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

Michael J Guertin, View ORCID ProfileFlorian Markowetz, View ORCID ProfileAndrew N Holding
doi: https://doi.org/10.1101/182261
Michael J Guertin
1Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Virginia, USA
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Florian Markowetz
2Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, Cambridgeshire, CB2 0RE, UK
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  • ORCID record for Florian Markowetz
Andrew N Holding
2Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, Cambridgeshire, CB2 0RE, UK
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  • ORCID record for Andrew N Holding
  • For correspondence: andrew.holding@cruk.cam.ac.uk
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Abstract

ChIP-seq (Chromatin ImmunoPrecipitation combined with massively parallel DNA Sequencing) maps protein/DNA interactions genome-wide with high resolution.

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 initially developed for transcriptomic data and these methods 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. Misapplication of these methods to ChIP-seq data results in the suppression of the biological signal or erroneous measurement of differential occupancy. The challenges in normalisation are confounded by experimental variability introduced during sample preparation and processing. Current experimental methodologies do not fully control for important variables, such as the efficiency of DNA recovery by immunoprecipitation.

We present a novel normalisation strategy utilising an internal standard of unchanged peaks for reference. We compare our approach to normalisation by total read depth and two alternative methods that utilise external controls to study transcription factor binding. We successfully resolve the key challenges in quantitative ChIP-seq analysis and demonstrate its application by monitoring the changes in Estrogen Receptor-alpha (ER) binding upon fulvestrant-mediated degradation of ER, which compromises ER binding genome-wide. Additionally, we developed 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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Key Results

  • ChIP-seq data can be normalised by utilising a second control antibody

  • Our implementation avoids downsampling of the normalised data

  • We developed a customisable pipeline to undertake the analysis, implementing both DESeq2 and DiffBind

  • We provide a robust, normalised dataset that quantifies the effect of fulvestrant on ER binding

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted August 30, 2017.
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Novel Quantitative ChIP-seq Methods Measure Absolute Fold-Change in ER Binding Upon Fulvestrant Treatment
Michael J Guertin, Florian Markowetz, Andrew N Holding
bioRxiv 182261; doi: https://doi.org/10.1101/182261
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Novel Quantitative ChIP-seq Methods Measure Absolute Fold-Change in ER Binding Upon Fulvestrant Treatment
Michael J Guertin, Florian Markowetz, Andrew N Holding
bioRxiv 182261; doi: https://doi.org/10.1101/182261

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