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

Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis

CS Thom, CD Jobaliya, K Lorenz, JA Maguire, A Gagne, P Gadue, DL French, BF Voight
doi: https://doi.org/10.1101/631895
CS Thom
Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, USADepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USADepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: thomc@email.chop.edu bvoight@pennmedicine.upenn.edu
CD Jobaliya
Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, PA, USADepartment of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
K Lorenz
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USADepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
JA Maguire
Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, PA, USADepartment of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
A Gagne
Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, PA, USADepartment of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
P Gadue
Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, PA, USADepartment of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DL French
Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, PA, USADepartment of Pathology and Laboratory Medicine, The Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
BF Voight
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USADepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USAInstitute of Translational Medicine and Therapeutics, University of Pennsylvania, PA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: thomc@email.chop.edu bvoight@pennmedicine.upenn.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Introductory paragraph

A better understanding of the genetic mechanisms regulating hematopoiesis are necessary, and could augment translational efforts to generate red blood cells (RBCs) and/or platelets in vitro. Using available genome-wide association data sets, we applied a machine-learning framework to identify genomic features enriched at established platelet trait associations and score variants genome-wide to identify biologically plausible gene candidates. We found that high-scoring SNPs marked relevant loci and genes, including an expression quantitative trait locus for Tropomyosin 1 (TPM1). CRISPR/Cas9-mediated TPM1 knockout in human induced pluripotent stem cells (iPSCs) unexpectedly enhanced early hematopoietic progenitor development. Our findings may help explain human genetics associations and identify a novel genetic strategy to enhance in vitro hematopoiesis, increasing RBC and MK yield.

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 May 08, 2019.
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.
Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis
CS Thom, CD Jobaliya, K Lorenz, JA Maguire, A Gagne, P Gadue, DL French, BF Voight
bioRxiv 631895; doi: https://doi.org/10.1101/631895
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis
CS Thom, CD Jobaliya, K Lorenz, JA Maguire, A Gagne, P Gadue, DL French, BF Voight
bioRxiv 631895; doi: https://doi.org/10.1101/631895

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

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (1544)
  • Biochemistry (2500)
  • Bioengineering (1757)
  • Bioinformatics (9727)
  • Biophysics (3928)
  • Cancer Biology (2990)
  • Cell Biology (4234)
  • Clinical Trials (135)
  • Developmental Biology (2653)
  • Ecology (4129)
  • Epidemiology (2033)
  • Evolutionary Biology (6931)
  • Genetics (5243)
  • Genomics (6531)
  • Immunology (2206)
  • Microbiology (7012)
  • Molecular Biology (2781)
  • Neuroscience (17410)
  • Paleontology (127)
  • Pathology (432)
  • Pharmacology and Toxicology (712)
  • Physiology (1068)
  • Plant Biology (2515)
  • Scientific Communication and Education (647)
  • Synthetic Biology (835)
  • Systems Biology (2698)
  • Zoology (439)