Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data

RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution

Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26–34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.

Transcriptome-Wide Analysis of Interplay between mRNA Stability, Translation and Small RNAs in Response to Neuronal Membrane Depolarization

Experience-dependent changes to neural circuitry are shaped by spatially-restricted activity-dependent mRNA translation. Although the complexity of mRNA translation in neuronal cells is widely appreciated, translational profiles associated with neuronal excitation remain largely uncharacterized, and the associated regulatory mechanisms are poorly understood. Here, we employed ribosome profiling, mRNA sequencing and small RNA sequencing to profile transcriptome-wide changes in mRNA translation after whole cell depolarization of differentiated neuroblast cultures, and investigate the contribution of sequence-specific regulatory mechanisms. Immediately after depolarization, a functional partition between transcriptional and translational responses was uncovered, in which many mRNAs were subjected to significant changes in abundance or ribosomal occupancy, but not both. After an extended (2 h) post-stimulus rest phase, however, these changes became synchronized, suggesting that there are different layers of post-transcriptional regulation which are temporally separated but become coordinated over time. Globally, changes in mRNA abundance and translation were found to be associated with a number of intrinsic mRNA features, including mRNA length, GC% and secondary structures; however, the effect of these factors differed between both post-depolarization time-points. Furthermore, small RNA sequencing revealed that miRNAs and tRNA-derived small RNA fragments were subjected to peak changes in expression immediately after stimulation, during which these molecules were predominantly associated with fluctuations in mRNA abundance, consistent with known regulatory mechanisms. These data suggest that excitation-associated neuronal translation is subjected to extensive temporal coordination, with substantial contributions from a number of sequence-dependent regulatory mechanisms.

RiboMiner: a toolset for mining multi-dimensional features of the translatome with ribosome profiling data

Background

Ribosome profiling has been widely used for studies of translation under a large variety of cellular and physiological contexts. Many of these studies have greatly benefitted from a series of data-mining tools designed for dissection of the translatome from different aspects. However, as the studies of translation advance quickly, the current toolbox still falls in short, and more specialized tools are in urgent need for deeper and more efficient mining of the important and new features of the translation landscapes.

Results

Here, we present RiboMiner, a bioinformatics toolset for mining of multi-dimensional features of the translatome with ribosome profiling data. RiboMiner performs extensive quality assessment of the data and integrates a spectrum of tools for various metagene analyses of the ribosome footprints and for detailed analyses of multiple features related to translation regulation. Visualizations of all the results are available. Many of these analyses have not been provided by previous methods. RiboMiner is highly flexible, as the pipeline could be easily adapted and customized for different scopes and targets of the studies.

Conclusions

Applications of RiboMiner on two published datasets did not only reproduced the main results reported before, but also generated novel insights into the translation regulation processes. Therefore, being complementary to the current tools, RiboMiner could be a valuable resource for dissections of the translation landscapes and the translation regulations by mining the ribosome profiling data more comprehensively and with higher resolution. RiboMiner is freely available at https://github.com/xryanglab/RiboMiner and https://pypi.org/project/RiboMiner.

Active Tonic mTORC1 Signals Shape Baseline Translation in Naive T Cells

Naive CD4⁺ T cells are an example of dynamic cell homeostasis: T cells need to avoid autoreactivity while constantly seeing self-peptides, yet they must be primed to react to foreign antigens during infection. The instructive signals that balance this primed yet quiescent state are unknown. Interactions with self-peptides result in membrane-proximal, tonic signals in resting T cells. Here we reveal selective and robust tonic mTORC1 signals in CD4⁺ T cells that influence T cell fate decisions. We find that the Ras exchange factor Rasgrp1 is necessary to generate tonic mTORC1 signals. Genome-wide ribosome profiling of resting, primary CD4⁺ T cells uncovers a baseline translational landscape rich in mTOR targets linked to mitochondria, oxidative phosphorylation, and splicing. Aberrantly increased tonic mTORC1 signals from a Rasgrp1^Anaef allele result in immunopathology with spontaneous appearance of T peripheral helper cells, follicular helper T cells, and anti-nuclear antibodies that are preceded by subtle alterations in the translational landscape.

Myers et al. evaluate a mouse model of autoimmunity, Rasgrp1^Anaef. They find that T cells with the Rasgrp1^Anaef allele exhibit altered signaling from Rasgrp1 to the mTORC1 pathway in the basal state. They show that increased basal Rasgrp1^Anaef-mTORC1 signals lead to an altered translational landscape in T cells and immunopathology.

Computational methods for ribosome profiling data analysis

Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation.

Widespread Alterations in Translation Elongation in the Brain of Juvenile Fmr1 Knockout Mice

FMRP (fragile X mental retardation protein) is a polysome-associated RNA-binding protein encoded by Fmr1 that is lost in fragile X syndrome. Increasing evidence suggests that FMRP regulates both translation initiation and elongation, but the gene specificity of these effects is unclear. To elucidate the impact of Fmr1 loss on translation, we utilize ribosome profiling for genome-wide measurements of ribosomal occupancy and positioning in the cortex of 24-day-old Fmr1 knockout mice. We find a remarkably coherent reduction in ribosome footprint abundance per mRNA for previously identified, high-affinity mRNA binding partners of FMRP and an increase for terminal oligopyrimidine (TOP) motif-containing genes canonically controlled by mammalian target of rapamycin-eIF4E-binding protein-eIF4E binding protein-eukaryotic initiation factor 4E (mTOR-4E-BP-eIF4E) signaling. Amino acid motif- and gene-level analyses both show a widespread reduction of translational pausing in Fmr1 knockout mice. Our findings are consistent with a model of FMRP-mediated regulation of both translation initiation through eIF4E and elongation that is disrupted in fragile X syndrome.

Characterising the Transcriptional and Translational Impact of the Schizophrenia-Associated miR-1271-5p in Neuronal Cells

MicroRNA (miRNA) coordinate complex gene expression networks in cells that are vital to support highly specialised morphology and cytoarchitecture. Neurons express a rich array of miRNA, including many that are specific or enriched, which have important functions in this context and implications for neurological conditions. While the neurological function of a number of brain-derived miRNAs have been examined thoroughly, the mechanistic basis of many remain obscure. In this case, we investigated the transcriptome-wide impact of schizophrenia-associated miR-1271-5p in response to bidirectional modulation. Alteration of miR-1271-5p induced considerable changes to mRNA abundance and translation, which spanned a diverse range of cellular functions, including directly targeted genes strongly associated with cytoskeletal dynamics and cellular junctions. Mechanistic analyses additionally revealed that upregulation of miR-1271-5p predominantly repressed mRNAs through destabilisation, wherein 3'UTR and coding sequence binding sites exhibited similar efficacy. Knockdown, however, produced no discernible trend in target gene expression and strikingly resulted in increased expression of the highly conserved miR-96-5p, which shares an identical seed region with miR-1271-5p, suggesting the presence of feedback mechanisms that sense disruptions to miRNA levels. These findings indicate that, while bidirectional regulation of miR-1271-5p results in substantial remodeling of the neuronal transcriptome, these effects are not inverse in nature. In addition, we provide further support for the idea that destabilisation of mRNA is the predominant mechanism by which miRNAs regulate complementary mRNAs.

The Ccr4-Not complex monitors the translating ribosome for codon optimality

Control of messenger RNA (mRNA) decay rate is intimately connected to translation elongation, but the spatial coordination of these events is poorly understood. The Ccr4-Not complex initiates mRNA decay through deadenylation and activation of decapping. We used a combination of cryo-electron microscopy, ribosome profiling, and mRNA stability assays to examine the recruitment of Ccr4-Not to the ribosome via specific interaction of the Not5 subunit with the ribosomal E-site in Saccharomyces cerevisiae This interaction occurred when the ribosome lacked accommodated A-site transfer RNA, indicative of low codon optimality. Loss of the interaction resulted in the inability of the mRNA degradation machinery to sense codon optimality. Our findings elucidate a physical link between the Ccr4-Not complex and the ribosome and provide mechanistic insight into the coupling of decoding efficiency with mRNA stability.

Pervasive functional translation of noncanonical human open reading frames

Ribosome profiling has revealed pervasive but largely uncharacterized translation outside of canonical coding sequences (CDSs). In this work, we exploit a systematic CRISPR-based screening strategy to identify hundreds of noncanonical CDSs that are essential for cellular growth and whose disruption elicits specific, robust transcriptomic and phenotypic changes in human cells. Functional characterization of the encoded microproteins reveals distinct cellular localizations, specific protein binding partners, and hundreds of microproteins that are presented by the human leukocyte antigen system. We find multiple microproteins encoded in upstream open reading frames, which form stable complexes with the main, canonical protein encoded on the same messenger RNA, thereby revealing the use of functional bicistronic operons in mammals. Together, our results point to a family of functional human microproteins that play critical and diverse cellular roles.

XPRESSyourself: Enhancing, standardizing, and automating ribosome profiling computational analyses yields improved insight into data

Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools for these data is bleak. We introduce XPRESSyourself, an analytical toolkit that eliminates barriers and bottlenecks associated with this specialized data type by filling gaps in the computational toolset for both experts and non-experts of ribosome profiling. XPRESSyourself automates and standardizes analysis procedures, decreasing time-to-discovery and increasing reproducibility. This toolkit acts as a reference implementation of current best practices in ribosome profiling analysis. We demonstrate this toolkit’s performance on publicly available ribosome profiling data by rapidly identifying hypothetical mechanisms related to neurodegenerative phenotypes and neuroprotective mechanisms of the small-molecule ISRIB during acute cellular stress. XPRESSyourself brings robust, rapid analysis of ribosome-profiling data to a broad and ever-expanding audience and will lead to more reproducible and accessible measurements of translation regulation. XPRESSyourself software is perpetually open-source under the GPL-3.0 license and is hosted at https://github.com/XPRESSyourself, where users can access additional documentation and report software issues.

YB-3 substitutes YB-1 in global mRNA binding

Y-box binding proteins are DNA- and RNA-binding proteins with an evolutionarily ancient and conserved cold shock domain. The Y-box binding protein 1 (YB-1) is the most studied due to its abundance in somatic cells. YB-1 is involved in a variety of cellular processes, including proliferation, differentiation and stress response. Here, using Ribo-Seq and RIP-Seq we confirm that YB-1 binds a wide range of mRNAs and globally acts as a translation inhibitor. Surprisingly, YBX1 knockout results in only minor alterations in the expression of other genes, mostly caused by changes in RNA abundance. But YB-3 mRNA is an exception: it is better translated in the absence of YB-1, thereby producing an increased amount of YB-3 and thus suggesting that its synthesis is under YB-1 negative control. We have shown that the set of mRNAs bound to YB-3 is strikingly similar to that of YB-1, and that the mRNA-binding by YB-3 is enhanced in the absence of YB-1, resulting in a similar global reduction of translation of bound mRNAs in YB-1-null cells. Thus, YB-3 acts as a substitute for YB-1 in mRNA binding and, probably, in global translational control.

Hallmarks and Determinants of Oncogenic Translation Revealed by Ribosome Profiling in Models of Breast Cancer

Gene expression is extensively and dynamically modulated at the level of translation. How cancer cells prioritize the translation of certain mRNAs over others from a pool of competing mRNAs remains an open question. Here, we analyze translation in cell line models of breast cancer and normal mammary tissue by ribosome profiling. We identify key recurrent themes of oncogenic translation: higher ribosome occupancy, greater variance of translational efficiencies, and preferential translation of transcriptional regulators and signaling proteins in malignant cells as compared with their nonmalignant counterpart. We survey for candidate RNA interacting proteins that could associate with the 5′untranslated regions of the transcripts preferentially translated in breast tumour cells. We identify SRSF1, a prototypic splicing factor, to have a pervasive direct and indirect impact on translation. In a representative estrogen receptor–positive and estrogen receptor–negative cell line, we find that protein synthesis relies heavily on SRSF1. SRSF1 is predominantly intranuclear. Under certain conditions, SRSF1 translocates from the nucleus to the cytoplasm where it associates with MYC and CDK1 mRNAs and upregulates their internal ribosome entry site–mediated translation. Our results point to a synergy between splicing and translation and unveil how certain RNA-binding proteins modulate the translational landscape in breast cancer.

DeepShape: estimating isoform-level ribosome abundance and distribution with Ribo-seq data

Background

Ribosome profiling brings insight to the process of translation. A basic step in profile construction at transcript level is to map Ribo-seq data to transcripts, and then assign a huge number of multiple-mapped reads to similar isoforms. Existing methods either discard the multiple mapped-reads, or allocate them randomly, or assign them proportionally according to transcript abundance estimated from RNA-seq data.

Results

Here we present DeepShape, an RNA-seq free computational method to estimate ribosome abundance of isoforms, and simultaneously compute their ribosome profiles using a deep learning model. Our simulation results demonstrate that DeepShape can provide more accurate estimations on both ribosome abundance and profiles when compared to state-of-the-art methods. We applied DeepShape to a set of Ribo-seq data from PC3 human prostate cancer cells with and without PP242 treatment. In the four cell invasion/metastasis genes that are translationally regulated by PP242 treatment, different isoforms show very different characteristics of translational efficiency and regulation patterns. Transcript level ribosome distributions were analyzed by “Codon Residence Index (CRI)” proposed in this study to investigate the relative speed that a ribosome moves on a codon compared to its synonymous codons. We observe consistent CRI patterns in PC3 cells. We found that the translation of several codons could be regulated by PP242 treatment.

Conclusion

In summary, we demonstrate that DeepShape can serve as a powerful tool for Ribo-seq data analysis.

Cycloheximide can distort measurements of mRNA levels and translation efficiency

Regulation of the efficiency with which an mRNA is translated into proteins represents a key mechanism for controlling gene expression. Such regulation impacts the number of actively translating ribosomes per mRNA molecule, referred to as translation efficiency (TE), which can be monitored using ribosome profiling and RNA-seq, or by evaluating the position of an mRNA in a polysome gradient. Here we show that in budding yeast, under nutrient limiting conditions, the commonly used translation inhibitor cycloheximide induces rapid transcriptional upregulation of hundreds of genes involved in ribosome biogenesis. Cycloheximide also prevents translation of these newly transcribed messages, leading to an apparent drop in TE of these genes under conditions that include key transitions during the yeast metabolic cycle, meiosis, and amino acid starvation; however, this effect is abolished when cycloheximide pretreatment is omitted. This response requires TORC1 signaling, and is modulated by the genetic background as well as the vehicle used to deliver the drug. The present work highlights an important caveat to the use of translation inhibitors when measuring TE or mRNA levels, and will hopefully aid in future experimental design as well as interpretation of prior results.

mQC: A post-mapping data exploration tool for ribosome profiling

BACKGROUND AND OBJECTIVE

Ribosome profiling is a recent next generation sequencing technique enabling the genome-wide study of gene expression in biomedical research at the translation level. Too often, researchers precipitously start trying to test their hypotheses after alignment of their data, without checking the quality and the general features of their mapped data. Despite the fact that these checks are essential to prevent errors and ensure valid conclusions afterwards, easy-to-use tools for visualizing the quality and overall outlook of mapped ribosome profiling data are lacking.

METHODS

We present mQC, a modular tool implemented as a Bioconda package and also available in the Galaxy tool shed. Herewith both bio-informaticians as well as non-experts can easily perform the indispensable visualization of both the quality and the general features of their mapped P-site corrected ribosome profiling reads. The user manual, the raw code and more information can be found on its GitHub repository (https://github.com/Biobix/mQC).

RESULTS

mQC was tested on multiple datasets to assess its general applicability and was compared to other tools that partly perform similar tasks.

CONCLUSIONS

Our results demonstrate that mQC can accomplish an unfilled but essential position in the ribosome profiling data analysis procedure by performing a thorough RIBO-Seq-specific exploration of aligned and P-site corrected ribosome profiling data.

PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms

PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. the sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data pre-exploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field. More practical information on the pipeline, raw code, the user manual (README) and explanations on the different modes of availability can be found at the GitHub repository of PROTEOFORMER: https://github.com/Biobix/proteoformer.

Selective ribosome profiling to study interactions of translating ribosomes in yeast

A number of enzymes, targeting factors and chaperones engage ribosomes to support fundamental steps of nascent protein maturation, including enzymatic processing, membrane targeting and co-translational folding. The selective ribosome profiling (SeRP) method is a new tool for studying the co-translational activity of maturation factors that provides proteome-wide information on a factor's nascent interactome, the onset and duration of binding and the mechanisms controlling factor engagement. SeRP is based on the combination of two ribosome-profiling (RP) experiments, sequencing the ribosome-protected mRNA fragments from all ribosomes (total translatome) and the ribosome subpopulation engaged by the factor of interest (factor-bound translatome). We provide a detailed SeRP protocol, exemplified for the yeast Hsp70 chaperone Ssb (stress 70 B), for studying factor interactions with nascent proteins that is readily adaptable to identifying nascent interactomes of other co-translationally acting eukaryotic factors. The protocol provides general guidance for experimental design and optimization, as well as detailed instructions for cell growth and harvest, the isolation of (factor-engaged) monosomes, the generation of a cDNA library and data analysis. Experience in biochemistry and RNA handling, as well as basic programing knowledge, is necessary to perform SeRP. Execution of a SeRP experiment takes 8-10 working days, and initial data analysis can be completed within 1-2 d. This protocol is an extension of the originally developed protocol describing SeRP in bacteria.

Computational resources for ribosome profiling: from database to Web server and software

Ribosome profiling is emerging as a powerful technique that enables genome-wide investigation of in vivo translation at sub-codon resolution. The increasing application of ribosome profiling in recent years has achieved remarkable progress toward understanding the composition, regulation and mechanism of translation. This benefits from not only the awesome power of ribosome profiling but also an extensive range of computational resources available for ribosome profiling. At present, however, a comprehensive review on these resources is still lacking. Here, we survey the recent computational advances guided by ribosome profiling, with a focus on databases, Web servers and software tools for storing, visualizing and analyzing ribosome profiling data. This review is intended to provide experimental and computational biologists with a reference to make appropriate choices among existing resources for the question at hand.

Multimapping confounds ribosome profiling analysis: A case-study of the Hsp90 molecular chaperone

Ribosome profiling (Ribo-seq) can potentially provide detailed information about ribosome position on transcripts and estimates of protein translation levels in vivo. Hsp90 chaperones, which play a critical role in stress tolerance, have characteristic patterns of differential expression under nonstressed and heat shock conditions. By analyzing published Ribo-seq data for the Hsp90 chaperones in S. cerevisiae, we find wide-ranging artifacts originating from "multimapping" reads (reads that cannot be uniquely assigned to one position), which constitute ~25% of typical S. cerevisiae Ribo-seq datasets and ~80% of the reads from HEK293 cells. Estimates of Hsp90 protein production as determined by Ribo-seq are reproducible but not robust, with inferred expression levels that can change 10-fold depending on how multimapping reads are processed. The differential expression of Hsp90 chaperones under nonstressed and heat shock conditions creates artificial peaks and valleys in their ribosome profiles that give a false impression of regulated translational pausing. Indeed, we find that multimapping can even create an appearance of reproducibility to the shape of the Hsp90 ribosome profiles from biological replicates. Adding further complexity, this artificial reproducibility is dependent on the computational method used to construct the ribosome profile. Given the ubiquity of multimapping reads in Ribo-seq experiments and the complexity of artifacts associated with multimapping, we developed a publicly available computational tool to identify transcripts most at risk for multimapping artifacts. In doing so, we identify biological pathways that are enriched in multimapping transcripts, meaning that particular biological pathways will be highly susceptible to multimapping artifacts.

RiboStreamR: a web application for quality control, analysis, and visualization of Ribo-seq data

BACKGROUND

Ribo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell's transcriptome. In practice, Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other.

RESULTS

We present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. Our platform is focused on providing a user-friendly experience, and includes various options for graphical customization, report generation, and anomaly detection within Ribo-seq datasets.

CONCLUSIONS

RiboStreamR takes advantage of the vast resources provided by the R and Bioconductor environments, and utilizes the Shiny R package to ensure a high level of usability. Our goal is to develop a tool which facilitates in-depth quality assessment of Ribo-seq data by providing reference datasets and automatically highlighting quality issues and anomalies within datasets.

Noncoding AUG circRNAs constitute an abundant and conserved subclass of circles

Circular RNAs (circRNAs) are a subset of noncoding RNAs previously considered as products of missplicing. Now, circRNAs are considered functional molecules, although to date, only few functions have been experimentally validated. Here, based on RNA sequencing from the ENCODE consortium, we identify and characterize a subset of circRNAs, coined AUG circRNAs, encompassing the annotated translational start codon from the protein-coding host genes. AUG circRNAs are more abundantly expressed and conserved than other groups of circRNAs, and they display flanking sequences that suggest an Alu-independent mechanism of biogenesis. The AUG circRNAs contain part of bona fide open reading frame, and in the recent years, several studies have reported cases of circRNA translation. However, using thorough cross-species analysis, extensive ribosome profiling, proteomics analyses, and experimental data on a selected panel of AUG circRNAs, we observe no indications of translation of AUG circRNAs or any other circRNAs. Our data provide a comprehensive classification of circRNAs and, collectively, the data suggest that the AUG circRNAs constitute an abundant subclass of circRNAs produced independently of primate-specific Alu elements.

Turnover of ribosome-associated transcripts from de novo ORFs produces gene-like characteristics available for de novo gene emergence in wild yeast populations

Little is known about the rate of emergence of de novo genes, what their initial properties are, and how they spread in populations. We examined wild yeast populations (Saccharomyces paradoxus) to characterize the diversity and turnover of intergenic ORFs over short evolutionary timescales. We find that hundreds of intergenic ORFs show translation signatures similar to canonical genes, and we experimentally confirmed the translation of many of these ORFs in laboratory conditions using a reporter assay. Compared with canonical genes, intergenic ORFs have lower translation efficiency, which could imply a lack of optimization for translation or a mechanism to reduce their production cost. Translated intergenic ORFs also tend to have sequence properties that are generally close to those of random intergenic sequences. However, some of the very recent translated intergenic ORFs, which appeared <110 kya, already show gene-like characteristics, suggesting that the raw material for functional innovations could appear over short evolutionary timescales.

Translation of upstream open reading frames in a model of neuronal differentiation

BACKGROUND

Upstream open reading frames (uORFs) initiate translation within mRNA 5' leaders, and have the potential to alter main coding sequence (CDS) translation on transcripts in which they reside. Ribosome profiling (RP) studies suggest that translating ribosomes are pervasive within 5' leaders across model systems. However, the significance of this observation remains unclear. To explore a role for uORF usage in a model of neuronal differentiation, we performed RP on undifferentiated and differentiated human neuroblastoma cells.

RESULTS

Using a spectral coherence algorithm (SPECtre), we identify 4954 consistently translated uORFs across 31% of all neuroblastoma transcripts. These uORFs predominantly utilize non-AUG initiation codons and exhibit translational efficiencies (TE) comparable to annotated coding regions. On a population basis, the global impact of both AUG and non-AUG initiated uORFs on basal CDS translation were small, even when analysis is limited to conserved and consistently translated uORFs. However, uORFs did alter the translation of a subset of genes, including the Diamond-Blackfan Anemia associated ribosomal gene RPS24. With retinoic acid induced differentiation, we observed an overall positive correlation in translational shifts between uORF/CDS pairs. However, CDSs downstream of uORFs show smaller shifts in TE with differentiation relative to CDSs without a predicted uORF, suggesting that uORF translation buffers cell state dependent fluctuations in CDS translation.

CONCLUSION

This work provides insights into the dynamic relationships and potential regulatory functions of uORF/CDS pairs in a model of neuronal differentiation.

Identifying A- and P-site locations on ribosome-protected mRNA fragments using Integer Programming

Identifying the A- and P-site locations on ribosome-protected mRNA fragments from Ribo-Seq experiments is a fundamental step in the quantitative analysis of transcriptome-wide translation properties at the codon level. Many analyses of Ribo-Seq data have utilized heuristic approaches applied to a narrow range of fragment sizes to identify the A-site. In this study, we use Integer Programming to identify the A-site by maximizing an objective function that reflects the fact that the ribosome's A-site on ribosome-protected fragments must reside between the second and stop codons of an mRNA. This identifies the A-site location as a function of the fragment's size and its 5' end reading frame in Ribo-Seq data generated from S. cerevisiae and mouse embryonic stem cells. The correctness of the identified A-site locations is demonstrated by showing that this method, as compared to others, yields the largest ribosome density at established stalling sites. By providing greater accuracy and utilization of a wider range of fragment sizes, our approach increases the signal-to-noise ratio of underlying biological signals associated with translation elongation at the codon length scale.

Mining for missed sORF-encoded peptides

INTRODUCTION

Small open reading frames (sORFs) with potential protein-coding capacity have been disclosed in various transcripts, including long noncoding RNAs (LncRNAs), mRNAs (5'-upstream, coding domain, and 3'-downstream), circular RNAs, pri-miRNAs, and ribosomal RNAs (rRNAs). Recent characterization of several sORF-encoded peptides (SEPs or micropeptides) revealed their important roles in many fundamental biological processes in a broad range of species from yeast to human. The success in the mining of micropeptides attributes to the advanced bioinformatics and high-throughput sequencing techniques. Areas covered: sORFs and SEPs were overlooked for their tiny size and the difficulty of identification by bioinformatics analyses. With more and more sORFs and SEPs have been identified, this field has attracted more attention. This review covers recent advances in the strategies for the detection and identification of sORFs and SEPs. Expert commentary: The advantages and drawbacks of the strategies for detection and identification of sORFs and SEPs are discussed, as well as the techniques that are used to decipher the roles of micropeptides in organisms are described.

Ribosomal Proteins Regulate MHC Class I Peptide Generation for Immunosurveillance

The MHC class I antigen presentation system enables T cell immunosurveillance of cancers and viruses. A substantial fraction of the immunopeptidome derives from rapidly degraded nascent polypeptides (DRiPs). By knocking down each of the 80 ribosomal proteins, we identified proteins that modulate peptide generation without altering source protein expression. We show that 60S ribosomal proteins L6 (RPL6) and RPL28, which are adjacent on the ribosome, play opposite roles in generating an influenza A virus-encoded peptide. Depleting RPL6 decreases ubiquitin-dependent peptide presentation, whereas depleting RPL28 increases ubiquitin-dependent and -independent peptide presentation. 40S ribosomal protein S28 (RPS28) knockdown increases total peptide supply in uninfected cells by increasing DRiP synthesis from non-canonical translation of "untranslated" regions and non-AUG start codons and sensitizes tumor cells for T cell targeting. Our findings raise the possibility of modulating immunosurveillance by pharmaceutical targeting ribosomes.

Production of Protein-Complex Components Is Stoichiometric and Lacks General Feedback Regulation in Eukaryotes

Constituents of multiprotein complexes are required at well-defined levels relative to each other. However, it remains unknown whether eukaryotic cells typically produce precise amounts of subunits, or instead rely on degradation to mitigate imprecise production. Here, we quantified the production rates of multiprotein complexes in unicellular and multicellular eukaryotes using ribosome profiling. By resolving read-mapping ambiguities, which occur for a large fraction of ribosome footprints and distort quantitation accuracy in eukaryotes, we found that obligate components of multiprotein complexes are produced in proportion to their stoichiometry, indicating that their abundances are already precisely tuned at the synthesis level. By systematically interrogating the impact of gene dosage variations in budding yeast, we found a general lack of negative feedback regulation protecting the normally precise rates of subunit synthesis. These results reveal a core principle of proteome homeostasis and highlight the evolution toward quantitative control at every step in the central dogma.

RiboProP: a probabilistic ribosome positioning algorithm for ribosome profiling

Motivation

Ribosome profiling has been widely used to study translation in a genome-wide fashion. It requires deep sequencing of ribosome protected mRNA fragments followed by mapping of fragments to the reference genome. For applications such as identification of ribosome pausing sites, it is not enough to map a fragment to a given gene, but the exact position of the ribosome represented by the fragment must be identified for each mRNA fragment. The assignment of the correct ribosome position is complicated by the broad length distribution of the ribosome protected fragments caused by the known sequence bias of micrococcal nuclease (MNase), the most widely used nuclease for digesting mRNAs in bacteria. Available mapping algorithms suffer from either MNase bias or low accuracy in characterizing the ribosome pausing kinetics.

Results

In this paper, we introduce a new computational method for mapping the ribosome protected fragments to ribosome locations. We first develop a mathematical model of the interplay between MNase digestion and ribosome protection of the mRNAs. We then use the model to reconstruct the ribosome occupancy profile on a per gene level. We demonstrate that our method has the capability of mitigating the sequence bias introduced by MNase and accurately locating ribosome pausing sites at codon resolution. We believe that our method can be broadly applied to ribosome profiling studies on bacteria where codon resolution is necessary.

Availability and implementation

Source code implementing our approach can be downloaded under GPL3 license at http://bioserv.mps.ohio-state.edu/RiboProP.

Supplementary information

Supplementary data are available at Bioinformatics online.

PausePred and Rfeet: webtools for inferring ribosome pauses and visualizing footprint density from ribosome profiling data

The process of translation is characterized by irregularities in the local decoding rates of specific mRNA codons. This includes the occurrences of long pauses that can take place when ribosomes decode certain peptide sequences, encounter strong RNA secondary structures, or decode "hungry" codons. Examples are known where such pausing or stalling is used for regulating protein synthesis. This can be achieved at the level of translation via direct alteration of ribosome progression through mRNA or by altering mRNA stability via NoGo decay. Ribosome pausing has also been implicated in the cotranslational folding of proteins. Ribosome profiling data often are used for inferring the locations of ribosome pauses. However, no dedicated online software is available for this purpose. Here we present PausePred (https://pausepred.ucc.ie/), which can be used to infer ribosome pauses from ribosome profiling (Ribo-seq) data. Peaks of ribosome footprint density are scored based on their magnitude relative to the background density within the surrounding area. The scoring allows the comparison of peaks across the transcriptome or genome. In addition to the score, PausePred reports the coordinates of the pause, the footprint density at the pause site, and the surrounding nucleotide sequence. The pauses can be visualized in the context of Ribo-seq and RNA-seq density plots generated for specific transcripts or genomic regions with the Rfeet tool. PausePred does not require input on the location of protein coding ORFs (although gene annotations can be optionally supplied). As a result, it can be used universally and its output does not depend on ever evolving annotations.

Fragile X mental retardation 1 gene enhances the translation of large autism-related proteins

Mutations in the fragile X mental retardation 1 gene (FMR1) cause the most common inherited human autism spectrum disorder. FMR1 influences messenger RNA (mRNA) translation, but identifying functional targets has been difficult. We analyzed quiescent Drosophila oocytes, which, like neural synapses, depend heavily on translating stored mRNA. Ribosome profiling revealed that FMR1 enhances rather than represses the translation of mRNAs that overlap previously identified FMR1 targets, and acts preferentially on large proteins. Human homologs of at least 20 targets are associated with dominant intellectual disability, and 30 others with recessive neurodevelopmental dysfunction. Stored oocytes lacking FMR1 usually generate embryos with severe neural defects, unlike stored wild-type oocytes, which suggests that translation of multiple large proteins by stored mRNAs is defective in fragile X syndrome and possibly other autism spectrum disorders.

riboWaltz: Optimization of ribosome P-site positioning in ribosome profiling data

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.

Translation Elongation Factor 4 (LepA) Contributes to Tetracycline Susceptibility by Stalling Elongating Ribosomes

Even though elongation factor 4 (EF4) is the third most conserved protein in bacteria, its physiological functions remain largely unknown and its proposed molecular mechanisms are conflicting among previous studies. In the present study, we show that the growth of an Escherichia coli strain is more susceptible to tetracycline than its EF4 knockout strain. Consistent with previous studies, our results suggested that EF4 affects ribosome biogenesis when tetracycline is present. Through ribosome profiling analysis, we discovered that EF4 causes 1-nucleotide shifting of ribosomal footprints on mRNA when cells have been exposed to tetracycline. In addition, when tetracycline is present, EF4 inhibits the elongation of protein synthesis, which leads to the accumulation of ribosomes in the early segment of mRNA. Altogether, when cells are exposed to tetracycline, EF4 alters both ribosome biogenesis and the elongation phase of protein synthesis.

Escherichia coli translation strategies differ across carbon, nitrogen and phosphorus limitation conditions

For cells to grow faster they must increase their protein production rate. Microorganisms have traditionally been thought to accomplish this increase by producing more ribosomes to enhance protein synthesis capacity, leading to the linear relationship between ribosome level and growth rate observed under most growth conditions previously examined. Past studies have suggested that this linear relationship represents an optimal resource allocation strategy for each growth rate, independent of any specific nutrient state. Here we investigate protein production strategies in continuous cultures limited for carbon, nitrogen and phosphorus, which differentially impact substrate supply for protein versus nucleic acid metabolism. Unexpectedly, we find that at slow growth rates, Escherichia coli achieves the same protein production rate using three different strategies under the three different nutrient limitations. Under phosphorus (P) limitation, translation is slow due to a particularly low abundance of ribosomes, which are RNA-rich and thus particularly costly for phosphorous-limited cells. Under nitrogen (N) limitation, translation elongation is slowed by processes including ribosome stalling at glutamine codons. Under carbon (C) limitation, translation is slowed by accumulation of inactive ribosomes not bound to messenger RNA. These extra ribosomes enable rapid growth acceleration during nutrient upshift. Thus, bacteria tune ribosome usage across different limiting nutrients to enable balanced nutrient-limited growth while also preparing for future nutrient upshifts.

Shoelaces: an interactive tool for ribosome profiling processing and visualization

Background

The emergence of ribosome profiling to map actively translating ribosomes has laid the foundation for a diverse range of studies on translational regulation. The data obtained with different variations of this assay is typically manually processed, which has created a need for tools that would streamline and standardize processing steps.

Results

We present Shoelaces, a toolkit for ribosome profiling experiments automating read selection and filtering to obtain genuine translating footprints. Based on periodicity, favoring enrichment over the coding regions, it determines the read lengths corresponding to bona fide ribosome protected fragments. The specific codon under translation (P-site) is determined by automatic offset calculations resulting in sub-codon resolution. Shoelaces provides both a user-friendly graphical interface for interactive visualisation in a genome browser-like fashion and a command line interface for integration into automated pipelines. We process 79 libraries and show that studies typically discard excessive amounts of quality data in their manual analysis pipelines.

Conclusions

Shoelaces streamlines ribosome profiling analysis offering automation of the processing, a range of interactive visualization features and export of the data into standard formats. Shoelaces stores all processing steps performed in an XML file that can be used by other groups to exactly reproduce the processing of a given study. We therefore anticipate that Shoelaces can aid researchers by automating what is typically performed manually and contribute to the overall reproducibility of studies. The tool is freely distributed as a Python package, with additional instructions, tutorial and demo datasets available at https://bitbucket.org/valenlab/shoelaces.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4912-6) contains supplementary material, which is available to authorized users.

miCLIP-MaPseq, a Substrate Identification Approach for Radical SAM RNA Methylating Enzymes

Although present across bacteria, the large family of radical SAM RNA methylating enzymes is largely uncharacterized. Escherichia coli RlmN, the founding member of the family, methylates an adenosine in 23S rRNA and several tRNAs to yield 2-methyladenosine (m²A). However, varied RNA substrate specificity among RlmN enzymes, combined with the ability of certain family members to generate 8-methyladenosine (m⁸A), makes functional predictions across this family challenging. Here, we present a method for unbiased substrate identification that exploits highly efficient, mechanism-based cross-linking between the enzyme and its RNA substrates. Additionally, by determining that the thermostable group II intron reverse transcriptase introduces mismatches at the site of the cross-link, we have identified the precise positions of RNA modification using mismatch profiling. These results illustrate the capability of our method to define enzyme-substrate pairs and determine modification sites of the largely uncharacterized radical SAM RNA methylating enzyme family.

Following Ribosome Footprints to Understand Translation at a Genome Wide Level

Protein translation is a key step in gene expression. The development of Ribosome Profiling has allowed the global analysis of this process at sub-codon resolution. In the last years the method has been applied to several models ranging from bacteria to mammalian cells yielding a surprising amount of insight on the mechanism and the regulation of translation. In this review we describe the key aspects of the experimental protocol and comment on the main conclusions raised in different models.

Palladin Is a Neuron-Specific Translational Target of mTOR Signaling That Regulates Axon Morphogenesis

The mTOR signaling pathway regulates protein synthesis and diverse aspects of neuronal morphology that are important for brain development and function. To identify proteins controlled translationally by mTOR signaling, we performed ribosome profiling analyses in mouse cortical neurons and embryonic stem cells upon acute mTOR inhibition. Among proteins whose translation was significantly affected by mTOR inhibition selectively in neurons, we identified the cytoskeletal regulator protein palladin, which is localized within the cell body and axons in hippocampal neurons. Knockdown of palladin eliminated supernumerary axons induced by suppression of the tuberous sclerosis complex protein TSC1 in neurons, demonstrating that palladin regulates neuronal morphogenesis downstream of mTOR signaling. Our findings provide novel insights into an mTOR-dependent mechanism that controls neuronal morphogenesis through translational regulation.SIGNIFICANCE STATEMENT This study reports the discovery of neuron-specific protein translational responses to alterations of mTOR activity. By using ribosome profiling analysis, which can reveal the location and quantity of translating ribosomes on mRNAs, multiple aspects of protein translation were quantitatively analyzed in mouse embryonic stem cells and cortical neurons upon acute mTOR inhibition. Neurons displayed distinct patterns of ribosome occupancy for each codon and ribosome stalling during translation at specific positions of mRNAs. Importantly, the cytoskeletal regulator palladin was identified as a translational target protein of mTOR signaling in neurons. Palladin operates downstream of mTOR to modulate axon morphogenesis. This study identifies a novel mechanism of neuronal morphogenesis regulated by mTOR signaling through control of translation of the key protein palladin.

Defining the physiological role of SRP in protein-targeting efficiency and specificity

The signal recognition particle (SRP) enables cotranslational delivery of proteins for translocation into the endoplasmic reticulum (ER), but its full in vivo role remains incompletely explored. We combined rapid auxin-induced SRP degradation with proximity-specific ribosome profiling to define SRP's in vivo function in yeast. Despite the classic view that SRP recognizes amino-terminal signal sequences, we show that SRP was generally essential for targeting transmembrane domains regardless of their position relative to the amino terminus. By contrast, many proteins containing cleavable amino-terminal signal peptides were efficiently cotranslationally targeted in SRP's absence. We also reveal an unanticipated consequence of SRP loss: Transcripts normally targeted to the ER were mistargeted to mitochondria, leading to mitochondrial defects. These results elucidate SRP's essential roles in maintaining the efficiency and specificity of protein targeting.

Ribosome Profiling in Maize

Ribosome profiling (also known as Ribo-seq) provides a genome-wide, high-resolution, and quantitative accounting of mRNA segments that are occupied by ribosomes in vivo. The method has been used to address numerous questions in bacteria, yeast, and metazoa, but its application to questions in plant biology is just beginning. This chapter provides a detailed protocol for profiling ribosomes in plant leaf tissue. The method was developed and optimized with maize, but it has been used successfully with Arabidopsis and tobacco as well. The method captures ribosome footprints from the chloroplast and cytosol in the same preparation, but it is not optimal for detecting the footprints of mitochondrial ribosomes. The protocol is robust and simpler than many of the methods reported previously for ribosome profiling in plants.

A Plant Biologist's Toolbox to Study Translation

Across a broad range of species and biological questions, more and more studies are incorporating translation data to better assess how gene regulation occurs at the level of protein synthesis. The inclusion of translation data improves upon, and has been shown to be more accurate than, transcriptional studies alone. However, there are many different techniques available to measure translation and it can be difficult, especially for young or aspiring scientists, to determine which methods are best applied in specific situations. We have assembled this review in order to enhance the understanding and promote the utilization of translational methods in plant biology. We cover a broad range of methods to measure changes in global translation (e.g., radiolabeling, polysome profiling, or puromycylation), translation of single genes (e.g., fluorescent reporter constructs, toeprinting, or ribosome density mapping), sequencing-based methods to uncover the entire translatome (e.g., Ribo-seq or translating ribosome affinity purification), and mass spectrometry-based methods to identify changes in the proteome (e.g., stable isotope labeling by amino acids in cell culture or bioorthogonal noncanonical amino acid tagging). The benefits and limitations of each method are discussed with a particular note of how applications from other model systems might be extended for use in plants. In order to make this burgeoning field more accessible to students and newer scientists, our review includes an extensive glossary to define key terms.

Genome-wide Quantification of Translation in Budding Yeast by Ribosome Profiling

Translation of mRNA into proteins is a complex process involving several layers of regulation. It is often assumed that changes in mRNA transcription reflect changes in protein synthesis, but many exceptions have been observed. Recently, a technique called ribosome profiling (or Ribo-Seq) has emerged as a powerful method that allows identification, with high accuracy, which regions of mRNA are translated into proteins and quantification of translation at the genome-wide level. Here, we present a generalized protocol for genome-wide quantification of translation using Ribo-Seq in budding yeast. In addition, combining Ribo-Seq data with mRNA abundance measurements allows us to simultaneously quantify translation efficiency of thousands of mRNA transcripts in the same sample and compare changes in these parameters in response to experimental manipulations or in different physiological states. We describe a detailed protocol for generation of ribosome footprints using nuclease digestion, isolation of intact ribosome-footprint complexes via sucrose gradient fractionation, and preparation of DNA libraries for deep sequencing along with appropriate quality controls necessary to ensure accurate analysis of in vivo translation.

Mining for Small Translated ORFs

Peptides encoded by short open reading frames (sORFs) are usually defined as peptides ≤100 aa long. Usually sORFs were ignored by automatic genome annotation programs due to the high probability of false discovery. However, improved computational tools along with a high-throughput RIBO-seq approach identified a myriad of translated sORFs. Their importance becomes evident as we are gaining experimental validation of their diverse cellular functions. This Review examines various computational and experimental approaches of sORFs identification as well as provides the summary of our current knowledge of their functional roles in cells.

Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control

N6-methyladenosine (m6A) is an abundant internal RNA modification in both coding and non-coding RNAs that is catalysed by the METTL3-METTL14 methyltransferase complex. However, the specific role of these enzymes in cancer is still largely unknown. Here we define a pathway that is specific for METTL3 and is implicated in the maintenance of a leukaemic state. We identify METTL3 as an essential gene for growth of acute myeloid leukaemia cells in two distinct genetic screens. Downregulation of METTL3 results in cell cycle arrest, differentiation of leukaemic cells and failure to establish leukaemia in immunodeficient mice. We show that METTL3, independently of METTL14, associates with chromatin and localizes to the transcriptional start sites of active genes. The vast majority of these genes have the CAATT-box binding protein CEBPZ present at the transcriptional start site, and this is required for recruitment of METTL3 to chromatin. Promoter-bound METTL3 induces m6A modification within the coding region of the associated mRNA transcript, and enhances its translation by relieving ribosome stalling. We show that genes regulated by METTL3 in this way are necessary for acute myeloid leukaemia. Together, these data define METTL3 as a regulator of a chromatin-based pathway that is necessary for maintenance of the leukaemic state and identify this enzyme as a potential therapeutic target for acute myeloid leukaemia.

Development of a tissue-specific ribosome profiling approach in Drosophila enables genome-wide evaluation of translational adaptations

Recent advances in next-generation sequencing approaches have revolutionized our understanding of transcriptional expression in diverse systems. However, measurements of transcription do not necessarily reflect gene translation, the process of ultimate importance in understanding cellular function. To circumvent this limitation, biochemical tagging of ribosome subunits to isolate ribosome-associated mRNA has been developed. However, this approach, called TRAP, lacks quantitative resolution compared to a superior technology, ribosome profiling. Here, we report the development of an optimized ribosome profiling approach in Drosophila. We first demonstrate successful ribosome profiling from a specific tissue, larval muscle, with enhanced resolution compared to conventional TRAP approaches. We next validate the ability of this technology to define genome-wide translational regulation. This technology is leveraged to test the relative contributions of transcriptional and translational mechanisms in the postsynaptic muscle that orchestrate the retrograde control of presynaptic function at the neuromuscular junction. Surprisingly, we find no evidence that significant changes in the transcription or translation of specific genes are necessary to enable retrograde homeostatic signaling, implying that post-translational mechanisms ultimately gate instructive retrograde communication. Finally, we show that a global increase in translation induces adaptive responses in both transcription and translation of protein chaperones and degradation factors to promote cellular proteostasis. Together, this development and validation of tissue-specific ribosome profiling enables sensitive and specific analysis of translation in Drosophila.

Recent advances in next-generation sequencing approaches have revolutionized our understanding of transcriptional expression in diverse systems. However, transcriptional expression alone does not necessarily report gene translation, the process of ultimate importance in understanding cellular function. Ribosome profiling is a powerful approach to quantify the number of ribosomes associated with each mRNA to determine rates of gene translation. However, ribosome profiling requires large quantities of starting material, limiting progress in developing tissue-specific approaches. Here, we have developed the first tissue-specific ribosome profiling system in Drosophila to reveal genome-wide changes in translation. We first demonstrate successful ribosome profiling from muscle cells that exhibit superior resolution compared to other translational profiling methods. We then use transcriptional and ribosome profiling to define whether transcriptional or translational mechanisms are necessary for synaptic signaling at the neuromuscular junction. Finally, we utilize ribosome profiling to reveal adaptive changes in cellular translation following cellular stress to muscle tissue. Together, this now enables the power of Drosophila genetics to be leveraged with ribosome profiling in specific tissues.

Transcriptome-wide Analysis of Roles for tRNA Modifications in Translational Regulation

Covalent nucleotide modifications in noncoding RNAs affect a plethora of biological processes, and new functions continue to be discovered even for well-known modifying enzymes. To systematically compare the functions of a large set of noncoding RNA modifications in gene regulation, we carried out ribosome profiling in budding yeast to characterize 57 nonessential genes involved in tRNA modification. Deletion mutants exhibited a range of translational phenotypes, with enzymes known to modify anticodons, or non-tRNA substrates such as rRNA, exhibiting the most dramatic translational perturbations. Our data build on prior reports documenting translational upregulation of the nutrient-responsive transcription factor Gcn4 in response to numerous tRNA perturbations, and identify many additional translationally regulated mRNAs throughout the yeast genome. Our data also uncover unexpected roles for tRNA-modifying enzymes in regulation of TY retroelements, and in rRNA 2'-O-methylation. This dataset should provide a rich resource for discovery of additional links between tRNA modifications and gene regulation.

Discovery of noncanonical translation initiation sites through mass spectrometric analysis of protein N termini

Translation initiation generally occurs at AUG codons in eukaryotes, although it has been shown that non-AUG or noncanonical translation initiation can also occur. However, the evidence for noncanonical translation initiation sites (TISs) is largely indirect and based on ribosome profiling (Ribo-seq) studies. Here, using a strategy specifically designed to enrich N termini of proteins, we demonstrate that many human proteins are translated at noncanonical TISs. The large majority of TISs that mapped to 5′ untranslated regions were noncanonical and led to N-terminal extension of annotated proteins or translation of upstream small open reading frames (uORF). It has been controversial whether the amino acid corresponding to the start codon is incorporated at the TIS or methionine is still incorporated. We found that methionine was incorporated at almost all noncanonical TISs identified in this study. Comparison of the TISs determined through mass spectrometry with ribosome profiling data revealed that about two-thirds of the novel annotations were indeed supported by the available ribosome profiling data. Sequence conservation across species and a higher abundance of noncanonical TISs than canonical ones in some cases suggests that the noncanonical TISs can have biological functions. Overall, this study provides evidence of protein translation initiation at noncanonical TISs and argues that further studies are required for elucidation of functional implications of such noncanonical translation initiation.

Human SHMT inhibitors reveal defective glycine import as a targetable metabolic vulnerability of diffuse large B-cell lymphoma

The enzyme serine hydroxymethyltransferse (SHMT) converts serine into glycine and a tetrahydrofolate-bound one-carbon unit. Folate one-carbon units support purine and thymidine synthesis, and thus cell growth. Mammals have both cytosolic SHMT1 and mitochondrial SHMT2, with the mitochondrial isozyme strongly up-regulated in cancer. Here we show genetically that dual SHMT1/2 knockout blocks HCT-116 colon cancer tumor xenograft formation. Building from a pyrazolopyran scaffold that inhibits plant SHMT, we identify small-molecule dual inhibitors of human SHMT1/2 (biochemical IC₅₀ ∼ 10 nM). Metabolomics and isotope tracer studies demonstrate effective cellular target engagement. A cancer cell-line screen revealed that B-cell lines are particularly sensitive to SHMT inhibition. The one-carbon donor formate generally rescues cells from SHMT inhibition, but paradoxically increases the inhibitor's cytotoxicity in diffuse large B-cell lymphoma (DLBCL). We show that this effect is rooted in defective glycine uptake in DLBCL cell lines, rendering them uniquely dependent upon SHMT enzymatic activity to meet glycine demand. Thus, defective glycine import is a targetable metabolic deficiency of DLBCL.

Beyond Read-Counts: Ribo-seq Data Analysis to Understand the Functions of the Transcriptome

By mapping the positions of millions of translating ribosomes in the cell, ribosome profiling (Ribo-seq) has established its role as a powerful tool to study gene expression. Several laboratories have introduced modifications to the experimental protocol and expanded the repertoire of biochemical methods to study translation transcriptome-wide. However, the diversity of protocols highlights a need for standardization. At the same time, different computational analysis strategies have used Ribo-seq data to identify the set of translated sequences with high confidence. In this review we present an overview of such methodologies, outlining their assumptions, data requirements, and availability. At the interface between RNA and proteins, Ribo-seq can complement data from multiple omics approaches, zooming in on the central role of translation in the molecular cell.

Transcriptome-wide measurement of translation by ribosome profiling

Translation is one of the fundamental processes of life. It comprises the assembly of polypeptides whose amino acid sequence corresponds to the codon sequence of an mRNA's ORF. Translation is performed by the ribosome; therefore, in order to understand translation and its regulation we must be able to determine the numbers and locations of ribosomes on mRNAs in vivo. Furthermore, we must be able to examine their redistribution in different physiological contexts and in response to experimental manipulations. The ribosome profiling method provides us with an opportunity to learn these locations, by sequencing a cDNA library derived from the short fragments of mRNA covered by the ribosome. Since its original description, the ribosome profiling method has undergone continuing development; in this article we describe the method's current state. Important improvements include: the incorporation of sample barcodes to enable library multiplexing, the incorporation of unique molecular identifiers to enable to removal of duplicated sequences, and the replacement of a gel-purification step with the enzymatic degradation of unligated linker.