Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.
Abstract:
Accurately predicting noise propagation in gene networks iscrucial for understanding signal fidelity in natural networksand designing noise-tolerant gene circuits. To quantify hownoise propagates through gene networks, we measured expressioncorrelations between genes in single cells. We found that noisein a gene was determined by its intrinsic fluctuations, transmittednoise from upstream genes, and global noise affecting all genes.A model was developed that explains the complex behavior exhibitedby the correlations and reveals the dominant noise sources.The model successfully predicts the correlations as the networkis systematically perturbed. This approach provides a step towardunderstanding and manipulating noise propagation in more complexgene networks.
Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
* To whom correspondence should be addressed: E-mail: avano{at}mit.edu
The editors suggest the following Related Resources on Science sites:
In Science Magazine
PERSPECTIVES
Farren J. Isaacs, William J. Blake, and James J. Collins (25 March 2005) Science307 (5717), 1886.
[DOI: 10.1126/science.1110797] |Summary »|Full Text »|PDF »
REPORTS
Nitzan Rosenfeld, Jonathan W. Young, Uri Alon, Peter S. Swain, and Michael B. Elowitz (25 March 2005) Science307 (5717), 1962.
[DOI: 10.1126/science.1106914] |Abstract »|Full Text »|PDF »|Supporting Online Material »
Tunable synthetic phenotypic diversification on Waddington's landscape through autonomous signaling.
R. Sekine, M. Yamamura, S. Ayukawa, K. Ishimatsu, S. Akama, M. Takinoue, M. Hagiya, and D. Kiga (2011)
PNAS
108, 17969-17973
|Abstract »|Full Text »|PDF »
Information Transduction Capacity of Noisy Biochemical Signaling Networks.
R. Cheong, A. Rhee, C. J. Wang, I. Nemenman, and A. Levchenko (2011)
Science
334, 354-358
|Abstract »|Full Text »|PDF »
T. Fournier, J.P. Gabriel, C. Mazza, J. Pasquier, J.L. Galbete, and N. Mermod (2007)
Bioinformatics
23, 3185-3192
|Abstract »|Full Text »|PDF »
Phenotypic variability of growing cellular populations.
T. Lu, T. Shen, M. R. Bennett, P. G. Wolynes, and J. Hasty (2007)
PNAS
104, 18982-18987
|Abstract »|Full Text »|PDF »
Cell-to-Cell Heterogeneity in Growth Rate and Gene Expression in Methylobacterium extorquens AM1.
T. J. Strovas, L. M. Sauter, X. Guo, and M. E. Lidstrom (2007)
J. Bacteriol.
189, 7127-7133
|Abstract »|Full Text »|PDF »
Biology by design: reduction and synthesis of cellular components and behaviour.
P. Marguet, F. Balagadde, C. Tan, and L. You (2007)
J R Soc Interface
4, 607-623
|Abstract »|Full Text »|PDF »
Chromosome-specific and noisy IFNB1 transcription in individual virus-infected human primary dendritic cells.
J. Hu, S. C. Sealfon, F. Hayot, C. Jayaprakash, M. Kumar, A. C. Pendleton, A. Ganee, A. Fernandez-Sesma, T. M. Moran, and J. G. Wetmur (2007)
Nucleic Acids Res.
|Abstract »|Full Text »|PDF »
Computational methods for diffusion-influenced biochemical reactions.
M. Dobrzynski, J. V. Rodriguez, J. A. Kaandorp, and J. G. Blom (2007)
Bioinformatics
23, 1969-1977
|Abstract »|Full Text »|PDF »
Combinatorial promoter design for engineering noisy gene expression.
A synthetic time-delay circuit in mammalian cells and mice.
W. Weber, J. Stelling, M. Rimann, B. Keller, M. Daoud-El Baba, C. C. Weber, D. Aubel, and M. Fussenegger (2007)
PNAS
104, 2643-2648
|Abstract »|Full Text »|PDF »