Noise reduction facilitated by dosage compensation in gene networks.

Weilin Peng, Ruijie Song, Murat Acar

Journal: Nature communications 2018;7():12959

PMID: 27694830

Abstract

Genetic noise together with genome duplication and volume changes during cell cycle are significant contributors to cell-to-cell heterogeneity. How can cells buffer the effects of these unavoidable epigenetic and genetic variations on phenotypes that are sensitive to such variations? Here we show that a simple network motif that is essential for network-dosage compensation can reduce the effects of extrinsic noise on the network output. Using natural and synthetic gene networks with and without the network motif, we measure gene network activity in single yeast cells and find that the activity of the compensated network is significantly lower in noise compared with the non-compensated network. A mathematical analysis provides intuitive insights into these results and a novel stochastic model tracking cell-volume and cell-cycle predicts the experimental results. Our work implies that noise is a selectable trait tunable by evolution.

Address: Department of Molecular, Cellular and Developmental Biology, Yale University, 219 Prospect Street, New Haven, Connecticut 06511, USA.; Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, Connecticut 06516, USA.; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 501, New Haven, Connecticut 06511, USA.; Department of Physics, Yale University, 217 Prospect Street, New Haven, Connecticut 06511, USA.
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