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

@article{citeulike:370428, 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.}, address = {National Centre for Biological Sciences, Tata Institute for Fundamental Research, Bangalore 560065, India.}, author = {Krishna, S. and Banerjee, B. and Ramakrishnan, T. V. and Shivashankar, G. V. }, citeulike-article-id = {370428}, doi = {10.1073/pnas.0406415102}, issn = {0027-8424}, journal = {Proc Natl Acad Sci U S A}, keywords = {biophys, gene\_expression}, month = {March}, number = {13}, pages = {4771--4776}, posted-at = {2008-05-02 14:51:22}, priority = {2}, title = {Stochastic simulations of the origins and implications of long-tailed distributions in gene expression.}, url = {http://dx.doi.org/10.1073/pnas.0406415102}, volume = {102}, year = {2005} }

TY - JOUR ID - citeulike:370428 L3 - citeulike-article-id:370428 TI - Stochastic simulations of the origins and implications of long-tailed distributions in gene expression. JF - Proc Natl Acad Sci U S A VL - 102 IS - 13 SP - 4771 EP - 4776 AD - National Centre for Biological Sciences, Tata Institute for Fundamental Research, Bangalore 560065, India. SN - 0027-8424 N2 - 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. KW - biophys KW - gene_expression AU - Krishna, S AU - Banerjee, B AU - Ramakrishnan, TV AU - Shivashankar, GV PY - 2005/03/29/ UR - http://dx.doi.org/10.1073/pnas.0406415102 ER -