A predictive computational framework for direct reprogramming between human cell types

Owen J L Rackham, Jaber Firas, Hai Fang, Matt E Oates, Melissa L Holmes, Anja S Knaupp, The FANTOM Consortium, Harukazu Suzuki, Christian M Nefzger, Carsten O Daub, Jay W Shin, Enrico Petretto, Alistair R R Forrest, Yoshihide Hayashizaki, Jose M Polo, Julian Gough

Research output: Contribution to journalLetterOtherpeer-review

Abstract

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 pages5
JournalNature Genetics
Volume48
Issue number3
DOIs
Publication statusPublished - 18 Jan 2016

Keywords

  • gene regulation
  • systems analysis
  • tissue engineering

Cite this

Rackham, O. J. L., Firas, J., Fang, H., Oates, M. E., Holmes, M. L., Knaupp, A. S., ... Gough, J. (2016). A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, 48(3), 331-335. https://doi.org/10.1038/ng.3487
Rackham, Owen J L ; Firas, Jaber ; Fang, Hai ; Oates, Matt E ; Holmes, Melissa L ; Knaupp, Anja S ; The FANTOM Consortium ; Suzuki, Harukazu ; Nefzger, Christian M ; Daub, Carsten O ; Shin, Jay W ; Petretto, Enrico ; Forrest, Alistair R R ; Hayashizaki, Yoshihide ; Polo, Jose M ; Gough, Julian. / A predictive computational framework for direct reprogramming between human cell types. In: Nature Genetics. 2016 ; Vol. 48, No. 3. pp. 331-335.
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Rackham, OJL, Firas, J, Fang, H, Oates, ME, Holmes, ML, Knaupp, AS, The FANTOM Consortium, Suzuki, H, Nefzger, CM, Daub, CO, Shin, JW, Petretto, E, Forrest, ARR, Hayashizaki, Y, Polo, JM & Gough, J 2016, 'A predictive computational framework for direct reprogramming between human cell types' Nature Genetics, vol. 48, no. 3, pp. 331-335. https://doi.org/10.1038/ng.3487

A predictive computational framework for direct reprogramming between human cell types. / Rackham, Owen J L; Firas, Jaber; Fang, Hai; Oates, Matt E; Holmes, Melissa L; Knaupp, Anja S; The FANTOM Consortium; Suzuki, Harukazu; Nefzger, Christian M; Daub, Carsten O; Shin, Jay W; Petretto, Enrico; Forrest, Alistair R R; Hayashizaki, Yoshihide; Polo, Jose M; Gough, Julian.

In: Nature Genetics, Vol. 48, No. 3, 18.01.2016, p. 331-335.

Research output: Contribution to journalLetterOtherpeer-review

TY - JOUR

T1 - A predictive computational framework for direct reprogramming between human cell types

AU - Rackham, Owen J L

AU - Firas, Jaber

AU - Fang, Hai

AU - Oates, Matt E

AU - Holmes, Melissa L

AU - Knaupp, Anja S

AU - The FANTOM Consortium

AU - Suzuki, Harukazu

AU - Nefzger, Christian M

AU - Daub, Carsten O

AU - Shin, Jay W

AU - Petretto, Enrico

AU - Forrest, Alistair R R

AU - Hayashizaki, Yoshihide

AU - Polo, Jose M

AU - Gough, Julian

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AB - 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.

KW - gene regulation

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KW - tissue engineering

UR - http://www.ncbi.nlm.nih.gov/pubmed/26780608

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DO - 10.1038/ng.3487

M3 - Letter

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SP - 331

EP - 335

JO - Nature Genetics

JF - Nature Genetics

SN - 1061-4036

IS - 3

ER -