CaltechAUTHORS
  A Caltech Library Service

Causal Gene Regulatory Network Modeling and Genomics: Second-Generation Challenges

Rothenberg, Ellen V. (2019) Causal Gene Regulatory Network Modeling and Genomics: Second-Generation Challenges. Journal of Computational Biology, 26 (7). pp. 703-718. ISSN 1066-5277. PMCID PMC6661971. https://resolver.caltech.edu/CaltechAUTHORS:20190513-081636901

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20190513-081636901

Abstract

Gene regulatory network modeling has played a major role in advancing the understanding of developmental systems, by crystallizing structures of relevant extant information, by formally posing hypothetical functional relationships between network elements, and by offering clear predictive tests to improve understanding of the mechanisms driving developmental progression. Both ordinary differential equation (ODE)-based and Boolean models have also been highly successful in explaining dynamics within subcircuits of more complex processes. In a very small number of cases, gene regulatory network models of much more global scope have been proposed that successfully predict the dynamics of the processes establishing most of an embryonic body plan. Can such successes be expanded to very different developmental systems, including post-embryonic mammalian systems? This perspective discusses several problems that must be solved in more quantitative and predictive theoretical terms, to make this possible. These problems include: the effects of cellular history on chromatin state and how these affect gene accessibility; the dose dependence of activities of many transcription factors (a problem for Boolean models); stochasticity of some transcriptional outputs (a problem for simple ODE models); response timing delays due to epigenetic remodeling requirements; functionally different kinds of repression; and the regulatory syntax that governs responses of genes with multiple enhancers.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1089/cmb.2019.0098DOIArticle
http://www.ncbi.nlm.nih.gov/pmc/articles/pmc6661971/PubMed CentralArticle
ORCID:
AuthorORCID
Rothenberg, Ellen V.0000-0002-3901-347X
Additional Information:© 2019 Mary Ann Liebert, Inc., publishers. The author is indebted to Hao Yuan Kueh, Barbara J. Wold, Michael B. Elowitz, Carsten Peterson, Cornelis Murre, Isabelle Peter, Scott Barolo, James Briscoe, and the late Eric H. Davidson, and to members of the Rothenberg research group, for many discussions through which the ideas for this perspective were developed. Current gene network research in the Rothenberg lab has been supported by grants from the National Institutes of Health, USPHS, R01HL119102, R01HD076915, and R01AI095943; by the Louis A. Garfinkle Memorial Laboratory Fund; and by the Al Sherman Foundation. The author also gratefully acknowledges support from the Albert Billings Ruddock Professorship of Biology.
Funders:
Funding AgencyGrant Number
NIHR01HL119102
NIHR01HD076915
NIHR01AI095943
Louis A. Garfinkle Memorial Laboratory FundUNSPECIFIED
Al Sherman FoundationUNSPECIFIED
Albert Billings Ruddock ProfessorshipUNSPECIFIED
Subject Keywords:developmental kinetics; developmental regulation; epigenetic constraint; gene silencing and de-repression; modeling causality
Issue or Number:7
PubMed Central ID:PMC6661971
Record Number:CaltechAUTHORS:20190513-081636901
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190513-081636901
Official Citation:Causal Gene Regulatory Network Modeling and Genomics: Second-Generation Challenges. Ellen V. Rothenberg. Journal of Computational Biology 2019 26:7, 703-718; doi: 10.1089/cmb.2019.0098
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:95419
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:13 May 2019 16:29
Last Modified:14 Apr 2020 18:49

Repository Staff Only: item control page