Ribosome Footprint Profiling of Translation throughout the Genome

Ribo-DT: An automated pipeline for inferring codon dwell times from ribosome profiling data

Protein synthesis is an energy consuming process characterised as a pivotal and highly regulated step in gene expression. The net protein output is dictated by a combination of translation initiation, elongation and termination rates that have remained difficult to measure. Recently, the development of ribosome profiling has enabled the inference of translation parameters through modelling, as this method informs on the ribosome position along the mRNA. Here, we present an automated, reproducible and portable computational pipeline to infer relative single-codon and codon-pair dwell times as well as gene flux from raw ribosome profiling sequencing data. As a case study, we applied our workflow to a publicly available yeast ribosome profiling dataset consisting of 57 independent gene knockouts related to RNA and tRNA modifications. We uncovered the effects of those modifications on translation elongation and codon selection during decoding. In particular, knocking out mod5 and trm7 increases codon-specific dwell times which indicates their potential tRNA targets, and highlights effects of nucleotide modifications on ribosome decoding rate.

Coupled protein synthesis and ribosome-guided piRNA processing on mRNAs

PIWI-interacting small RNAs (piRNAs) protect the germline genome and are essential for fertility. piRNAs originate from transposable element (TE) RNAs, long non-coding RNAs, or 3´ untranslated regions (3´UTRs) of protein-coding messenger genes, with the last being the least characterized of the three piRNA classes. Here, we demonstrate that the precursors of 3´UTR piRNAs are full-length mRNAs and that post-termination 80S ribosomes guide piRNA production on 3´UTRs in mice and chickens. At the pachytene stage, when other co-translational RNA surveillance pathways are sequestered, piRNA biogenesis degrades mRNAs right after pioneer rounds of translation and fine-tunes protein production from mRNAs. Although 3´UTR piRNA precursor mRNAs code for distinct proteins in mice and chickens, they all harbor embedded TEs and produce piRNAs that cleave TEs. Altogether, we discover a function of the piRNA pathway in fine-tuning protein production and reveal a conserved piRNA biogenesis mechanism that recognizes translating RNAs in amniotes.

How to Illuminate the Dark Proteome Using the Multi-omic OpenProt Resource

Ten of thousands of open reading frames (ORFs) are hidden within genomes. These alternative ORFs, or small ORFs, have eluded annotations because they are either small or within unsuspected locations. They are found in untranslated regions or overlap a known coding sequence in messenger RNA and anywhere in a "non-coding" RNA. Serendipitous discoveries have highlighted these ORFs' importance in biological functions and pathways. With their discovery came the need for deeper ORF annotation and large-scale mining of public repositories to gather supporting experimental evidence. OpenProt, accessible at https://openprot.org/, is the first proteogenomic resource enforcing a polycistronic model of annotation across an exhaustive transcriptome for 10 species. Moreover, OpenProt reports experimental evidence cumulated across a re-analysis of 114 mass spectrometry and 87 ribosome profiling datasets. The multi-omics OpenProt resource also includes the identification of predicted functional domains and evaluation of conservation for all predicted ORFs. The OpenProt web server provides two query interfaces and one genome browser. The query interfaces allow for exploration of the coding potential of genes or transcripts of interest as well as custom downloads of all information contained in OpenProt. © 2020 The Authors. Basic Protocol 1: Using the Search interface Basic Protocol 2: Using the Downloads interface.

Not4 and Not5 modulate translation elongation by Rps7A ubiquitination, Rli1 moonlighting, and condensates that exclude eIF5A

In this work, we show that Not4 and Not5 from the Ccr4-Not complex modulate translation elongation dynamics and change ribosome A-site dwelling occupancy in a codon-dependent fashion. These codon-specific changes in not5Δ cells are very robust and independent of codon position within the mRNA, the overall mRNA codon composition, or changes of mRNA expression levels. They inversely correlate with codon-specific changes in cells depleted for eIF5A and positively correlate with those in cells depleted for ribosome-recycling factor Rli1. Not5 resides in punctate loci, co-purifies with ribosomes and Rli1, but not with eIF5A, and limits mRNA solubility. Overexpression of wild-type or non-complementing Rli1 and loss of Rps7A ubiquitination enable Not4 E3 ligase-dependent translation of polyarginine stretches. We propose that Not4 and Not5 modulate translation elongation dynamics to produce a soluble proteome by Rps7A ubiquitination, dynamic condensates that limit mRNA solubility and exclude eIF5A, and a moonlighting function of Rli1.

Humans and other commonly used model organisms are resistant to cycloheximide-mediated biases in ribosome profiling experiments

Ribosome profiling measures genome-wide translation dynamics at sub-codon resolution. Cycloheximide (CHX), a widely used translation inhibitor to arrest ribosomes in these experiments, has been shown to induce biases in yeast, questioning its use. However, whether such biases are present in datasets of other organisms including humans is unknown. Here we compare different CHX-treatment conditions in human cells and yeast in parallel experiments using an optimized protocol. We find that human ribosomes are not susceptible to conformational restrictions by CHX, nor does it distort gene-level measurements of ribosome occupancy, measured decoding speed or the translational ramp. Furthermore, CHX-induced codon-specific biases on ribosome occupancy are not detectable in human cells or other model organisms. This shows that reported biases of CHX are species-specific and that CHX does not affect the outcome of ribosome profiling experiments in most settings. Our findings provide a solid framework to conduct and analyze ribosome profiling experiments.

Ribosome profiling has become the gold standard to analyze mRNA translation dynamics, and the translation inhibitor cycloheximide (CHX) is often used in its application. Here the authors systematically demonstrate that CHX does not bias the outcome of ribosome profiling experiments in most organisms.

Comparative ribosome profiling reveals distinct translational landscapes of salt-sensitive and -tolerant rice

BACKGROUND

Soil salinization represents a serious threat to global rice production. Although significant research has been conducted to understand salt stress at the genomic, transcriptomic and proteomic levels, few studies have focused on the translatomic responses to this stress. Recent studies have suggested that transcriptional and translational responses to salt stress can often operate independently.

RESULTS

We sequenced RNA and ribosome-protected fragments (RPFs) from the salt-sensitive rice (O. sativa L.) cultivar 'Nipponbare' (NB) and the salt-tolerant cultivar 'Sea Rice 86' (SR86) under normal and salt stress conditions. A large discordance between salt-induced transcriptomic and translatomic alterations was found in both cultivars, with more translationally regulated genes being observed in SR86 in comparison to NB. A biased ribosome occupancy, wherein RPF depth gradually increased from the 5' ends to the 3' ends of coding regions, was revealed in NB and SR86. This pattern was strengthened by salt stress, particularly in SR86. On the contrary, the strength of ribosome stalling was accelerated in salt-stressed NB but decreased in SR86.

CONCLUSIONS

This study revealed that translational reprogramming represents an important layer of salt stress responses in rice, and the salt-tolerant cultivar SR86 adopts a more flexible translationally adaptive strategy to cope with salt stress compared to the salt susceptible cultivar NB. The differences in translational dynamics between NB and SR86 may derive from their differing levels of ribosome stalling under salt stress.

Malaria parasites both repress host CXCL10 and use it as a cue for growth acceleration

Pathogens are thought to use host molecular cues to control when to initiate life-cycle transitions, but these signals are mostly unknown, particularly for the parasitic disease malaria caused by Plasmodium falciparum. The chemokine CXCL10 is present at high levels in fatal cases of cerebral malaria patients, but is reduced in patients who survive and do not have complications. Here we show a Pf 'decision-sensing-system' controlled by CXCL10 concentration. High CXCL10 expression prompts P. falciparum to initiate a survival strategy via growth acceleration. Remarkably, P. falciparum inhibits CXCL10 synthesis in monocytes by disrupting the association of host ribosomes with CXCL10 transcripts. The underlying inhibition cascade involves RNA cargo delivery into monocytes that triggers RIG-I, which leads to HUR1 binding to an AU-rich domain of the CXCL10 3'UTR. These data indicate that when the parasite can no longer keep CXCL10 at low levels, it can exploit the chemokine as a cue to shift tactics and escape.

A systematic survey of PRMT interactomes reveals the key roles of arginine methylation in the global control of RNA splicing and translation

Thousands of proteins undergo arginine methylation, a widespread post-translational modification catalyzed by several protein arginine methyltransferases (PRMTs). However, global understanding of their biological functions is limited due to the lack of a complete picture of the catalytic network for each PRMT. Here, we systematically identified interacting proteins for all human PRMTs and demonstrated their functional importance in mRNA splicing and translation. We demonstrated significant overlapping of interactomes of human PRMTs with the known methylarginine-containing proteins. Different PRMTs are functionally redundant with a high degree of overlap in their substrates and high similarities between their putative methylation motifs. Importantly, RNA-binding proteins involved in regulating RNA splicing and translation contain highly enriched arginine methylation regions. Moreover, inhibition of PRMTs globally alternates alternative splicing (AS) and suppresses translation. In particular, ribosomal proteins are extensively modified with methylarginine, and mutations in their methylation sites suppress ribosome assembly, translation, and eventually cell growth. Collectively, our study provides a global view of different PRMT networks and uncovers critical functions of arginine methylation in regulating mRNA splicing and translation.

Global translational landscape of the Candida albicans morphological transition

Candida albicans, a major human fungal pathogen associated with high mortality and/or morbidity rates in a wide variety of immunocompromised individuals, undergoes a reversible morphological transition from yeast to filamentous cells that is required for virulence. While previous studies have identified and characterized global transcriptional mechanisms important for driving this transition, as well as other virulence properties, in C. albicans and other pathogens, considerably little is known about the role of genome-wide translational mechanisms. Using ribosome profiling, we report the first global translational profile associated with C. albicans morphogenesis. Strikingly, many genes involved in pathogenesis, filamentation, and the response to stress show reduced translational efficiency (TE). Several of these genes are known to be strongly induced at the transcriptional level, suggesting that a translational fine-tuning mechanism is in place. We also identify potential upstream open reading frames (uORFs), associated with genes involved in pathogenesis, and novel ORFs, several of which show altered TE during filamentation. Using a novel bioinformatics method for global analysis of ribosome pausing that will be applicable to a wide variety of genetic systems, we demonstrate an enrichment of ribosome pausing sites in C. albicans genes associated with protein synthesis and cell wall functions. Altogether, our results suggest that the C. albicans morphological transition, and most likely additional virulence processes in fungal pathogens, is associated with widespread global alterations in TE that do not simply reflect changes in transcript levels. These alterations affect the expression of many genes associated with processes essential for virulence and pathogenesis.

Estimation of peptide elongation times from ribosome profiling spectra

Ribosome profiling spectra bear rich information on translation control and dynamics. Yet, due to technical biases in library generation, extracting quantitative measures of discrete translation events has remained elusive. Using maximum likelihood statistics and data set from Escherichia coli we develop a robust method for neutralizing technical biases (e.g. base specific RNase preferences in ribosome-protected mRNA fragments (RPF) generation), which allows for correct estimation of translation times at single codon resolution. Furthermore, we validated the method with available datasets from E. coli treated with antibiotic to inhibit isoleucyl-tRNA synthetase, and two datasets from Saccharomyces cerevisiae treated with two RNases with distinct cleavage signatures. We demonstrate that our approach accounts for RNase cleavage preferences and provides bias-corrected translation times estimates. Our approach provides a solution to the long-standing problem of extracting reliable information about peptide elongation times from highly noisy and technically biased ribosome profiling spectra.

Transcriptome and translatome changes in germinated pollen under heat stress uncover roles of transporter genes involved in pollen tube growth

Plant reproduction is one key biological process that is very sensitive to heat stress and, as a result, enhanced global warming becomes a serious threat to agriculture. In this work, we have studied the effects of heat on germinated pollen of Arabidopsis thaliana both at the transcriptional and translational level. We have used a high-resolution ribosome profiling technology to provide a comprehensive study of the transcriptome and the translatome of germinated pollen at permissive and restrictive temperatures. We have found significant down-regulation of key membrane transporters required for pollen tube growth by heat, thus uncovering heat-sensitive targets. A subset of the heat-repressed transporters showed coordinated up-regulation with canonical heat-shock genes at permissive conditions. We also found specific regulations at the translational level and we have uncovered the presence of ribosomes on sequences annotated as non-coding. Our results demonstrate that heat impacts mostly on membrane transporters thus explaining the deleterious effects of heat stress on pollen growth. The specific regulations at the translational level and the presence of ribosomes on non-coding RNAs highlights novel regulatory aspects on plant fertilization.

Transcriptome and translatome changes in germinated pollen under heat stress uncover roles of transporter genes involved in pollen tube growth

Plant reproduction is one key biological process that is very sensitive to heat stress and, as a result, enhanced global warming becomes a serious threat to agriculture. In this work, we have studied the effects of heat on germinated pollen of Arabidopsis thaliana both at the transcriptional and translational level. We have used a high-resolution ribosome profiling technology to provide a comprehensive study of the transcriptome and the translatome of germinated pollen at permissive and restrictive temperatures. We have found significant down-regulation of key membrane transporters required for pollen tube growth by heat, thus uncovering heat-sensitive targets. A subset of the heat-repressed transporters showed coordinated up-regulation with canonical heat-shock genes at permissive conditions. We also found specific regulations at the translational level and we have uncovered the presence of ribosomes on sequences annotated as non-coding. Our results demonstrate that heat impacts mostly on membrane transporters thus explaining the deleterious effects of heat stress on pollen growth. The specific regulations at the translational level and the presence of ribosomes on non-coding RNAs highlights novel regulatory aspects on plant fertilization.

Polysomally protected viruses

It is conceivable that an RNA virus could use a polysome, that is, a string of ribosomes covering the RNA strand, to protect the genetic material from degradation inside a host cell. This paper discusses how such a virus might operate, and how its presence might be detected by ribosome profiling. There are two possible forms for such apolysomally protected virus, depending upon whether just the forward strand or both the forward and complementary strands can be encased by ribosomes (these will be termed type 1 and type 2, respectively). It is argued that in the type 2 case the viral RNA would evolve anambigrammaticproperty, whereby the viral genes are free of stop codons in a reverse reading frame (with forward and reverse codons aligned). Recent observations of ribosome profiles of ambigrammatic narnavirus sequences are consistent with our predictions for the type 2 case.

Tissue- and stage-specific landscape of the mouse translatome

The current understanding of how overall principles of translational control govern the embryo-to-adult transition in mammals is still far from comprehensive. Herein we profiled the translatomes and transcriptomes of six tissues from the mice at embryonic and adult stages and presented the first report of tissue- and stage-specific translational landscape in mice. We quantified the extent of gene expression divergence among different expression layers, tissues and stages, detected significant changes in gene composition and function underlying these divergences and revealed the changing architecture of translational regulation. We further showed that dynamic translational regulation can be largely achieved via modulation of translational efficiency. Translational efficiency could be altered by alternative splicing (AS), upstream and downstream open reading frames (uORFs and dORFs). We revealed AS-mediated translational repression that was exerted in an event type-dependent manner. uORFs and dORFs exhibited mutually exclusive usage and the opposing effects of translational regulation. Furthermore, we discovered many novel microproteins encoded by long noncoding RNAs and demonstrated their regulatory potential and functional relevance. Our data and analyses will facilitate a better understanding of the complexity of translation and translational regulation across tissue and stage spectra and provide an important resource to the translatome research community.

Polysome Profiling without Gradient Makers or Fractionation Systems

Polysome fractionation by sucrose density gradient centrifugation is a powerful tool that can be used to create ribosome profiles, identify specific mRNAs being translated by ribosomes, and analyze polysome associated factors. While automated gradient makers and gradient fractionation systems are commonly used with this technique, these systems are generally expensive and can be cost-prohibitive for laboratories that have limited resources or cannot justify the expense due to their infrequent or occasional need to perform this method for their research. Here, a protocol is presented to reproducibly generate polysome profiles using standard equipment available in most molecular biology laboratories without specialized fractionation instruments. Moreover, a comparison of polysome profiles generated with and without a gradient fractionation system is provided. Strategies to optimize and produce reproducible polysome profiles are discussed. Saccharomyces cerevisiae is utilized as a model organism in this protocol. However, this protocol can be easily modified and adapted to generate ribosome profiles for many different organisms and cell types.

Impact of uORFs in mediating regulation of translation in stress conditions

Background

A large fraction of genes contains upstream ORFs (uORFs) in the 5′ untranslated region (5’UTR). The translation of uORFs can inhibit the translation of the main coding sequence, for example by causing premature dissociation of the two ribosomal units or ribosome stalling. However, it is currently unknown if most uORFs are inhibitory or if this activity is restricted to specific cases. Here we interrogate ribosome profiling data from three different stress experiments in yeast to gain novel insights into this question.

Results

By comparing ribosome occupancies in different conditions and experiments we obtain strong evidence that, in comparison to primary coding sequences (CDS), which undergo translational arrest during stress, the translation of uORFs is mostly unaffected by changes in the environment. As a result, the relative abundance of uORF-encoded peptides increases during stress. In general, the changes in the translational efficiency of regions containing uORFs do not seem to affect downstream translation. The exception are uORFs found in a subset of genes that are significantly up-regulated at the level of translation during stress; these uORFs tend to be translated at lower levels in stress conditions than in optimal growth conditions, facilitating the translation of the CDS during stress. We find new examples of uORF-mediated regulation of translation, including the Gcn4 functional homologue fil1 and ubi4 genes in S. pombe.

Conclusion

We find evidence that the relative amount of uORF-encoded peptides increases during stress. The increased translation of uORFs is however uncoupled from the general CDS translational repression observed during stress. In a subset of genes that encode proteins that need to be rapidly synthesized upon stress uORFs act as translational switches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-021-00363-9.

Refinement of the clinical variant interpretation framework by statistical evidence and machine learning

BACKGROUND

Although the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-based guidelines.

METHODS

Statistical assessment of average deleteriousness of start-lost, stop-lost, and in-frame insertion and deletion (indel) variants and extraction of deleterious subsets was performed, being informed by proportions of rare variants in the general population of the Genome Aggregation Database (gnomAD). A machine learning-based model scoring the pathogenicity of start-lost variants (the PoStaL model) was constructed by predicting possible translation initiation sites on transcripts by deep learning and training a random forest on known pathogenic and likely benign variants.

FINDINGS

The proportion of rare variants was highest in stop-lost variants, followed by in-frame indels and start-lost variants, suggesting that the criteria in the ACMG/AMP guidelines assigning PVS (pathogenic very strong) to start-lost variants and PM (pathogenic moderate) to stop-lost and in-frame indel variants would not be appropriate. Regarding deleterious subsets, stop-lost variants introducing extensions of more than 30 amino acids and in-frame indels computationally predicted to be damaging are enriched for rare and known pathogenic variants. For start-lost variants, we developed the PoStaL model, which outperforms existing tools. We also provide comprehensive lists of the PoStaL scores for start-lost variants and the length of extended amino acids by stop-lost variants.

CONCLUSIONS

Our study could contribute to refinement of the ACMG/AMP guidelines, provides resources for future investigation, and provides an example of how to improve knowledge-based frameworks by data-driven approaches.

FUNDING

The study was supported by grants from the Japan Agency for Medical Research and Development (AMED) and the Japan Society for the Promotion of Science (JSPS).

RiboDoc: A Docker-based package for ribosome profiling analysis

Ribosome profiling (RiboSeq) has emerged as a powerful technique for studying the genome-wide regulation of translation in various cells. Several steps in the biological protocol have been improved, but the bioinformatics part of RiboSeq suffers from a lack of standardization, preventing the straightforward and complete reproduction of published results. Too many published studies provide insufficient detail about the bioinformatics pipeline used. The broad range of questions that can be asked with RiboSeq makes it difficult to use a single bioinformatics tool. Indeed, many scripts have been published for addressing diverse questions. Here (https://github.com/equipeGST/RiboDoc), we propose a unique tool (for use with multiple operating systems, OS) to standardize the general steps that must be performed systematically in RiboSeq analysis, together with the statistical analysis and quality control of the sample. The data generated can then be exploited with more specific tools. We hope that this tool will help to standardize bioinformatics analyses pipelines in the field of translation.

Molecular engineering improves antigen quality and enables integrated manufacturing of a trivalent subunit vaccine candidate for rotavirus

BACKGROUND

Vaccines comprising recombinant subunit proteins are well-suited to low-cost and high-volume production for global use. The design of manufacturing processes to produce subunit vaccines depends, however, on the inherent biophysical traits presented by an individual antigen of interest. New candidate antigens typically require developing custom processes for each one and may require unique steps to ensure sufficient yields without product-related variants.

RESULTS

We describe a holistic approach for the molecular design of recombinant protein antigens-considering both their manufacturability and antigenicity-informed by bioinformatic analyses such as RNA-seq, ribosome profiling, and sequence-based prediction tools. We demonstrate this approach by engineering the product sequences of a trivalent non-replicating rotavirus vaccine (NRRV) candidate to improve titers and mitigate product variants caused by N-terminal truncation, hypermannosylation, and aggregation. The three engineered NRRV antigens retained their original antigenicity and immunogenicity, while their improved manufacturability enabled concomitant production and purification of all three serotypes in a single, end-to-end perfusion-based process using the biotechnical yeast Komagataella phaffii.

CONCLUSIONS

This study demonstrates that molecular engineering of subunit antigens using advanced genomic methods can facilitate their manufacturing in continuous production. Such capabilities have potential to lower the cost and volumetric requirements in manufacturing vaccines based on recombinant protein subunits.

Big data, integrative omics and network biology

A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other metabolic activities of a cell. These networks regulate signal perception and processing that drives biological functions. The biological complexity cannot be fully captured by a single -omics discipline. The holistic study of an organism-in health, perturbation, exposure to environment and disease, is studied under systems biology. The bottom-up molecular approaches (genes, mRNA, protein, metabolite, etc.) have laid the foundation of current biological knowledge covering the horizon from viruses, bacteria, fungi, plants and animals. Yet, these techniques provide a rather myopic view of biology at the molecular level. To understand how the interconnected molecular components are formed and rewired in disease or exposure to environmental stimuli is the holy grail of modern biology. The omics era was heralded by the genomics revolution but advanced sequencing techniques are now also ubiquitous in transcriptomics, proteomics, metabolomics and lipidomics. Multi-omics data analysis and integration techniques are driving the quest for deeper insights into how the different layers of biomolecules talk to each other in diverse contexts.

The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches

Macromolecular complexes of proteins and RNAs are essential building blocks of cells. These stable supramolecular particles can be viewed as minimal biochemical units whose structural organization, i.e., the way the RNA and the protein interact with each other, is directly linked to their biological function. Whether those are dynamic regulatory ribonucleoproteins (RNPs) or integrated molecular machines involved in gene expression, the comprehensive knowledge of these units is critical to our understanding of key molecular mechanisms and cell physiology phenomena. Such is the goal of diverse complexomic approaches and in particular of the recently developed gradient profiling by sequencing (Grad-seq). By separating cellular protein and RNA complexes on a density gradient and quantifying their distributions genome-wide by mass spectrometry and deep sequencing, Grad-seq charts global landscapes of native macromolecular assemblies. In this review, we propose a function-based ontology of stable RNPs and discuss how Grad-seq and related approaches transformed our perspective of bacterial and eukaryotic ribonucleoproteins by guiding the discovery of new RNA-binding proteins and unusual classes of noncoding RNAs. We highlight some methodological aspects and developments that permit to further boost the power of this technique and to look for exciting new biology in understudied and challenging biological models.

Two repeated motifs enriched within some enhancers and origins of replication are bound by SETMAR isoforms in human colon cells

Setmar is a gene specific to simian genomes. The function(s) of its isoforms are poorly understood and their existence in healthy tissues remains to be validated. Here we profiled SETMAR expression and its genome-wide binding landscape in colon tissue. We found isoforms V3 and V6 in healthy and tumour colon tissues as well as incell lines. In two colorectal cell lines SETMAR binds to several thousand Hsmar1 and MADE1 terminal ends, transposons mostly located in non-genic regions of active chromatin including in enhancers. It also binds to a 12-bp motifs similar to an inner motif in Hsmar1 and MADE1 terminal ends. This motif is interspersed throughout the genome and is enriched in GC-rich regions as well as in CpG islands that contain constitutive replication origins. It is also found in enhancers other than those associated with Hsmar1 and MADE1. The role of SETMAR in the expression of genes, DNA replication and in DNA repair are discussed.

The role of micropeptides in biology

Micropeptides are small polypeptides coded by small open-reading frames. Progress in computational biology and the analyses of large-scale transcriptomes and proteomes have revealed that mammalian genomes produce a large number of transcripts encoding micropeptides. Many of these have been previously annotated as long noncoding RNAs. The role of micropeptides in cellular homeostasis maintenance has been demonstrated. This review discusses different types of micropeptides as well as methods to identify them, such as computational approaches, ribosome profiling, and mass spectrometry.

Mammalian Alternative Translation Initiation Is Mostly Nonadaptive

Alternative translation initiation (ATLI) refers to the existence of multiple translation initiation sites per gene and is a widespread phenomenon in eukaryotes. ATLI is commonly assumed to be advantageous through creating proteome diversity or regulating protein synthesis. We here propose an alternative hypothesis that ATLI arises primarily from nonadaptive initiation errors presumably due to the limited ability of ribosomes to distinguish sequence motifs truly signaling translation initiation from similar sequences. Our hypothesis, but not the adaptive hypothesis, predicts a series of global patterns of ATLI, all of which are confirmed at the genomic scale by quantitative translation initiation sequencing in multiple human and mouse cell lines and tissues. Similarly, although many codons differing from AUG by one nucleotide can serve as start codons, our analysis suggests that using non-AUG start codons is mostly disadvantageous. These and other findings strongly suggest that ATLI predominantly results from molecular error, requiring a major revision of our understanding of the precision and regulation of translation initiation.

Decreased expression of ARID1A invasively downregulates the expression of ribosomal proteins in hepatocellular carcinoma

Background: There was increasing evidence showing that ARID1A alterations correlated with higher tumor mutational burden, but there were limited studies focusing on the adaptive mechanisms for tumor cells to survive under excessive genomic alterations. Materials & methods: To further explore the adaptive mechanisms under ARID1A alterations, we performed RNA sequencing in ARID1A knockdown hepatocellular carcinoma cell lines, and demonstrated that decreased expression of ARID1A controlled global ribosomal proteins synthesis. The results were further confirmed by quantitative reverse transcription-PCR and bioinformatic analysis in The Cancer Genome Atlas Liver Hepatocellular Carcinoma database. Conclusion: The present study was the first to demonstrate that ARID1A might be involved in the translation pathway and served as an adaptive mechanism for tumor cells to survive under stress.

Full-length ribosome density prediction by a multi-input and multi-output model

Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS.

Translation elongation is a process in which amino acids are linked into proteins by ribosomes in cells. Translation elongation rates along the mRNAs are not constant, and are regulated by a series of mechanisms, such as codon rarity and mRNA stability. In this study, we modeled the translation elongation process at a full-length coding sequence level and developed a deep learning based approach to predict the translation elongation rates from mRNA sequences, through extracting the regulatory codes of elongation rates from the contextual sequences. The analyses, based on our interpretable metric named codon impact score, for the first time (to the best of our knowledge), revealed that in addition to the neighboring codons of the ribosomal A sites, the remote codons may also have an important impact on the translation elongation rates. This new finding may stimulate additional experiments and shed light on the regulatory mechanisms of protein synthesis.

RiboA: a web application to identify ribosome A-site locations in ribosome profiling data

Background

Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations.

Results

We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms.

Conclusions

The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/. The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.

Reprogramming of translation in yeast cells impaired for ribosome recycling favors short, efficiently translated mRNAs

In eukaryotes, 43S preinitiation complex (PIC) formation is a rate-determining step of translation. Ribosome recycling following translation termination produces free 40S subunits for re-assembly of 43S PICs. Yeast mutants lacking orthologs of mammalian eIF2D (Tma64), and either MCT-1 (Tma20) or DENR (Tma22), are broadly impaired for 40S recycling; however, it was unknown whether this defect alters the translational efficiencies (TEs) of particular mRNAs. Here, we conducted ribosome profiling of a yeast tma64∆/tma20∆ double mutant and observed a marked reprogramming of translation, wherein the TEs of the most efficiently translated ('strong') mRNAs increase, while those of 'weak' mRNAs generally decline. Remarkably, similar reprogramming was seen on reducing 43S PIC assembly by inducing phosphorylation of eIF2α or by decreasing total 40S subunit levels by depleting Rps26. Our findings suggest that strong mRNAs outcompete weak mRNAs in response to 43S PIC limitation achieved in various ways, in accordance with previous mathematical modeling.

Genetic basis of mitochondrial diseases

Mitochondrial disorders are monogenic disorders characterized by a defect in oxidative phosphorylation and caused by pathogenic variants in one of over 340 different genes. The implementation of whole-exome sequencing has led to a revolution in their diagnosis, duplicated the number of associated disease genes, and significantly increased the diagnosed fraction. However, the genetic etiology of a substantial fraction of patients exhibiting mitochondrial disorders remains unknown, highlighting limitations in variant detection and interpretation, which calls for improved computational and DNA sequencing methods, as well as the addition of OMICS tools. More intriguingly, this also suggests that some pathogenic variants lie outside of the protein-coding genes and that the mechanisms beyond the Mendelian inheritance and the mtDNA are of relevance. This review covers the current status of the genetic basis of mitochondrial diseases, discusses current challenges and perspectives, and explores the contribution of factors beyond the protein-coding regions and monogenic inheritance in the expansion of the genetic spectrum of disease.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

riboCIRC: a comprehensive database of translatable circRNAs

riboCIRC is a translatome data-oriented circRNA database specifically designed for hosting, exploring, analyzing, and visualizing translatable circRNAs from multi-species. The database provides a comprehensive repository of computationally predicted ribosome-associated circRNAs; a manually curated collection of experimentally verified translated circRNAs; an evaluation of cross-species conservation of translatable circRNAs; a systematic de novo annotation of putative circRNA-encoded peptides, including sequence, structure, and function; and a genome browser to visualize the context-specific occupant footprints of circRNAs. It represents a valuable resource for the circRNA research community and is publicly available at http://www.ribocirc.com .

Personal Neoantigen Vaccines for the Treatment of Cancer

Cancer vaccines can generate and amplify tumor-specific T cell responses with the promise to provide long-term control of cancer. All cancer cells harbor genetic alterations encoding neoantigens that are specific to the tumor and not present in normal tissue. Similar to foreign antigens targeted by T cells in infectious disease settings, neoantigens represent the long elusive immunogens for cancer vaccination. Since the vast majority of mutations are unique to individual tumors, neoantigen vaccines require custom design for each patient. The availability of rapid and cost-effective genome sequencing, along with advanced bioinformatics tools, now allows neoantigen-target discovery and vaccine manufacturing in sufficient time for the treatment of cancer patients. Clinical trials in melanoma and glioblastoma have demonstrated the feasibility, immunogenicity, and signals of efficacy of this personalized immunotherapy approach. Key unresolved areas include identification of the most effective vaccine delivery platforms, validation and consensus of neoantigen target selection, and optimal strategies for partnering immunotherapies. Given the universal presence of mutations in cancer and the patient-tailored paradigm, personalized neoantigen vaccines have potential applicability for all cancer patients.

Determinants of genome-wide distribution and evolution of uORFs in eukaryotes

Upstream open reading frames (uORFs) play widespread regulatory functions in modulating mRNA translation in eukaryotes, but the principles underlying the genomic distribution and evolution of uORFs remain poorly understood. Here, we analyze ~17 million putative canonical uORFs in 478 eukaryotic species that span most of the extant taxa of eukaryotes. We demonstrate how positive and purifying selection, coupled with differences in effective population size (Ne), has shaped the contents of uORFs in eukaryotes. Besides, gene expression level is important in influencing uORF occurrences across genes in a species. Our analyses suggest that most uORFs might play regulatory roles rather than encode functional peptides. We also show that the Kozak sequence context of uORFs has evolved across eukaryotic clades, and that noncanonical uORFs tend to have weaker suppressive effects than canonical uORFs in translation regulation. This study provides insights into the driving forces underlying uORF evolution in eukaryotes.

Riboexp: an interpretable reinforcement learning framework for ribosome density modeling

Translation elongation is a crucial phase during protein biosynthesis. In this study, we develop a novel deep reinforcement learning-based framework, named Riboexp, to model the determinants of the uneven distribution of ribosomes on mRNA transcripts during translation elongation. In particular, our model employs a policy network to perform a context-dependent feature selection in the setting of ribosome density prediction. Our extensive tests demonstrated that Riboexp can significantly outperform the state-of-the-art methods in predicting ribosome density by up to 5.9% in terms of per-gene Pearson correlation coefficient on the datasets from three species. In addition, Riboexp can indicate more informative sequence features for the prediction task than other commonly used attribution methods in deep learning. In-depth analyses also revealed the meaningful biological insights generated by the Riboexp framework. Moreover, the application of Riboexp in codon optimization resulted in an increase of protein production by around 31% over the previous state-of-the-art method that models ribosome density. These results have established Riboexp as a powerful and useful computational tool in the studies of translation dynamics and protein synthesis. Availability: The data and code of this study are available on GitHub: https://github.com/Liuxg16/Riboexp. Contact:  zengjy321@tsinghua.edu.cn; songsen@tsinghua.edu.cn.

Translational landscape and protein biogenesis demands of the early secretory pathway in Komagataella phaffii

Background

Eukaryotes use distinct networks of biogenesis factors to synthesize, fold, monitor, traffic, and secrete proteins. During heterologous expression, saturation of any of these networks may bottleneck titer and yield. To understand the flux through various routes into the early secretory pathway, we quantified the global and membrane-associated translatomes of Komagataella phaffii.

Results

By coupling Ribo-seq with long-read mRNA sequencing, we generated a new annotation of protein-encoding genes. By using Ribo-seq with subcellular fractionation, we quantified demands on co- and posttranslational translocation pathways. During exponential growth in rich media, protein components of the cell-wall represent the greatest number of nascent chains entering the ER. Transcripts encoding the transmembrane protein PMA1 sequester more ribosomes at the ER membrane than any others. Comparison to Saccharomyces cerevisiae reveals conservation in the resources allocated by gene ontology, but variation in the diversity of gene products entering the secretory pathway.

Conclusion

A subset of host proteins, particularly cell-wall components, impose the greatest biosynthetic demands in the early secretory pathway. These proteins are potential targets in strain engineering aimed at alleviating bottlenecks during heterologous protein production.

OpenProt 2021: deeper functional annotation of the coding potential of eukaryotic genomes

OpenProt (www.openprot.org) is the first proteogenomic resource supporting a polycistronic annotation model for eukaryotic genomes. It provides a deeper annotation of open reading frames (ORFs) while mining experimental data for supporting evidence using cutting-edge algorithms. This update presents the major improvements since the initial release of OpenProt. All species support recent NCBI RefSeq and Ensembl annotations, with changes in annotations being reported in OpenProt. Using the 131 ribosome profiling datasets re-analysed by OpenProt to date, non-AUG initiation starts are reported alongside a confidence score of the initiating codon. From the 177 mass spectrometry datasets re-analysed by OpenProt to date, the unicity of the detected peptides is controlled at each implementation. Furthermore, to guide the users, detectability statistics and protein relationships (isoforms) are now reported for each protein. Finally, to foster access to deeper ORF annotation independently of one's bioinformatics skills or computational resources, OpenProt now offers a data analysis platform. Users can submit their dataset for analysis and receive the results from the analysis by OpenProt. All data on OpenProt are freely available and downloadable for each species, the release-based format ensuring a continuous access to the data. Thus, OpenProt enables a more comprehensive annotation of eukaryotic genomes and fosters functional proteomic discoveries.

Performing Ribosome Profiling to Assess Translation in Vegetative and Meiotic Yeast Cells

Ribosome profiling, first developed in 2009, is the gold standard for quantifying and qualifying changes to translation genome-wide (Ingolia et al., Science, 2009). Though first designed and optimized in vegetative budding yeast, it has since been modified and specialized for use in diverse cellular states in yeast, as well as in bacteria, plants, human cells, and many other organisms (Ingolia et al. Science, 2009, reviewed in (Ingolia et al., Cold Spring Harb Perspect Biol, 2019; Brar and Weissman, Nat Rev Mol Cell Biol, 2015)). Here we report the current ribosome profiling protocol used in our lab to study genome-wide changes to translation in budding yeast undergoing the developmental process of meiosis (Brar et al., Science, 2012; Cheng et al., Cell, 2018). We describe this protocol in detail, including the following steps: collection and flash freezing samples, cell lysis and extract preparation, sucrose gradient centrifugation and monosome collection, RNA extraction, library preparation, and library quality control. Almost every step presented here should be directly applicable to performing ribosome profiling in other eukaryotic cell types or cell states.

Codon Resolution Analysis of Ribosome Profiling Data

Translation is a central biological process in living cells. Ribosome profiling approach enables assessing translation on a global, cell-wide level. Extracting versatile information from the ribosome profiling data usually requires specialized expertise for handling the sequencing data that is not available to the broad community of experimentalists. Here, we provide an easy-to-use and modifiable workflow that uses a small set of commands and enables full data analysis in a standardized way, including precise positioning of the ribosome-protected fragments, for determining codon-specific translation features. The workflow is complemented with simple step-by-step explanations and is accessible to scientists with no computational background.

Expanding small-molecule target space to mRNA translation regulation

Multiple layers of regulation are in place on mRNA translation to ensure that cells respond in a fast manner to environmental cues in a tissue-specific and mRNA-selective manner. Here, we discuss mRNA translation regulatory mechanisms and potential drug-intervention targets. Taking on a new scientific rational of translation regulation and consequently a new target space, we have developed a unique discovery platform that is able to identify selective small molecule drugs that affect translation of specific proteins. This approach has enabled targeting of proteins that have been considered undruggable. Our discovery platform was repeatedly utilized to identify compounds in multiple therapeutic programs, including fibrosis, oncology, anti-virals and Huntington's disease. In fibrosis, the lead compound ANI-21 has demonstrated a tissue-specific effect in lowering the translation of Collagen-I and superior efficacy over best standard of care, in both cell and animal models, mediated by a novel mechanism of action. This program is expected to enter clinical studies within 12-18 months.

A translational program that suppresses metabolism to shield the genome

Translatome reprogramming is a primary determinant of protein levels during stimuli adaptation. This raises the question: what are the translatome remodelers that reprogram protein output to activate biochemical adaptations. Here, we identify a translational pathway that represses metabolism to safeguard genome integrity. A system-wide MATRIX survey identified the ancient eIF5A as a pH-regulated translation factor that responds to fermentation-induced acidosis. TMT-pulse-SILAC analysis identified several pH-dependent proteins, including the mTORC1 suppressor Tsc2 and the longevity regulator Sirt1. Sirt1 operates as a pH-sensor that deacetylates nuclear eIF5A during anaerobiosis, enabling the cytoplasmic export of eIF5A/Tsc2 mRNA complexes for translational engagement. Tsc2 induction inhibits mTORC1 to suppress cellular metabolism and prevent acidosis-induced DNA damage. Depletion of eIF5A or Tsc2 leads to metabolic re-initiation and proliferation, but at the expense of incurring substantial DNA damage. We suggest that eIF5A operates as a translatome remodeler that suppresses metabolism to shield the genome.

Pairs of amino acids at the P- and A-sites of the ribosome predictably and causally modulate translation-elongation rates

Variation in translation-elongation kinetics along a transcript's coding sequence plays an important role in the maintenance of cellular protein homeostasis by regulating co-translational protein folding, localization, and maturation. Translation-elongation speed is influenced by molecular factors within mRNA and protein sequences. For example, the presence of proline in the ribosome's P- or A-site slows down translation, but the effect of other pairs of amino acids, in the context of all 400 possible pairs, has not been characterized. Here, we study Saccharomyces cerevisiae using a combination of bioinformatics, mutational experiments, and evolutionary analyses, and show that many different pairs of amino acids and their associated tRNA molecules predictably and causally encode translation rate information when these pairs are present in the A- and P-sites of the ribosome independent of other factors known to influence translation speed including mRNA structure, wobble base pairing, tripeptide motifs, positively charged upstream nascent chain residues, and cognate tRNA concentration. The fast-translating pairs of amino acids that we identify are enriched four-fold relative to the slow-translating pairs across Saccharomyces cerevisiae's proteome, while the slow-translating pairs are enriched downstream of domain boundaries. Thus, the chemical identity of amino acid pairs contributes to variability in translation rates, elongation kinetics are causally encoded in the primary structure of proteins, and signatures of evolutionary selection indicate their potential role in co-translational processes.

Ribosome biogenesis is a downstream effector of the oncogenic U2AF1-S34F mutation

U2 Small Nuclear RNA Auxiliary Factor 1 (U2AF1) forms a heterodimeric complex with U2AF2 that is primarily responsible for 3' splice site selection. U2AF1 mutations have been identified in most cancers but are prevalent in Myelodysplastic Syndrome (MDS) and Acute Myeloid Leukemia (AML), and the most common mutation is a missense substitution of serine-34 to phenylalanine (S34F). The U2AF heterodimer also has a noncanonical function as a translational regulator. Here, we report that the U2AF1-S34F mutation results in specific misregulation of the translation initiation and ribosome biogenesis machinery. The net result is an increase in mRNA translation at the single-cell level. Among the translationally up-regulated targets of U2AF1-S34F is Nucleophosmin 1 (NPM1), which is a major driver of myeloid malignancy. Depletion of NPM1 impairs the viability of the U2AF1-S34F mutant cells and causes ribosomal RNA (rRNA) processing defects, thus indicating an unanticipated synthetic interaction between U2AF1, NPM1, and ribosome biogenesis. Our results establish a unique molecular phenotype for the U2AF1 mutation that recapitulates translational misregulation in myeloid disease.

Selecting Target Antigens for Cancer Vaccine Development

One of the principal goals of cancer immunotherapy is the development of efficient therapeutic cancer vaccines that are able to elicit an effector as well as memory T cell response specific to tumor antigens. In recent years, the attention has been focused on the personalization of cancer vaccines. However, the efficacy of therapeutic cancer vaccines is still disappointing despite the large number of vaccine strategies targeting different tumors that have been evaluated in recent years. While the preclinical data have frequently shown encouraging results, clinical trials have not provided satisfactory data to date. The main reason for such failures is the complexity of identifying specific target tumor antigens that should be unique or overexpressed only by the tumor cells compared to normal cells. Most of the tumor antigens included in cancer vaccines are non-mutated overexpressed self-antigens, eliciting mainly T cells with low-affinity T cell receptors (TCR) unable to mediate an effective anti-tumor response. In this review, the target tumor antigens employed in recent years in the development of therapeutic cancer vaccine strategies are described, along with potential new classes of tumor antigens such as the human endogenous retroviral elements (HERVs), unconventional antigens, and/or heteroclitic peptides.

Modelling of pathogen-host systems using deeper ORF annotations and transcriptomics to inform proteomics analyses

The Zika virus is a flavivirus that can cause fulminant outbreaks and lead to Guillain-Barré syndrome, microcephaly and fetal demise. Like other flaviviruses, the Zika virus is transmitted by mosquitoes and provokes neurological disorders. Despite its risk to public health, no antiviral nor vaccine are currently available. In the recent years, several studies have set to identify human host proteins interacting with Zika viral proteins to better understand its pathogenicity. Yet these studies used standard human protein sequence databases. Such databases rely on genome annotations, which enforce a minimal open reading frame (ORF) length criterion. An ever-increasing number of studies have demonstrated the shortcomings of such annotation, which overlooks thousands of functional ORFs. Here we show that the use of a customized database including currently non-annotated proteins led to the identification of 4 alternative proteins as interactors of the viral capsid and NS4A proteins. Furthermore, 12 alternative proteins were identified in the proteome profiling of Zika infected monocytes, one of which was significantly up-regulated. This study presents a computational framework for the re-analysis of proteomics datasets to better investigate the viral-host protein interplays upon infection with the Zika virus.

GCN sensitive protein translation in yeast

Levels of protein translation by ribosomes are governed both by features of the translation machinery as well as sequence properties of the mRNAs themselves. We focus here on a striking three-nucleotide periodicity, characterized by overrepresentation of GCN codons and underrepresentation of G at the second position of codons, that is observed in Open Reading Frames (ORFs) of mRNAs. Our examination of mRNA sequences in Saccharomyces cerevisiae revealed that this periodicity is particularly pronounced in the initial codons-the ramp region-of ORFs of genes with high protein expression. It is also found in mRNA sequences immediately following non-standard AUG start sites, located upstream or downstream of the standard annotated start sites of genes. To explore the possible influences of the ramp GCN periodicity on translation efficiency, we tested edited ramps with accentuated or depressed periodicity in two test genes, SKN7 and HMT1. Greater conformance to (GCN)n was found to significantly depress translation, whereas disrupting conformance had neutral or positive effects on translation. Our recent Molecular Dynamics analysis of a subsystem of translocating ribosomes in yeast revealed an interaction surface that H-bonds to the +1 codon that is about to enter the ribosome decoding center A site. The surface, comprised of 16S/18S rRNA C1054 and A1196 (E. coli numbering) and R146 of ribosomal protein Rps3, preferentially interacts with GCN codons, and we hypothesize that modulation of this mRNA-ribosome interaction may underlie GCN-mediated regulation of protein translation. Integration of our expression studies with large-scale reporter studies of ramp sequence variants suggests a model in which the C1054-A1196-R146 (CAR) interaction surface can act as both an accelerator and braking system for ribosome translation.

Accurate detection of short and long active ORFs using Ribo-seq data

MOTIVATION

Ribo-seq, a technique for deep-sequencing ribosome-protected mRNA fragments, has enabled transcriptome-wide monitoring of translation in vivo. It has opened avenues for re-evaluating the coding potential of open reading frames (ORFs), including many short ORFs that were previously presumed to be non-translating. However, the detection of translating ORFs, specifically short ORFs, from Ribo-seq data, remains challenging due to its high heterogeneity and noise.

RESULTS

We present ribotricer, a method for detecting actively translating ORFs by directly leveraging the three-nucleotide periodicity of Ribo-seq data. Ribotricer demonstrates higher accuracy and robustness compared with other methods at detecting actively translating ORFs including short ORFs on multiple published datasets across species inclusive of Arabidopsis, Caenorhabditis elegans, Drosophila, human, mouse, rat, yeast and zebrafish.

AVAILABILITY AND IMPLEMENTATION

Ribotricer is available at https://github.com/smithlabcode/ribotricer. All analysis scripts and results are available at https://github.com/smithlabcode/ribotricer-results.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification and analysis of small proteins and short open reading frame encoded peptides in Hep3B cell

The small proteins and short open reading frames encoded peptides (SEPs) are of fundamental importance because of their essential roles in biological processes. However, the annotation or identification of them is challenging, in part owing to the limitation of the traditional genome annotation pipeline and their inherent characteristics of low abundance and low molecular weight. To discover and characterize SEPs in Hep3B cell line, we developed an optimized peptidomic assay by combining different peptide extraction and separation methods. The organic solvent precipitation method in peptidomic showed promotion in the enrichment of low molecular proteins or peptides, and the data clearly showed a beneficial effect from the reduction of sample complexity, resulting in high-quality MS/MS spectra. Furthermore, different strategies exhibited good complementarity in improving the total amount of small proteins and their sequence coverage. In total, 1192 proteins within less than 100 amino acids were identified, including 271 newly discovered SEPs that been annotated in the OpenProt database and 147 SEPs of them encoded from ncRNA or lincRNA. Results in this work provide robust evidence to date that the human proteome is more complicated than previously appreciated, and this will be a benefit to discoveries of proteins without function annotation. SIGNIFICANCE: In this work, methods were optimized to identify SEPs in Hep3B. The organic solvent precipitation presents promotion in enrichment of low molecular proteins or peptides, and the data clearly showed a beneficial effect from the reduction of sample complexity, resulting in high quality MS/MS spectra. Different strategies exhibited good complementarity in improving total amount of small proteins and their sequence coverage. In total, 1192 proteins within less than 100 amino acids were identified, including 271 newly discovered SEPs that been annotated in the OpenProt database and 147 SEPs of them encoded from ncRNA or lincRNA. Furthermore, 22 SEPs generated from the uORF may has potential effect in translation control, and 149 newly identified SEPs have known functional domains or cross-species conservation. Results in this work present robust evidence for the coding potential of the ignored region of human genomes and may provide additional insights into tumor biology.

uORFs: Important Cis-Regulatory Elements in Plants

Gene expression is regulated at many levels, including mRNA transcription, translation, and post-translational modification. Compared with transcriptional regulation, mRNA translational control is a more critical step in gene expression and allows for more rapid changes of encoded protein concentrations in cells. Translation is highly regulated by complex interactions between cis-acting elements and trans-acting factors. Initiation is not only the first phase of translation, but also the core of translational regulation, because it limits the rate of protein synthesis. As potent cis-regulatory elements in eukaryotic mRNAs, upstream open reading frames (uORFs) generally inhibit the translation initiation of downstream major ORFs (mORFs) through ribosome stalling. During the past few years, with the development of RNA-seq and ribosome profiling, functional uORFs have been identified and characterized in many organisms. Here, we review uORF identification, uORF classification, and uORF-mediated translation initiation. More importantly, we summarize the translational regulation of uORFs in plant metabolic pathways, morphogenesis, disease resistance, and nutrient absorption, which open up an avenue for precisely modulating the plant growth and development, as well as environmental adaption. Additionally, we also discuss prospective applications of uORFs in plant breeding.

Implications of RNG140 (caprin2)-mediated translational regulation in eye lens differentiation

Regulation of gene expression at the translational level is key to determining cell fate and function. An RNA-binding protein, RNG140 (caprin2), plays a role in eye lens differentiation and has been reported to function in translational regulation. However, the mechanism and its role in eyes has remained unclear. Here, we show that RNG140 binds to the translation initiation factor eukaryotic initiation factor 3 (eIF3) and suppresses translation through mechanisms involving suppression of eIF3-dependent translation initiation. Comprehensive ribosome profiling revealed that overexpression of RNG140 in cultured Chinese hamster ovary cells reduces translation of long mRNAs, including those associated with cell proliferation. RNG140-mediated translational regulation also operates in the mouse eye, where RNG140 knockout increased the translation of long mRNAs. mRNAs involved in lens differentiation, such as crystallin mRNAs, are short and can escape translational inhibition by RNG140 and be translated in differentiating lenses. Thus, this study provides insights into the mechanistic basis of lens cell transition from proliferation to differentiation via RNG140-mediated translational regulation.

Ribosomal proteins: mutant phenotypes by the numbers and associated gene expression changes

Ribosomal proteins are highly conserved, many universally so among organisms. All ribosomal proteins are structural parts of the same molecular machine, the ribosome. However, when ribosomal proteins are mutated individually, they often lead to distinct and intriguing phenotypes, including specific human pathologies. This review is an attempt to collect and analyse all the reported phenotypes of each ribosomal protein mutant in several eukaryotes (Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Mus musculus, Homo sapiens). These phenotypes were processed with unbiased computational approaches to reveal associations between different phenotypes and the contributions of individual ribosomal protein genes. An overview of gene expression changes in ribosomal protein mutants, with emphasis on ribosome profiling studies, is also presented. The available data point to patterns that may account for most of the observed phenotypes. The information presented here may also inform future studies about the molecular basis of the phenotypes that arise from mutations in ribosomal proteins.