A Caltech Library Service

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression

Phillips, Rob and Belliveau, Nathan M. and Chure, Griffin and Garcia, Hernan G. and Razo-Mejia, Manuel and Scholes, Clarissa (2019) Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression. Annual Review of Biophysics, 48 . pp. 121-163. ISSN 1936-122X. doi:10.1146/annurev-biophys-052118-115525.

[img] PDF - Submitted Version
Creative Commons Attribution.

[img] PDF - Supplemental Material
See Usage Policy.


Use this Persistent URL to link to this item:


It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles’ heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input–output function describing how the level of expression depends upon the parameters of the regulated gene—for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles’ heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Phillips, Rob0000-0003-3082-2809
Belliveau, Nathan M.0000-0002-1536-1963
Chure, Griffin0000-0002-2216-2057
Razo-Mejia, Manuel0000-0002-9510-0527
Additional Information:© 2019 Annual Reviews. We are grateful to a long list of generous colleagues who have helped us learn about this topic. We want to thank Stephanie Barnes, Lacra Bintu, James Boedicker, Rob Brewster, Robijn Bruinsma, Nick Buchler, Steve Busby, Jean-Pierre Changeux, Barak Cohen, Tal Einav, Uli Gerland, Ido Golding, Terry Hwa, Bill Ireland, Justin Kinney, Jane Kondev, Tom Kuhlman, Mitch Lewis, Sarah Marzen, Leonid Mirny, Alvaro Sanchez, Eran Segal, Marc Sherman, Kim Sneppen, Franz Weinert, Ned Wingreen, and Jon Widom. We are grateful to Steve Busby, Ido Golding, Justin Kinney, Tom Kuhlman, Steve Quake, and Alvaro Sanchez for reading the paper and providing important feedback. We are especially grateful to Nigel Orme, who has worked with us for years to create illustrations that tell a conceptual and quantitative story about physical biology. It has also been a privilege to be entrusted by the National Science Foundation (NSF), the National Institutes of Health (NIH), the California Institute of Technology, and La Fondation Pierre Gilles de Gennes with the funds that make this kind of research possible. Specifically we are grateful to the NIH for support through award numbers DP1 OD000217 (Director's Pioneer Award) and R01 GM085286. H.G.G. was supported by the Burroughs Wellcome Fund Career Award at the Scientific Interface, the Sloan Research Foundation, the Human Frontiers Science Program, the Searle Scholars Program, the Shurl & Kay Curci Foundation, the Hellman Foundation, the NIH Director's New Innovator Award (DP2 OD024541-01), and an NSF CAREER Award (1652236). Only a limited number of references from this vast field could be cited due to space considerations. Disclosure Statement: The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.
Funding AgencyGrant Number
NIHDP1 OD000217
La Fondation Pierre Gilles de GennesUNSPECIFIED
NIHR01 GM085286
Burroughs Wellcome FundUNSPECIFIED
Alfred P. Sloan FoundationUNSPECIFIED
Human Frontier Science ProgramUNSPECIFIED
Searle Scholars ProgramUNSPECIFIED
Shurl and Kay Curci FoundationUNSPECIFIED
Hellman FoundationUNSPECIFIED
NIHDP2 OD024541-01
Subject Keywords:gene regulation, transcription, allostery, biophysics, simple repression
Record Number:CaltechAUTHORS:20190520-085650396
Persistent URL:
Official Citation:Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression. Rob Phillips, Nathan M. Belliveau, Griffin Chure, Hernan G. Garcia, Manuel Razo-Mejia, Clarissa Scholes. Annual Review of Biophysics 2019 48:1, 121-163; doi: 10.1146/annurev-biophys-052118-115525
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:95587
Deposited By: Tony Diaz
Deposited On:20 May 2019 16:13
Last Modified:16 Nov 2021 17:13

Repository Staff Only: item control page