Scientists Map Single-Cell Gene Activity in 3D
Researchers developed scHiCAR technology that maps gene activity, regulation, and 3D DNA folding in individual cells simultaneously. This breakthrough could revolutionize cancer and brain disease research by revealing how genes interact spatially within cells. The technique builds on earlier single-cell methods but adds the crucial 3D dimension that's been missing from cellular analysis.
The new method, scHiCAR, was developed by a collaborative team led by Professor Inkyung Jung at the Korea Advanced Institute of Science and Technology (KAIST) and Professor Yarui Diao at Duke University. Their work was supported by organizations including the Suh Kyungbae Foundation and the Samsung Science and Technology Foundation. This technique represents a significant leap from previous methods like Hi-C, which also map chromatin interactions. Unlike its predecessors that analyzed data from thousands of cells in bulk, scHiCAR can simultaneously profile the transcriptome, epigenome, and 3D genome within a single cell, a "trimodal" approach that offers unprecedented accuracy. The scHiCAR method more efficiently captures long-range interactions between genes and the distant regulatory elements that control them. This is crucial for understanding how the physical folding of DNA brings specific enhancers into contact with gene promoters to activate or silence them. In one application, researchers used scHiCAR to create a high-resolution molecular map of 1.6 million mouse brain cells. This allowed them to define the unique transcriptomes, accessible regulatory elements, and enhancer-promoter pairs across 22 different brain cell types with a resolution of 5 kilobases. The technology has also been used to study the dynamics of muscle stem cell regeneration. By tracking how the 3D genome structure changes in real-time, scientists can better understand the gene regulation that governs cell fate, which is critical for research into aging and degenerative diseases. By linking genetic risk factors to specific cell types, this 3D view can refine our understanding of complex brain disorders. For instance, studies have suggested that in Alzheimer's disease, genetic risk factors may be concentrated in microglia, while epigenetic changes are more linked to neurons and oligodendrocytes. The application of 3D genomics is also advancing cancer research by identifying how the abnormal folding of chromosomes can activate oncogenes. This detailed mapping could lead to new diagnostic biomarkers and therapeutic targets by revealing the structural changes cancerous cells rely on to grow.
