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Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity
Author(s) -
Songjoon Baek,
Ido Goldstein,
Gordon L. Hager
Publication year - 2017
Publication title -
cell reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.264
H-Index - 154
eISSN - 2639-1856
pISSN - 2211-1247
DOI - 10.1016/j.celrep.2017.05.003
Subject(s) - footprinting , transcription factor , bivariate analysis , transcription (linguistics) , computational biology , biology , genetics , gene , statistics , mathematics , linguistics , philosophy
In response to activating signals, transcription factors (TFs) bind DNA and regulate gene expression. TF binding can be measured by protection of the bound sequence from DNase digestion (i.e., footprint). Here, we report that 80% of TF binding motifs do not show a measurable footprint, partly because of a variable cleavage pattern within the motif sequence. To more faithfully portray the effect of TFs on chromatin, we developed an algorithm that captures two TF-dependent effects on chromatin accessibility: footprinting and motif-flanking accessibility. The algorithm, termed bivariate genomic footprinting (BaGFoot), efficiently detects TF activity. BaGFoot is robust to different accessibility assays (DNase-seq, ATAC-seq), all examined peak-calling programs, and a variety of cut bias correction approaches. BaGFoot reliably predicts TF binding and provides valuable information regarding the TFs affecting chromatin accessibility in various biological systems and following various biological events, including in cases where an absolute footprint cannot be determined.

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