Ribosome profiling is a powerful technique used to study translation at the genome-wide level, generating unique information concerning ribosome positions along RNAs. Optimal localization of ribosomes requires the proper identification of the ribosome P-site in each ribosome protected fragment, a crucial step to determine the trinucleotide periodicity of translating ribosomes, and draw correct conclusions concerning where ribosomes are located. To determine the P-site within ribosome footprints at nucleotide resolution, the precise estimation of its offset with respect to the protected fragment is necessary. Here we present riboWaltz, an R package for calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data. Compared to existing tools, riboWaltz shows improved accuracies for P-site estimation and neat ribosome positioning in multiple case studies. riboWaltz was implemented in R and is available as an R package at https://github.com/LabTranslationalArchitectomics/RiboWaltz.

The contribution of ribosome heterogeneity and ribosome-associated proteins to the molecular control of proteomes in health and disease remains enigmatic. We demonstrate that Survival Motor Neuron (SMN) protein, loss of which causes the neuromuscular disease spinal muscular atrophy (SMA), binds to ribosomes and that this interaction is tissue-dependent. SMN-primed ribosomes are preferentially positioned within the first five codons of a set of mRNAs which are enriched for translational enhancer sequences in the 5’UTR and rare codons at the beginning of their coding sequence. These SMN-specific mRNAs are associated with neurogenesis, lipid metabolism, ubiquitination, chromatin regulation and translation. Loss of SMN induces ribosome depletion, especially at the beginning of the coding sequence of SMN-specific mRNAs, leading to impairment of proteins involved in motor neuron function and stability, including acetylcholinesterase. Thus, SMN plays a crucial role in the regulation of ribosome fluxes along mRNAs which encode proteins relevant to SMA pathogenesis.

Highlights d RiboLace isolates ribosomes in active translation by antibody-free and tag-free pull-down d RiboLace works reliably with low amounts of input material in vitro and in vivo d RiboLace provides positional data of active ribosomes with nucleotide resolution d RiboLace estimates translation levels and predicts protein levels with accuracy

Ribosome profiling is a powerful technique used to study translation at the genome-wide level, generating unique information concerning ribosome positions along RNAs. Optimal localization of ribosomes requires the proper identification of the ribosome P-site in each ribosome protected fragment, a crucial step to determine trinucleotide periodicity of translating ribosomes, and draw correct conclusions concerning where ribosomes are located. To determine the P-site within ribosome footprints at nucleotide resolution, the precise estimation of its offset with respect to the protected fragment is necessary. Here we present riboWaltz, an R package for calculation of optimal P-site offsets, diagnostic analysis and visual inspection of data. Compared to existing tools, riboWaltz shows improved accuracies for P-site estimation and neat ribosome positioning in multiple case studies.

Ribosome profiling, or Ribo-Seq, is based around large-scale sequencing of RNA fragments protected from nuclease digestion by ribosomes. Thanks to its unique ability to provide positional information concerning ribosomes flowing along transcripts, this method can be used to shed light on mechanistic aspects of translation. However, current Ribo-Seq approaches lack the ability to distinguish between fragments protected by ribosomes in active translation or by inactive ribosomes. To overcome these significant limitation, we developed RiboLace: a novel method based on an original puromycin-containing molecule capable of isolating active ribosomes by means of an antibody-free and tag-free pull-down approach. RiboLace is fast, works reliably with low amounts of input material, and can be easily and rapidly applied both in vitro and in vivo, thereby generating a global snapshot of active ribosome footprints at single nucleotide resolution.