Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine. The identification of key transcription factors for reprogramming is currently limited by the cost of exhaustive experimental testing of plausible sets of factors, an approach that is inefficient and unscalable. Now, scientists present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. They have applied Mogrify to 173 human cell types and 134 tissues, defining an atlas of cellular reprogramming. Mogrify correctly predicts the transcription factors used in known transdifferentiations. Furthermore, they validated two new transdifferentiations predicted by Mogrify. The researchers provide a practical and efficient mechanism for systematically implementing novel cell conversions, facilitating the generalization of reprogramming of human cells. Predictions are made available to help rapidly further the field of cell conversion.
To achieve this game-changing result, Professor Gough worked with then-PhD student Dr Owen Rackham (who now works at Duke-NUS Medical School in Singapore) for five years to develop a computational algorithm to predict the cellular factors for cell conversions. The algorithm was conceived from data collected as a part of the FANTOM international consortium (based at RIKEN, Japan) of which Professor Gough is a long time member. The algorithm, called Mogrify, has been made available online for other researchers and scientists, so that the field may advance rapidly.