Scientists from Gladstone Institutes, UC San Francisco, and Stanford University, in collaboration with Biohub, have unveiled a massive, high-resolution functional map of human immune cells that promises to transform our understanding of how genetics control health and disease.
Published in the journal Cell, the study represents a landmark achievement in immunology and genomics. By systematically stress-testing genes across the genome in 22 million human immune cells, scientists moved beyond mere DNA sequencing to decode the dynamic circuits that govern how these genes actually work in the context of health and disease. This leap from observation to intervention offers a powerful new framework for designing cancer immunotherapies and treating autoimmune conditions, among other things.
"To understand the significance of this study, you have to look at the last three decades of biology," says Alex Marson, MD, PhD, director of the Gladstone-UCSF Institute of Genomic Immunology and a senior author of the study. "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."
The resulting dataset also stands as the largest contribution yet to the Billion Cells Project, a Biohub-led effort to generate a massive, open-source dataset of one billion single cells—data that can be used to train advanced AI models that can predict how cells behave, speed scientific discovery, and uncover new ways to treat disease. The project is part of Biohub's global Virtual Biology Initiative , which seeks to create the open-data foundation for AI-accelerated biology.
Human T Cells Provide Real-World Insights
The study used a cutting-edge technology called Perturb-seq, which allowed the team to "turn off" nearly 12,800 different genes one by one in human T cells—the critical cells that orchestrate how the body fights disease.
Rather than relying on experimental cell lines that have long been the standard in laboratory research, the team instead performed massive screens on actual human immune cells, or so-called "primary" cells, from blood donors. Through this, they observed how genes function in their natural state, providing a much clearer roadmap for treating autoimmune diseases and designing better cancer therapies.
"The effects of these genetic perturbations are highly distinctive in real T cells," says Emma Dann, PhD, a postdoctoral scholar at Gladstone and co-first author. "These cells retain their ability to respond to signals that activate the immune system. And, because we're screening directly in cells from real individuals, we can make direct comparisons with the immune variation we see in actual patients. This gives us the data we need to understand why some people are at higher risk for certain diseases."
Context Is Critical
Among key findings, the study reveals the intricacies of how genes work together to influence immune function—and how these "circuits" operate very differently depending on circumstances such as whether cells are resting or fighting an infection.
"Previously, we were just cataloging individual genes," explains Ronghui (Ron) Zhu, PhD, a postdoctoral scholar at Gladstone and the study's co-first author. "Now, we can begin to connect them into a circuit, much like the circuits that control your computer. This is fundamental to understanding how a cell actually 'thinks' and responds to its environment."
This context-specific data is also essential for the future of "virtual biology," where AI models are used to predict cell behavior. Notably, it serves as proof that such models must be trained on a diverse set of cell states and health scenarios to make accurate, reliable predictions.
"If we only look at one context, AI will struggle to predict how cells behave in the real world," Marson says. "To build a serious virtual cell, we need this kind of rich, systematic data that includes context-dependent responses."
Jonathan Pritchard, PhD, professor of genetics and biology at Stanford University and a senior author of the study, says the dataset provides the missing link between a person's DNA and their health.
"Interpreting genetic associations with complex traits has always been a challenge," Pritchard says. "This study allows us to identify the regulatory pathways through which natural genetic variants influence traits like lymphocyte counts, moving us closer to understanding the functional drivers of immune-related diseases."
Fueling AI-Driven Discovery
"This study demonstrates how standardized, large-scale functional genomics datasets can serve as the foundation for the next generation of AI models of biology," says Garabet Yeretssian, PhD, Biohub's director of extramural research and partnerships. "By making these data open-source and freely available, we're enabling scientists around the world working at the intersection of AI and biology to build more predictive models of cellular behavior, accelerate biological discovery, and ultimately make transformative advances in precision medicine."
The massive scale of the research was enabled by partnerships with industry leaders 10x Genomics and Ultima Genomics: 10x Genomics for its high-resolution single-cell analysis, and Ultima Genomics for its high-throughput sequencing capabilities. Together, these platforms allowed the scientists to screen a staggering 33.4 million cells—ultimately yielding 22 million high-quality cells used for the final analysis and map.
In collaboration with Weill Cancer Hub West, the scientists are already pivoting to the next phase of their work, which will focus specifically on cancer. They plan to apply their genome-scale Perturb-seq approach to track how genetic changes alter human T cells as they infiltrate and interact with complex tumor environments.
"We now have a fundamental rulebook of how genes control T cell responses," Marson says. "Our hope is that this becomes a standard lookup table for the entire field, allowing any scientist to instantly see how a specific gene affects cells of the human immune system."
About the Study
The study, "Genome-Scale Perturb-seq in Primary Human CD4+ T cells Maps Context-Specific Regulators of T Cell Programs and Human Immune Traits," appears online in Cell on August 28, 2026.
Authors are Ronghui Zhu, Emma Dann, Jun Yan, Justine Reyes Retana, Ryunosuke Goto, Reese C. Guitche, Lillian Brixi, Mineto Ota, Austin Hartman, Theodore L. Roth, Ansuman T. Satpathy, Jonathan K. Pritchard, and Alexander Marson. Participating institutions include Gladstone Institutes, Gladstone-UCSF Institute of Genomic Immunology; Stanford University; University of San Francisco; Biohub; Arc Institute; Weill Foundation West Coast Cancer Hub; UC San Francisco; Innovative Genomics Institute; Parker Institute for Cancer Immunotherapy; and University of Tokyo.
About Gladstone Institutes
Gladstone Institutes is an independent, nonprofit life science research organization that uses visionary science and technology to overcome disease. Established in 1979, it is located in the epicenter of biomedical and technological innovation, in the Mission Bay neighborhood of San Francisco. Gladstone has created a research model that disrupts how science is done, funds big ideas, and attracts the brightest minds.
