Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks

被引:0
|
作者
Vishnevsky, Oleg V. [1 ,2 ]
Bocharnikov, Andrey V. [2 ]
Ignatieva, Elena V. [1 ,2 ]
Chen, Ming
机构
[1] Inst Cytol & Genet, Novosibirsk 630090, Russia
[2] Novosibirsk State Univ, Dept Nat Sci, Novosibirsk 630090, Russia
关键词
chromatin immunoprecipitation with massively parallel sequencing; transcription factor binding sites; IUPAC motifs; co-binding of transcription factors; composite elements; multiple regression; FACTOR-BINDING SITES; EXPRESSED TRANSCRIPTION FACTOR; COMPOSITE REGULATORY ELEMENTS; DNA-BINDING; PROTEIN COMPLEXES; GENE-EXPRESSION; NF-Y; CHROMATIN; DATABASE; MOUSE;
D O I
10.3390/ijms25021011
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.
引用
收藏
页数:29
相关论文
共 50 条
  • [31] Iterative Fragmentation Improves the Detection of ChIP-seq Peaks for Inactive Histone Marks
    Laczik, Miklos
    Hendrickx, Jan
    Veillard, Anne-Clemence
    Tammoh, Mustafa
    Marzi, Sarah
    Poncelet, Dominique
    BIOINFORMATICS AND BIOLOGY INSIGHTS, 2016, 10 : 209 - 224
  • [32] Greenscreen: A simple method to remove artifactual signals and enrich for true peaks in genomic datasets including ChIP-seq data
    Klasfeld, Samantha
    Roule, Thomas
    Wagner, Doris
    PLANT CELL, 2022, 34 (12): : 4795 - 4815
  • [33] BroadPeak: a novel algorithm for identifying broad peaks in diffuse ChIP-seq datasets
    Wang, Jianrong
    Lunyak, Victoria V.
    Jordan, I. King
    BIOINFORMATICS, 2013, 29 (04) : 492 - 493
  • [34] WACS: improving ChIP-seq peak calling by optimally weighting controls
    Awdeh, Aseel
    Turcotte, Marcel
    Perkins, Theodore J.
    BMC BIOINFORMATICS, 2021, 22 (01)
  • [35] Picking ChIP-seq peak detectors for analyzing chromatin modification experiments
    Micsinai, Mariann
    Parisi, Fabio
    Strino, Francesco
    Asp, Patrik
    Dynlacht, Brian D.
    Kluger, Yuval
    NUCLEIC ACIDS RESEARCH, 2012, 40 (09)
  • [36] PeakRanger: A cloud-enabled peak caller for ChIP-seq data
    Feng, Xin
    Grossman, Robert
    Stein, Lincoln
    BMC BIOINFORMATICS, 2011, 12
  • [37] RECAP reveals the true statistical significance of ChIP-seq peak calls
    Chitpin, Justin G.
    Awdeh, Aseel
    Perkins, Theodore J.
    BIOINFORMATICS, 2019, 35 (19) : 3592 - 3598
  • [38] PeakRanger: A cloud-enabled peak caller for ChIP-seq data
    Xin Feng
    Robert Grossman
    Lincoln Stein
    BMC Bioinformatics, 12
  • [39] The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding
    Karl Kornacker
    Morten Beck Rye
    Tony Håndstad
    Finn Drabløs
    BMC Bioinformatics, 13
  • [40] OccuPeak: ChIP-Seq Peak Calling Based on Internal Background Modelling
    de Boer, Bouke A.
    van Duijvenboden, Karel
    van den Boogaard, Malou
    Christoffels, Vincent M.
    Barnett, Phil
    Ruijter, Jan M.
    PLOS ONE, 2014, 9 (06):