A predictive computational framework for direct reprogramming between human cell types

O.J.L. Rackham, J. Firas, H. Fang, M.E. Oates, M.L. Holmes, A.S. Knaupp, H. Suzuki, C.M. Nefzger, C.O. Daub, J.W. Shin, E. Petretto, Alistair Forrest, Y. Hayashizaki, J.M. Polo, J. Gough

Research output: Contribution to journalArticle

125 Citations (Scopus)

Abstract

© 2016 Nature America, Inc. 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. Here we present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. We 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, we validated two new transdifferentiations predicted by Mogrify. We 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.
Original languageEnglish
Pages (from-to)331-335
Number of pages4
JournalNature Genetics
Volume48
Issue number3
Early online date18 Jan 2016
DOIs
Publication statusPublished - Mar 2016

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