Single-cell multiome technology is a significant advancement in biological research, moving the focus from studying the average molecular profile of millions of cells to examining thousands of individual cells in detail. This approach simultaneously captures multiple distinct layers of molecular information from the exact same cell, offering a unified view of cellular function. Traditional bulk methods obscure the differences between individual cells, treating a complex population as a single, uniform entity. Multiome reveals this hidden cellular heterogeneity, transforming our understanding of health and disease by mapping the intricate regulatory programs that determine cell identity and behavior.
Defining the Multi-Layered Data
The core power of single-cell multiome lies in combining two major types of cellular data, providing a comprehensive snapshot of a cell’s identity and activity. The most common multiome assay pairs gene expression with chromatin accessibility, linking a cell’s long-term potential to its immediate actions. Gene expression, measured through single-cell RNA sequencing (scRNA-seq), reveals which genes are actively being transcribed into messenger RNA (mRNA). This is the cell’s “to-do list,” indicating the proteins it is currently manufacturing and the functions it is actively performing.
Chromatin accessibility, measured by single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), offers a complementary view of the cell’s regulatory landscape. Chromatin is the complex of DNA and proteins that forms chromosomes. Its structure determines whether the DNA is “open” and available for transcription factors to bind, or “closed” and silenced. This accessibility profile is the cell’s “potential blueprint,” showing which sections of the genome are structurally ready to be activated.
Combining these two datasets from the same nucleus allows scientists to directly connect the “blueprint” with the “to-do list.” For example, a region of DNA might be accessible, but the corresponding gene may not yet show high expression. This suggests the cell is primed for a functional change but has not yet initiated it—an insight impossible to gain from measuring either data type alone. This unified view provides a deeper understanding of the gene regulatory networks that orchestrate cell identity and function.
The Technology Behind Simultaneous Measurement
The technical challenge of single-cell multiome is ensuring that both the RNA and the accessible DNA fragments originate from the same nucleus and remain linked throughout sequencing. This is achieved through sophisticated microfluidic and molecular barcoding systems. High-throughput platforms use microfluidic chips to isolate tens of thousands of individual nuclei into tiny, nanoliter-sized water-in-oil droplets, known as Gel Beads in Emulsion (GEMs).
Each droplet contains a single nucleus and a bead coated with unique DNA sequences that serve as molecular barcodes. When the nucleus is lysed within the droplet, these barcodes are released and simultaneously attach to the messenger RNA molecules and the fragments of accessible DNA. Because all molecules within a single droplet acquire the same unique barcode, the resulting data can be traced back to their original cell.
The accessible DNA fragments are tagged using a modified enzyme called a transposase, which cuts the open chromatin and inserts a sequencing adapter that includes the cell-specific barcode (tagmentation). Simultaneously, the cell’s RNA is captured and converted into complementary DNA (cDNA), also incorporating the unique cellular barcode. After the droplets are broken and pooled, two separate sequencing libraries—one for RNA and one for ATAC—are prepared. The sequencing data is then computationally “demultiplexed” using the unique barcodes to create a unified, paired dataset for each individual cell, linking gene expression and the chromatin profile.
Transforming Biological and Medical Research
Obtaining this unified molecular portrait from single cells is changing how scientists approach complex biological questions. Multiome technology offers high resolution for understanding how a cell’s identity is established and maintained.
Mapping Cell Fate Decisions
One application is mapping cell fate decisions, such as how a stem cell differentiates into a specialized cell type, like a neuron or a heart cell. By tracing changes in both the chromatin landscape and gene expression along a differentiation trajectory, researchers can pinpoint regulatory events that precede visible changes in gene activity. Multiome data allows for the identification of transcription factors—proteins that control gene expression—that remodel the chromatin to prime a cell for a new identity before the genes are turned on. This insight into “epigenomic priming” reveals the timing and mechanism of commitment to a specific fate, a process previously masked by measuring only RNA.
Precision Disease Characterization
Single-cell multiome is valuable in characterizing the molecular basis of disease, especially in conditions with complex cellular heterogeneity, such as cancer and neurological disorders. Traditional analyses of tumor tissue average the signal from malignant, immune, and stromal cells, hiding the unique characteristics of aggressive cells. Multiome allows researchers to isolate and characterize dysfunctional molecular links within rare, disease-driving cell types, such as drug-resistant cancer cells or specific immune cells driving inflammation. This characterization can reveal the regulatory dysfunctions—the abnormal open chromatin regions—that drive the misexpression of disease-related genes in a specific cell population.
Drug Target Identification
The technology is valuable for identifying new and precise drug targets by linking regulatory elements to their functional output. Many disease-associated genetic variations are found not within the protein-coding parts of a gene, but within the non-coding regulatory regions of the DNA. Multiome can show whether an accessible regulatory region is active in a diseased cell type and which gene’s expression it controls, offering a direct functional link. This ability to connect a regulatory element to a specific gene provides researchers with better candidates for therapeutic intervention, allowing for the development of drugs that target the regulatory mechanism driving the pathology.