A Map of Minor Groove Shape and Electrostatic Potential from Hydroxyl Radical Cleavage Patterns of DNA

Bishop, Eric; Rohs, Remo; Parker, Stephen C. J.; West, Sean M.; Liu, Peng; Mann, Richard S.; Honig, Barry; Tullius, Tom

doi:10.1021/cb200155t

Cited by 85 publications

(100 citation statements)

References 40 publications

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“…Earlier reports have shown that the phosphodiester backbone at purine-pyrimidine (RpY) dinucleotides, which intrinsically widen the minor groove, are cleaved by DNase I at higher rates (32,33). Having a widened minor groove where the backbone is cleaved would thus seem to be beneficial (34).…”

Section: Resultsmentioning

confidence: 99%

Probing DNA shape and methylation state on a genomic scale with DNase I

Lazarovici

Zhou

Shafer

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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153

187

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DNA binding proteins find their cognate sequences within genomic DNA through recognition of specific chemical and structural features. Here we demonstrate that high-resolution DNase I cleavage profiles can provide detailed information about the shape and chemical modification status of genomic DNA. Analyzing millions of DNA backbone hydrolysis events on naked genomic DNA, we show that the intrinsic rate of cleavage by DNase I closely tracks the width of the minor groove. Integration of these DNase I cleavage data with bisulfite sequencing data for the same cell type's genome reveals that cleavage directly adjacent to cytosine-phosphate-guanine (CpG) dinucleotides is enhanced at least eightfold by cytosine methylation. This phenomenon we show to be attributable to methylationinduced narrowing of the minor groove. Furthermore, we demonstrate that it enables simultaneous mapping of DNase I hypersensitivity and regional DNA methylation levels using dense in vivo cleavage data. Taken together, our results suggest a general mechanism by which CpG methylation can modulate protein-DNA interaction strength via the remodeling of DNA shape.

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Section: Resultsmentioning

confidence: 99%

Probing DNA shape and methylation state on a genomic scale with DNase I

Lazarovici

Zhou

Shafer

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

153

187

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“…CBR associations with Crx −/− up-or down-regulated genes were taken from Corbo et al (18). Minor groove width was predicted at base pair resolution using the ORChID2 program (28), and ORChID2 scores were summed across all base pairs in each CRE or Crx motif to give a total sequence minor groove width score. CpG island annotations were obtained from the UCSC Genome Browser at http://genome.ucsc.edu/index.html (39).…”

Section: Methodsmentioning

confidence: 99%

“…High GC content is associated with several distinct features that can affect the cis-regulatory potential of a sequence (4, 23), including high nucleosome occupancy (24-26) and a wide DNA minor groove (27,28). In some cases, TF binding is promoted by high nucleosome occupancy (29), and minor groove width can affect the binding specificity of homeodomain TFs (12).…”

Section: High Local Gc Content Distinguishes Functional Crx Sites Frommentioning

confidence: 99%

Massively parallel in vivo enhancer assay reveals that highly local features determine thecis-regulatory function of ChIP-seq peaks

White

Myers

Corbo

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

192

263

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Transcription factors (TFs) recognize short sequence motifs that are present in millions of copies in large eukaryotic genomes. TFsmust distinguish their target binding sites from a vast genomic excess of spurious motif occurrences; however, it is unclear whether functional sites are distinguished from nonfunctional motifs by local primary sequence features or by the larger genomic context in which motifs reside. We used a massively parallel enhancer assay in living mouse retinas to compare 1,300 sequences bound in the genome by the photoreceptor transcription factor Cone-rod homeobox (Crx), to 3,000 control sequences. We found that very short sequences bound in the genome by Crx activated transcription at high levels, whereas unbound genomic regions with equal numbers of Crx motifs did not activate above background levels, even when liberated from their larger genomic context. High local GC content strongly distinguishes bound motifs from unbound motifs across the entire genome. Our results show that the cis-regulatory potential of TF-bound DNA is determined largely by highly local sequence features and not by genomic context. (1), yet the sequence features that distinguish functional cis-regulatory sites from the millions of spurious motif occurrences in large eukaryotic genomes are poorly understood (2-6). Several models have been proposed to explain how TFs distinguish between functional cis-regulatory elements (CREs) and nonfunctional motif occurrences (3, 6, 7). In one model, large-scale chromatin context directs TF binding to target sites while limiting TF access to spurious motif occurrences (7-9). This model is supported by recent analyses of genomic DNaseI hypersensitivity, which show that only 1% of the genome typically resides in open chromatin in any given cell type (1, 10), suggesting that most spurious motif occurrences are inaccessible. A second model states that target sites are recognized through cooperative TF binding to highly specific combinations of sequence motifs, which are unlikely to occur by chance in nonregulatory regions of the genome (6, 11). This model is supported by evidence that the binding specificity of many TFs is affected by cooperative interactions with cofactors (12). A third model states that most TF binding is promiscuous, low occupancy, and nonfunctional, whereas functional CREs are characterized by high TF occupancy, achieved through either a permissive chromatin context or high affinity for TFs (3,6). This model is motivated by recent genomewide binding studies demonstrating that binding locations of functionally diverse TFs overlap substantially (13, 14), a result that suggests binding is unlikely to be primarily determined by rare, specific combinations of cooperative interactions. Regardless of the mechanisms by which TFs select functional CREs, the distinction between functional and nonfunctional motif occurrences must ultimately depend on information encoded either locally or within the larger sequence context surrounding functional CREs.To distinguish between t...

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“…Two primary sequence features (PSFs) (GC content and minor groove width as estimated by ORChID2 [Rohs et al 2009;Bishop et al 2011] score) and six chromatin features (The ENCODE Project Consortium 2012; Hoffman et al 2013) (DNase I HS from Duke; DNase I HS from University of Washington [UW]; FAIRE-seq; and ChIP-seq of H3K4me1, H3K36me3, and RNA polymerase POLR2A) are significantly enriched in sequences that drive high expression in our assay (Wilcoxon rank sum test, P < 0.05 Bonferroni correction with N = 16) (Supplemental Table 2). We used these data to develop a quantitative model that distinguishes active CREs from inactive CREs.…”

Section: Sequence and Chromatin Featuresmentioning

confidence: 99%

“…ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeRegTfbsClustered/. GC-content and ORChID2 (Rohs et al 2009;Bishop et al 2011) scores were calculated from the nucleotide sequences of the CREs.…”

Section: à4mentioning

confidence: 99%

High-throughput functional testing of ENCODE segmentation predictions

et al. 2014

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The histone modification state of genomic regions is hypothesized to reflect the regulatory activity of the underlying genomic DNA. Based on this hypothesis, the ENCODE Project Consortium measured the status of multiple histone modifications across the genome in several cell types and used these data to segment the genome into regions with different predicted regulatory activities. We measured the cis-regulatory activity of more than 2000 of these predictions in the K562 leukemia cell line. We tested genomic segments predicted to be Enhancers, Weak Enhancers, or Repressed elements in K562 cells, along with other sequences predicted to be Enhancers specific to the H1 human embryonic stem cell line (H1-hESC). Both Enhancer and Weak Enhancer sequences in K562 cells were more active than negative controls, although surprisingly, Weak Enhancer segmentations drove expression higher than did Enhancer segmentations. Lower levels of the covalent histone modifications H3K36me3 and H3K27ac, thought to mark active enhancers and transcribed gene bodies, associate with higher expression and partly explain the higher activity of Weak Enhancers over Enhancer predictions. While DNase I hypersensitivity (HS) is a good predictor of active sequences in our assay, transcription factor (TF) binding models need to be included in order to accurately identify highly expressed sequences. Overall, our results show that a significant fraction (~26%) of the ENCODE enhancer predictions have regulatory activity, suggesting that histone modification states can reflect the cis-regulatory activity of sequences in the genome, but that specific sequence preferences, such as TF-binding sites, are the causal determinants of cis-regulatory activity.[Supplemental material is available for this article.]It is widely reported that specific combinations of covalent histone modifications reflect the regulatory function of underlying genomic DNA sequence (Strahl and Allis 2000). As part of the ENCODE Project, the genomic locations of a variety of covalent histone modifications were determined by chromatin immunoprecipitation sequencing (ChIP-seq) in a number of cell types and cell lines. Two studies used these data to train computational models that predict different functional regions of the human genome. These unsupervised learning algorithms, Segway (Hoffman et al. 2012) and ChromHMM Kellis 2010, 2012), take functional genomics data as input (DNase-seq; FAIRE-seq; and ChIP-seq of histone modifications, RNA polymerase II large subunit [POLR2A], and CTCF) and return segmentation classes, which are then assigned a hypothesized function using current knowledge of histone modification function. As part of the ENCODE Project, these two sets of predictions were consolidated to create a unified annotation of the entire human genome with seven functional classes in multiple cell types. These segmentations include Transcription Start Site, Promoter Flanking, Transcribed, CTCF-bound, Enhancer, Weak Enhancer, and Repressed or Inactive segments (The ENCODE Project ...

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A Map of Minor Groove Shape and Electrostatic Potential from Hydroxyl Radical Cleavage Patterns of DNA

Cited by 85 publications

References 40 publications

Probing DNA shape and methylation state on a genomic scale with DNase I

Probing DNA shape and methylation state on a genomic scale with DNase I

Massively parallel in vivo enhancer assay reveals that highly local features determine thecis-regulatory function of ChIP-seq peaks

High-throughput functional testing of ENCODE segmentation predictions

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