Global mapping of protein-DNA interactions in vivo by digital genomic footprinting

By J. Hesselberth, Xiaoyu Chen, Zhihong Zhang, P. Sabo, R. Sandstrom, Alex P. Reynolds, Robert E. Thurman, Shane J. Neph, Michael S. Kuehn, William Stafford Noble and 2 more. Nature Methods, 2009

620 citations recorded by the source corpus.

The orchestrated binding of transcriptional activators and repressors to specific DNA sequences in the context of chromatin defines the regulatory program of eukaryotic genomes. We developed a digital approach to assay regulatory protein occupancy on genomic DNA in vivo by dense mapping of individual DNase I cleavages from intact nuclei using massively parallel DNA sequencing. Analysis of >23 million cleavages across the Saccharomyces cerevisiae genome revealed thousands of protected regulatory protein footprints, enabling de novo derivation of factor binding motifs and the identification of hundreds of new binding sites for major regulators. We observed striking correspondence between single-nucleotide resolution DNase I cleavage patterns and protein-DNA interactions determined by crystallography. The data also yielded a detailed view of larger chromatin features including positioned nucleosomes flanking factor binding regions. Digital genomic footprinting should be a powerful approach to delineate the cis-regulatory framework of any organism with an available genome sequence.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a28ec0a9ffcbe1ee2bbb0c09277b22fd9103e67f

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Citations in the corpus

Increased methylation variation in epigenetic domains across cancer types (2011, neutral): “Our gene ontology enrichment analysis 15 of genes associated with hypervariable expression in blocks (FDR 0.05)showed enrichment for categories including extracellular matrix remodeling genes (Supplementary Table 13).”
The human mitochondrial transcriptome (2011, methodology): “DNaseI Hypersensitivity Mapping and Alignment DNaseI hypersensitivity preparation, sequencing, and mapping were performed as previously described (Hesselberth et al., 2009; Sabo et al., 2006) and further detailed within the Extended Experimental Procedures.”
A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility. (2018, background): “Chromatin accessibility is a generic marker of regulatory DNA classically measured by DNase I hypersensitivity, now read out by sequencing (DNase-seq) (Hesselberth et al., 2009).”
DNaseI sensitivity QTLs are a major determinant of human expression variation (2012, methodology): “DNase-seq is a genome-wide extension of the classical DNase I footprinting metho”
A User's Guide to the Encyclopedia of DNA Elements (ENCODE) (2011, background): “Deep sampling of highly enriched libraries of DNaseI-released fragments (see above) enables digital quantification of per nucleotide DNaseI cleavage, which in turn enables resolution of DNaseI footprints on a large scale [55,77,78].”
Learning from mistakes: Accurate prediction of cell type-specific transcription factor binding (2017, methodology): “High-throughput sequencing may also be used to obtain genome-wide assays of chro-55 matin accessibility (e.g., DNase-seq (Hesselberth et al. , 2009), ATAC-seq (Buenrostro et al. , 2013)), which has been considered one of the key features distinguishing func-57 tional from non-functional TF binding…”
Defining cell types and states with single-cell genomics (2015, background): “Later work by Sui Huang showed that a simple regulatory network with just two genes that inhibit one another but promote their own expression is sufficient to generate a hypothetical landscape with three stable cell fates (Huang et al. 2007).”
An Integrated Encyclopedia of DNA Elements in the Human Genome (2012, background): “Using genomic DNaseI footprinting 33,34 on 41 cell types we identified 8.4 million distinct DNaseI footprints (FDR 1”
Comprehensive Genome-wide Protein-DNA Interactions Detected at Single Nucleotide Resolution (2011, background): “Digital genomic footprinting can detect highly occupied binding sites at high resolution (Hesselberth et al., 2009), but identifying the source of protected genomic footprints requires a priori knowledge of which protein binds to the identified sequence.”
Linking disease associations with regulatory information in the human genome (2012, methodology): “DNase footprinting (Hesselberth et al. 2009; Boyle et al. 2011; Pique-Regi et al. 2011) was used to detect binding between proteins and the genome at a nucleotide resolution.”
Precise genome-wide mapping of single nucleosomes and linkers in vivo (2018, methodology): “Three data sets were downloaded from the NCBI Sequence Read Archive, using the following accession numbers: SRP033438, Rpb1 ChIP-seq data [78]; SRA059355, H1 ChIP-exo data [80]; SRP000620, DNase-seq data [65].”
An encyclopedia of mouse DNA elements (Mouse ENCODE) (2012, methodology): “…using stateoftheart approaches, including DNaseI hypersensitive sites by DNaseseq [19], DNaseI footprints by digital genomic footprinting [20], RNAseq [21], histone modifications by ChIPseq [22], transcrip tion factor and polymerase occupancy sites by ChIPseq [23], and DNA…”
Dynamic reprogramming of chromatin accessibility during Drosophila embryo development (2011, methodology): “To map individual DNaseI cleavages to the genome, DNaseI-released fragments were assembled into sequencing libraries and end-sequenced on an Illumina GA2 instrument [27], yielding an average of approximately 14 million genomic reads per sample that mapped to a unique position within the approximatel”