Our research is focussed on understanding the dynamics and evolution of translational regulation.
1. Evolution of translational regulation in bacteria:
Using Lenski's long-term E. coli evolution experiment as a model system, we are characterizing the transcriptional and translational changes during 50,000 generations of adaptation.
2. Whole-cell models of yeast protein synthesis:
Using a whole-cell simulation model that integrates transcriptional noise with translation, we are studying how transcriptional bursts, codon usage patterns, and tRNA charging influences the dynamics of protein synthesis in yeast.
3. Sequence determinants of transcriptional and translational noise:
Using smFISH, flow cytometry, and large oligo pools, we are characterizing how various sequence-based features of genes influence transcriptional and translational noise in yeast.
4. tRNA charging and yeast stress response:
Using high-throughput tRNA sequencing, we are characterizing how codon usage patterns and tRNA pools change during yeast growth under stress.
Weinberg DE*, Shah P*, et al. Improved ribosome-footprint and mRNA measurements provide insights into dynamics and regulation of yeast translation. Cell Reports (2016)
Shah P*, McCandlish DM* and Plotkin JB. Contingency and entrenchment in protein evolution under purifying selection.PNAS 112: E3226–E3235 (2015)
Shah P, et al. Rate-limiting steps in yeast protein translation.Cell 153 (7): 1589-1601 (2013)
Xu Y, Ma P, Shah P, et al. Non-optimal codon usage is a mechanism to achieve circadian clock conditionality. Nature 495: 116-120 (2013)
Shah P, and Gilchrist MA. Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift. PNAS 108: 10231-6 (2011)
Shah P, and Gilchrist MA. Effect of correlated tRNA abundances on translation errors and the evolution of codon usage bias.PLOS Genetics 6 (9): e1001128 (2010)