Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Computational approaches identify novel transcription factor combinations that promote corticospinal axon growth after injury

Ishwariya Venkatesh, Vatsal Mehra, Zimei Wang, Matthew T. Simpson, Erik Eastwood, Advaita Chakraborty, Zac Beine, Derek Gross, Michael Cabahug, Greta Olson, Murray G. Blackmore
doi: https://doi.org/10.1101/2020.06.12.146159
Ishwariya Venkatesh
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ishwariya.venkatesh@marquette.edu murray.blackmore@marquette.edu
Vatsal Mehra
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zimei Wang
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew T. Simpson
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Erik Eastwood
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Advaita Chakraborty
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zac Beine
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Derek Gross
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael Cabahug
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Greta Olson
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Murray G. Blackmore
1Department of Biomedical Sciences, Marquette University, Milwaukee, WI
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ishwariya.venkatesh@marquette.edu murray.blackmore@marquette.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Transcription factors (TFs) act as powerful levers to regulate neural physiology and can be targeted to improve cellular responses to injury or disease. Because TFs often depend on cooperative activity, a major challenge is to identify and deploy optimal sets. Here we developed a novel bioinformatics pipeline, centered on TF co-occupancy of regulatory DNA, and used it to predict factors that improve axon growth in corticospinal tract (CST) axons when combined with a known pro-regenerative TF, Klf6. Assays of neurite outgrowth confirmed cooperative activity by 12 candidates, and in vivo testing showed strong promotion of CST growth upon combined expression of Klf6 and Nr5a2. Transcriptional profiling of CST neurons identified Klf6/Nr5a2-responsive gene networks involved in macromolecule biosynthesis and DNA repair. These data identify novel TF combinations that promote enhanced CST growth, clarify the transcriptional correlates, and provide a bioinformatics roadmap to detect TF synergy.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Conflict of Interest: None

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted June 12, 2020.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Computational approaches identify novel transcription factor combinations that promote corticospinal axon growth after injury
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Computational approaches identify novel transcription factor combinations that promote corticospinal axon growth after injury
Ishwariya Venkatesh, Vatsal Mehra, Zimei Wang, Matthew T. Simpson, Erik Eastwood, Advaita Chakraborty, Zac Beine, Derek Gross, Michael Cabahug, Greta Olson, Murray G. Blackmore
bioRxiv 2020.06.12.146159; doi: https://doi.org/10.1101/2020.06.12.146159
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Computational approaches identify novel transcription factor combinations that promote corticospinal axon growth after injury
Ishwariya Venkatesh, Vatsal Mehra, Zimei Wang, Matthew T. Simpson, Erik Eastwood, Advaita Chakraborty, Zac Beine, Derek Gross, Michael Cabahug, Greta Olson, Murray G. Blackmore
bioRxiv 2020.06.12.146159; doi: https://doi.org/10.1101/2020.06.12.146159

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (2533)
  • Biochemistry (4975)
  • Bioengineering (3486)
  • Bioinformatics (15229)
  • Biophysics (6908)
  • Cancer Biology (5395)
  • Cell Biology (7751)
  • Clinical Trials (138)
  • Developmental Biology (4539)
  • Ecology (7157)
  • Epidemiology (2059)
  • Evolutionary Biology (10233)
  • Genetics (7516)
  • Genomics (9790)
  • Immunology (4860)
  • Microbiology (13231)
  • Molecular Biology (5142)
  • Neuroscience (29464)
  • Paleontology (203)
  • Pathology (838)
  • Pharmacology and Toxicology (1465)
  • Physiology (2142)
  • Plant Biology (4754)
  • Scientific Communication and Education (1013)
  • Synthetic Biology (1338)
  • Systems Biology (4014)
  • Zoology (768)