10.17863/CAM.21600
Guertin, Michael J
Michael J
Guertin
Cullen, Amy E
Amy E
Cullen
Markowetz, Florian
Florian
Markowetz
https://orcid.org/0000-0002-2784-5308
Holding, Andrew N
Andrew N
Holding
Parallel factor ChIP provides essential internal control for quantitative differential ChIP-seq.
Oxford University Press (OUP)
2018
Article
Animals
Antibodies
CCCTC-Binding Factor
Chromatin Immunoprecipitation
Drosophila melanogaster
Estrogen Receptor alpha
High-Throughput Nucleotide Sequencing
Histones
Humans
MCF-7 Cells
Mice
Reference Standards
Sequence Analysis, DNA
Apollo-University Of Cambridge Repository
University Of Cambridge
https://ror.org/013meh722
2018-06-21
2018-06-21
2018-07-06
en
https://www.repository.cam.ac.uk/handle/1810/277361
Creative Commons Attribution 4.0 International
open.access
A key challenge in quantitative ChIP combined with high-throughput sequencing (ChIP-seq) is the normalization of data in the presence of genome-wide changes in occupancy. Analysis-based normalization 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 (TF) binding, these assumptions do not hold true. The challenges in normalization are confounded by experimental variability during sample preparation, processing and recovery. We present a novel normalization strategy utilizing 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 normalization. We compare our approach to normalization by total read depth and two alternative methods that utilize external experimental controls to study TF 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 normalize and quantify differential TF binding genome-wide and generate metrics for differential binding at individual sites.
Cancer Research UK
C14303/A17197
Breast Cancer Campaign
2012NovemberPR042
Cancer Research UK
A19274