DNA elements such as genes and their regulatory regions must become accessible for protein binding when transcription is activated, which requires reorganization of the nucleosomes that fold the DNA into chromatin fibers. MNase-seq has been instrumental in uncovering the interplay between gene activity and chromatin organization by mapping the average nucleosome occupancy in populations of cells. However, better mechanistic understanding can be obtained from assays that can map nucleosomes along long strands of DNA at single-molecule resolution and without averaging. Here, we show that the combination of DNA methylation, long-read Nanopore sequencing and a novel nucleosome mapping algorithm based on statistical physics results in precise nucleosome footprinting at the single-molecule level over DNA loci exceeding several 10s of kbp. Accurate nucleosome mapping was verified in vitro, using chromatin reconstituted on tandem arrays of nucleosome positioning elements. Genome-wide application on Saccharomyces cerevisiae grown in different transcriptional conditions revealed large heterogeneity of nucleosome distributions upon transcription activation of the model GAL locus. Moreover, neighboring repeats of the ribosomal transcript RDN1 featured long-range correlations in nucleosome occupancy that we attribute to differential transcriptional activity. This enhanced assay allows for both meta-occupancy analysis, as well as in-depth single-fiber comparisons of local chromatin aberrations in context of transcription, DNA repair and other processes, illustrating the added value of single-molecule nucleosome mapping using long-read sequencing compared to traditional population averaged maps.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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