25Protein synthesis is dysregulated in many diseases, but we lack a systems-level picture of how signaling 26 molecules and RNA binding proteins interact with the translational machinery, largely due to 27 technological limitations. Here we present riboPLATE-seq, a scalable method for generating paired 28 libraries of ribosome-associated and total mRNA. As an extension of the PLATE-seq protocol, riboPLATE-29 seq utilizes barcoded primers for pooled library preparation, but additionally leverages rRNA 30 immunoprecipitation on whole polysomes to measure ribosome association (RA). We demonstrate the 31 performance of riboPLATE-seq and its utility in detecting translational alterations induced by inhibition 32 of protein kinases. 33 34 KEYWORDS 35 RNA-seq, translation, ribosome, immunoprecipitation, mTOR, MNK 36 37 BACKGROUND 38The cellular responses to many physiologic stimuli require new programs of protein production. 39Transcriptional regulation allows direct control of gene expression over a broad dynamic range, but cells 40 can often more rapidly adjust protein expression levels through translational control. Consequently, 41 alongside transcription factors and their associated regulatory networks, there are mechanisms of 42 modulating the translation of specific genes. mTOR is an important example of a translational regulator 43 that integrates many potential extracellular signals to regulate cellular metabolism and protein 44 synthesis. Activated through the PI3K/Akt/mTOR signaling axis, mTORC1 phosphorylates eIF4E inhibitors 45 (4E-binding proteins, or 4E-BPs), which releases eIF4E and promotes formation of the eIF4F complex in 46 3 the initial steps of translational initiation 1 . The actions of mTORC1 are mediated in a sequence-specific 47 manner by 5' terminal oligopyrimidine (5'TOP) motifs, which are C/T-rich sequences in the 5' UTRs of 48 mTORC1 target transcripts 2 . The mTOR protein, the 4E-BP/eIF4E axis, and the 5'TOP tract-containing 49 genes (TOP genes) constitute a basic translational regulatory network. 50Despite the attention garnered by profiling and modeling transcription control networks, less progress 51 has been made in understanding systems-level translational control. This is in part due to technological 52 limitations of current translational profiling protocols, which lack the scalability for coupling 53 measurements of protein synthesis with a large number of perturbations. Early genome-wide studies of 54 translational regulation combined polysome profiling and microarray analysis to quantify ribosome 55 association on a gene-by-gene basis 3 . The combination of nuclease footprinting of ribosomes 4 and deep 56 sequencing led to the development of ribosome profiling, which refines translational profiling by 57 resolving the positions of bound ribosomes throughout the transcriptome with single-nucleotide 58 resolution 5 More recent modifications expand on this concept, such as cell type specificity through 59 recombinant tagging of ribosomes driven by cell type-specific markers (e.g. Ri...