New single-cell method can revolutionize how we analyze cells

The genes in our cells work both independently and connected to each other. Understanding exactly how genes are turned on or off in each cell is critical to uncovering the processes that guide immune responses, cell development, and disease. Technologies that measure gene expression (RNA) and chromatin accessibility - how “open” or “closed” parts of the genome are -  at the single-cell resolution have already transformed biology. However, until now, these methods have been limited by their cost and scalability, restricting their use in larger studies.

But researchers from University of Basel, Tampere University and Aarhus University have now developed a powerful new method called SUM-seq, that makes it possible to analyze gene activity and DNA accessibility in up to hundred samples and up to a million single cells—in one experiment. 

"SUM-seq sets a new standard in single-cell research—enabling millions of cells to be profiled at once, it unlocks how our genes switch on and off in health and disease, paving the way for precision medicine," explains Professor Kyung Min Noh from the Department of Biomedicine at Aarhus University.

SUM-seq builds on existing technology but adds a multiplexing strategy that drastically increases throughput while reducing costs. It allows researchers to study how cells respond over time or under different conditions—using fixed or frozen samples, which is especially valuable for clinical or collaborative studies.

The research team which was led by Professor Judith Zaugg at the University of Basel and Professor Kyung Min Noh at Aarhus University applied SUM-seq in three systems: tracking immune responses during macrophage polarization, studying T cell differentiation from human donors, and mapping gene regulation after CRISPR-based gene perturbations in differentiating stem cells. These case studies show that SUM-seq can reveal the complex gene regulatory programs that govern how cells behave, develop, or respond to disease-relevant signals.

“We believe it will open up opportunities for large-scale screens, disease models and clinical studies and thus better understand and potentially treat complex diseases,” Kyung Min Noh explains.

The research - more information

• Collaborators: Judith Zaugg, University of Basel | Basel University Hospital, Department of Biomedicine
• External funding: EMBL Research Fund
• Read more in the scientific paper: https://www.nature.com/articles/s41592-025-02700-8

Contact

Professor Kyung Min Noh
Department of Biomedicine, Health, Aarhus University
Mail:mnoh@biomed.au.dk

This press release was written in collaboration with the University of Basel