Computational approaches for predicting key transcription factors in targeted cell reprogramming (Review)

Molecular Medicine Reports
Guillermo-Issac Guerrero-RamirezVictor Trevino

Abstract

There is a need for specific cell types in regenerative medicine and biological research. Frequently, specific cell types may not be easily obtained or the quantity obtained is insufficient for study. Therefore, reprogramming by the direct conversion (transdifferentiation) or re‑induction of induced pluripotent stem cells has been used to obtain cells expressing similar profiles to those of the desired types. Therefore, a specific cocktail of transcription factors (TFs) is required for induction. Nevertheless, identifying the correct combination of TFs is difficult. Although certain computational approaches have been proposed for this task, their methods are complex, and corresponding implementations are difficult to use and generalize for specific source or target cell types. In the present review four computational approaches that have been proposed to obtain likely TFs were compared and discussed. A simplified view of the computational complexity of these methods is provided that consists of three basic ideas: i) The definition of target and non‑target cell types; ii) the estimation of candidate TFs; and iii) filtering candidates. This simplified view was validated by analyzing a well‑documented cardiomyocyte differentiation...Continue Reading

References

Jun 1, 1961·Journal of Molecular Biology·F JACOB, J MONOD
Dec 21, 2004·Nucleic Acids Research·Tanya BarrettRon Edgar
Oct 4, 2005·Proceedings of the National Academy of Sciences of the United States of America·Aravind SubramanianJill P Mesirov
Feb 16, 2006·Statistical Methods in Medical Research·Seo Young KimIn Suk Sohn
Apr 7, 2007·Developmental Biology·Sui HuangTariq Enver
Jan 25, 2008·Proceedings of the National Academy of Sciences of the United States of America·Martin Rosvall, Carl T Bergstrom
Dec 19, 2008·Development·Catherine A RisebroPaul R Riley
Feb 17, 2009·Developmental Cell·Masaki IedaDeepak Srivastava
Mar 11, 2009·Nature Reviews. Genetics·Juan M VaquerizasNicholas M Luscombe
Apr 21, 2009·Nature Genetics·UNKNOWN FANTOM ConsortiumYoshihide Hayashizaki
Jan 29, 2010·Nature·Thomas VierbuchenMarius Wernig
Dec 17, 2011·BMC Bioinformatics·Qiyuan LiAron C Eklund
Feb 2, 2012·Archives of Medical Research·Rodrigo López-González, Iván Velasco
May 12, 2012·Journal of Molecular and Cellular Cardiology·Stephanie ProtzeUrsula Ravens
Jul 24, 2012·Nature Reviews. Molecular Cell Biology·Mo LiJuan Carlos Izpisua Belmonte
Jul 25, 2012·Proceedings of the National Academy of Sciences of the United States of America·Jose Francisco IslasRobert J Schwartz
Nov 30, 2012·Nucleic Acids Research·Tanya BarrettAlexandra Soboleva
Nov 30, 2012·Nucleic Acids Research·Kate R RosenbloomW James Kent
Apr 18, 2013·Journal of Molecular and Cellular Cardiology·Russell C AddisJohn D Gearhart
Sep 3, 2013·Journal of Graduate Medical Education·Gail M Sullivan, Richard Feinn
Sep 21, 2013·Current Eye Research·John L BradleyRoderick J Fullard
Dec 5, 2013·Briefings in Bioinformatics·Fatemeh SeyednasrollahLaura L Elo
Dec 10, 2013·Stem Cell Reports·Ji-Dong FuDeepak Srivastava
Jan 18, 2014·Nature Reviews. Genetics·Viviane Tabar, Lorenz Studer
Aug 16, 2014·Cell·Patrick CahanJames J Collins
Oct 30, 2014·Nucleic Acids Research·Damian SzklarczykChristian von Mering
Nov 2, 2014·Nucleic Acids Research·Nikolay KolesnikovAlvis Brazma
Nov 8, 2014·Investigative Ophthalmology & Visual Science·Ricardo F FraustoAnthony J Aldave
Feb 28, 2015·Genome Biology·Marina LizioUNKNOWN FANTOM consortium
Nov 26, 2015·Stem Cell Reports·Ana C D'AlessioRichard A Young
Jan 19, 2016·Nature Genetics·Owen J L RackhamJulian Gough

❮ Previous
Next ❯

Citations

Mar 6, 2021·Biochemical Society Transactions·Sebastian L Wild, David Tosh
Jul 25, 2021·Clinical Epigenetics·Amitava Basu, Vijay K Tiwari

❮ Previous
Next ❯

Methods Mentioned

BETA
RNA-Seq

Software Mentioned

FANTOM5
FANTOM
Mogrify
ArrayExpress
InfoMap
Spreadsheet
ENCODE
GSEA
R
STRING

Related Concepts

Related Feeds

Cell Fate Conversion By mRNA

mRNA-based technology is being studied as a potential technology that could be used to reprogram cell fate. This technique provides the potential to generate safe reprogrammed cells that can be used for clinical applications. Here is the latest research on cell fate conversion by mRNA.

Allogenic & Autologous Therapies

Allogenic therapies are generated in large batches from unrelated donor tissues such as bone marrow. In contrast, autologous therapies are manufactures as a single lot from the patient being treated. Here is the latest research on allogenic and autologous therapies.