Biology:DNase-Seq

From HandWiki

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.[1][2][3] 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.[4] 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.[4]

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,[5] Boyle method[6] and Neph method.[7] 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[8] and Cuellar-Partida method.[9]

References

  1. ↑ Boyle, AP; Davis S; Shulha HP; Meltzer P; Margulies EH; Weng Z; Furey TS; Crawford GE (2008). "High-resolution mapping and characterization of open chromatin across the genome". Cell 132 (2): 311–22. doi:10.1016/j.cell.2007.12.014. PMID 18243105. 
  2. ↑ Crawford, GE; Holt, IE; Whittle, J; Webb, BD; Tai, D; Davis, S; Margulies, EH; Chen, Y et al. (January 2006). "Genome-wide mapping of DNase hypersensitive sites using massively parallel signature sequencing (MPSS).". Genome Research 16 (1): 123–131. doi:10.1101/gr.4074106. PMID 16344561. 
  3. ↑ Madrigal, P; Krajewski, P (October 2012). "Current bioinformatic approaches to identify DNase I hypersensitive sites and genomic footprints from DNase-seq data.". Front Genet 3: 230. doi:10.3389/fgene.2012.00230. PMID 23118738. 
  4. ↑ 4.0 4.1 Prabhakar S., Vibhor Kumar; Rayan NA; Kraus P; Lufkin T; Ng HH (July 2013). "Uniform, optimal signal processing of mapped deep-sequencing data.". Nature Biotechnology 31 (7): 615–22. doi:10.1038/nbt.2596. PMID 23770639. 
  5. ↑ Gusmao, EG; Dieterich, C; Zenke, M; Costa, IG (Aug 2014). "Detection of Active Transcription Factor Binding Sites with the Combination of DNase Hypersensitivity and Histone Modifications.". Bioinformatics 30 (22): 3143–51. doi:10.1093/bioinformatics/btu519. PMID 25086003. 
  6. ↑ Boyle, AP (Mar 2011). "High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.". Genome Research 21 (3): 456–464. doi:10.1101/gr.112656.110. PMID 21106903. 
  7. ↑ Neph, S (Sep 2012). "An expansive human regulatory lexicon encoded in transcription factor footprints.". Nature 489 (7414): 83–90. doi:10.1038/nature11212. PMID 22955618. Bibcode: 2012Natur.489...83N. 
  8. ↑ Pique-Regi, R (Mar 2011). "Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.". Genome Research 21 (3): 447–455. doi:10.1101/gr.112623.110. PMID 21106904. 
  9. ↑ Cuellar-Partida, G (Jan 2012). "Epigenetic priors for identifying active transcription factor binding sites.". Bioinformatics 28 (1): 56–62. doi:10.1093/bioinformatics/btr614. PMID 22072382. 

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