Comprehensive Genome-wide Protein-DNA Interactions Detected at Single Nucleotide Resolution

By H. Rhee, B. Franklin Pugh. 2011

803 citations recorded by the source corpus.

SUMMARY Chromatin immunoprecipitation (ChIP-chip and ChIP-seq) assays identify where proteins bind throughout a genome. However, DNA contamination and DNA fragmentation heterogeneity produce false positives (erroneous calls) and imprecision in mapping. Consequently, stringent data filtering produces false negatives (missed calls). Here we describe ChIP-exo, where an exonuclease trims ChIP DNA to a precise distance from the crosslinking site. Bound locations are detectable as peak-pairs by deep sequencing. Contaminating DNA is degraded or fails to form complementary peak-pairs. With the single bp accuracy provided by ChIP-exo, we show an unprecedented view into genome-wide binding of the yeast transcription factors Reb1, Gal4, Phd1, Rap1, and human CTCF. Each of these factors was chosen to address potential limitations of ChIP-exo. We found that binding sites become unambiguous and reveal diverse tendencies governing in vivo DNA binding specificity that include sequence variants, functionally distinct motifs, motif clustering, secondary interactions, and combinatorial modules within a compound motif.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Impact of cytosine methylation on DNA binding specificities of human transcription factors (2017, methodology): “When the confluence reaches 60 to 70%, ChIP-exo experiments were performed essentially as described by Rhee and Pugh (71) with modifications from Katainen et al.”
FactorNet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data (2017, methodology): “Given that ChIP-seq signal noise can significantly influence the accuracy of predictions (Figure 2), we propose that future data generation efforts should use protocol improvements such as ChIP-exo[57], CUT&RUN[58], or higher quality antibodies to complement the development of prediction models.”
Targeted in situ genome-wide profiling with high efficiency for low cell numbers (2018, neutral): “Single-end sequencing is not recommended for CUT&RUN, as it sacrifices resolution and discrimination between TFs and neighboring nucleosomes.”
CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription. (2015, methodology): “See also Figures S2E–S2G. of CTCF (Rhee and Pugh, 2011) and ChIP-nexus data of RAD21 were plotted tified by occupancy peaks.”
CRISPR Inversion of CTCF Sites Alters Genome Topology and Enhancer/Promoter Function (2015, neutral): “Non-random CBS Orientations in the Two Pcdh CCDs A CBS motif is located within all of the Pcdh a, b, and g promoters, except ac2, b1, gc4, and gc5 (Figure 1A) (Guo et al., 2012; Kim et al., 2007; Monahan et al., 2012; Nakahashi et al., 2013; Rhee and Pugh, 2011; Schmidt et al., 2012; Wu et al., 2001”
Ruler elements in chromatin remodelers set nucleosome array spacing and phasing (2020, background): “In vivo distances between Reb1 and +1 nucleosomes are 60-80 bp (Figure S3B, (Rhee and Pugh, 2011)), which are within remodeler-specific distances to Reb1 at medium or low density (81-86 bp for INO80, 70-74 bp for ISW2, 58-60 bp for ISW1a).”