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Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks. / Vishnevsky, Oleg V; Bocharnikov, Andrey V; Ignatieva, Elena V.
In: International Journal of Molecular Sciences, Vol. 25, No. 2, 1011, 01.2024.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks
AU - Vishnevsky, Oleg V
AU - Bocharnikov, Andrey V
AU - Ignatieva, Elena V
N1 - This research was funded by Russian government project № FWNR-2022-0020.
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - Chromatin Immunoprecipitation Sequencing
KW - Chromatin Immunoprecipitation
KW - Sequence Analysis, DNA
KW - Transcription Factors/genetics
KW - DNA/genetics
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85183334059&origin=inward&txGid=be19431db850386f1b3941c2c4e7fc25
UR - https://www.mendeley.com/catalogue/7273e33c-5702-39ad-aa59-04d310cf624e/
U2 - 10.3390/ijms25021011
DO - 10.3390/ijms25021011
M3 - Article
C2 - 38256085
VL - 25
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
SN - 1661-6596
IS - 2
M1 - 1011
ER -
ID: 60411673