Identifying ribosome heterogeneity using ribosome profiling

Recent studies have revealed multiple mechanisms that can lead to heterogeneity in ribosomal composition. This heterogeneity can lead to preferential translation of specific panels of mRNAs, and is defined in large part by the ribosomal protein (RP) content, amongst other things. However, it is currently unknown to what extent ribosomal composition is heterogeneous across tissues, which is compounded by a lack of tools available to study it. Here we present dripARF, a method for detecting differential RP incorporation into the ribosome using Ribosome Profiling (Ribo-seq) data. We combine the 'waste' rRNA fragment data generated in Ribo-seq with the known 3D structure of the human ribosome to predict differences in the composition of ribosomes in the material being studied. We have validated this approach using publicly available data, and have revealed a potential role for eS25/RPS25 in development. Our results indicate that ribosome heterogeneity can be detected in Ribo-seq data, providing a new method to study this phenomenon. Furthermore, with dripARF, previously published Ribo-seq data provides a wealth of new information, allowing the identification of RPs of interest in many disease and normal contexts. dripARF is available as part of the ARF R package and can be accessed through https://github.com/fallerlab/ARF.

Automated summary

Recent studies have identified multiple mechanisms that contribute to the heterogeneity in ribosomal composition, and have developed a new method, called dripARF, to study this phenomenon. This method uses Ribosome Profiling (Ribo-seq) data to detect differential protein incorporation into the ribosome by combining "waste" rRNA fragment data with the known 3D structure of the human ribosome. The results indicate that ribosome heterogeneity can be detected in Ribo-seq data, providing a new tool to study this phenomenon.