Ribosome-protected mRNA Fragments Research Articles

A review of Ribosome profiling and tools used in Ribo-seq data analysis

Translational regulation plays the most critical role in gene expression. Ribosome profiling sequencing (Ribo-Seq) is one of the methods to study translation and its regulation. It is a high throughput technology based on deep sequencing, which targets ribosome protected mRNA fragments to produce a ‘global snapshot’ of translatome. There has been an annual increase in the number of publications incorporating Ribo-seq technology. Because of its importance, we used PubMed database to conduct a comprehensive bibliometric analysis on Ribo-seq. We identified 2744 published articles that utilized the term ‘Ribo-seq’ between 2009 and Jan 2024, and 684 articles that contained both Ribo-seq and RNA-seq terms. Based on keywords correlation analysis, we discovered that the primary focus of Ribo-seq articles lies in the areas of translation, transcriptome, and ribosome in the past few years and other topics such as single-cell ribo-seq and crispr within two years, reflecting current areas of interests in Ribo-seq research. The Ribo-seq data analysis applications were also explored and summarized, providing a guide for researchers to choose corresponding tools for different types of analysis. Overall, we highlighted the advances made by Ribo-seq technologies, and the possibilities of utilizing machine learning models to unravel information from multi-omics data. The integration of Ribo-seq with other omics data, such as RNA-seq, is essential to understand the gene expression in complex biological systems.

Refinement of Leishmania donovani Genome Annotations in the Light of Ribosome-Protected mRNAs Fragments (Ribo-Seq Data).

Advances in next-generation sequencing methodologies have facilitated the assembly of an ever-increasing number of genomes. Gene annotations are typically conducted via specialized software, but the most accurate results require additional manual curation that incorporates insights derived from functional and bioinformatic analyses (e.g., transcriptomics, proteomics, and phylogenetics). In this study, we improved the annotation of the Leishmania donovani (strain HU3) genome using publicly available data from the deep sequencing of ribosome-protected mRNA fragments (Ribo-Seq). As a result of this analysis, we uncovered 70 previously non-annotated protein-coding genes and improved the annotation of around 600 genes. Additionally, we present evidence for small upstream open reading frames (uORFs) in a significant number of transcripts, indicating their potential role in the translational regulation of gene expression. The bioinformatics pipelines developed for these analyses can be used to improve the genome annotations of other organisms for which Ribo-Seq data are available. The improvements provided by these studies will bring us closer to the ultimate goal of a complete and accurately annotated L. donovani genome and will enhance future transcriptomics, proteomics, and genetics studies.

Beginners guide to ribosome profiling

Beginners guide to ribosome profiling

Translational Landscape of a C4 Plant, Sorghum bicolor, Under Normal and Sulfur-Deficient Conditions.

Recent accumulation of genomic and transcriptomic information has facilitated genetic studies. Increasing evidence has demonstrated that translation is an important regulatory step, and the transcriptome does not necessarily reflect the profile of functional protein production. Deep sequencing of ribosome-protected mRNA fragments (ribosome profiling or Ribo-seq) has enabled genome-wide analysis of translation. Sorghum is a C4 cereal important not only as food but also as forage and a bioenergy resource. Its resistance to harsh environments has made it an agriculturally important research subject. Yet genome-wide translational profiles in sorghum are still missing. In this study, we took advantage of Ribo-seq and identified actively translated reading frames throughout the genome. We detected translation of 4,843 main open reading frames (ORFs) annotated in the sorghum reference genome version 3.1 and revealed a number of unannotated translational events. A comparison of the transcriptome and translatome between sorghums grown under normal and sulfur-deficient conditions revealed that gene expression is modulated independently at transcript and translation levels. Our study revealed the translational landscape of sorghum's response to sulfur and provides datasets that could serve as a fundamental resource to extend genetic research on sorghum, including studies on translational regulation.

High-Resolution Ribosome Profiling for Determining Ribosome Functional States During Translation Elongation.

Translation elongation is a highly choreographed process that involves substantial conformational changes of the ribosome to accommodate aminoacyl-tRNAs and traverse along the mRNA template. To capture distinct functional states of the ribosome, a high-resolution ribosome profiling-based approach has been developed. By deep-sequencing differently sized ribosome-protected mRNA fragments, this approach captures not only ribosome positions but also their functional states in vivo across the Saccharomyces cerevisiae transcriptome with codon resolution. This chapter presents a condensed and step-by-step protocol for preserving ribosomes in their functional states using a cocktail of antibiotics that traps distinct steps of elongating ribosomes and for constructing a cDNA library derived from the ribosome-protected mRNA fragments for deep sequencing.

Ribosome distribution affects stalling in amino-acid starved cancer cells

Protein synthesis is a process central to all life on Earth, including mammalian cells. During this process, ribosomes attach to mRNA strands and translate them into proteins using amino acids. Under stress (for example, when the supply of circulating amino acids has been disrupted by tissue injury), ribosomes can stall. Ribosome profiling, a technique that creates a snapshot of active ribosomes in a cell by sequencing ribosome-protected mRNA fragments, captures a snapshot of ribosomes along transcripts and can detect such stalling events. This method has also revealed that the patterns of ribosomes along transcripts can vary from transcript to transcript in a manner that has not yet been explained. Here, we analyzed ribosome profiling data from amino acid-starved pancreatic cancer cells to explore whether the pattern of ribosome distribution along transcripts under normal conditions can predict the degree of ribosome stalling under stress. We hypothesized that ribosomes would stall more along “elongation-limited” transcripts that have fewer ribosome footprints near the start and stop codons than “initiation-limited” transcripts that have a large fraction of footprints at the start codon. Indeed, we found that ribosomes in amino acid-deprived cells stalled more along elongation-limited transcripts. By contrast, we observed no relationship between read density near start and stop and disparities between mRNA sequencing reads and ribosome profiling reads. This research identifies an important relationship between read distribution and propensity for ribosomes to stall, although more work is needed to fully understand the patterns of ribosome distribution along transcripts in ribosome profiling data.

RiboNT: A Noise-Tolerant Predictor of Open Reading Frames from Ribosome-Protected Footprints

Ribo-seq, also known as ribosome profiling, refers to the sequencing of ribosome-protected mRNA fragments (RPFs). This technique has greatly advanced our understanding of translation and facilitated the identification of novel open reading frames (ORFs) within untranslated regions or non-coding sequences as well as the identification of non-canonical start codons. However, the widespread application of Ribo-seq has been hindered because obtaining periodic RPFs requires a highly optimized protocol, which may be difficult to achieve, particularly in non-model organisms. Furthermore, the periodic RPFs are too short (28 nt) for accurate mapping to polyploid genomes, but longer RPFs are usually produced with a compromise in periodicity. Here we present RiboNT, a noise-tolerant ORF predictor that can utilize RPFs with poor periodicity. It evaluates RPF periodicity and automatically weighs the support from RPFs and codon usage before combining their contributions to identify translated ORFs. The results demonstrate the utility of RiboNT for identifying both long and small ORFs using RPFs with either good or poor periodicity. We implemented the pipeline on a dataset of RPFs with poor periodicity derived from membrane-bound polysomes of Arabidopsis thaliana seedlings and identified several small ORFs (sORFs) evolutionarily conserved in diverse plant species. RiboNT should greatly broaden the application of Ribo-seq by minimizing the requirement of RPF quality and allowing the use of longer RPFs, which is critical for organisms with complex genomes because these RPFs can be more accurately mapped to the position from which they were derived.

Increased MHC Class I Expression on Platelets in Human and Murine Sepsis

Complications from sepsis are largely driven by maladaptive immune responses. Platelets impact innate and adaptive immune responses, but whether platelets regulate adaptive immune responses in sepsis, including CD8+ T cell responses, remains unknown. To explore a possible contribution of platelets to the altered immune response in sepsis, we used deep sequencing of ribosome-protected RNA (RPR) fragments (also called ribosome footprint profiling) to acquire a global picture of translation in platelets from healthy and septic individuals. Using this method, we identified altered translation of transcripts related to adaptive CD8+T cell responses. We further confirmed these changes using megakaryocyte cultures, and an in vivo model of murine sepsis. Finally, we employed in vitro models to examine their functional relevance.Genome-wide sequencing of ribosome-protected mRNA fragments of human platelets isolated from septic patients and healthy donors revealed more than 1,000 genes under active translation in platelets. Sepsis altered the total RNA expression and translation of more than 300 genes by at least 2 fold compared to healthy individuals. Among these, classic MHC class I genes including HLA-A, B, and C were actively translated, and increased in sepsis. For example the expression of HLA-A increased almost 3 fold (RPR of healthy 62±77 vs sepsis 166±340; N=4-5). HLA-A mRNA expression changes were confirmed by real-time qPCR. We further demonstrated consistent changes in platelet surface expression of MHC class I proteins by flow cytometry.Since platelets are anucleated and don't actively transcribe RNAs, we hypothesized that the increased mRNA of HLA-A in platelets initiated within megakaryocytes. To mimic the acute inflammation in vitro, human CD34+ derived megakaryocytes were treated with either interferon gamma at 250U/mL or LPS that was supplemented with lipid binding protein and CD14 at 100ng/mL for 16 hours. Treatments significantly increased HLA-A RNA expression (IFN-gamma 443±163% and LPS 161±41% as compared to untreated, N=5, P<0.01,) and cell surface MHC class I protein expression (MFI: IFN-gamma 220±60% and LPS 155±28% as compared to untreated, N=6, P<0.01).To examine whether sepsis directly induced MHC class I in mice, we used a murine sepsis model induced by cecal ligation and puncture (CLP). CLP induced approximately 40% mortality and a 50% decrease of platelet count. Deep sequencing of ribosome protected RNAs from control and CLP mice platelets showed a 6 fold increase in murine MHC class I expression in platelets (H2D and H2K) after CLP, (RPR counts: H-2D 36±29, 227±103; H-2K 2.5±1.3 vs 16±2.6; N=3). H2D protein increased on the platelet surface by 1.5 fold 48 h after CLP. This was associated with a significantly decreased CD8+ T cell population in the spleen.Activated platelets have been shown able to prime CD8+ T cells through MHC class I. To measure antigen cross-presentation by MHC class I, isolated platelets from CLP or sham control mice were pulsed with ovalbumin at 0.5mg/mL for 2 hours, and antigen cross-presentation was detected by an antibody specifically targeting the ovalbumin peptide SIINFEKL presented by H-2K using flow cytometry. Our studies indicated antigen cross-presentation by platelets significantly increased in the CLP group (MFI: Sham 21±2, CLP 42±24, N=3-8, P<0.05) compared to controls.Together, our studies demonstrate dynamic regulation of MHC class I on platelets. Expression of MHC class I mRNAs and active translation increase during sepsis in both human and mouse platelets. Furthermore, antigen cross-presentation by platelet MHC class I could be upregulated in sepsis and its effect on CD8+ T cell responses is under investigation. DisclosuresNo relevant conflicts of interest to declare.

A tool for analyzing and visualizing ribo-seq data at the isoform level

BackgroundTranslational regulation is one important aspect of gene expression regulation. Dysregulation of translation results in abnormal cell physiology and leads to diseases. Ribosome profiling (RP), also called ribo-seq, is a powerful experimental technique to study translational regulation. It can capture a snapshot of translation by deep sequencing of ribosome-protected mRNA fragments. Many ribosome profiling data processing tools have been developed. However, almost all tools analyze ribosome profiling data at the gene level. Since different isoforms of a gene may produce different proteins with distinct biological functions, it is advantageous to analyze ribosome profiling data at the isoform level. To meet this need, previously we developed a pipeline to analyze 610 public human ribosome profiling data at the isoform level and constructed HRPDviewer database.ResultsTo allow other researchers to use our pipeline as well, here we implement our pipeline as an easy-to-use software tool called RPiso. Compared to Ribomap (a widely used tool which provides isoform-level ribosome profiling analyses), our RPiso (1) estimates isoform abundance more accurately, (2) supports analyses on more species, and (3) provides a web-based viewer for interactively visualizing ribosome profiling data on the selected mRNA isoforms.ConclusionsIn this study, we developed RPiso software tool (http://cosbi7.ee.ncku.edu.tw/RPiso/) to provide isoform-level ribosome profiling analyses. RPiso is very easy to install and execute. RPiso also provides a web-based viewer for interactively visualizing ribosome profiling data on the selected mRNA isoforms. We believe that RPiso is a useful tool for researchers to analyze and visualize their own ribosome profiling data at the isoform level.

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.

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

BackgroundTranslation 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.ResultsWe 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.ConclusionsThe 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.

Ribosome profiling at isoform level reveals evolutionary conserved impacts of differential splicing on the proteome

The differential production of transcript isoforms from gene loci is a key cellular mechanism. Yet, its impact in protein production remains an open question. Here, we describe ORQAS (ORF quantification pipeline for alternative splicing), a pipeline for the translation quantification of individual transcript isoforms using ribosome-protected mRNA fragments (ribosome profiling). We find evidence of translation for 40–50% of the expressed isoforms in human and mouse, with 53% of the expressed genes having more than one translated isoform in human, and 33% in mouse. Differential splicing analysis revealed that about 40% of the splicing changes at RNA level are concordant with changes in translation. Furthermore, orthologous cassette exons between human and mouse preserve the directionality of the change, and are enriched in microexons in a comparison between glia and glioma. ORQAS leverages ribosome profiling to uncover a widespread and evolutionarily conserved impact of differential splicing on translation, particularly of microexon-containing isoforms.

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

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

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.

Monitoring Cell-Type-Specific Gene Expression Using Ribosome Profiling In Vivo During Cardiac Hemodynamic Stress.

Gene expression profiles have been mainly determined by analysis of transcript abundance. However, these analyses cannot capture posttranscriptional gene expression control at the level of translation, which is a key step in the regulation of gene expression, as evidenced by the fact that transcript levels often poorly correlate with protein levels. Furthermore, genome-wide transcript profiling of distinct cell types is challenging due to the fact that lysates from tissues always represent a mixture of cells. This study aimed to develop a new experimental method that overcomes both limitations and to apply this method to perform a genome-wide analysis of gene expression on the translational level in response to pressure overload. By combining ribosome profiling (Ribo-seq) with a ribosome-tagging approach (Ribo-tag), it was possible to determine the translated transcriptome in specific cell types from the heart. After pressure overload, we monitored the cardiac myocyte translatome by purifying tagged cardiac myocyte ribosomes from cardiac lysates and subjecting the ribosome-protected mRNA fragments to deep sequencing. We identified subsets of mRNAs that are regulated at the translational level and found that translational control determines early changes in gene expression in response to cardiac stress in cardiac myocytes. Translationally controlled transcripts are associated with specific biological processes related to translation, protein quality control, and metabolism. Mechanistically, Ribo-seq allowed for the identification of upstream open reading frames in transcripts, which we predict to be important regulators of translation. This method has the potential to (1) provide a new tool for studying cell-specific gene expression at the level of translation in tissues, (2) reveal new therapeutic targets to prevent cellular remodeling, and (3) trigger follow-up studies that address both, the molecular mechanisms involved in the posttranscriptional control of gene expression in cardiac cells, and the protective functions of proteins expressed in response to cellular stress.

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.

Ribosome profiling as an innovative tool to study the process of protein synthesis

The ribosome profiling approach (Ribo-seq) is currently the most effective method to study the protein synthesis in vivo. This technique relies on sequencing of ribosome protected mRNA fragments (so-called ribosomal footprints) allowing to indicate the exact positions of ribosomes on transcripts. Advanced bioinformatic analysis of Ribo-seq data enables selection of ribosomal footprints originated from translating ribosomes, providing information about authentic translational status of mRNA. Here, authors present principles of ribosome profiling method with special attention to basic experimental and bioinformatics strategies important for obtaining satisfactory results. Review includes examples of applications of ribosome profiling technique in various biological systems, giving the significant insight into the translation process and its regulation.

High-Resolution Ribosome Profiling Defines Discrete Ribosome Elongation States and Translational Regulation during Cellular Stress

Ribosomes undergo substantial conformational changes during translation elongation to accommodate incoming aminoacyl-tRNAs and translocate along the mRNA template. We used multiple elongation inhibitors and chemical probing to define ribosome conformational states corresponding to differently sized ribosome-protected mRNA fragments (RPFs) generated by ribosome profiling. We show, using various genetic and environmental perturbations, that short 20-22 or classical 27-29 nucleotide RPFs correspond to ribosomes with open or occupied ribosomal A sites, respectively. These distinct states of translation elongation are readily discerned by ribosome profiling in all eukaryotes we tested, including fungi, worms, and mammals. This high-resolution ribosome profiling approach reveals mechanisms of translation-elongation arrest during distinct stress conditions. Hyperosmotic stress inhibits translocation through Rck2-dependent eEF2 phosphorylation, whereas oxidative stress traps ribosomes in a pre-translocation state, independent of Rck2-driven eEF2 phosphorylation. These results provide insights and approaches for defining the molecular events that impact translation elongation throughout biology.

Ribosome Profiling of Vaccinia Virus-Infected Cells.

Ribosome profiling is a method that determines genome-wide mRNA translation through measuring ribosome-protected mRNA fragments by deep sequencing. This method can be used to quantify gene expression at the translational level and precisely pinpoint ribosome loading onto mRNA with codon-level resolution. Genome-wide regulation of mRNA translation can also be determined if RNA-Sequencing (RNA-Seq) is carried out in parallel. Here, we describe a protocol for simultaneously performing ribosome profiling and RNA-Seq in cells infected with vaccinia virus.