scholarly journals Identifying differential transcription factor binding in ChIP-seq

2015 ◽  
Vol 6 ◽  
Author(s):  
Dai-Ying Wu ◽  
Danielle Bittencourt ◽  
Michael R. Stallcup ◽  
Kimberly D. Siegmund
Keyword(s):  
Transcription Factor ◽  
Transcription Factor Binding ◽  
Factor Binding ◽  
Differential Transcription

scholarly journals DNase-capture reveals differential transcription factor binding modalities

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0187046
Author(s):  
Daniel Kang ◽  
Richard Sherwood ◽  
Amira Barkal ◽  
Tatsunori Hashimoto ◽  
Logan Engstrom ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factor Binding ◽  
Factor Binding ◽  
Differential Transcription

scholarly journals Novel Quantitative ChIP-seq Methods Measure Absolute Fold-Change in ER Binding Upon Fulvestrant Treatment

2017 ◽  
Author(s):  
Michael J. Guertin ◽  
Amy E Cullen ◽  
Florian Markowetz ◽  
Andrew N. Holding
Keyword(s):  
Transcription Factor ◽  
Estrogen Receptor Alpha ◽  
Internal Standard ◽  
Read Depth ◽  
Transcription Factor Binding ◽  
Alternative Methods ◽  
Underlying Assumption ◽  
Factor Binding ◽  
Genome Wide ◽  
Differential Transcription

A key challenge in quantitative ChIP-seq is the normalisation of data in the presence of genome-wide changes in occupancy. Analysis-based normalisation methods were developed for transcriptomic data and these are dependent on the underlying assumption that total transcription does not change between conditions. For genome-wide changes in transcription factor binding, these assumptions do not hold true. The challenges in normalisation are confounded by experimental variability during sample preparation, processing, and recovery. We present a novel normalisation strategy utilising an internal standard of unchanged peaks for reference. Our method can be readily applied to monitor genome- wide changes by ChIP-seq that are otherwise lost or misrepresented through analytical normalisation. We compare our approach to normalisation by total read depth and two alternative methods that utilise external experimental controls to study transcription factor binding. We successfully resolve the key challenges in quantitative ChIP-seq analysis and demonstrate its application by monitoring the loss of Estrogen Receptor-alpha (ER) binding upon fulvestrant treatment, ER binding in response to estrodiol, ER mediated change in H4K12 acetylation and profiling ER binding in Patient-Derived Xenographs. This is supported by an adaptable pipeline to normalise and quantify differential transcription factor binding genome- wide and generate metrics for differential binding at individual sites.

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