Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics

Therapeutic mRNAs and vaccines are being developed for a broad range of human diseases, including COVID-19. However, their optimization is hindered by mRNA instability and inefficient protein expression. Here, we describe design principles that overcome these barriers. We develop an RNA sequencing-based platform called PERSIST-seq to systematically delineate in-cell mRNA stability, ribosome load, as well as in-solution stability of a library of diverse mRNAs. We find that, surprisingly, in-cell stability is a greater driver of protein output than high ribosome load. We further introduce a method called In-line-seq, applied to thousands of diverse RNAs, that reveals sequence and structure-based rules for…

• NS
  National Science Foundation
• DR
  Damon Runyon Cancer Research Foundation
• P
  Pfizer
• OS
  Oregon State University
• B
  Baidu
• NI
  National Institutes of Health

  Awards: R35 GM122579, R01HD086634, R21 CA219847, GM122579
• UO
  University of California, San Francisco
• SB
  Stanford Bio-X
• CE
  Chemistry, Engineering and Medicine for Human Health, Stanford University
• CI
  Canadian Institutes of Health Research