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

Autor: Wester RA; Department of Molecular Biology, Faculty of Science, Oncode Institute, Radboud University, Radboud Institute for Molecular Life Sciences (RIMLS), Nijmegen, the Netherlands., Neikes HK; Department of Molecular Biology, Faculty of Science, Oncode Institute, Radboud University, Radboud Institute for Molecular Life Sciences (RIMLS), Nijmegen, the Netherlands., Lindeboom RGH; Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, the Netherlands. r.lindeboom@nki.nl., Vermeulen M; Department of Molecular Biology, Faculty of Science, Oncode Institute, Radboud University, Radboud Institute for Molecular Life Sciences (RIMLS), Nijmegen, the Netherlands. Michiel.vermeulen@ru.nl.; Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam, the Netherlands. Michiel.vermeulen@ru.nl.
Jazyk: angličtina
Zdroj: Nature protocols [Nat Protoc] 2024 Jul 30. Date of Electronic Publication: 2024 Jul 30.
DOI: 10.1038/s41596-024-01026-7
Abstrakt: 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 (K d App ) 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.
(© 2024. Springer Nature Limited.)
Databáze: MEDLINE
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