- About Us
- People
- Undergrad
- Graduate
- Research
- News & Events
-
News by Year
- 2022
- Physics Professors named Canada Research Chairs
- Physics Faculty and Graduate Student Win Teaching Awards
- SFU Physics Professor wins 2021 Buchalter Cosmology Prize
- Dr. Hayden's Research in SFU Scholarly Impact
- Karen Kavanagh selected as a Fellow of the MRS
- Applied Physics undergrad wins AMPP Poster Competition
- Physics BSc Grad Gives Convocation Address
- 2021
- Simmons wins Women of Distinction Award
- Pogosian's Research in SFU Scholarly Impact
- PhD Graduate Awarded Convocation Medal
- Convocation Speaker Aidan Wright
- Nancy Forde Elected BSC President
- Bechhoefer named Royal Society of Canada Fellow
- Jeff Sonier Named American Physical Society Fellow
- SFU undergrads receive quantum grant award
- 2020
- 2019
- 2018
- 2022
- Events by Year
- Events By Category
-
News by Year
- Outreach
- _how-to
- Congratulations to our Class of 2021
- Archive
Biophysics and Soft Matter Seminar
Dissecting the causes of natural variation in protein expression dynamics
Daniel Pollard
Dept of Biology, Western Washington University
Dissecting the causes of natural variation in protein expression dynamics
Mar 09, 2016
Synopsis
Yeast cells respond to their environment by coordinating the expression of thousands of genes to produce a specific complement of millions of protein molecules. Natural genetic variation has the potential to impact protein expression dynamics by acting at different levels, including transcription, mRNA stability, translation, and protein stability. The link between genetic variation and mRNA expression divergence is well established, however, the importance of genetic variation acting on protein translation and degradation rates is poorly resolved. To distinguish genetic variation acting directly on mRNA levels from genetic variation acting directly on protein levels, and to dissect how these two types of variation affect different phases of a dynamic cellular response, we measured both mRNA and protein expression dynamics in the Saccharomyces cerevisiae laboratory strain S288c and the clinical strain YJM145. I will present our analysis of variation in protein expression dynamics in the mating pheromone response network. Our results suggest that genetic variation commonly acts on protein translation and degradation rates, independently of mRNA levels. I will discuss our ongoing efforts to dissect this new class of genetic variants, including whole proteome analysis, mapping causative variants, and characterizing molecular mechanisms.