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Researchers quantify more noise in gene expression

Human identical twins have different fingerprints and march to the beat of subtly different phenotypes, an indication of heterogeneity which led bioengineering researchers at the University of California, San Diego (UCSD) to devised computer algorithms that identify the underlying sources of variation at the basic level of life: unscripted fluctuations within individual cells and variations between identical cells.

"Scientists might assume that natural selection would prune any sloppiness at the level of gene expression, but recent studies by our group at UCSD and others have shown that is definitely not the case," said Jeff Hasty, a bioengineering professor at UCSD's Jacobs School of Engineering. "Many individual genes produce less than 10 copies of regulatory messenger molecules, which is such a small number that it makes clockwork-like regularity of downstream cellular circuits statistically impossible. Our group and others have detected and classified significant downstream fluctuations that result from this source of 'intrinsic noise' in gene expression."

Hasty leads a team of researchers at UCSD that will report in the Dec. 21 issue of Nature a mathematical description of "extrinsic noise," an even larger component of variation in gene expression. This second type of noise results because no two genetically identical cells can keep the same time. The measurement of extrinsic noise was based on experiments involving baker's yeast, Saccharomyces cerevisiae, but the phenomenon and the way it is described mathematically would apply to other types of cells and other species.

"Individual yeast cells exist at various stages of their growth cycle, and this extrinsic variability explains a large component of the noise that must be accounted for in creating a mathematical model of the cell," said Dmitri Volfson, project scientist and a co-author of the study. "In this case, one yeast cell may be preparing to divide, another may be the result of a recent division, and the phenotypes of these two otherwise identical cells can be very different."

Macroscopic variations are routinely observed in the genetically identical cells of organisms ranging in complexity from bacteria to mammals. "Watchmakers can neither make individual watches with intrinsically perfect accuracy, nor perfectly synchronize any two watches to eliminate extrinsic variations," said Hasty. "And intrinsic and extrinsic variation in gene expression also prevents genetically identical cells growing side-by-side from ticking in unison."

Intrinsic noise resulting from low copy numbers of molecules has been the focus of earlier studies by Hasty's group. Its Nature paper focuses on extrinsic noise, an even larger source of variation between identical cells growing side-by-side in identical conditions. "This extrinsic noise originates from cells being out of phase in their growth cycle," said Hasty. "It's unavoidable. This study also established an 'extrinsic-noise floor' in 11 genes for which intrinsic noise is negligible."

The group measured the noise floor by used genetically engineered strains of yeast with a green fluorescence marker linked to a gene involved in the metabolism of the sugar galactose. The galactose gene and 10 others were chosen because they are expressed in yeast cells in high copy numbers, a feature that makes intrinsic noise in their expression statistically insignificant. By making cell-to-cell comparisons of the activation of the galactose-fluorescence gene pair in experiments with one to five copies of the gene pair per cell, the team was able to measure the extrinsic-noise floor, a parameter that is needed to create a mathematical algorithm describing gene-expression variation in yeast.

"This may sound relatively straightforward: extrinsic variability is due to individual cells growing out of phase with one another," said Hasty. "However, this study is the first rigorous description of this variability, which will be very helpful to researchers eager to account for variations in gene expression as they build rigorous, comprehensive models of this and other types of cells."


Source:University of California - San Diego

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