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Background Ribosomes are highly conserved molecular machines whose core composition has traditionally been regarded as invariant. However, recent studies have reported intriguing differences in the expression of some ribosomal proteins (RPs) across tissues and highly specific effects on the translation of individual mRNAs. Results To determine whether RPs are more generally linked to cell identity, we analyze the heterogeneity of RP expression in a large set of human tissues, primary cells, and tumors. We find that about a quarter of human RPs exhibit tissue-specific expression and that primary hematopoietic cells display the most complex patterns of RP expression, likely shaped by context-restricted transcriptional regulators. Strikingly, we uncover patterns of dysregulated expression of individual RPs across cancer types that arise through copy number variations and are predictive for disease progression. Conclusions Our study reveals an unanticipated plasticity of RP expression across normal and malignant human cell types and provides a foundation for future characterization of cellular behaviors that are orchestrated by specific RPs.

With human median lifespan extending into the 80s in many developed countries, the societal burden of age-related muscle loss (sarcopenia) is increasing. mTORC1 promotes skeletal muscle hypertrophy, but also drives organismal aging. Here, we address the question of whether mTORC1 activation or suppression is beneficial for skeletal muscle aging. We demonstrate that chronic mTORC1 inhibition with rapamycin is overwhelmingly, but not entirely, positive for aging mouse skeletal muscle, while genetic, muscle fiber-specific activation of mTORC1 is sufficient to induce molecular signatures of sarcopenia. Through integration of comprehensive physiological and extensive gene expression profiling in young and old mice, and following genetic activation or pharmacological inhibition of mTORC1, we establish the phenotypically-backed, mTORC1-focused, multi-muscle gene expression atlas, SarcoAtlas (https://sarcoatlas.scicore.unibas.ch/), as a user-friendly gene discovery tool. We uncover inter-muscle divergence in the primary drivers of sarcopenia and identify the neuromuscular junction as a focal point of mTORC1-driven muscle aging. mTORC1 expression is increased during ageing of muscle, and on the other hand, its activation promotes muscle hypertrophy. Here, the authors assess whether mTORC1 has positive or negative effects on ageing, and show that its long-term inhibition preserves muscle mass and function and neuromuscular junction integrity, whereas muscle-specific activation is associated with sarcopenia.

Despite substantial progress in single-cell RNA-seq (scRNA-seq) data analysis methods, there is still little agreement on how to best normalize such data. Starting from the basic requirements that inferred expression states should correct for both biological and measurement sampling noise and that changes in expression should be measured in terms of fold changes, we here derive a Bayesian normalization procedure called Sanity (SAmpling-Noise-corrected Inference of Transcription activitY) from first principles. Sanity estimates expression values and associated error bars directly from raw unique molecular identifier (UMI) counts without any tunable parameters. Using simulated and real scRNA-seq datasets, we show that Sanity outperforms other normalization methods on downstream tasks, such as finding nearest-neighbor cells and clustering cells into subtypes. Moreover, we show that by systematically overestimating the expression variability of genes with low expression and by introducing spurious correlations through mapping the data to a lower-dimensional representation, other methods yield severely distorted pictures of the data. A Bayesian procedure overcomes challenges in single-cell RNA-seq data normalization.

Although protein synthesis dynamics has been studied both with theoretical models and by profiling ribosome footprints, the determinants of ribosome flux along open reading frames (ORFs) are not fully understood. Combining measurements of protein synthesis rate with ribosome footprinting data, we here inferred translation initiation and elongation rates for over a 1,000 ORFs in exponentially growing wild-type yeast cells. We found that the amino acid composition of synthesized proteins is as important a determinant of translation elongation rate as parameters related to codon and transfer RNA (tRNA) adaptation. We did not find evidence of ribosome collisions curbing the protein output of yeast transcripts, either in high translation conditions associated with exponential growth, or in strains in which deletion of individual ribosomal protein (RP) genes leads to globally increased or decreased translation. Slow translation elongation is characteristic of RP-encoding transcripts, which have markedly lower protein output compared with other transcripts with equally high ribosome densities.

Preserving skeletal muscle function is essential to maintain life quality at high age. Calorie restriction (CR) potently extends health and lifespan, but is largely unachievable in humans, making “CR mimetics” of great interest. CR targets nutrient-sensing pathways centering on mTORC1. The mTORC1 inhibitor, rapamycin, is considered a potential CR mimetic and is proven to counteract age-related muscle loss. Therefore, we tested whether rapamycin acts via similar mechanisms as CR to slow muscle aging. Here we show that long-term CR and rapamycin unexpectedly display distinct gene expression profiles in geriatric mouse skeletal muscle, despite both benefiting aging muscles. Furthermore, CR improves muscle integrity in mice with nutrient-insensitive, sustained muscle mTORC1 activity and rapamycin provides additive benefits to CR in naturally aging mouse muscles. We conclude that rapamycin and CR exert distinct, compounding effects in aging skeletal muscle, thus opening the possibility of parallel interventions to counteract muscle aging. The anti-aging intervention calorie restriction (CR) is thought to act via the nutrient-sensing multiprotein complex mTORC1. Here the authors show that the mTORC1-inhibitor rapamycin and CR use largely distinct mechanisms to slow mouse muscle aging.

Background The design of nucleotide sequences with defined properties is a long-standing problem in bioengineering. An important application is protein expression, be it in the context of research or the production of mRNA vaccines. The rate of protein synthesis depends on the 5′ untranslated region (5′UTR) of the mRNAs, and recently, deep learning models were proposed to predict the translation output of mRNAs from the 5′UTR sequence. At the same time, large data sets of endogenous and reporter mRNA translation have become available. Results In this study, we use complementary data obtained in two different cell types to assess the accuracy and generality of currently available models for predicting translational output. We find that while performing well on the data sets on which they were trained, deep learning models do not generalize well to other data sets, in particular of endogenous mRNAs, which differ in many properties from reporter constructs. Conclusions These differences limit the ability of deep learning models to uncover mechanisms of translation control and to predict the impact of genetic variation. We suggest directions that combine high-throughput measurements and machine learning to unravel mechanisms of translation control and improve construct design.

We present RCRUNCH, an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins. RCRUNCH can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment. By applying RCRUNCH to the eCLIP data from the ENCODE project, we have constructed a comprehensive and homogeneous resource of in-vivo-bound RBP sequence motifs. RCRUNCH automates the reproducible analysis of CLIP data, enabling studies of post-transcriptional control of gene expression.

The comparison of cross-linking and immunoprecipitation (CLIP) and photoactivatable ribonucleoside–enhanced CLIP (PAR-CLIP) protocols shows specific biases of each method in enriching subsets of binding sites of RNA-binding proteins and shows ways around these biases. Cross-linking and immunoprecipitation (CLIP) is increasingly used to map transcriptome-wide binding sites of RNA-binding proteins. We developed a method for CLIP data analysis, and applied it to compare CLIP with photoactivatable ribonucleoside–enhanced CLIP (PAR-CLIP) and to uncover how differences in cross-linking and ribonuclease digestion affect the identified sites. We found only small differences in accuracies of these methods in identifying binding sites of HuR, which binds low-complexity sequences, and Argonaute 2, which has a complex binding specificity. We found that cross-link–induced mutations led to single-nucleotide resolution for both PAR-CLIP and CLIP. Our results confirm the expectation from original CLIP publications that RNA-binding proteins do not protect their binding sites sufficiently under the denaturing conditions used during the CLIP procedure, and we show that extensive digestion with sequence-specific RNases strongly biases the recovered binding sites. This bias can be substantially reduced by milder nuclease digestion conditions.

Background Nonsense-mediated mRNA decay (NMD) is a eukaryotic, translation-dependent degradation pathway that targets mRNAs with premature termination codons and also regulates the expression of some mRNAs that encode full-length proteins. Although many genes express NMD-sensitive transcripts, identifying them based on short-read sequencing data remains a challenge. Results To identify and analyze endogenous targets of NMD, we apply cDNA Nanopore sequencing and short-read sequencing to human cells with varying expression levels of NMD factors. Our approach detects full-length NMD substrates that are highly unstable and increase in levels or even only appear when NMD is inhibited. Among the many new NMD-targeted isoforms that our analysis identifies, most derive from alternative exon usage. The isoform-aware analysis reveals many genes with significant changes in splicing but no significant changes in overall expression levels upon NMD knockdown. NMD-sensitive mRNAs have more exons in the 3΄UTR and, for those mRNAs with a termination codon in the last exon, the length of the 3΄UTR per se does not correlate with NMD sensitivity. Analysis of splicing signals reveals isoforms where NMD has been co-opted in the regulation of gene expression, though the main function of NMD seems to be ridding the transcriptome of isoforms resulting from spurious splicing events. Conclusions Long-read sequencing enables the identification of many novel NMD-sensitive mRNAs and reveals both known and unexpected features concerning their biogenesis and their biological role. Our data provide a highly valuable resource of human NMD transcript targets for future genomic and transcriptomic applications.

Mutations in the RNA-binding protein Fused in Sarcoma (FUS) cause early-onset amyotrophic lateral sclerosis (ALS). However, a detailed understanding of central RNA targets of FUS and their implications for disease remain elusive. Here, we use a unique blend of crosslinking and immunoprecipitation (CLIP) and NMR spectroscopy to identify and characterise physiological and pathological RNA targets of FUS. We find that U1 snRNA is the primary RNA target of FUS via its interaction with stem-loop 3 and provide atomic details of this RNA-mediated mode of interaction with the U1 snRNP. Furthermore, we show that ALS-associated FUS aberrantly contacts U1 snRNA at the Sm site with its zinc finger and traps snRNP biogenesis intermediates in human and murine motor neurons. Altogether, we present molecular insights into a FUS toxic gain-of-function involving direct and aberrant RNA-binding and strengthen the link between two motor neuron diseases, ALS and spinal muscular atrophy (SMA). Mutations in the RNA binding protein FUS cause amyotrophic lateral sclerosis (ALS). Here the authors characterize FUS-binding to U1 snRNP and show that ALS-associated FUS aberrantly contacts U1 snRNA which interferes with its biogenesis pathway.