NOMePlot: analysis of DNA methylation and nucleosome occupancy at the single molecule

Study on chromatin regulation patterns of expression vectors in the PhiC31 integration site

The PhiC31 integration system allows for targeted and efficient transgene integration and expression by recognizing pseudo attP sites in mammalian cells and integrating the exogenous genes into the open chromatin regions of active chromatin. In order to investigate the regulatory patterns of efficient gene expression in the open chromatin region of PhiC31 integration, this study utilized Ubiquitous Chromatin Opening Element (UCOE) and activating RNA (saRNA) to modulate the chromatin structure in the promoter region of the PhiC31 integration vector. The study analysed the effects of DNA methylation and nucleosome occupancy changes in the integrated promoter on gene expression levels. The results showed that for the OCT4 promoter with moderate CG density, DNA methylation had a smaller impact on expression compared to changes in nucleosome positioning near the transcription start site, which was crucial for enhancing downstream gene expression. On the other hand, for the SOX2 promoter with high CG density, increased methylation in the CpG island upstream of the transcription start site played a key role in affecting high expression, but the positioning and clustering of nucleosomes also had an important influence. In conclusion, analysing the DNA methylation patterns, nucleosome positioning, and quantity distribution of different promoters can determine whether the PhiC31 integration site possesses the potential to further enhance expression or overcome transgene silencing effects by utilizing chromatin regulatory elements.

Orphan CpG islands amplify poised enhancer regulatory activity and determine target gene responsiveness

CpG islands (CGIs) represent a widespread feature of vertebrate genomes, being associated with ~70% of all gene promoters. CGIs control transcription initiation by conferring nearby promoters with unique chromatin properties. In addition, there are thousands of distal or orphan CGIs (oCGIs) whose functional relevance is barely known. Here we show that oCGIs are an essential component of poised enhancers that augment their long-range regulatory activity and control the responsiveness of their target genes. Using a knock-in strategy in mouse embryonic stem cells, we introduced poised enhancers with or without oCGIs within topologically associating domains harboring genes with different types of promoters. Analysis of the resulting cell lines revealed that oCGIs act as tethering elements that promote the physical and functional communication between poised enhancers and distally located genes, particularly those with large CGI clusters in their promoters. Therefore, by acting as genetic determinants of gene-enhancer compatibility, CGIs can contribute to gene expression control under both physiological and potentially pathological conditions.

Methylscaper: an R/shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data

SUMMARY

Differential DNA methylation and chromatin accessibility are associated with disease development, particularly cancer. Methods that allow profiling of these epigenetic mechanisms in the same reaction and at the single-molecule or single-cell level continue to emerge. However, a challenge lies in jointly visualizing and analyzing the heterogeneous nature of the data and extracting regulatory insight. Here, we present methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin accessibility landscapes. Methylscaper implements a weighted principal component analysis that orders DNA molecules, each providing a record of the chromatin state of one epiallele, and reveals patterns of nucleosome positioning, transcription factor occupancy, and DNA methylation. We demonstrate methylscaper's utility on a long-read, single-molecule methyltransferase accessibility protocol for individual templates (MAPit-BGS) dataset and a single-cell nucleosome, methylation, and transcription sequencing (scNMT-seq) dataset. In comparison to other procedures, methylscaper is able to readily identify chromatin features that are biologically relevant to transcriptional status while scaling to larger datasets.

AVAILABILITY AND IMPLEMENTATION

Methylscaper, is implemented in R (version > 4.1) and available on Bioconductor: https://bioconductor.org/packages/methylscaper/, GitHub: https://github.com/rhondabacher/methylscaper/, and Web: https://methylscaper.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.