This Title All WIREs
How to cite this WIREs title:
WIREs Syst Biol Med
Impact Factor: 4.192

Using variability in gene expression as a tool for studying gene regulation

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

With the advent of quantitative tools for measuring gene expression in single cells, researchers have made the discovery that in many contexts, messenger RNA and protein levels can vary widely from cell to cell, often because of inherently stochastic events associated with gene expression. The study of this cellular individuality has become a field of study in its own right, characterized by a blend of technological development, theoretical analysis, and, more recently, applications to biological phenomena. In this review, we focus on the use of the variability inherent to gene expression as a tool to understand gene regulation. We discuss the use of variability as a natural systems‐level perturbation, its use in quantitatively characterizing the biological processes underlying transcription, and its application to the discovery of new gene regulatory interactions. We believe that use of variability can provide new biological insights into different aspects of transcriptional control and can provide a powerful complementary approach to that of existing techniques. WIREs Syst Biol Med 2013, 5:751–759. doi: 10.1002/wsbm.1243 This article is categorized under: Analytical and Computational Methods > Analytical Methods Laboratory Methods and Technologies > Genetic/Genomic Methods

This WIREs title offers downloadable PowerPoint presentations of figures for non-profit, educational use, provided the content is not modified and full credit is given to the author and publication.

Download a PowerPoint presentation of all images

Characterizing gene regulation using expression variability. (a,b) Depiction of different types of regulation and how they would manifest themselves as correlations or anticorrelations in gene expression at the single‐cell level (assuming only intrinsic noise in gene expression). (c) Time‐lapse microscopy of an individual Escherichia coli cell that triggers a positive gene expression feedback loop. (d) Using variability to map out the threshold level of expression required to trigger the feedback loop. (c and d: Reprinted with permission from Ref . Copyright 2008 The American Association for the Advancement of Science)
[ Normal View | Magnified View ]
Multiplex imaging‐based approaches for measuring the expression of multiple genes at the same time in single cells. (a) Color‐coding and barcoding approaches currently enable the measurement of up to 32 genes simultaneously in yeast. (b) Expression profiles of 32 genes in single cells cluster into distinct categories of genes. (a and b: Reprinted with permission from Ref . Copyright 2012). (c) Simultaneous measurement of transcriptional activity of 20 genes on chromosome 19 in primary human cells. (d) Correlating the transcriptional activity of the 20 genes on a per‐chromosome basis revealed a strong anticorrelation between two genes separated by roughly 14 Mb. (c and d: Reprinted with permission from Ref . Copyright 2013 Nature Publishing Group)
[ Normal View | Magnified View ]

Browse by Topic

Laboratory Methods and Technologies > Genetic/Genomic Methods
Analytical and Computational Methods > Analytical Methods

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts