Published in Cell, the study introduces RegVelo, an AI based model that combines cellular dynamics with gene regulatory networks to predict how cells transition into specialised cell types such as pigment cells, blood cells, or neurons. The framework also allows researchers to simulate how genetic changes may alter these developmental pathways.

A significant proportion of the biological research underpinning the study was carried out in Oxford through the work of Professor Tatjana Sauka Spengler’s research group. Professor Sauka Spengler moved her laboratory from the University of Oxford to the Stowers Institute in 2022 and remains affiliated with the Radcliffe Department of Medicine and MRC Weatherall Institute of Molecular Medicine (MRC WIMM) as a Visiting Researcher.

The collaboration brought together expertise in developmental biology, single cell genomics, and computational modelling. Using zebrafish neural crest cells, the team demonstrated that RegVelo could identify previously unknown regulators involved in cell fate decisions. These predictions were then experimentally validated using CRISPR Cas9 and single cell Perturb seq approaches.

Professor Sauka Spengler said:

“What we really want to understand is how cells make decisions and transition from one state to another. RegVelo models how those fate decisions are encoded in gene regulatory networks over time, and what drives them.”

The researchers believe the framework could help accelerate discoveries in developmental biology and regenerative medicine, while also improving understanding of disease related cell states and potential therapeutic targets.

Read the paper in Cell