DNase-Seq

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title: "DNase-Seq" type: doc version: 1 created: 2026-02-28 author: "Wikipedia contributors" status: active scope: public tags: ["molecular-biology-techniques"] topic_path: "science/biology" source: "https://en.wikipedia.org/wiki/DNase-Seq" license: "CC BY-SA 4.0" wikipedia_page_id: 0 wikipedia_revision_id: 0

DNase-seq (DNase I hypersensitive sites sequencing) is a method in molecular biology used to identify the location of regulatory regions, based on the genome-wide sequencing of regions sensitive to cleavage by DNase I. FAIRE-Seq is a successor of DNase-seq for the genome-wide identification of accessible DNA regions in the genome. Both the protocols for identifying open chromatin regions have biases depending on underlying nucleosome structure. For example, FAIRE-seq provides higher tag counts at non-promoter regions. On the other hand, DNase-seq signal is higher at promoter regions, and DNase-seq has been shown to have better sensitivity than FAIRE-seq even at non-promoter regions.

DNase-seq Footprinting

DNase-seq requires some downstream bioinformatics analyses in order to provide genome-wide DNA footprints. The computational tools proposed can be categorized in two classes: segmentation-based and site-centric approaches. Segmentation-based methods are based on the application of Hidden Markov models or sliding window methods to segment the genome into open/closed chromatin region. Examples of such methods are: HINT, Boyle method and Neph method. Site-centric methods, on the other hand, find footprints given the open chromatin profile around motif-predicted binding sites, i.e., regulatory regions predicted using DNA-protein sequence information (encoded in structures such as Position weight matrix). Examples of these methods are CENTIPEDE and Cuellar-Partida method.

References

References

  1. Boyle, AP. (2008). "High-resolution mapping and characterization of open chromatin across the genome". Cell.
  2. Crawford, GE. (January 2006). "Genome-wide mapping of DNase hypersensitive sites using massively parallel signature sequencing (MPSS).". Genome Research.
  3. Madrigal, P. (October 2012). "Current bioinformatic approaches to identify DNase I hypersensitive sites and genomic footprints from DNase-seq data.". Front Genet.
  4. Prabhakar S., Vibhor Kumar. (July 2013). "Uniform, optimal signal processing of mapped deep-sequencing data.". Nature Biotechnology.
  5. Gusmao, EG. (Aug 2014). "Detection of Active Transcription Factor Binding Sites with the Combination of DNase Hypersensitivity and Histone Modifications.". Bioinformatics.
  6. Boyle, AP. (Mar 2011). "High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.". Genome Research.
  7. Neph, S. (Sep 2012). "An expansive human regulatory lexicon encoded in transcription factor footprints.". Nature.
  8. Pique-Regi, R. (Mar 2011). "Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.". Genome Research.
  9. Cuellar-Partida, G. (Jan 2012). "Epigenetic priors for identifying active transcription factor binding sites.". Bioinformatics.

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molecular-biology-techniques