A new genome-scale atlas is offering an unprecedented look at how individual genes shape the transcriptional landscape of human induced pluripotent stem cells (iPSCs). Published in Nature Biotechnology, the resource catalogs the effects of perturbing 11,692 expressed genes across more than 2.5 million single cells, creating a reference framework for understanding how pluripotent identity is maintained and regulated.
The study is titled, “A genome-scale CRISPRi perturbation atlas of human induced pluripotent stem cells.”
Human iPSCs can differentiate into virtually any cell type, yet the functions of most genes within this state remain poorly understood. Prashant Mali, PhD, senior author and professor of bioengineering at UC San Diego, said the team set out to fill that gap by systematically switching off genes one by one using CRISPR interference (CRISPRi) and measuring the resulting transcriptome-wide changes. “The result is a kind of reference atlas; it’s a way to look up what perturbing almost any gene does to a stem cell’s behavior, measured here as the impact on its whole transcriptome,” Mali said.
The dataset captures how gene perturbations cluster into shared molecular signatures, revealing functional relationships among protein complexes, metabolic pathways, and self-renewal genes. By correlating transcriptional phenotypes across thousands of perturbations, the researchers reconstructed a map of the pluripotent state that recapitulates known regulatory modules while surfacing previously unrecognized ones.
Exploring the atlas led the team to identify new regulators of stem cell biology. They uncovered ZBTB41 as a metabolic factor and RNF7 as a contributor to pluripotency regulation, validating both through metabolic tracing, immunofluorescence, and protein–protein interaction assays. The resource also enabled a genome-scale screen of A‑to‑I RNA editing modulators, revealing DBR1 as a potent regulator of adenosine-to-inosine conversion.
Co-first author Yesh Doctor, a bioengineering PhD student in Mali’s lab, described the atlas as a “hypothesis engine” for stem cell researchers. Instead of running thousands of perturbation experiments, scientists can now query the open-access map to identify candidate genes involved in differentiation, metabolism, or disease-relevant pathways. “Scientists can use it to look up the functions of genes and build hypotheses on them instead of having to run the experiments themselves,” Doctor said.
Beyond basic biology, the team sees the atlas as a foundation for computational modeling. The scale and consistency of the dataset make it well suited for training AI systems aimed at predicting genotype–phenotype relationships. “These comprehensive, genome-scale screens enable generation of reference maps that are not just invaluable for basic science discovery, but also an important resource for powering future computational and AI tools for genotype-phenotype prediction,” Mali said.
The open-access atlas is available here, providing a new reference point for understanding how genes shape human stem cell identity and offering a tool for virtual disease modeling and target discovery.