A Technical Whisper: Solving the Resolution Bottleneck
For researchers mapping the three-dimensional genome, the goal is often clear: capture the physical arrangement of chromatin in enough detail to connect structure with function. Yet conventional Hi-C, constrained by restriction enzyme cutting sites, imposes a resolution ceiling. Important features—promoter–enhancer loops, subtle TAD shifts, or nucleosome folding patterns—are often blurred or entirely missed.
Micro-C XL changes this landscape. By combining dual crosslinking (formaldehyde plus a long-range agent) with MNase digestion, it frees the experiment from the uneven distribution of restriction sites. MNase cleaves chromatin at nucleosome boundaries without sequence bias, producing uniform coverage and enabling interaction maps at ~200 bp resolution.
The result is not merely a sharper image. At this scale, loops become discrete, stripes appear with clarity, and insulation boundaries are precisely defined. This depth allows you to resolve how regulatory elements—such as enhancers, promoters, and insulators—are physically positioned to influence transcription. For projects in functional genomics, epigenetic regulation, or comparative 3D genome architecture, Micro-C XL delivers a level of detail that transforms hypotheses into testable models.
Why This Matters in Your Research
In high-throughput chromosome conformation capture, resolution defines the boundaries of discovery. When the signal is limited to kilobase-scale bins, many interactions that shape gene regulation are averaged out, leaving key structural and functional relationships hidden.
Micro-C XL lifts these constraints. At nucleosome-level resolution, interaction maps reveal:
More loops with greater confidence — Enhancer–promoter and promoter–promoter contacts that are otherwise undetectable in Hi-C datasets.
Sharper TAD boundaries — Precise demarcation of insulated neighborhoods, enabling a more accurate interpretation of domain-level regulation.
Richer signal-to-noise ratio — Uniform MNase digestion eliminates gaps caused by uneven restriction site distribution, allowing high-confidence detection across the genome.
Cross-kingdom adaptability — Whether mapping yeast chromatin or investigating plant and mammalian genomes, the method retains its resolution and consistency.
For research in developmental biology, disease-associated chromatin remodeling, or comparative genomics, Micro-C XL provides the granularity needed to align structural features with molecular function. This means hypotheses about regulatory mechanisms can be tested against high-fidelity structural evidence, closing the gap between genome architecture and transcriptional outcome.
Service Workflow
Micro-C XL Workflow: From Crosslinking to Sequencing
Micro-C XL is built on the principle that every step — from fixation to sequencing — shapes the resolution and interpretability of your data. Our workflow preserves spatial proximity while generating uniform, high-resolution coverage across the genome:
Dual Crosslinking for Stability – Short-range formaldehyde locks local chromatin contacts, while a long-range agent (DSG or EGS) captures interactions between nucleosomes further apart.
MNase Digestion without Bias – Micrococcal nuclease cleaves chromatin at nucleosome boundaries, free from sequence-specific constraints. This ensures even coverage across the genome.
End Repair and Biotin Labeling – Fragment ends are polished and biotin-tagged for downstream enrichment.
Ligation of Spatially Adjacent DNA Fragments – Spatially close DNA fragments are ligated, preserving the true three-dimensional connectivity of the chromatin fiber.
Crosslink Reversal and DNA Purification – Carefully optimized to recover intact ligation products while removing crosslinking agents.
Library Construction and High-Depth Sequencing – Generating datasets capable of resolving interactions from megabase compartments down to nucleosome-scale loops.
At the heart of this workflow lies enzyme titration — determining the precise MNase amount for each species and sample type. Too little digestion leaves fragments too long for nucleosome-scale resolution; too much disrupts adjacency between nucleosomes. Our titration process ensures that the resulting libraries reflect genuine chromatin organization rather than technical artifacts.
Service Workflow — From Inquiry to Data Delivery
Sample Requirements
Sample Requirements
Sample Type
Recommended Amount
Preservation Method
Transport Condition
Cell Lines
≥10⁷ cells
Fresh or cryopreserved
Dry ice or liquid nitrogen
Animal Tissue
≥1 g (e.g., liver, muscle)
Flash-frozen
Dry ice or liquid nitrogen
Plant Tissue
≥2 g (young, tender leaves preferred)
Flash-frozen
Dry ice or liquid nitrogen
Blood
≥3 mL in EDTA tube
Keep cool, avoid hemolysis
Dry ice shipping
Note: For all sample types, please avoid repeated freeze–thaw cycles. Contact our technical team for detailed QC guidelines before shipment.
Bioinformatics Analysis
Data That Speaks: From Raw Reads to Nucleosome-Level Maps
A Micro-C XL experiment generates vast amounts of raw sequence data — but its value lies in how effectively it is transformed into meaningful structural insights. Our bioinformatics pipeline is designed to capture every layer of chromatin organization, from large-scale compartments to nucleosome-level loops.
Key Analysis Modules:
Interaction Matrix Construction – Multi-resolution heatmaps tailored for genome-wide or region-specific inspection.
Distance–Decay Profiles – Quantifying how interaction frequency changes with genomic distance.
Compartment Analysis – Distinguishing active (A) and inactive (B) chromatin domains through principal component analysis.
TAD Identification – Pinpointing domain boundaries with high precision, revealing changes between conditions or cell states.
Loop Detection – Mapping significant enhancer–promoter, promoter–promoter, and structural loops with statistical validation.
Differential Interaction Analysis – Comparing interaction landscapes across experimental conditions to detect functional changes.
Each result is delivered with publication-quality visualizations, making it easier to interpret patterns, generate hypotheses, and integrate findings with complementary datasets such as RNA-seq, ATAC-seq, or ChIP-seq.
Applications
Real Applications — From Yeast to Crops
Micro-C XL is not confined to a single research niche — its nucleosome-level resolution has unlocked discoveries across kingdoms of life. Whether studying compact microbial genomes, complex mammalian chromatin, or plant-specific regulatory landscapes, the technology consistently delivers structural detail that fuels new hypotheses.
Application Areas:
Model Organisms – Deciphering promoter–enhancer networks, nucleosome folding patterns, and domain insulation in yeast and Drosophila.
Mammalian Systems – Resolving fine-scale loops and stripes in embryonic stem cells, linking chromatin topology to transcriptional activity.
Plant Genomics – Mapping super-enhancer–promoter loops in Arabidopsis and analyzing TAD boundary signatures in rice, opening new chapters in plant 3D genome research.
Evolutionary Biology – Revealing how chromatin looping emerged and diversified in early-branching animals compared to unicellular relatives.
Research Highlights: When Resolution Changes the Story
Mammalian Embryonic Stem Cells – Micro-C XL identified thousands of promoter-associated loops invisible to Hi-C, providing direct evidence for the role of chromatin folding in regulating pluripotency-associated genes.
Arabidopsis – Achieved 200 bp interaction mapping, uncovering super-enhancer–promoter loops and associated protein factors that regulate single-gene transcription.
Rice – Characterized the sequence and epigenetic features of TAD boundaries across multiple varieties, revealing structural patterns linked to trait variation.
Each case underscores a central point: with Micro-C XL, structural features that once appeared blurred become actionable insights.
Deliverables
What You Receive: Research-Ready Deliverables
Every Micro-C XL project is designed to deliver outputs that are both scientifically rigorous and immediately usable in your research workflow. Our deliverables are optimized for transparency, reproducibility, and direct integration into downstream analyses or publications.
You will receive:
High-Resolution Interaction Maps – Multi-bin-size contact matrices capturing chromatin architecture from compartments to nucleosome-level loops.
Comprehensive Bioinformatics Report – A structured document detailing methods, quality metrics, key findings, and interpretive summaries.
Publication-Ready Visualizations – Heatmaps, loop arc diagrams, and compartment/TAD tracks suitable for inclusion in figures and supplementary data.
Data Packages – Both raw sequencing data (FASTQ) and processed analysis files (e.g., normalized contact matrices, loop lists, compartment tracks) for complete transparency.
All results are delivered in widely compatible formats, ensuring they can be directly viewed in standard genome browsers or integrated with other omics datasets such as RNA-seq, ATAC-seq, or ChIP-seq.
Advantages
Why Partner with CD Genomics for Micro-C XL
Executing a Micro-C XL experiment at nucleosome-level resolution requires more than following a protocol — it demands precise technical control, from enzyme titration to advanced bioinformatics. At CD Genomics, we combine methodological expertise with flexible service design to ensure your project's success.
Optimized MNase Titration
Custom digestion profiles for each species and sample type to preserve true nucleosome adjacency.
Dual-Crosslinking Expertise
Fine-tuned fixation strategies to capture both proximal and distal interactions with minimal noise.
Cross-Species Capability
Proven workflows for mammalian, plant, yeast, and microbial genomes, adapting protocols to unique chromatin contexts.
Integrated Bioinformatics
End-to-end analysis that delivers ready-to-use maps, statistical results, and visual interpretations.
Reproducibility & Data Quality
Rigorous QC checkpoints from sample intake to final report, ensuring consistent, publication-grade output.
When you partner with CD Genomics, you gain not only a high-resolution map of chromatin interactions but also the confidence that every data point has been generated and analyzed to the highest technical standard.
