Model-guided engineering of DNA sequences with predictable site-specific recombination rates

Abstract

Site-specific recombination (SSR) is an important tool in synthetic biology, but its applications are limited by the inability to predictably tune SSR reaction rates. Here, using quantitative high-throughput experiments and machine learning, the authors achieve rational control of a DNA attachment site sequence to predictably modulate site-specific recombination rates both in vitro and in cells.