TY - JOUR T1 - The genetic and biochemical determinants of mRNA degradation rates in mammals JF - bioRxiv DO - 10.1101/2022.03.18.484474 SP - 2022.03.18.484474 AU - Vikram Agarwal AU - David Kelley Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/03/19/2022.03.18.484474.abstract N2 - Background Degradation rate is a fundamental aspect of mRNA metabolism, and the factors governing it remain poorly characterized. Understanding the genetic and biochemical determinants of mRNA half-life would enable a more precise identification of variants that perturb gene expression through post-transcriptional gene regulatory mechanisms.Results Here, we establish a compendium of 54 human and 27 mouse transcriptome-wide mRNA decay rate datasets. A meta-analysis of these data identified a prevalence of technical noise and measurement bias, induced partially by the underlying experimental strategy. Correcting for these biases allowed us to derive more precise, consensus measurements of half-life which exhibit enhanced consistency between species. We trained substantially improved statistical models based upon genetic and biochemical features to better predict half-life and characterize the factors molding it. Our state-of-the-art model, Saluki, is a hybrid convolutional and recurrent deep neural network which relies only upon an mRNA sequence annotated with coding frame and splice sites to predict half-life (r=0.77). Saluki predicts the impact of RNA sequences and genetic mutations therein on mRNA stability, in agreement with functional measurements derived from massively parallel reporter assays.Conclusions Our work produces a more robust “ground truth” with regards to transcriptome-wide mRNA half-lives in mammalian cells. Using these consolidated measurements, we trained a model that is over 50% more accurate in predicting half-life from sequence than existing models. Our best model, Saluki, succinctly captures many of the known determinants of mRNA half-life and can be rapidly deployed to predict the functional consequences of arbitrary mutations in the transcriptome.Competing Interest StatementV.A. and D.R.K. are employees of Calico Life Sciences LLC. ER -