Every cell in the human body, from a neuron to a skin cell, originates from the same genetic instructions. This shared DNA blueprint gives rise to an incredible diversity of cell types, which has led scientists to a key understanding. A cell’s identity is determined not just by which genes it has, but by which genes are turned on or off at any given moment.
A major factor in this regulation is the physical organization of DNA within the nucleus. The long DNA strands are intricately folded into a complex, three-dimensional structure. The challenge for biologists has been to simultaneously observe this 3D structure and measure its direct consequence—gene activity—within a single cell.
Understanding the Core Technologies
Mapping 3D Genome Structure with Hi-C
The technique known as Hi-C creates a detailed map of the genome’s three-dimensional architecture. It works by capturing a snapshot of all the points where the linear DNA strand folds, creating physical touchpoints. These interactions form organized structures like loops and domains that are involved in gene regulation.
The process begins by using a chemical like formaldehyde to fix a cell’s components in place, acting like a molecular glue to cross-link DNA segments that are physically close. The DNA is then cut into smaller fragments. The ends of these cross-linked fragments are rejoined, fusing pieces of DNA that were spatially near but might be linearly distant. By sequencing these newly joined fragments, scientists create a comprehensive interaction map.
This map often shows distinct regions called topologically associating domains (TADs), which are neighborhoods of DNA that interact frequently with each other but less so with sequences outside their boundary. These domains are thought to be a basic unit of genome organization and help to compartmentalize the genome for different functions. By bringing specific genes into contact with their regulatory elements, these 3D structures help orchestrate which genes are active.
Measuring Gene Function with RNA-seq
While Hi-C reveals the genome’s physical structure, a different technology measures its functional output. Gene expression is the process where information in a gene is used to create a product, often a protein. The first step is transcription, where DNA is copied into a messenger RNA (mRNA) molecule. The collection of all RNA molecules in a cell, the transcriptome, provides a snapshot of which genes are active.
The method used to measure this is RNA sequencing, or RNA-seq. This technique involves collecting all RNA from a cell, converting it to a more stable DNA form, and then sequencing each molecule. By counting how many RNA copies exist for each gene, researchers get a quantitative measure of gene activity. A high number of transcripts for a gene indicates it is highly active, while a low number suggests it is less active or turned off.
The Importance of the Single-Cell Perspective
Early applications of Hi-C and RNA-seq were performed on “bulk” samples, analyzing genetic material pooled from thousands of cells at once. This approach provides an averaged view that masks the diversity between individual cells. In a complex tissue, such as the brain or a cancerous tumor, no two cells are identical.
Analyzing single cells one at a time reveals this hidden heterogeneity. Single-cell analysis allows researchers to identify rare cell populations, understand the subtle differences between closely related cell types, and track the dynamic changes that occur as a cell develops or responds to its environment.
The Unified Method: Capturing Structure and Function Together
To link the genome’s form to its function, scientists developed methods to capture both sets of information from the same cell. This unified approach, sometimes called HiRES, provides a direct connection between a specific 3D genome architecture and its resulting gene expression profile.
The process begins with the careful isolation of a single cell from a larger sample. The cell is then treated with a cross-linking agent like formaldehyde, which freezes the 3D DNA structure in place and preserves its interactions, creating a stable snapshot of the cell’s nuclear organization.
Next, the cell is gently broken open, allowing for the physical separation of its contents. The nucleus, containing the cross-linked DNA, is separated from the surrounding cytoplasm, which holds the cell’s RNA. This separation ensures that the material for structural and functional analysis originates from the exact same cell.
With the components separated, they are processed in parallel. The nuclear material undergoes the Hi-C protocol to map its 3D structure, while the RNA from the cytoplasm is subjected to the RNA-seq protocol to quantify gene expression.
Finally, the two datasets are linked computationally. Because both the structural map and functional readout came from one cell, scientists can directly correlate specific chromatin loops and domains with the activity levels of the genes within them. This provides a high-resolution picture of how DNA folding influences which genes are turned on or off in an individual cell.
Insights into Cell Development and Diversity
An application of this unified method is in the study of cell development. Multicellular organisms begin as embryonic stem cells, which can differentiate into every cell type in the body. This process involves a series of decisions where cells become more specialized, guided by precise changes in gene regulation.
Using a unified method, researchers can track individual cells as they move through these developmental pathways. Studies on developing mouse embryos show how the 3D genome physically refolds as cells specialize. In an undifferentiated stem cell, the genome is configured to keep genes associated with “stemness” active, and as the cell commits to a lineage, the genome reorganizes.
This refolding process involves the formation of new chromatin loops and the dissolution of old ones. These structural changes bring lineage-specific genes into contact with their enhancers, turning them on, while simultaneously sequestering genes for other lineages in inactive compartments. For instance, a cell destined to become a neuron will form new 3D contacts that activate genes required for nerve signaling, while genes for muscle contraction remain dormant.
Observing these changes in a single cell provides direct evidence of how structure drives function during development. Researchers have found that in many cases, the chromatin rewiring occurs before the corresponding changes in gene expression are detected. This suggests the physical reorganization of the genome is a preparatory step that sets the stage for the functional changes that define a cell’s identity.
Applications in Understanding Disease
The insights from linking genome structure to function extend into the study of human disease, particularly cancer. A single tumor is not a uniform mass but a complex ecosystem of distinct cell populations. These different cancer cells can have varied behaviors, with some being more aggressive, more likely to metastasize, and others resistant to treatment.
By applying simultaneous Hi-C and RNA-seq to individual tumor cells, researchers can dissect this complexity at a molecular level. This approach allows them to identify how a cancer cell’s genome is misfolded. These aberrant folding patterns can create new, disease-driving interactions, such as bringing an enhancer into proximity with an oncogene, leading to its uncontrolled activation.
This technique is also useful for understanding and combating drug resistance. In a patient undergoing chemotherapy, some tumor cells may be killed by the treatment while a small subpopulation survives. By analyzing the 3D genome and transcriptome of these resistant cells, scientists can identify the specific structural and gene expression signatures that allow them to evade the drug’s effects.
Identifying these molecular signatures provides a deeper understanding of why cancers often recur after treatment. It also opens the door to new therapeutic strategies. If a specific aberrant chromatin loop is found to drive resistance, it may be possible to develop drugs that specifically target and disrupt that interaction. This could re-sensitize the cancer to existing therapies or offer a new line of attack, a step toward more personalized and effective cancer treatments.