Q: What makes R-loop Cut&Tag better than DRIP-seq?

R-loop Cut&Tag requires much less input, preserves chromatin in its natural state, offers higher resolution, and reduces background compared to DRIP-seq.

Q: Can I use low amounts of clinical or frozen samples?

Yes, this service supports limited or frozen samples and is designed for low-input R-loop profiling with reliable results.

Q: Does R-loop Cut&Tag detect strand-specific R-loops?

Yes, while not inherently strand-specific, the data can be integrated with transcriptomic analyses to determine RNA strand origin.

Q: How specific is R-loop detection with Cut&Tag?

A negative control using RNase digestion confirms specificity. The method selectively profiles DNA–RNA hybrids with minimal off-target signal.

Q: What is the general workflow?

We prepare nuclei, bind a DNA–RNA hybrid recognition reagent, tether Tn5 enzyme for in situ tagging, sequence the library, and provide comprehensive bioinformatics analysis.

Q: Can R-loop Cut&Tag be validated against other R-loop mapping methods?

Yes, results are consistent with DRIPc-seq and ssDRIP-seq for cross-validation and enhanced confidence.

Q: Do I get bioinformatics outputs directly?

Yes, every project includes processed data, peak annotations, visualizations, and functional analyses suitable for publication or exploration.

Q: Which organisms can you profile?

Any species with a reference genome can be profiled. We routinely support human, animal, plant, and model organisms.

R-loop Cut&Tag Service | Low-Input, High-Resolution R-loop Profiling

Introduction

Unresolved R-loops are a major source of genome instability, contributing to transcription–replication conflicts and DNA damage. For researchers studying transcriptional regulation, chromatin biology, or disease mechanisms, precise detection of these three-stranded nucleic acid structures is essential.

Traditional assays such as DRIP-seq provide genome-wide coverage but demand large sample input and involve labor-intensive workflows. These limitations restrict their use in clinical studies, scarce material, or time-sensitive projects.

R-loop Cut&Tag overcomes these barriers by enabling a streamlined R-loop assay with minimal input requirements. This method preserves the native chromatin state, reduces background noise, and delivers high-resolution R-loop profiling suitable for both basic and applied research.

Technical Parameters of the R-loop Cut&Tag Service

Our R-loop Cut&Tag assay is optimized to ensure data accuracy, reproducibility, and compatibility with diverse research projects.

Parameter	Specification / Notes
Genome requirements	Diploid species with chromosome-level assemblies preferred; polyploid species require evaluation
Sequencing depth	Optimized coverage for genome-wide R-loop profiling with minimal background noise
Controls included	Isotype control and RNase-treated negative control to confirm signal specificity
Reproducibility	Consistent enrichment across biological replicates; suitable for comparative studies
Data quality	High signal-to-noise ratio, reduced sequencing depth, and library complexity reports

Technology	Key Feature	Typical Application Scenario
DRIP-seq service	Genome-wide coverage	Construct general R-loop distribution maps
DRIPc-seq service	Strand-specific, identifies RNA origins	Study transcriptional regulation and RNA-driven mechanisms
ssDRIP-seq service	Single-strand library prep, higher resolution	Precision mapping of genome-wide R-loops
R-loop Cut&Tag	Low input, high resolution, native-state detection	Clinical or limited samples, rapid and reproducible profiling

How the R-loop Cut&Tag Workflow Delivers High-Resolution Profiling

CD Genomics adapts the CUT&Tag platform to provide precise R-loop profiling across species. The workflow integrates DNA–RNA hybrid recognition with in situ enzymatic tagging, ensuring accurate detection while preserving chromatin integrity.

Step-by-Step Workflow

Sample preparation – Nuclei are isolated from cells or tissues to maintain chromatin context.

R-loop recognition – A specialized binding reagent targets DNA–RNA hybrid regions.

Enzyme tethering – A tethered transposase is guided to R-loop sites.

Adapter integration – DNA near R-loops is fragmented and tagged with sequencing adapters in situ.

Library construction and sequencing – Tagged fragments are processed for high-throughput sequencing.

Bioinformatics analysis – Peak calling, annotation, motif discovery, and pathway analysis complete the workflow.

R-loop Cut&Tag workflow infographic showing step-by-step R-loop assay and profiling process

Step	Deliverables / Outputs	Value for Client
Raw data QC	Cleaned FASTQ files, quality reports (Q20/Q30)	Confirms sequencing integrity
Alignment & mapping	Aligned BAM files, genome coverage statistics	Ensures accurate genome-wide R-loop detection
Peak calling	BED files of R-loop enrichment regions	Identifies functional genomic loci
Annotation	Peak distribution across promoters, gene bodies, intergenic regions	Provides biological context

Step	Deliverables / Outputs	Value for Client
Differential analysis	Volcano plots, enrichment tables	Identifies condition-specific R-loop changes
Motif discovery	Sequence motifs and logos near R-loop sites	Reveals sequence determinants of R-loop formation
Functional enrichment	GO terms, KEGG pathways linked to R-loop peaks	Connects R-loops to biological processes and disease pathways
Visualization & reporting	Heatmaps, metagene profiles, clustering, Venn diagrams	Publication-ready figures and comparative views
Custom analyses (optional)	Integration with ATAC-seq, caRNA-seq, or other omics	Tailored insights for multi-omics projects

Applications of R-loop Cut&Tag in Genome and Transcriptome Research

The R-loop Cut&Tag assay enables precise R-loop profiling across multiple research areas. By combining high resolution with low sample input requirements, this method supports both fundamental biology and translational projects.

Key Applications

Transcription regulation

Detect promoter-proximal R-loops and study RNA polymerase II pausing.

Genome stability

Identify regions of R-loop accumulation linked to DNA damage and replication stress.

Chromatin biology

Explore how R-loops interact with histone modifications and chromatin accessibility.

Noncoding RNA mechanisms

Investigate lncRNA-driven R-loop formation and its regulatory roles.

Comparative profiling

Analyse R-loop dynamics across developmental stages, treatments, or disease models.

Sample Requirements for R-loop Cut&Tag Assays

To ensure reliable results, CD Genomics specifies minimum input amounts and handling conditions for R-loop Cut&Tag profiling. Our team can also provide customized guidance for challenging or non-standard sample types.

Sample Type	Recommended Input	Notes
Cultured cells	≥ 2 × 10^6 cells	High viability preferred; cryopreserve in freezing medium
Animal tissue	≥ 200 mg	Fresh-frozen in liquid nitrogen; store at −80 °C before shipping
Plant tissue	≥ 1 g	Reference genome required; consult for polyploid or complex genomes
Other samples	Upon consultation	Protocols adapted for difficult matrices (e.g., bone, fat, low nucleic acid content)

Preservation and Transport

Cells: freeze in appropriate cryopreservation medium.
Tissues: snap-freeze in liquid nitrogen, store at −80 °C.
All samples should be shipped on dry ice following standard biosample transport guidelines.

FAQs: R-loop Cut&Tag Service

- Q: What makes R-loop Cut&Tag better than DRIP-seq?
  - R-loop Cut&Tag requires much less input, preserves chromatin in its natural state, offers higher resolution, and reduces background compared to DRIP-seq.
- Q: Can I use low amounts of clinical or frozen samples?
  - Yes, this service supports limited or frozen samples and is designed for low-input R-loop profiling with reliable results.
- Q: Does R-loop Cut&Tag detect strand-specific R-loops?
  - Yes, while not inherently strand-specific, the data can be integrated with transcriptomic analyses to determine RNA strand origin.
- Q: How specific is R-loop detection with Cut&Tag?
  - A negative control using RNase digestion confirms specificity. The method selectively profiles DNA–RNA hybrids with minimal off-target signal.
- Q: What is the general workflow?
  - We prepare nuclei, bind a DNA–RNA hybrid recognition reagent, tether Tn5 enzyme for in situ tagging, sequence the library, and provide comprehensive bioinformatics analysis.
- Q: Can R-loop Cut&Tag be validated against other R-loop mapping methods?
  - Yes, results are consistent with DRIPc-seq and ssDRIP-seq for cross-validation and enhanced confidence.
- Q: Do I get bioinformatics outputs directly?
  - Yes, every project includes processed data, peak annotations, visualizations, and functional analyses suitable for publication or exploration.
- Q: Which organisms can you profile?
  - Any species with a reference genome can be profiled. We routinely support human, animal, plant, and model organisms.

Demo

R-loop peak annotation across genomic features R-loop peaks were classified into promoters, exons, introns, and intergenic regions, providing an overview of genomic distribution.

Pie chart showing R-loop peak distribution by genomic feature Pie chart showing the proportion of R-loop peaks located in promoters, exons, introns, terminators, and intergenic regions.

Observed versus expected enrichment of R-loop peaks Bar chart comparing the observed fraction of R-loop peaks (red) with the expected fraction based on genomic length (blue).

Metagene profile of R-loop signal around TSS and TES Average R-loop peak density plotted around transcription start sites (TSS) and transcription end sites (TES), showing enrichment at gene boundaries.