Lorent, J. | bioRxiv Science

bioRxiv2017

Genome-wide analysis of differential translation and differential translational buffering using anota2seq

mRNA translation plays an evolutionarily conserved role in homeostasis and when dysregulated results in various disorders. Optimal and universally applicable analytical methods to study transcriptome-wide changes in translational efficiency are therefore critical for understanding the complex role of translation regulation under physiological and pathological conditions. Techniques used to interrogate translatomes, including polysome- and ribosome-profiling, require adjustment for changes in total mRNA levels to capture bona fide alterations in translational efficiency. Herein, we present the anota2seq algorithm for such analysis using data from ribosome- or polysome-profiling quantified by DNA-microarrays or RNA sequencing, which outperforms current methods for identification of changes in translational efficiency. In contrast to available analytical methods, anota2seq also allows capture of an underappreciated mode for regulation of gene expression whereby translation acts as a buffering mechanism which maintains constant protein levels despite fluctuations in mRNA levels (\"translational buffering\"). Application of anota2seq shows that insulin affects gene expression at multiple levels, in a largely mTOR-dependent manner. Moreover, insulin induces levels of a subset of mRNAs independently of mTOR that undergo translational buffering upon mTOR inhibition. Thus, the universal anota2seq algorithm allows efficient and hitherto unprecedented interrogation of translatomes and enables studies of translational buffering which represents an unexplored mechanism for regulating of gene expression.

bioinformatics↗

bioRxiv2017

Polysome-profiling in small tissue samples

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.

molecular biology↗