Genome-wide patterns of sequence divergence over evolutionary time provide a unique window into the fundamental metabolic costs imposed on cellular life. Purifying selection eliminates mutations that increase costs and/or promote genetic disease. This process can discern minor cost differences, even ones that may not be readily measurable by direct laboratory experiments. This project will identify and interpret the evolutionary signals imprinted into genomes by one specific cost, the cost of erroneously translating proteins. Mistranslation events lead to protein misfolding, misfolded proteins can be cytotoxic or require costly cleanup, and selection operates both on the codon and on the amino-acid level to minimize cellular exposure to misfolded proteins. The working hypothesis for this project is that among the costs linked to translation, mistranslation-induced misfolding is the dominant one, whereas other costs, including mistranslation-induced loss of function and translation at reduced speed, play a minor role. This hypothesis will be tested using a combination of bioinformatics, mathematical modeling, and computer simulation, and the relative importance of the various translation- linked costs will be quantified. There are three specific aims. 1. What makes translationally optimal codons optimal? 2. Does selection against protein misfolding shapes synonymous codon usage? 3. How does protein biophysics interact with translational selection to constrain sequence evolution?

Public Health Relevance

All organisms have to translate proteins accurately and efficiently;mutations that interfere with efficient translation impair cellular function and cause disease states in humans. This project will identify the specific costs associated with mutations that affect translation, and will provide insight into which mutations are most likely to impose meaningful costs on cellular function. This research will impact several health-related areas, including the industrial production of drug compounds in genetically modified microbes and the cause and detection of certain kinds of genetic diseases in humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM088344-01
Application #
7694950
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Eckstrand, Irene A
Project Start
2009-08-01
Project End
2013-05-31
Budget Start
2009-08-01
Budget End
2010-05-31
Support Year
1
Fiscal Year
2009
Total Cost
$261,707
Indirect Cost
Name
University of Texas Austin
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
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