caRNA-Seq Service for Chromatin-Associated RNA Profiling

CD Genomics provides professional caRNA-Seq (chromatin-associated RNA sequencing) services to capture RNA molecules bound to chromatin. Unlike conventional RNA-Seq, caRNA-Seq reveals enhancer RNAs, promoter-associated RNAs, centromeric RNAs, and other regulatory transcripts that control gene expression and chromatin organisation.

Our service helps researchers overcome challenges in studying transcriptional feedback, R-loop formation, and RNA modifications, offering high-quality datasets for epigenetics, cancer research, and biomarker discovery.

Why Choose CD Genomics caRNA-Seq?

  • Complete profiling of chromatin-associated RNAs
  • One-stop service from sample preparation to analysis
  • Optimised protocols adapted from leading publications
  • Strict quality control for reliable and reproducible results
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Visual schematic of chromatin-associated RNA interactions including R-loop and protein-mediated binding
Why caRNA-Seq Workflow Bioinformatics Demo Results Sample Requirements FAQ Case Study Related Services Inquiry

Why Chromatin-Associated RNAs Matter

While conventional RNA sequencing focuses on total or polyadenylated RNA, it often overlooks chromatin-associated RNAs (caRNAs)—a class of RNAs that remain tethered to chromatin during or after transcription. These RNAs are not transcriptional bystanders; they are integral regulators of genome structure and gene expression.

What are caRNAs?

Coding caRNAs: nascent pre-mRNAs that remain anchored during transcription

Non-coding caRNAs: lncRNAs, enhancer RNAs (eRNAs), promoter-associated RNAs (paRNAs), centromeric RNAs (cenRNAs), and other structured regulatory RNAs

These RNAs engage in two primary types of interaction with chromatin:

Direct interaction: caRNAs form R-loop structures with DNA at promoter, enhancer, or terminator regions

Indirect interaction: caRNAs interact via RNA-binding proteins and chromatin modifiers, influencing transcription factor recruitment and epigenetic modification

Why it matters:

caRNAs regulate transcription initiation, pausing, elongation, and termination

They influence chromatin state, epigenetic memory, and genome stability

Aberrant caRNA activity and modification (e.g., m6A methylation) are linked to cancer progression, making them high-value targets for mechanistic studies and biomarker discovery

By capturing this regulatory layer, caRNA-Seq enables insights that conventional RNA-Seq simply cannot provide.

Why Choose caRNA-Seq?

Addressing Limitations of Conventional RNA-Seq

Standard RNA-Seq captures total or poly(A)+ RNA, but it fails to detect RNAs that remain bound to chromatin during transcription. These chromatin-associated RNAs (caRNAs) are often short-lived, low-abundance, or non-polyadenylated—making them invisible to traditional methods.

Key research challenges include:

Missing enhancer RNAs (eRNAs), paRNAs, and repeat RNAs

Inability to map nascent RNA-DNA hybrids like R-loops

Lack of reproducible workflows tailored to caRNA detection

What Makes caRNA-Seq Different?

CD Genomics' caRNA-Seq service is designed to overcome these challenges by selectively enriching chromatin-bound RNA fractions and applying high-resolution sequencing combined with expert bioinformatics.

Key advantages of caRNA-Seq:

Targets both coding and non-coding caRNAs

Detects direct (R-loop) and indirect (protein-mediated) chromatin interactions

Compatible with downstream modification analysis (e.g., m6A on caRNA)

Captures regulatory RNAs that impact transcription, epigenetics, and chromatin state

Applications Across Biological Research

Cancer Biology: Identify dysregulated eRNAs or cenRNAs involved in chromosomal instability

Epigenetics: Study RNA-guided chromatin remodeling

Functional Genomics: Reveal regulatory roles of low-abundance RNAs

R-loop Mapping: Complement DRIPc-Seq and ssDRIP-Seq with RNA-layer insights

Biomarker Discovery: Explore novel RNA features as diagnostic or prognostic tools

caRNA-Seq Workflow

CD Genomics has developed an optimized and reproducible caRNA-Seq workflow to ensure selective enrichment of chromatin-associated RNAs and high-quality downstream sequencing. Our process is adapted from peer-reviewed protocols and refined through in-house validation.

Nuclear Isolation

Cells or tissues are gently lysed to preserve nuclear integrity. The nuclei are then purified using a sucrose cushion to remove cytoplasmic RNA contaminants.

Chromatin Fractionation

Purified nuclei are subjected to a lysis buffer under agitation to disrupt the nuclear envelope. This releases chromatin-associated components, including RNA bound to DNA and chromatin-associated proteins.

caRNA Extraction

Total RNA is extracted from the chromatin fraction. This includes enhancer RNAs (eRNAs), promoter-associated RNAs (paRNAs), centromeric RNAs (cenRNAs), antisense RNAs, and other regulatory transcripts.

Library Preparation

We remove ribosomal RNA (rRNA) to enrich for functional non-coding and nascent RNAs. Libraries are then constructed using strand-specific protocols to retain transcriptional directionality.

High-Throughput Sequencing

Sequencing is performed on Illumina platforms to generate high-depth datasets, ensuring reliable quantification of low-abundance caRNAs.

Bioinformatics Analysis

Our expert team performs read alignment, caRNA identification and classification, differential expression analysis, and pathway enrichment. Custom analyses such as integration with mRNA-Seq or caRNA modification profiling are available upon request.

Stepwise diagram of the caRNA-Seq workflow, from nuclear extraction to high-throughput sequencing

Bioinformatics Deliverables

Analysis Module Description
Raw Data QC Adapter trimming, quality filtering, read length distribution
Mapping & Transcript Assembly Alignment to reference genome; transcript assembly for caRNA classification
caRNA Classification Identification of coding vs. non-coding caRNAs (e.g., lncRNA, eRNA, paRNA)
Expression Quantification TPM/FPKM calculation at gene and transcript level
Differential Expression Analysis Statistical comparison between groups to identify differentially expressed caRNAs
Functional Enrichment GO term and KEGG pathway enrichment of nearby genes within 1 kb of caRNAs
Data Visualization Heatmaps, volcano plots, scatter plots, classification pie charts
Custom Analysis (optional) m6A profiling, R-loop mapping (via DRIPc-Seq), co-expression with mRNA

Demo Results

caRNA classification summary:

Pie charts showing the proportion of caRNA types detected (e.g., lncRNA, eRNA, cenRNA, paRNA, snoRNA).

Heatmap of differential caRNA expression:

Clustering of caRNAs across samples, revealing expression patterns and sample relationships.

Volcano plot of DE-caRNAs:

Visual display of fold change and significance for differentially expressed caRNAs.

GO functional enrichment:

Bar plots showing enriched biological processes and molecular functions of genes near DE-caRNAs.

KEGG pathway enrichment:

Pathways related to chromatin regulation, RNA processing, or transcription modulation are highlighted.

Scatter plot of group comparisons:

Overview of gene expression shifts between experimental groups.

Optional analysis:

m6A-calling on caRNA (from MeRIP-seq), DRIPc-Seq integration to link R-loops and caRNAs, or correlation with mRNA-Seq datasets.

Sample Requirements

Sample Type Minimum Amount Required Notes
Cultured Cells ≥ 5 × 10⁷ cells Viable or cryopreserved; avoid freeze-thaw cycles
Tissue ≥ 200 mg Fresh-frozen preferred; heart, liver, spleen, etc.
Purified caRNA ≥ 2 µg total RNA High-quality, free of genomic DNA contamination

Frequently Asked Questions (FAQ)

Case Study: Chromatin-Associated RNAs Shape 3D Genome Architecture through Compartment and Loop Interactions

Chromatin-associated RNAs (caRNAs) are not only regulatory molecules but also physical scaffolds that may influence 3D genome structure. Although non-coding RNAs like lncRNAs have been linked to chromatin remodeling, the global relationship between caRNAs and chromatin topology had not been fully elucidated. This study aimed to determine how caRNAs influence spatial genome organisation in human cells.

Researchers combined chromatin-associated RNA sequencing (caRNA-seq) with Hi-C to explore caRNA distribution and function in IMR90 cells.

Key technical approaches included:

  • Fractionation and sequencing of chromatin-associated RNA (caRNA-seq)
  • Genome-wide Hi-C to detect A/B compartments, TADs, and loops
  • RNA-seq and chromatin-bound nascent transcript mapping
  • CRISPR-mediated depletion of specific caRNAs
  • Bioinformatics integration of RNA abundance with chromatin contact maps
  • caRNAs preferentially localized to active (A) chromatin compartments, and their abundance strongly correlated with compartment identity.
  • Depletion of specific caRNAs (e.g., U2 snRNA) led to compartment switching, revealing caRNAs as active determinants of chromatin state.
  • caRNA-rich regions aligned with enhancer-promoter loops, and knockdown disrupted loop strength and contact frequency.
  • RNA-binding protein motif analysis revealed a distinct regulatory code for chromatin-interacting RNAs versus cytoplasmic RNAs.

Hi-C contact map showing reduced chromatin loop interactions after U2 RNA depletion Depletion of chromatin-associated U2 RNA reduces enhancer–promoter loop strength, demonstrating functional impact of caRNAs on 3D genome structure.

This study demonstrated that chromatin-associated RNAs not only mark active genome compartments but also functionally modulate chromatin loops and nuclear architecture. caRNA-seq was instrumental in capturing spatial RNA occupancy and revealing its genome-wide correlation with structural features. These findings support the use of caRNA-seq for dissecting the RNA–chromatin axis in epigenomics and chromatin biology.

Demo

Bar chart of GO biological process enrichment near differentially expressed chromatin-associated RNAs GO enrichment analysis of protein-coding genes located near differentially expressed caRNAs. Terms related to stress response, post-translational modification, and GTPase signaling are significantly enriched.

Bar plot of KEGG pathway enrichment for genes adjacent to differentially expressed chromatin-associated RNAs KEGG pathway enrichment analysis of genes near differentially expressed caRNAs. Enriched pathways include amino acid metabolism, PPAR signalling, and complement cascades.

Heatmap of caRNA expression clustering across biological replicates in different conditions Hierarchical clustering heatmap of differentially expressed chromatin-associated RNAs. Red indicates upregulation, blue indicates downregulation. Samples cluster by expression similarity.

References:

  1. Kang Z, Li R, Liu C, Dong X, Hu Y, Xu L, Liu X, Xiang Y, Gao L, Si W, Wang L, Li Q, Zhang L, Wang H, Yang X, Liu J. m6A-modified cenRNA stabilizes CENPA to ensure centromere integrity in cancer cells. Cell. 2024 Oct 17;187(21):6035-6054.e27. doi: 10.1016/j.cell.2024.08.040. Epub 2024 Sep 20. PMID: 39305902.
  2. Calandrelli, R., Wen, X., Charles Richard, J.L. et al. Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells. Nat Commun 14, 6519 (2023).
  3. Wu R, Sun C, Chen X, Yang R, Luan Y, Zhao X, Yu P, Luo R, Hou Y, Tian R, Bian S, Li Y, Dong Y, Liu Q, Dai W, Fan Z, Yan R, Pan B, Feng S, Wu J, Chen F, Yang C, Wang H, Dai H, Shu M. NSUN5/TET2-directed chromatin-associated RNA modification of 5-methylcytosine to 5-hydroxymethylcytosine governs glioma immune evasion. Proc Natl Acad Sci U S A. 2024 Apr 2;121(14):e2321611121. doi: 10.1073/pnas.2321611121. Epub 2024 Mar 28. PMID: 38547058; PMCID: PMC10998593.


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