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Quantifying genome-wide transcription factor binding affinities for chromatin using BANC-seq

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Abstract

Transcription factors (TFs) bind specific DNA sequences to regulate transcription. Apart from DNA sequences, local factors such as DNA accessibility and chromatin structure determine the affinity of a TF for any given locus. Including these factors when measuring TF–DNA affinities has proven difficult. To address this challenge, we recently developed a method called binding affinities in native chromatin by sequencing (BANC-seq). In BANC-seq, intact mammalian nuclei are incubated with a concentration range of epitope-tagged TF, followed by either chromatin immunoprecipitation or cleavage under target and release using nuclease with spike-in DNA. This allows determination of apparent dissociation constant (KdApp) values, defined by the concentration of TF at which half-maximum binding occurs, across the genome. Here we present a detailed stepwise protocol for BANC-seq, including downstream data analysis. In principle, any molecular biologist should be able to perform a BANC-seq experiment in as little as 1.5 d (excluding analysis). However, preprocessing and analysis of the sequencing data does require some experience in command-line shell and R programming.

Key points

  • BANC-seq enables the quantification of genome-wide transcription factor binding affinities in the native chromatin context. This protocol describes implementations based on chromatin immunoprecipitation or cleavage under target and release using nuclease, followed by library preparation, sequencing and data analysis.

  • Unlike traditional methods for measuring transcription factor affinities, BANC-seq measurements incorporate the effects of the chromatin landscape, DNA accessibility and the impact of cofactors.

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Fig. 1: Schematic overview of ChIP-based and CUT&RUN-based BANC-seq workflow.
Fig. 2: Analysis pipeline for BANC-seq data.
Fig. 3: BANC-seq detects TF-DNA affinities across the genome.

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Data availability

Next-generation sequencing data used as example data for this paper can be retrieved from the Gene Expression Omnibus with accession code GSE219035.

Code availability

The workflow for pre-processing of sequencing data and to perform KdApp determination from raw count files is freely available at https://github.com/HNeikes/BANCseq_protocol.

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Acknowledgements

The Vermeulen laboratory is part of the Oncode Institute, which is partly funded by the Dutch Cancer Society (KWF). In addition, research at the Netherlands Cancer Institute is supported by institutional grants of the Dutch Cancer Society and of the Dutch Ministry of Health, Welfare and Sport.

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Authors and Affiliations

Authors

Contributions

R.G.H.L. and M.V. conceived the study. R.G.H.L. designed the methodology and analyses. H.K.N. adapted the methodology to the CUT&RUN-based protocol. R.G.H.L., H.K.N. and R.A.W. performed experiments and analysis. R.A.W., H.K.N., R.G.H.L. and M.V. wrote the manuscript.

Corresponding authors

Correspondence to Rik G. H. Lindeboom or Michiel Vermeulen.

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The authors declare no competing interests.

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Nature Protocols thanks Sebastian Pott and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key reference using this protocol

Neikes, H. K. et al. Nat. Biotechnol. 41, 1801–1809 (2023): https://doi.org/10.1038/s41587-023-01715-w

Supplementary information

Supplementary Information

Supplementary Table 1 and Fig. 1.

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Wester, R.A., Neikes, H.K., Lindeboom, R.G.H. et al. Quantifying genome-wide transcription factor binding affinities for chromatin using BANC-seq. Nat Protoc (2024). https://doi.org/10.1038/s41596-024-01026-7

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