Journal article
Single-molecule long-read sequencing reveals the chromatin basis of gene expression
Genome research, Vol.29(8), pp.1329-1342
08/2019
DOI: 10.1101/gr.251116.119
PMCID: PMC6673713
PMID: 31201211
Abstract
Genome-wide chromatin accessibility and nucleosome occupancy profiles have been widely investigated, while the long-range dynamics remain poorly studied at the single-cell level. Here, we present a new experimental approach, methyltransferase treatment followed by single-molecule long-read sequencing (MeSMLR-seq), for long-range mapping of nucleosomes and chromatin accessibility at single DNA molecules and thus achieve comprehensive-coverage characterization of the corresponding heterogeneity. MeSMLR-seq offers direct measurements of both nucleosome-occupied and nucleosome-evicted regions on a single DNA molecule, which is challenging for many existing methods. We applied MeSMLR-seq to haploid yeast, where single DNA molecules represent single cells, and thus we could investigate the combinatorics of many (up to 356) nucleosomes at long range in single cells. We illustrated the differential organization principles of nucleosomes surrounding the transcription start site for silent and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNA-seq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively in a highly heterogeneous scenario. Moreover, we quantified the openness of promoters and investigated the coupled chromatin changes of adjacent genes at single DNA molecules during transcription reprogramming. In addition, we revealed the coupled changes of chromatin accessibility for two neighboring glucose transporter genes in response to changes in glucose concentration.
Details
- Title: Subtitle
- Single-molecule long-read sequencing reveals the chromatin basis of gene expression
- Creators
- Yunhao Wang - The Ohio State UniversityAnqi Wang - The Ohio State UniversityZujun Liu - The Ohio State UniversityAndrew L Thurman - University of IowaLinda S Powers - University of IowaMeng Zou - University of IowaYue Zhao - The Ohio State UniversityAdam Hefel - University of IowaYunyi Li - University of IowaJoseph Zabner - University of IowaKin Fai Au - Department of Biostatistics, University of Iowa, Iowa City, Iowa 52242, USA
- Resource Type
- Journal article
- Publication Details
- Genome research, Vol.29(8), pp.1329-1342
- DOI
- 10.1101/gr.251116.119
- PMID
- 31201211
- PMCID
- PMC6673713
- ISSN
- 1549-5469
- eISSN
- 1549-5469
- Grant note
- P30 ES005605 / NIEHS NIH HHS P30 DK054759 / NIDDK NIH HHS R01 HG008759 / NHGRI NIH HHS T32 HL007638 / NHLBI NIH HHS
- Language
- English
- Date published
- 08/2019
- Academic Unit
- Pulmonary, Critical Care, and Occupational Medicine; Internal Medicine
- Record Identifier
- 9984359688102771
Metrics
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