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Express yourself: UCLA researchers develop

Jan 10th 2014 at 8:51 PM

Individuals differ from each other genetically, each carrying a unique version of the human genome. Some of the genetic differences influence traits such as height, weight or vulnerability to certain diseases. But precisely what these genetic variants are and how they exercise their impact is still mostly unknown. However, UCLA researchers have developed a novel approach to study how these differences between individuals affect how strongly genes are expressed, or translated into the proteins that do the actual work in cells. Researchers developed their approach using different strains of yeast called Saccharomyces cerevisiae, a single-celled fungus excellent for the study of cellular and molecular biology and genetics.

They studied hundreds of thousands of genetically different yeast cells - orders of magnitude more than previously examined - making their approach statistically powerful and revealing more about how genetic differences influence gene expression than was previously known. Researchers also directly studied protein levels, differing their approach from earlier work that focused on the levels of messenger RNA (mRNA), intermediate molecules cells use to read genes and translate them into proteins. mRNAs are easier to measure than proteins, but their levels don't always correspond to protein levels.

The 2.5-year study found that the protein expression of a typical gene is influenced by many more genetic variants than previously thought, and that the effects of genetic differences on mRNA levels corresponded much better to the effects on protein expression than seen earlier. Additionally, there is a complex web of variants that each affects a large fraction of the proteins in the cells. The work could shed light on the study of disease risk in humans, as genetic variants that influence disease often act by affecting the expression of genes. Clinical applications may eventually flow from a better understanding of the process of genetic variants and protein expression.

The research appears in the Jan. 8, 2014 early online edition of the journal Nature.

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