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Precise genome-wide mapping of single nucleosomes and linkers in vivo.

ABSTRACT: We developed a chemical cleavage method that releases single nucleosome dyad-containing fragments, allowing us to precisely map both single nucleosomes and linkers with high accuracy genome-wide in yeast. Our single nucleosome positioning data reveal that nucleosomes occupy preferred positions that differ by integral multiples of the DNA helical repeat. By comparing nucleosome dyad positioning maps to existing genomic and transcriptomic data, we evaluated the contributions of sequence, transcription, and histones H1 and H2A.Z in defining the chromatin landscape. We present a biophysical model that neglects DNA sequence and shows that steric occlusion suffices to explain the salient features of nucleosome positioning.

SUBMITTER: Chereji RV

PROVIDER: S-EPMC5807854 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Precise genome-wide mapping of single nucleosomes and linkers in vivo.

Chereji Răzvan V RV Ramachandran Srinivas S Bryson Terri D TD Henikoff Steven S

Genome biology 20180209 1

We developed a chemical cleavage method that releases single nucleosome dyad-containing fragments, allowing us to precisely map both single nucleosomes and linkers with high accuracy genome-wide in yeast. Our single nucleosome positioning data reveal that nucleosomes occupy preferred positions that differ by integral multiples of the DNA helical repeat. By comparing nucleosome dyad positioning maps to existing genomic and transcriptomic data, we evaluated the contributions of sequence, transcrip ...[more]

PMID: 29426353

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Project description:MOTIVATION:RNAs fold into complex structures that are integral to the diverse mechanisms underlying RNA regulation of gene expression. Recent development of transcriptome-wide RNA structure profiling through the application of structure-probing enzymes or chemicals combined with high-throughput sequencing has opened a new field that greatly expands the amount of in vitro and in vivo RNA structural information available. The resultant datasets provide the opportunity to investigate RNA structural information on a global scale. However, the analysis of high-throughput RNA structure profiling data requires considerable computational effort and expertise. RESULTS:We present a new platform, StructureFold, that provides an integrated computational solution designed specifically for large-scale RNA structure mapping and reconstruction across any transcriptome. StructureFold automates the processing and analysis of raw high-throughput RNA structure profiling data, allowing the seamless incorporation of wet-bench structural information from chemical probes and/or ribonucleases to restrain RNA secondary structure prediction via the RNAstructure and ViennaRNA package algorithms. StructureFold performs reads mapping and alignment, normalization and reactivity derivation, and RNA structure prediction in a single user-friendly web interface or via local installation. The variation in transcript abundance and length that prevails in living cells and consequently causes variation in the counts of structure-probing events between transcripts is accounted for. Accordingly, StructureFold is applicable to RNA structural profiling data obtained in vivo as well as to in vitro or in silico datasets. StructureFold is deployed via the Galaxy platform. AVAILABILITY AND IMPLEMENTATION:StructureFold is freely available as a component of Galaxy available at: https://usegalaxy.org/. CONTACT:yxt148@psu.edu or sma3@psu.edu SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Project description:The eukaryotic genome, first packed into nucleosomes of about 150 bp around the histone core, is organized into euchromatin and heterochromatin, corresponding to the A and B compartments, respectively. Here, we asked if individual nucleosomes in vivo know where to go. That is, do mono-nucleosomes by themselves contain A/B compartment information, associated with transcription activity, in their biophysical properties? We purified native mono-nucleosomes to high monodispersity and used physiological concentrations of biological polyamines to determine their condensability. The chromosomal regions known to partition into A compartments have low condensability and vice versa. In silico chromatin polymer simulations using condensability as the only input showed that biophysical information needed to form compartments is all contained in single native nucleosomes and no other factors are needed. Condensability is also strongly anticorrelated with gene expression, and especially so near the promoter region and in a cell type dependent manner. Therefore, individual nucleosomes in the promoter know whether the gene is on or off, and that information is contained in their biophysical properties. Comparison with genetic and epigenetic features suggest that nucleosome condensability is a very meaningful axis onto which to project the high dimensional cellular chromatin state. Analysis of condensability using various condensing agents including those that are protein-based suggests that genome organization principle encoded into individual nucleosomes is electrostatic in nature. Polyamine depletion in mouse T cells, by either knocking out ornithine decarboxylase (ODC) or inhibiting ODC, results in hyperpolarized condensability, suggesting that when cells cannot rely on polyamines to translate biophysical properties of nucleosomes to control gene expression and 3D genome organization, they accentuate condensability contrast, which may explain dysfunction known to occur with polyamine deficiency.

Dataset Information

Precise genome-wide mapping of single nucleosomes and linkers in vivo.

Publications

Precise genome-wide mapping of single nucleosomes and linkers in vivo.

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