Microfluidic Single-Cell CUT&Tag Services
High-throughput single-cell chromatin profiling of histone modifications and transcription factor binding via droplet-based microfluidics — resolve cell-type-specific regulatory landscapes across tens of thousands of single cells, jointly profile histone marks and transcriptomes from the same cell with Paired-Tag, and map multiple chromatin targets in parallel for combinatorial regulatory state annotation.
Why CD Genomics for microfluidic scCUT&Tag:
- Droplet-based high throughput — microfluidic droplet encapsulation captures thousands to tens of thousands of single nuclei per run, enabling deep sampling of rare cell populations and heterogeneous tissues
- Paired-Tag multimodal profiling — jointly profile histone modifications and whole transcriptome from the same single cell, directly linking chromatin state to gene expression for regulatory network inference
- Multi-target flexibility — profile histone modifications (H3K27ac, H3K4me3, H3K27me3, H3K4me1, H3K36me3, and more), transcription factors, or chromatin-associated proteins from parallel or the same samples
- Streamlined antibody-guided workflow — pA-Tn5 fusion protein directs tagmentation to target-specific chromatin features, delivering high signal-to-noise enrichment with substantially lower cell input requirements than ChIP-seq
How Microfluidic Droplet-Based scCUT&Tag Works
Microfluidic droplet-based single-cell CUT&Tag combines antibody-guided chromatin profiling with high-throughput droplet microfluidics. Unlike microwell-based platforms that rely on gravity-driven cell settling, droplet microfluidics encapsulates single nuclei in nanoliter-scale oil-water emulsion droplets together with barcoded gel beads — enabling simultaneous processing of thousands to tens of thousands of single cells in a single run.
The CUT&Tag chemistry uses a protein A-Tn5 (pA-Tn5) fusion protein: protein A binds the Fc region of the target antibody, positioning the Tn5 transposase at antibody-bound chromatin sites. Upon magnesium activation, Tn5 simultaneously fragments the DNA and inserts sequencing adapters at these targeted loci — achieving substantially higher signal-to-noise ratios than ChIP-seq while requiring far fewer input cells.
In the droplet microfluidic workflow, antibody-stained and tagmented nuclei are co-encapsulated with oligonucleotide-barcoded gel beads in aqueous droplets suspended in oil. Within each droplet, cell-specific barcodes are released and ligated to the tagmented chromatin fragments. For Paired-Tag multimodal experiments, a bridge adapter on the pA-Tn5 complex enables simultaneous capture of both chromatin fragments for histone modification profiling and mRNA for transcriptome profiling from the same single cell — providing direct, cell-by-cell linkage between chromatin state and gene expression.
| Key Platform Specifications | |
|---|---|
| Capture mechanism | Droplet microfluidics — oil-water emulsion encapsulation |
| Cell throughput range | 1,000–20,000 nuclei per channel; multiple channels per run |
| Target types | Histone modifications (H3K27ac, H3K4me3, H3K27me3, H3K4me1, H3K36me3, H3K9me3), transcription factors, chromatin-associated proteins |
| Multi-target capability | Parallel profiling of multiple histone marks from matched samples for combinatorial chromatin state annotation |
| Multi-omics capability | Paired-Tag: simultaneous histone modification + whole transcriptome (WTA) from the same single cell |
| Sample types | Fresh or cryopreserved single-cell suspensions, primary tissues, cultured cells; nuclei-based protocol compatible with frozen tissue |
| Sequencing | Illumina paired-end 50×50 bp; 25,000–50,000 read pairs per cell recommended |
| Data pipeline | bwa-mem2 → sinto → MACS2/SEACR → Signac → chromVAR |
Service Workflow
- Study Design and Antibody Selection
Target antibodies are evaluated for CUT&Tag compatibility, and experimental design is optimized for target mark, sample type, and desired throughput. For Paired-Tag projects, RNA integrity and chromatin quality are assessed. QC Checkpoint: Antibody specificity validation and nuclei isolation optimization.
- Nuclei Isolation and Antibody Staining
Nuclei are isolated from fresh or cryopreserved samples. Permeabilized nuclei are incubated with target-specific primary antibody, followed by pA-Tn5 fusion protein binding. For Paired-Tag experiments, the pA-Tn5 complex carries a bridge adapter for concurrent mRNA capture. QC Checkpoint: Nuclei yield, morphology, and antibody labeling efficiency.
- Tagmentation and Droplet Encapsulation
Magnesium-activated tagmentation fragments antibody-bound chromatin and inserts sequencing adapters. Tagmented nuclei are loaded onto the microfluidic chip for co-encapsulation with barcoded gel beads in nanoliter-scale aqueous droplets within an oil emulsion. Each droplet functions as an independent single-cell reaction chamber. QC Checkpoint: Droplet quality, nuclei encapsulation rate, and barcode viability.
- In-Droplet Barcoding and Library Preparation
Cell-specific barcodes are released from gel beads and ligated to tagmented chromatin fragments within droplets. For Paired-Tag runs, reverse transcription is performed simultaneously to capture mRNA. After demulsification, libraries are amplified, purified, size-selected, and quantified. QC Checkpoint: Library fragment size distribution on Bioanalyzer, concentration, and adapter-dimer levels.
- Sequencing
Libraries are sequenced on Illumina platforms (NovaSeq or NextSeq series) at the recommended depth, paired-end 50×50 bp. For Paired-Tag experiments, separate DNA (chromatin) and RNA (transcriptome) libraries are sequenced. QC Checkpoint: Q30 scores ≥85%, sequencing saturation, and per-cell read distribution.
- Primary Data Processing
Raw FASTQ files are processed: read quality filtering, bwa-mem2 alignment (MAPQ ≥30), sinto fragment generation, MACS2 or SEACR peak calling, and Signac cell-by-peak matrix construction. For Paired-Tag data, transcriptomic reads are processed in parallel. QC Checkpoint: FRiP, TSS enrichment for promoter-associated marks, fragment size distribution by target, and valid cell barcode count.
- Bioinformatics Analysis and Data Delivery
Secondary analysis includes TF-IDF + LSI dimensionality reduction, UMAP/t-SNE clustering, cell-type annotation, differential peak analysis, chromVAR TF motif enrichment, and for Paired-Tag, integrated chromatin state–gene expression correlation. QC Checkpoint: Final data review against project specifications before delivery.
Sample Requirements
| Requirement | Specification |
|---|---|
| Sample type | Fresh or cryopreserved single-cell suspensions, primary tissues, cultured cells; nuclei-based protocol compatible with frozen tissue |
| Species | Human, mouse, and additional species (case-by-case evaluation) |
| Cell viability | >80% viable cells recommended; nuclei isolation protocols are optimized per sample type |
| Cell input range | 1,000–20,000 nuclei per sample; higher throughput available for multi-sample pooling |
| Target antibody | Validated primary antibody against histone modification or transcription factor; antibody qualification included in project workflow |
| Multi-target studies | Multiple antibodies can be profiled from parallel aliquots of the same specimen |
| Buffer | Optimized nuclei suspension and antibody binding buffers |
| Shipping | Fresh tissue in transport medium on wet ice; cryopreserved cells on dry ice; frozen tissue on dry ice |
Common targets successfully profiled include histone modifications (H3K27ac, H3K4me3, H3K27me3, H3K4me1, H3K36me3, H3K9me3) and transcription factors across brain, spleen, lymph node, lung, liver, kidney, tumor biopsies, PBMCs, and sorted cell populations. For Paired-Tag multimodal experiments, samples are assessed for both chromatin integrity and RNA quality during project planning.
Bioinformatics Analysis
All microfluidic scCUT&Tag projects include a standard bioinformatics pipeline. Analysis scope is matched to your experimental design, target mark, and biological question.
Standard Analysis (Included)
- Raw data QC and fragment-level quality assessment (fragment size distribution, FRiP, TSS enrichment for promoter-associated marks)
- Read alignment, cell barcode demultiplexing, and data filtering
- Peak calling (MACS2 or SEACR) and peak annotation — genomic distribution: promoter, exon, intron, intergenic
- Cell-by-peak matrix construction and low-quality cell filtering
- Dimensionality reduction (TF-IDF normalization → LSI)
- Unsupervised clustering with UMAP/t-SNE visualization
- Cell-type annotation using chromatin modification signatures
- Differential peak analysis between cell types or experimental conditions
- For Paired-Tag projects: parallel scRNA-seq analysis — clustering, marker gene identification, differential expression
- QC report with sequencing metrics, cell statistics, and sample-level summaries
Advanced Analysis (Optional)
- Transcription factor motif enrichment and TF activity deviation analysis (chromVAR)
- Differential peak-associated gene GO/KEGG pathway enrichment
- Pseudotime trajectory inference and cell-state transition analysis
- For Paired-Tag: integrated chromatin state–gene expression correlation, enhancer–gene pairing, and regulatory network inference
- Multi-target integration: joint analysis of multiple histone marks from parallel samples for combinatorial chromatin state annotation
- Integration with external scRNA-seq, scATAC-seq, or spatial transcriptomics data
- Custom visualization — interactive HTML reports, publication-quality figures
Analysis deliverables are compatible with R (Signac, Seurat, chromVAR, ArchR), Python (Scanpy, epiScanpy, scvi-tools), and Loupe Browser. All analysis parameters, software versions, and intermediate files are documented for reproducibility.
Deliverables
| Deliverable | Description |
|---|---|
| Raw sequencing data | Demultiplexed FASTQ files for CUT&Tag and, if applicable, transcriptome libraries |
| Processed peak matrix | Cell-by-peak count matrix in standard formats (h5ad, mtx, h5) |
| Gene expression matrix (Paired-Tag) | Cell-by-gene count matrix for simultaneous transcriptome profiling |
| Peak annotation file | Genomic annotation of called peaks — promoter, exon, intron, intergenic, TSS-proximal |
| Cell metadata | Cell-level QC metrics, cluster assignments, cell-type annotations, and modality labels |
| Clustering report | UMAP/t-SNE visualizations, cluster-specific peak heatmaps, annotation summaries |
| Differential peak tables | Differentially enriched peaks between cell types or conditions, with fold changes, adjusted p-values, and associated gene annotations |
| Integrated analysis report (Paired-Tag) | Chromatin state–gene expression correlation, enhancer–gene pair predictions, regulatory network maps |
| Multi-target chromatin state report (if ordered) | Combinatorial annotation of active promoters, active enhancers, poised enhancers, Polycomb-repressed, and heterochromatin regions |
| TF motif enrichment report (if ordered) | chromVAR TF motif deviation scores, ranked motif tables, per-cell motif activity matrices |
| Bioinformatics report | Methods documentation, full QC metrics, analysis parameter logs, and publication-ready figures |
| Data archive | All intermediate analysis files, scripts, and processing logs for reproducibility |
Applications
Tumor heterogeneity and epigenetic subclone detection
Map histone modification landscapes across thousands of intratumoral cells — identify rare epigenetic subclones distinguished by H3K27me3 silencing patterns or H3K27ac enhancer activation states. Paired-Tag enables direct correlation of chromatin state with transcriptomic output in the same cell, revealing which epigenetic subclones are transcriptionally active drivers of drug resistance or metastasis.
Immunology and immune cell epigenomics
Profile histone modification landscapes across immune cell subsets at scale — naive, effector, memory, and exhausted states. H3K4me1+H3K27ac co-profiling distinguishes poised from active enhancers during immune activation and differentiation. The high cell throughput of droplet-based capture enables deep sampling of rare immune populations without FACS enrichment.
Developmental biology and cell fate specification
Track histone modification dynamics along developmental trajectories at single-cell resolution. Resolve bivalent promoter states (H3K4me3+H3K27me3) that mark lineage-primed genes in stem and progenitor cells. Paired-Tag links chromatin state transitions directly to transcriptional changes during cell fate commitment.
Neuroscience and brain cell atlas
Profile neuron- and glia-specific histone modification patterns from complex brain regions at scale. Droplet-based throughput enables systematic sampling of dozens of neuronal subtypes from a single brain region. Nuclei-based protocols are compatible with frozen brain tissue banks — see snRNA Sequencing Services for matched transcriptomic profiling.
Drug development and epigenetic target engagement
Evaluate drug-induced chromatin remodeling at single-cell resolution across large cell populations — determine population-level response heterogeneity to HDAC inhibitors, EZH2 inhibitors, or other epigenetic drugs. scCUT&Tag directly measures the histone modification changes induced by treatment, providing quantitative target engagement evidence.
Multi-target combinatorial chromatin state annotation
Profiling multiple histone marks from parallel aliquots enables genome-wide chromatin state annotation at single-cell resolution — distinguishing active promoters, active enhancers, poised enhancers, Polycomb-repressed regions, transcribed gene bodies, and heterochromatin. This provides a regulatory annotation far more complete than any single mark. See Spatial Epigenomics Services for spatial chromatin state mapping.
Platform Selection: Droplet Microfluidics vs. BD Rhapsody Microwell for scCUT&Tag
CD Genomics offers scCUT&Tag on two complementary platforms. The choice depends on your study design priorities — throughput and Paired-Tag multi-omics vs. batch effect control and gentle nuclei handling.
| Feature | Droplet Microfluidic scCUT&Tag | BD Rhapsody scCUT&Tag |
|---|---|---|
| Capture mechanism | Pressure-based droplet encapsulation in oil-water emulsion | Gravity-based microwell settling |
| Throughput | 1,000–20,000 nuclei per channel; scalable multi-channel | 500–50,000 nuclei per cartridge lane |
| Sample multiplexing | Limited native multiplexing | Up to 6 samples per lane via antibody-oligo tags |
| Batch effect control | Requires computational batch correction | Inherent — all samples in a single reaction |
| Multi-omics | Paired-Tag: histone + mRNA from same single cell | CUT&Tag + mRNA (WTA) from same nuclei |
| Multi-target | Parallel aliquots for multiple antibodies | Parallel aliquots for multiple antibodies |
| Nuclei shear stress | Moderate — microfluidic channels | Lower — gravity settling, no shear stress |
| Best for | Large-scale discovery, rare population detection, Paired-Tag multi-omics | Multi-condition comparisons, fragile samples, batch-sensitive study designs |
When to choose droplet microfluidics: Your study requires high cell throughput for deep sampling of heterogeneous populations, or you need Paired-Tag multimodal profiling linking histone state to transcription in the same single cell.
When to choose BD Rhapsody microwell: Your study design involves multiple samples, conditions, or time points where batch effects are the primary concern, or your cell types are fragile and sensitive to microfluidic shear stress. See BD Rhapsody Single-Cell CUT&Tag Services for the microwell-based workflow.
Both platforms are available at CD Genomics. For chromatin accessibility profiling, see BD Rhapsody Single-Cell ATAC-seq Services and Single-Cell ATAC Sequencing Services.
Frequently Asked Questions (FAQ)
References
- Kaya-Okur HS, Wu SJ, Codomo CA, et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nature Communications. 2019;10:1930. DOI: 10.1038/s41467-019-09982-5.
- Bartosovic M, Kabbe M, Castelo-Branco G. Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nature Biotechnology. 2021;39(7):825–835. DOI: 10.1038/s41587-021-00869-9.
- Xie Y, Zhu C, Wang Z, et al. Droplet-based single-cell joint profiling of histone modifications and transcriptomes. Nature Structural & Molecular Biology. 2023;30(10):1428–1433. DOI: 10.1038/s41594-023-01060-1.
- Wu SJ, Furlan SN, Mihalas AB, et al. Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nature Biotechnology. 2021;39(7):819–824. DOI: 10.1038/s41587-021-00865-z.
- Janssens DH, Otto DJ, Meers MP, et al. Scalable single-cell profiling of chromatin modifications with sciCUT&Tag. Nature Protocols. 2024;19(1):83–112. DOI: 10.1038/s41596-023-00905-9.
