Understanding the relationship between codon optimality and mRNA stability

NIH RePORTER · NIH · R35 · $608,823 · view on reporter.nih.gov ↗

Abstract

Project Summary Messenger RNA transmits genetic information from DNA to protein. The regulation of mRNA levels is a fine balance between transcription rate and degradation rate. Transcriptional control is well documented and studied. Although the major pathways in mRNA turnover have been identified, accounting for disparate half-lives has been elusive. My lab has shown that codon optimality is a general feature that contributes greatly to mRNA stability in eukaryotes. Codon optimality reflects the disproportionate rate by which the ribosome deciphers each of the 61 codons. The randomness of tRNA selection during the mRNA decoding process manifests in codon optimality wherein tRNA concentrations/functionality dramatically influence rate. Accordingly, codon optimality is ultimately gauged by the relative prevalence of cognate tRNAs, wherein a codon is deemed `optimal' when tRNAs are in excess and conversely `non-optimal' when tRNAs are more limiting. Codon optimality is also determined by the thermodynamic stability of codon/anticodon pairing. Our major advance has been to show that the mRNA degradation machinery monitors ribosome speed and responds to degrade message when ribosome movement is relatively slow. In this proposal, we investigate how the mRNA degradation complex senses ribosome translocation rate as a function of codon optimality. We will determine the precise molecular events that occur in response to ribosome hesitations. Moreover, we focus on biological context where codon optimality is regulated both through mRNA chemical modification and tRNA regulated expression. Lastly the influence of codon optimality is now seen to be the major determinant of mRNA stability in yeast and in early development. Thus work through this project has uncovered a central and critical principle in biology that contributes broadly to gene expression regulation.

Key facts

NIH application ID
10330674
Project number
1R35GM144114-01
Recipient
JOHNS HOPKINS UNIVERSITY
Principal Investigator
Jeffery Coller
Activity code
R35
Funding institute
NIH
Fiscal year
2022
Award amount
$608,823
Award type
1
Project period
2022-06-01 → 2027-05-31