Stochastic simulations of the origins and implications of long-tailed distributions in gene expression

Krishna, Sandeep and Banerjee, Bidisha and Ramakrishnan, TV and Shivashankar, GV (2005) Stochastic simulations of the origins and implications of long-tailed distributions in gene expression. In: Proceedings of National Academy of Science United States America, 102 (13). pp. 4771-4776.

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Abstract

Gene expression noise results in protein number distributions ranging from long-tailed to Gaussian. We show how long-tailed distributions arise from a stochastic model of the constituent chemical reactions and suggest that, in conjunction with cooperative switches, they lead to more sensitive selection of a subpopulation of cells with high protein number than is possible with Gaussian distributions. Single-cell-tracking experiments are presented to validate some of the assumptions of the stochastic simulations. We also examine the effect of DNA looping on the shape of protein distributions. We further show that when switches are incorporated in the regulation of a gene via a feedback loop, the distributions can become bimodal. This might explain the bimodal distribution of certain morphogens during early embryogenesis.

Item Type:	Journal Article
Publication:	Proceedings of National Academy of Science United States America
Publisher:	National Academy of Sciences
Additional Information:	Copyright of this article belongs to National Academy of Sciences.
Department/Centre:	Division of Physical & Mathematical Sciences > Physics
Date Deposited:	29 Apr 2010 06:58
Last Modified:	19 Sep 2010 06:01
URI:	http://eprints.iisc.ac.in/id/eprint/27382

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