Deciphering mRNA Sequence Determinants of Protein Production Rate

Juraj Szavits-Nossan (1) , Luca Ciandrini (2, 3) , M. Carmen Romano (4)

1 SUPA School of Physics and Astronomy [Edinburgh]
2 L2C - Laboratoire Charles Coulomb
3 DIMNP - Dynamique des interactions membranaires normales et pathologiques
4 University of Aberdeen

One of the greatest challenges in biophysical models of translation is to identify coding sequences features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allow us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, together with the value of the initiation rate, are the main determinants of protein production rate. Finally, we interpret the obtained analytic results based on the evolutionary role of codons' choice for regulating translation rates and ribosome densities.

Domaines: Biophysique [physics.bio-ph]; Mécanique statistique [cond-mat.stat-mech]; Organisation et fonctions cellulaires [q-bio.SC]

Juraj Szavits-Nossan, Luca Ciandrini, M. Carmen Romano. Deciphering mRNA Sequence Determinants of Protein Production Rate. Physical Review Letters, 2018, 120, pp.128101. ⟨10.1103/PhysRevLett.120.128101⟩. ⟨hal-01585251⟩