Publication Date:
2012-04-14
Description:
Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a major source of this variability, and its physiological consequences have been topics of intense research for the last decade. Several recent studies have measured variability in protein and messenger RNA levels, and they have discovered strong connections between noise and gene regulation mechanisms. When integrated with discrete stochastic models, measurements of cell-to-cell variability provide a sensitive "fingerprint" with which to explore fundamental questions of gene regulation. In this review, we highlight several studies that used gene expression variability to develop a quantitative understanding of the mechanisms and dynamics of gene regulation.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3358231/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉 〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3358231/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Munsky, Brian -- Neuert, Gregor -- van Oudenaarden, Alexander -- 1DP1OD003936/OD/NIH HHS/ -- DP1 CA174420/CA/NCI NIH HHS/ -- DP1 OD003936/OD/NIH HHS/ -- New York, N.Y. -- Science. 2012 Apr 13;336(6078):183-7. doi: 10.1126/science.1216379.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Nonlinear Studies, the National Flow Cytometry Resource, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. munsky@lanl.gov〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22499939" target="_blank"〉PubMed〈/a〉
Keywords:
Animals
;
*Gene Expression
;
*Gene Expression Regulation
;
Humans
;
*Models, Genetic
;
Models, Statistical
;
Phenotype
;
RNA, Messenger/genetics/metabolism
;
Stochastic Processes
;
Transcription, Genetic
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
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