TY - JOUR T1 - Polysome-profiling in small tissue samples JF - bioRxiv DO - 10.1101/104596 SP - 104596 AU - Shuo Liang AU - Hermano Bellato AU - Julie Lorent AU - Fernanda Lupinacci AU - Vincent Van Hoef AU - Laia Masvidal AU - Glaucia Hajj AU - Ola Larsson Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/02/01/104596.abstract N2 - Polysome-profiling is commonly used to study genome wide patterns of translational efficiency, i.e. the translatome. The standard approach for collecting efficiently translated polysome-associated RNA results in laborious extraction of RNA from a large volume spread across multiple fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts such as primary cells or frozen tissues. To address this we optimized a non-linear sucrose gradient which reproducibly enriches for mRNAs associated with >3 ribosomes in only one or two fractions, thereby reducing sample handling 5-10 fold. The technique can be applied to cells and frozen tissue samples from biobanks, and generates RNA with a quality reflecting the starting material. When coupled with smart-seq2, a single-cell RNA sequencing technique, translatomes from small tissue samples can be obtained. Translatomes acquired using optimized non-linear gradients are very similar to those obtained when applying linear gradients. Polysome-profiling using optimized nonlinear gradients in HCT-116 cells with or without p53 identified a translatome associated with p53 status under serum starvation. Thus, here we present a polysome-profiling technique applicable to larger studies, primary cells where RNA amount is low and frozen tissue samples. ER -