Skip to main content
  • Submit
  • About
    • Editorial Board
    • PNAS Staff
    • FAQ
    • Accessibility Statement
    • Rights and Permissions
    • Site Map
  • Contact
  • Journal Club
  • Subscribe
    • Subscription Rates
    • Subscriptions FAQ
    • Open Access
    • Recommend PNAS to Your Librarian
  • Log in
  • My Cart

Main menu

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
  • About
    • Editorial Board
    • PNAS Staff
    • FAQ
    • Accessibility Statement
    • Rights and Permissions
    • Site Map
  • Contact
  • Journal Club
  • Subscribe
    • Subscription Rates
    • Subscriptions FAQ
    • Open Access
    • Recommend PNAS to Your Librarian

User menu

  • Log in
  • My Cart

Search

  • Advanced search
Home
Home

Advanced Search

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses

New Research In

Physical Sciences

Featured Portals

  • Physics
  • Chemistry
  • Sustainability Science

Articles by Topic

  • Applied Mathematics
  • Applied Physical Sciences
  • Astronomy
  • Computer Sciences
  • Earth, Atmospheric, and Planetary Sciences
  • Engineering
  • Environmental Sciences
  • Mathematics
  • Statistics

Social Sciences

Featured Portals

  • Anthropology
  • Sustainability Science

Articles by Topic

  • Economic Sciences
  • Environmental Sciences
  • Political Sciences
  • Psychological and Cognitive Sciences
  • Social Sciences

Biological Sciences

Featured Portals

  • Sustainability Science

Articles by Topic

  • Agricultural Sciences
  • Anthropology
  • Applied Biological Sciences
  • Biochemistry
  • Biophysics and Computational Biology
  • Cell Biology
  • Developmental Biology
  • Ecology
  • Environmental Sciences
  • Evolution
  • Genetics
  • Immunology and Inflammation
  • Medical Sciences
  • Microbiology
  • Neuroscience
  • Pharmacology
  • Physiology
  • Plant Biology
  • Population Biology
  • Psychological and Cognitive Sciences
  • Sustainability Science
  • Systems Biology
Research Article

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

Maria Angels de Luis Balaguer, Adam P. Fisher, Natalie M. Clark, Maria Guadalupe Fernandez-Espinosa, Barbara K. Möller, Dolf Weijers, View ORCID ProfileJan U. Lohmann, Cranos Williams, Oscar Lorenzo, and Rosangela Sozzani
PNAS September 5, 2017 114 (36) E7632-E7640; first published August 21, 2017; https://doi.org/10.1073/pnas.1707566114
Maria Angels de Luis Balaguer
aPlant and Microbial Biology Department, North Carolina State University, Raleigh, NC 27695;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Adam P. Fisher
aPlant and Microbial Biology Department, North Carolina State University, Raleigh, NC 27695;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Natalie M. Clark
aPlant and Microbial Biology Department, North Carolina State University, Raleigh, NC 27695;
bBiomathematics Program, North Carolina State University, Raleigh, NC 27695;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maria Guadalupe Fernandez-Espinosa
cDepartamento de Botánica y Fisiología Vegetal, Instituto Hispano-Luso de Investigaciones Agrarias, Facultad de Biología, Universidad de Salamanca, 37185 Salamanca, Spain;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Barbara K. Möller
dLaboratory of Biochemistry, Wageningen University, 6703HA, Wageningen, The Netherlands;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dolf Weijers
dLaboratory of Biochemistry, Wageningen University, 6703HA, Wageningen, The Netherlands;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jan U. Lohmann
eDepartment of Stem Cell Biology, University of Heidelberg, Heidelberg D-69120, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jan U. Lohmann
Cranos Williams
fElectrical and Computer Engineering Department, North Carolina State University, Raleigh, NC 27695
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Oscar Lorenzo
cDepartamento de Botánica y Fisiología Vegetal, Instituto Hispano-Luso de Investigaciones Agrarias, Facultad de Biología, Universidad de Salamanca, 37185 Salamanca, Spain;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rosangela Sozzani
aPlant and Microbial Biology Department, North Carolina State University, Raleigh, NC 27695;
bBiomathematics Program, North Carolina State University, Raleigh, NC 27695;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ross_sozzani@ncsu.edu
  1. Edited by Julia Bailey-Serres, University of California, Riverside, CA, and approved July 31, 2017 (received for review May 7, 2017)

  • Article
  • Figures & SI
  • Info & Metrics
  • PDF
Loading

Significance

We developed a computational pipeline that uses gene expression datasets for inferring relationships among genes and predicting their importance. We showed that the capacity of our pipeline to integrate spatial and temporal transcriptional datasets improves the performance of inference algorithms. The combination of this pipeline with Arabidopsis stem cell-specific data resulted in networks that capture the regulations of stem cell-enriched genes in the stem cells and throughout root development. Our combined approach of molecular biology, computational biology, and mathematical biology, led to successful findings of factors that could play important roles in stem cell regulation and, in particular, quiescent center function.

Abstract

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells.

  • root stem cell
  • root development
  • cell-type expression profile
  • gene regulatory network
  • modeling

Footnotes

  • ↵1Present addresses: Department of Plant Systems Biology, Flanders Institute for Biotechnology (VIB), B-9052 Ghent, Belgium; and Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium.

  • ↵2To whom correspondence should be addressed. Email: ross_sozzani{at}ncsu.edu.
  • Author contributions: M.A.d.L.B. and R.S. designed research; M.A.d.L.B., A.P.F., N.M.C., M.G.F.-E., B.K.M., D.W., O.L., and R.S. performed research; J.U.L. and C.W. contributed new reagents/analytic tools; M.A.d.L.B., A.P.F., and N.M.C. analyzed data; and M.A.d.L.B. and R.S. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • Data deposition: The data reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database, https://www.ncbi.nlm.nih.gov/geo (accession nos. GSE76710, GSE97792, and GSE97857).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1707566114/-/DCSupplemental.

View Full Text
PreviousNext
Back to top
Article Alerts
Email Article

Thank you for your interest in spreading the word on PNAS.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells
(Your Name) has sent you a message from PNAS
(Your Name) thought you would like to see the PNAS web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Predicting GRNs in Arabidopsis root stem cells
Maria Angels de Luis Balaguer, Adam P. Fisher, Natalie M. Clark, Maria Guadalupe Fernandez-Espinosa, Barbara K. Möller, Dolf Weijers, Jan U. Lohmann, Cranos Williams, Oscar Lorenzo, Rosangela Sozzani
Proceedings of the National Academy of Sciences Sep 2017, 114 (36) E7632-E7640; DOI: 10.1073/pnas.1707566114

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Predicting GRNs in Arabidopsis root stem cells
Maria Angels de Luis Balaguer, Adam P. Fisher, Natalie M. Clark, Maria Guadalupe Fernandez-Espinosa, Barbara K. Möller, Dolf Weijers, Jan U. Lohmann, Cranos Williams, Oscar Lorenzo, Rosangela Sozzani
Proceedings of the National Academy of Sciences Sep 2017, 114 (36) E7632-E7640; DOI: 10.1073/pnas.1707566114
Digg logo Reddit logo Twitter logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Mendeley logo Mendeley
Proceedings of the National Academy of Sciences: 114 (36)
Table of Contents

Submit

Sign up for Article Alerts

Article Classifications

  • Biological Sciences
  • Plant Biology

Jump to section

  • Article
    • Abstract
    • Results
    • Discussion
    • Methods
    • Acknowledgments
    • Footnotes
    • References
  • Figures & SI
  • Info & Metrics
  • PDF

You May Also be Interested in

Surgeons hands during surgery
Inner Workings: Advances in infectious disease treatment promise to expand the pool of donor organs
Despite myriad challenges, clinicians see room for progress.
Image credit: Shutterstock/David Tadevosian.
Setting sun over a sun-baked dirt landscape
Core Concept: Popular integrated assessment climate policy models have key caveats
Better explicating the strengths and shortcomings of these models will help refine projections and improve transparency in the years ahead.
Image credit: Witsawat.S.
Double helix
Journal Club: Noncoding DNA shown to underlie function, cause limb malformations
Using CRISPR, researchers showed that a region some used to label “junk DNA” has a major role in a rare genetic disorder.
Image credit: Nathan Devery.
Steamboat Geyser eruption.
Eruption of Steamboat Geyser
Mara Reed and Michael Manga explore why Yellowstone's Steamboat Geyser resumed erupting in 2018.
Listen
Past PodcastsSubscribe
Birds nestling on tree branches
Parent–offspring conflict in songbird fledging
Some songbird parents might improve their own fitness by manipulating their offspring into leaving the nest early, at the cost of fledgling survival, a study finds.
Image credit: Gil Eckrich (photographer).

Similar Articles

Site Logo
Powered by HighWire
  • Submit Manuscript
  • Twitter
  • Facebook
  • RSS Feeds
  • Email Alerts

Articles

  • Current Issue
  • Special Feature Articles – Most Recent
  • List of Issues

PNAS Portals

  • Anthropology
  • Chemistry
  • Classics
  • Front Matter
  • Physics
  • Sustainability Science
  • Teaching Resources

Information

  • Authors
  • Editorial Board
  • Reviewers
  • Librarians
  • Press
  • Site Map
  • PNAS Updates

Feedback    Privacy/Legal

Copyright © 2021 National Academy of Sciences. Online ISSN 1091-6490