footprinting alongside a computational tool. We demonstrate that differential footprinting is associated with differential gene expression and can be used to define cell types by their specific TF occupancy patterns. Conclusions Our new tool, Wellington-bootstrap, will enable the detection of differential TF binding facilitating the study of gene regulatory systems. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2081-4) contains supplementary material, which is available to authorized users.
  • References (32)
    32 references, page 1 of 4

    1. Galas DJ, Schmitz A. DNAse footprinting: a simple method for the detection of protein-DNA binding specificity. Nucleic Acids Res. 1978;5:3157-70.

    2. Boyle AP, Davis S, Shulha HP, Meltzer P, Margulies EH, Weng Z, et al. High-resolution mapping and characterization of open chromatin across the genome. Cell. 2008;132:311-22.

    3. Cockerill PN. Structure and function of active chromatin and DNase I hypersensitive sites. FEBS J. 2011;278:2182-210.

    4. Hesselberth JR, Chen X, Zhang Z, Sabo PJ, Sandstrom R, Reynolds AP, et al. Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nature Methods. 2009;6:283-9.

    5. Boyle AP, Song L, Lee B-K, London D, Keefe D, Birney E, et al. Highresolution genome-wide in vivo footprinting of diverse transcription factors in human cells. Genome Research. 2011;21:456-64.

    6. Pique-Regi R, Degner JF, Pai AA, Gaffney DJ, Gilad Y, Pritchard JK. Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data. Genome Research. 2011;21:447-55.

    7. Neph S, Vierstra J, Stergachis AB, Reynolds AP, Haugen E, Vernot B, et al. An expansive human regulatory lexicon encoded in transcription factor footprints. Nature. 2012;489:83-90.

    8. Piper J, Elze MC, Cauchy P, Cockerill PN, Bonifer C, Ott S. Wellington: a novel method for the accurate identification of digital genomic footprints from DNase-seq data. Nucleic Acids Res. 2013;41:e201.

    9. Sherwood RI, Hashimoto T, O'Donnell CW, Lewis S, Barkal AA, van Hoff JP, et al. Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape. Nat Biotechnol. 2014;32:171-8.

    10. Sung M-H, Guertin MJ, Baek S, Hager GL. DNase footprint signatures are dictated by factor dynamics and DNA sequence. Mol Cell. 2014;56:275-85.

  • Metrics
    No metrics available
Share - Bookmark