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Chromatin-Associated RNA Sequencing (ChAR-seq) Service

Accelerate your RNA-chromatin interaction studies with our optimized ChAR-seq service. We provide a complete "sample-to-result" solution for mapping genome-wide RNA-DNA contacts in situ. Receive publication-ready interaction matrices and rigorous QC reports designed for mechanism discovery. Research Use Only.

  • Capture nascent & chromatin-associated RNAs in situ
  • High-resolution mapping of RNA-DNA contacts
  • Comprehensive bioinformatics: Heatmaps to Circos plots
  • Ideal for lncRNA & enhancer function studies
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Schematic of Chromatin-Associated RNA Sequencing (ChAR-seq) workflow showing RNA-DNA ligation

Map Genome-Wide RNA-to-DNA Interactions with High Sensitivity

RNA molecules are not just passive messengers. They are active architects of the genome. They guide chromatin modifiers, stabilize loops, and regulate transcription. However, traditional methods often fail to capture these transient and complex interactions.

ChAR-seq solves this problem. It uses a proximity ligation approach—similar to Hi-C—to physically link RNA molecules to the DNA sequences they are close to within the 3D nuclear space.

How It Works

Our standardized ChAR-seq workflow performs the critical chemistry inside the intact nucleus:

  • Crosslinking: We treat cells with formaldehyde to "freeze" RNA and DNA in their natural positions.
  • In Situ Ligation: An oligonucleotide bridge acts as a linker, connecting the 3' end of an RNA molecule to the nearby genomic DNA.
  • Sequencing: The resulting chimeric molecules (part RNA, part DNA) are sequenced and mapped to reveal exactly where every captured RNA was located on the chromatin.

This method allows you to see the "cloud" of RNA that surrounds specific genomic loci, providing a direct view of transcriptional regulation and nuclear organization.

Why Choose ChAR-seq for Your Mechanism Study?

  • Broad Capture Range: Unbiased capture of all chromatin-associated RNAs (lncRNAs, snRNAs, nascent transcripts) without specific probes.
  • High Specificity: In situ ligation drastically reduces background noise, ensuring contacts represent genuine cellular proximity.
  • Comprehensive Data: Simultaneously obtain gene expression counts, chromatin accessibility data, and the detailed RNA-DNA interactome.
  • Defensible Evidence: Rigorous QC metrics including valid chimeric read counts and interaction ratios.

Method Comparison: ChAR-seq vs. GRID-seq vs. RADICL-seq

To help you choose the correct method for your biological question, we compare ChAR-seq with other leading technologies available in our 3D genomics portfolio.

Feature ChAR-seq GRID-seq RADICL-seq
Primary Mechanism Proximity Ligation (Oligo Bridge) Proximity Ligation (Linker) RNase H Digestion & Ligation
Bias Source 3' end bias (poly-A focused usually) Linker ligation bias Reduced enzymatic bias
Resolution High (Gene/Peak level) Moderate High
Sample Input Moderate to High (Millions of cells) Moderate Lower Input Possible
Best For... Broad discovery of RNA-DNA contacts; mapping nascent RNA. Structural validation; known interactions. Difficult samples; high-resolution contact mapping.

Unsure which is right for you? Our technical team can review your biological question (e.g., "I need to find where lncRNA X binds") and recommend the most cost-effective path. We also offer R-Loop Sequencing if your focus is specifically on RNA-DNA hybrid structures rather than spatial proximity.

Applications: From Transcription Regulation to 3D Genome Organization

Variant-to-Gene (V2G) & Enhancer Mapping

Non-coding variants often lie in enhancer regions. ChAR-seq can link enhancer-derived RNAs (eRNAs) to their target promoters, providing physical evidence connecting a disease variant to a specific gene—crucial for drug target validation.

LncRNA Functional Screening

LncRNAs are key regulators, but their targets are often unknown. ChAR-seq maps the genomic binding sites of thousands of lncRNAs in parallel, discovering if a specific lncRNA acts in cis (near its own gene) or in trans (regulating distant chromosomes).

Studying Nuclear Compartments

The nucleus is organized into active and inactive compartments. ChAR-seq data reveals how RNA molecules help organize these compartments, which is especially useful for studying nuclear speckles or nucleoli interactions.

Evolutionary & De Novo Assembly Support

For non-model organisms, ChAR-seq adds a layer of functional annotation to genome assembly, showing which scaffolds are transcriptionally active and physically associated.

Sample Requirements & Submission Guidelines

High-quality data starts with high-quality samples. ChAR-seq relies on preserving the nuclear structure, so sample preparation is the most critical step.

Sample Type Minimum Input Recommended Input Risk Level
Mammalian Cells 2 Million Cells 5–10 Million Cells Low
Animal Tissue 50 mg 100+ mg Moderate
Plant Tissue 200 mg 500+ mg High (requires nuclei isolation)

Note: We accept fresh cells (preferred) or cryopreserved/flash-frozen samples. Samples with low viability (<80%) or high degradation may lead to high background noise.

Service Workflow & Quality Control

1. Sample QC

We receive tissues, cells, or nuclei and assess viability, integrity, and suitability for cross-linking.

2. Library Construction (In Situ)

Nuclei permeabilization followed by in situ ligation of RNA to DNA using specific bridge oligonucleotides. Includes Reverse transcription and cDNA synthesis.

3. Library QC

Fragment size distribution is checked via Agilent Bioanalyzer. We run a "nano" sequencing run to check the percentage of valid chimeric reads before deep sequencing.

4. Sequencing

Illumina NovaSeq (PE150). Typically 300–600 million reads per sample, customizable based on genome size.

5. Bioinformatic Analysis

Filtering of non-chimeric reads, mapping to reference genome, removal of PCR duplicates, and generation of interaction matrices.

ChAR-seq service workflow steps

Explore Demo Results & Deliverables

  • Interaction Heatmaps: Global views of the matrix showing DNA-DNA proximity and off-diagonal signals representing RNA interacting with distant DNA.
  • Metagene Plots: Charts showing the average binding profile of RNAs around Transcription Start Sites (TSS).
  • Circos Plots: Circular diagrams showing connections between different chromosomes, highlighting trans interactions.
  • Deliverables: Clean FASTQ files, QC Report, Interaction Matrices (.cool/.hic), and Contact Lists.

ChAR-seq interaction matrix heatmap demo result showing RNA-DNA contacts

Selected Case Study: Mapping RNA-Chromatin Architecture

In a foundational study by Bell et al. (2018), researchers needed to map the interactions of all chromatin-associated RNAs in Drosophila cells. Their goal was to understand how RNAs localize to specific genomic binding sites and distinguish local versus distant regulation.

The team utilized ChAR-seq to capture in situ RNA-DNA contacts. They generated deep sequencing data to resolve high-resolution contact maps, filtering for unique chimeric reads that mapped to both the transcriptome and the genome.

The study successfully generated a genome-wide map of RNA-to-DNA contacts. They observed that most RNAs stay close to their transcription site (cis-interaction). However, specific RNAs, such as those involved in dosage compensation (roX1 and roX2), showed distinct "trans" binding patterns, spreading across the X chromosome. The interaction heatmaps clearly distinguished these specific binding patterns from the general background.

Genome-wide map of RNA-to-DNA contacts in Drosophila cells from Bell et al 2018

This case confirms that ChAR-seq is a robust tool for distinguishing between RNAs that act locally (cis) versus those that regulate distant genomic regions (trans). Our service replicates this high standard of library preparation and analysis to deliver comparable insights.

Frequently Asked Questions

References

  1. Bonetti, A., et al. Genome-Wide Technologies to Study RNA–Chromatin Interactions. Int J Mol Sci. 2020;21(12):4376.
  2. Bell, J.C., et al. Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts. eLife. 2018;7:e27024.
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