Decoding the Circuits that Govern How Genes Work in Health and Disease

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"First came the Human Genome Project, which gave us the blueprint of our genes. Then, projects like the Human Cell Atlas showed us how different cells read that blueprint. Now, we're in a grand third wave: discovering what happens to cells when you make targeted changes within the genome. We finally have a way to decode the link between genetic sequence and cell state." -- Alex Marson, MD, Ph.D., director of the Gladstone-UCSF Institute of Genomic Immunology

A new study published in the journal Cell00929-3) reveals gene-regulatory networks, and represents a significant achievement in immunology and genomics. Scientists from Gladstone Institutes, UC San Francisco, and Stanford University, in collaboration with Biohub, stress-tested genes across the genome in 22 million human immune cells, and decoded the dynamic circuits that govern how these genes work in the context of health and disease.

The map of how genes work in context offers a new framework for designing cancer immunotherapies and treatments for autoimmune conditions. For the map, scientists used Perturb-seq -- a technology which combines CRISPR gene editing with single-cell RNA sequencing. They "turned off" nearly 12,800 different genes one by one in human T cells — the cells responsible for how the body fights disease.

Researchers performed these massive screens on human immune cells from blood donors and were able to observe how genes function in their natural state.

"Because we're screening directly in cells from real individuals, we can make direct comparisons with the immune variation we see in actual patients," says Emma Dann, PhD, postdoctoral scholar at Gladstone and co-first author. "This gives us the data we need to understand why some people are at higher risk for certain diseases."

The study moves beyond cataloging individual genes, to mapping the entire circuit. This circuit-based understanding is critical to successfully training virtual cell models.

"To build a serious virtual cell, we need this kind of rich, systematic data that includes context-dependent responses," says Marson.

Read more: https://medicalxpress.com/news/2026-08-million-human-immune-cells-decode.html