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DynaTag for efficient mapping of transcription factors in low-input samples and at single-cell resolution

Authors: Pascal Hunold; Giulia Pizzolato; Nadia Heramvand; Laura Kaiser; Giulia Barbiera; Olivia van Ray; Roman Thomas; +3 Authors

DynaTag for efficient mapping of transcription factors in low-input samples and at single-cell resolution

Abstract

Abstract Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. Here, we present cleavage under Dyna mic targets and Tag mentation (DynaTag), enabling robust mapping of TF-DNA interactions using a physiological salt solution during sample preparation. DynaTag uncovers occupancy alterations for 15 TFs in stem cell and cancer tissue models. We highlight changes in TF-DNA binding for NANOG, MYC, and OCT4, during stem-cell differentiation, at both bulk and single-cell resolutions. DynaTag surpasses CUT&RUN and ChIP-seq in signal-to-background ratio and resolution. Furthermore, using tumours of a small cell lung cancer model derived from a single female donor, DynaTag reveals increased chromatin occupancy of FOXA1, MYC, and the mutant p53 R248Q at enriched gene pathways (e.g. epithelial-mesenchymal transition), following chemotherapy treatment. Collectively, we believe that DynaTag represents a significant technological advancement, facilitating precise characterization of TF landscapes across diverse biological systems and complex models.

Keywords

Hepatocyte Nuclear Factor 3-alpha, Cell Differentiation, Nanog Homeobox Protein, DNA, Article, Chromatin, Proto-Oncogene Proteins c-myc, Cell Line, Tumor, Humans, Animals, Female, Single-Cell Analysis, Tumor Suppressor Protein p53, Octamer Transcription Factor-3, Transcription Factors

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold
Related to Research communities
Cancer Research