Genome-wide identification and differential analysis of translational initiation

Thousands of human non-AUG extended proteoforms lack evidence of evolutionary selection among mammals

The synthesis of most proteins begins at AUG codons, yet a small number of non-AUG initiated proteoforms are also known. Here we analyse a large number of publicly available Ribo-seq datasets to identify novel, previously uncharacterised non-AUG proteoforms using Trips-Viz implementation of a novel algorithm for detecting translated ORFs. In parallel we analyse genomic alignment of 120 mammals to identify evidence of protein coding evolution in sequences encoding potential extensions. Unexpectedly we find that the number of non-AUG proteoforms identified with ribosome profiling data greatly exceeds those with strong phylogenetic support suggesting their recent evolution. Our study argues that the protein coding potential of human genome greatly exceeds that detectable through comparative genomics and exposes the existence of multiple proteins encoded by the same genomic loci.

An Optimized Proteomics Approach Reveals Novel Alternative Proteins in Mouse Liver Development

Alternative ORFs (AltORFs) are unannotated sequences in genome that encode novel peptides or proteins named alternative proteins (AltProts). Although ribosome profiling and bioinformatics predict a large number of AltProts, mass spectrometry as the only direct way of identification is hampered by the short lengths and relative low abundance of AltProts. There is an urgent need for improvement of mass spectrometry methodologies for AltProt identification. Here, we report an approach based on size-exclusion chromatography for simultaneous enrichment and fractionation of AltProts from complex proteome. This method greatly simplifies the variance of AltProts discovery by enriching small proteins smaller than 40 kDa. In a systematic comparison between 10 methods, the approach we reported enabled the discovery of more AltProts with overall higher intensities, with less cost of time and effort compared to other workflows. We applied this approach to identify 89 novel AltProts from mouse liver, 39 of which were differentially expressed between embryonic and adult mice. During embryonic development, the upregulated AltProts were mainly involved in biological pathways on RNA splicing and processing, whereas the AltProts involved in metabolisms were more active in adult livers. Our study not only provides an effective approach for identifying AltProts but also novel AltProts that are potentially important in developmental biology.

Integrative analysis of macrophage ribo-Seq and RNA-Seq data define glucocorticoid receptor regulated inflammatory response genes into distinct regulatory classes

Glucocorticoids such as dexamethasone (Dex) are widely used to treat both acute and chronic inflammatory conditions. They regulate immune responses by dampening cell-mediated immunity in a glucocorticoid receptor (GR)-dependent manner, by suppressing the expression of pro-inflammatory cytokines and chemokines and by stimulating the expression of anti-inflammatory mediators. Despite its evident clinical benefit, the mechanistic underpinnings of the gene regulatory networks transcriptionally controlled by GR in a context-specific manner remain mysterious. Next generation sequencing methods such mRNA sequencing (RNA-seq) and Ribosome profiling (ribo-seq) provide tools to investigate the transcriptional and post-transcriptional mechanisms that govern gene expression. Here, we integrate matched RNA-seq data with ribo-seq data from human acute monocytic leukemia (THP-1) cells treated with the TLR4 ligand lipopolysaccharide (LPS) and with Dex, to investigate the global transcriptional and translational regulation (translational efficiency, ΔTE) of Dex-responsive genes. We find that the expression of most of the Dex-responsive genes are regulated at both the transcriptional and the post-transcriptional level, with the transcriptional changes intensified on the translational level. Overrepresentation pathway analysis combined with STRING protein network analysis and manual functional exploration, identified these genes to encode immune effectors and immunomodulators that contribute to macrophage-mediated immunity and to the maintenance of macrophage-mediated immune homeostasis. Further research into the translational regulatory network underlying the GR anti-inflammatory response could pave the way for the development of novel immunomodulatory therapeutic regimens with fewer undesirable side effects.

Developmental dynamics of RNA translation in the human brain

The precise regulation of gene expression is fundamental to neurodevelopment, plasticity and cognitive function. Although several studies have profiled transcription in the developing human brain, there is a gap in understanding of accompanying translational regulation. In this study, we performed ribosome profiling on 73 human prenatal and adult cortex samples. We characterized the translational regulation of annotated open reading frames (ORFs) and identified thousands of previously unknown translation events, including small ORFs that give rise to human-specific and/or brain-specific microproteins, many of which we independently verified using proteomics. Ribosome profiling in stem-cell-derived human neuronal cultures corroborated these findings and revealed that several neuronal activity-induced non-coding RNAs encode previously undescribed microproteins. Physicochemical analysis of brain microproteins identified a class of proteins that contain arginine-glycine-glycine (RGG) repeats and, thus, may be regulators of RNA metabolism. This resource expands the known translational landscape of the human brain and illuminates previously unknown brain-specific protein products.

A high-resolution map of human RNA translation

Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome.

The Translational Landscape of SARS-CoV-2-infected Cells Reveals Suppression of Innate Immune Genes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes a number of strategies to modulate viral and host mRNA translation. Here, we used ribosome profiling in SARS-CoV-2-infected model cell lines and primary airway cells grown at an air-liquid interface to gain a deeper understanding of the translationally regulated events in response to virus replication. We found that SARS-CoV-2 mRNAs dominate the cellular mRNA pool but are not more efficiently translated than cellular mRNAs. SARS-CoV-2 utilized a highly efficient ribosomal frameshifting strategy despite notable accumulation of ribosomes within the slippery sequence on the frameshifting element. In a highly permissive cell line model, although SARS-CoV-2 infection induced the transcriptional upregulation of numerous chemokine, cytokine, and interferon-stimulated genes, many of these mRNAs were not translated efficiently. The impact of SARS-CoV-2 on host mRNA translation was more subtle in primary cells, with marked transcriptional and translational upregulation of inflammatory and innate immune responses and downregulation of processes involved in ciliated cell function. Together, these data reveal the key role of mRNA translation in SARS-CoV-2 replication and highlight unique mechanisms for therapeutic development. IMPORTANCE SARS-CoV-2 utilizes a number of strategies to modulate host responses to ensure efficient propagation. Here, we used ribosome profiling in SARS-CoV-2-infected cells to gain a deeper understanding of the translationally regulated events in infected cells. We found that although viral mRNAs are abundantly expressed, they are not more efficiently translated than cellular mRNAs. SARS-CoV-2 utilized a highly efficient ribosomal frameshifting strategy and alternative translation initiation sites that help increase the coding potential of its RNAs. In permissive cells, SARS-CoV-2 infection induced the translational repression of numerous innate immune mediators. Though the impact of SARS-CoV-2 on host mRNA translation was more subtle in primary airway cell cultures, we noted marked transcriptional and translational upregulation of inflammatory and innate immune responses and downregulation of processes involved in ciliated cell function. Together, these data provide new insight into how SARS-CoV-2 modulates innate host responses and highlight unique mechanisms for therapeutic intervention.

Direct epitranscriptomic regulation of mammalian translation initiation through N4-acetylcytidine

mRNA function is influenced by modifications that modulate canonical nucleobase behavior. We show that a single modification mediates distinct impacts on mRNA translation in a position-dependent manner. Although cytidine acetylation (ac4C) within protein-coding sequences stimulates translation, ac4C within 5' UTRs impacts protein synthesis at the level of initiation. 5' UTR acetylation promotes initiation at upstream sequences, competitively inhibiting annotated start codons. Acetylation further directly impedes initiation at optimal AUG contexts: ac4C within AUG-flanking Kozak sequences reduced initiation in base-resolved transcriptome-wide HeLa results and in vitro utilizing substrates with site-specific ac4C incorporation. Cryo-EM of mammalian 80S initiation complexes revealed that ac4C in the -1 position adjacent to an AUG start codon disrupts an interaction between C and hypermodified t6A at nucleotide 37 of the initiator tRNA. These findings demonstrate the impact of RNA modifications on nucleobase function at a molecular level and introduce mRNA acetylation as a factor regulating translation in a location-specific manner.

Ultrasensitive Ribo-seq reveals translational landscapes during mammalian oocyte-to-embryo transition and pre-implantation development

In mammals, translational control plays critical roles during oocyte-to-embryo transition (OET) when transcription ceases. However, the underlying regulatory mechanisms remain challenging to study. Here, using low-input Ribo-seq (Ribo-lite), we investigated translational landscapes during OET using 30-150 mouse oocytes or embryos per stage. Ribo-lite can also accommodate single oocytes. Combining PAIso-seq to interrogate poly(A) tail lengths, we found a global switch of translatome that closely parallels changes of poly(A) tails upon meiotic resumption. Translation activation correlates with polyadenylation and is supported by polyadenylation signal proximal cytoplasmic polyadenylation elements (papCPEs) in 3' untranslated regions. By contrast, translation repression parallels global de-adenylation. The latter includes transcripts containing no CPEs or non-papCPEs, which encode many transcription regulators that are preferentially re-activated before zygotic genome activation. CCR4-NOT, the major de-adenylation complex, and its key adaptor protein BTG4 regulate translation downregulation often independent of RNA decay. BTG4 is not essential for global de-adenylation but is required for selective gene de-adenylation and production of very short-tailed transcripts. In sum, our data reveal intimate interplays among translation, RNA stability and poly(A) tail length regulation underlying mammalian OET.

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.

Proteomic-driven identification of short open reading frame-encoded peptides

Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods. This article is protected by copyright. All rights reserved.

RiboReport - benchmarking tools for ribosome profiling-based identification of open reading frames in bacteria

Small proteins encoded by short open reading frames (ORFs) with 50 codons or fewer are emerging as an important class of cellular macromolecules in diverse organisms. However, they often evade detection by proteomics or in silico methods. Ribosome profiling (Ribo-seq) has revealed widespread translation in genomic regions previously thought to be non-coding, driving the development of ORF detection tools using Ribo-seq data. However, only a handful of tools have been designed for bacteria, and these have not yet been systematically compared. Here, we aimed to identify tools that use Ribo-seq data to correctly determine the translational status of annotated bacterial ORFs and also discover novel translated regions with high sensitivity. To this end, we generated a large set of annotated ORFs from four diverse bacterial organisms, manually labeled for their translation status based on Ribo-seq data, which are available for future benchmarking studies. This set was used to investigate the predictive performance of seven Ribo-seq-based ORF detection tools (REPARATION_blast, DeepRibo, Ribo-TISH, PRICE, smORFer, ribotricer and SPECtre), as well as IRSOM, which uses coding potential and RNA-seq coverage only. DeepRibo and REPARATION_blast robustly predicted translated ORFs, including sORFs, with no significant difference for ORFs in close proximity to other genes versus stand-alone genes. However, no tool predicted a set of novel, experimentally verified sORFs with high sensitivity. Start codon predictions with smORFer show the value of initiation site profiling data to further improve the sensitivity of ORF prediction tools in bacteria. Overall, we find that bacterial tools perform well for sORF detection, although there is potential for improving their performance, applicability, usability and reproducibility.

Deficiency of ribosomal proteins reshapes the transcriptional and translational landscape in human cells

Human ribosomes have long been thought to be uniform factories with little regulatory function. Accumulating evidence emphasizes the heterogeneity of ribosomal protein (RP) expression in specific cellular functions and development. However, a systematic understanding of functional relevance of RPs is lacking. Here, we surveyed translational and transcriptional changes after individual knockdown of 75 RPs, 44 from the large subunit (60S) and 31 from the small subunit (40S), by Ribo-seq and RNA-seq analyses. Deficiency of individual RPs altered specific subsets of genes transcriptionally and translationally. RP genes were under cotranslational regulation upon ribosomal stress, and deficiency of the 60S RPs and the 40S RPs had opposite effects. RP deficiency altered the expression of genes related to eight major functional classes, including the cell cycle, cellular metabolism, signal transduction and development. 60S RP deficiency led to greater inhibitory effects on cell growth than did 40S RP deficiency, through P53 signaling. Particularly, we showed that eS8/RPS8 deficiency stimulated apoptosis while eL13/RPL13 or eL18/RPL18 deficiency promoted senescence. We also validated the phenotypic impacts of uL5/RPL11 and eL15/RPL15 deficiency on retina development and angiogenesis, respectively. Overall, our study provides a valuable resource for and novel insights into ribosome regulation in cellular activities, development and diseases.

Ribosome profiling reveals novel regulation of C9ORF72 GGGGCC repeat-containing RNA translation

GGGGCC (G₄C₂) repeat expansion in the first intron of C9ORF72 causes amyotrophic lateral sclerosis and frontotemporal dementia. Repeat-containing RNA is translated into dipeptide repeat (DPR) proteins, some of which are neurotoxic. Using dynamic ribosome profiling, we identified three translation initiation sites in the intron upstream of (G₄C₂) repeats; these sites are detected irrespective of the presence or absence of the repeats. During translocation, ribosomes appear to be stalled on the repeats. An AUG in the preceding C9ORF72 exon initiates a uORF that inhibits downstream translation. Polysome isolation indicates that unspliced (G₄C₂) repeat-containing RNA is a substrate for DPR protein synthesis. (G₄C₂) repeat-containing RNA translation is 5' cap-independent but inhibited by the initiation factor DAP5, suggesting an interplay with uORF function. These results define novel translational mechanisms of expanded (G₄C₂) repeat-containing RNA in disease.

Green plant genomes: What we know in an era of rapidly expanding opportunities

Green plants play a fundamental role in ecosystems, human health, and agriculture. As de novo genomes are being generated for all known eukaryotic species as advocated by the Earth BioGenome Project, increasing genomic information on green land plants is essential. However, setting standards for the generation and storage of the complex set of genomes that characterize the green lineage of life is a major challenge for plant scientists. Such standards will need to accommodate the immense variation in green plant genome size, transposable element content, and structural complexity while enabling research into the molecular and evolutionary processes that have resulted in this enormous genomic variation. Here we provide an overview and assessment of the current state of knowledge of green plant genomes. To date fewer than 300 complete chromosome-scale genome assemblies representing fewer than 900 species have been generated across the estimated 450,000 to 500,000 species in the green plant clade. These genomes range in size from 12 Mb to 27.6 Gb and are biased toward agricultural crops with large branches of the green tree of life untouched by genomic-scale sequencing. Locating suitable tissue samples of most species of plants, especially those taxa from extreme environments, remains one of the biggest hurdles to increasing our genomic inventory. Furthermore, the annotation of plant genomes is at present undergoing intensive improvement. It is our hope that this fresh overview will help in the development of genomic quality standards for a cohesive and meaningful synthesis of green plant genomes as we scale up for the future.

RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data

The increasing volume of ribosome profiling (Ribo-seq) data, computational complexity of its data processing and operational handicap of related analytical procedures present a daunting set of informatics challenges. These impose a substantial barrier to researchers particularly with no or limited bioinformatics expertise in analyzing and decoding translation information from Ribo-seq data, thus driving the need for a new research paradigm for data computation and information extraction. In this knowledge base, we herein present a novel interactive web platform, RiboChat (https://db.cngb.org/ribobench/chat.html), for direct analyzing and annotating Ribo-seq data in the form of a chat conversation. It consists of a user-friendly web interface and a backend cloud-computing service. When typing a data analysis question into the chat window, the object-text detection module will be run to recognize relevant keywords from the input text. Based on the features identified in the input, individual analytics modules are then scored to find the perfect-matching candidate. The corresponding analytics module will be further executed after checking the completion status of the uploading of datasets and configured parameters. Overall, RiboChat represents an important step forward in the emerging direction of next-generation data analytics and will enable the broad research community to conveniently decipher translation information embedded within Ribo-seq data.

A Novel Assessment Model Based on Molecular Subtypes of Hypoxia-Related LncRNAs for Prognosis of Bladder Cancer

Hypoxia is a common feature in various tumors that regulates aggressiveness. Previous studies have demonstrated that some dysregulated long non-coding RNAs (lncRNAs) are correlated with tumor progression, including bladder cancer (BCa). However, the prognostic effect of hypoxia-related lncRNAs (HRLs) and their clinical relevance, as well as their regulatory effect on the tumor immune microenvironment, are largely unknown in BCa. A co-expression analysis between hypoxia genes and lncRNA expression, which was downloaded from the TCGA database, was performed to identify HRLs. Univariate Cox regression analysis was performed to select the most desirable lncRNAs for molecular subtype, and further LASSO analysis was performed to develop a prognostic model. This molecular subtype based on four HRLs (AC104653, AL136084, AL139393, and LINC00892) showed good performance in the tumor microenvironment and tumor mutation burden. The prognostic risk model suggested better performance in predicting BCa patients' prognosis and obtained a close correlation with clinicopathologic features. Furthermore, four of five first-line clinical chemotherapies showed different sensitivities to this model, and nine immune checkpoints showed different expression in the molecular subtypes or the risk model. In conclusion, this study indicates that this molecular subtype and risk model based on HRLs may be useful in improving the prognostic prediction of BCa patients with different clinical situations and may help to find a useful target for tumor therapy.

The Small Open Reading Frame-Encoded Peptides: Advances in Methodologies and Functional Studies

Small open reading frames (sORFs) are an important class of genes with less than 100 codons. They were historically annotated as noncoding or even junk sequences. In recent years, accumulating evidence suggests that sORFs could encode a considerable number of polypeptides, many of which play important roles in both physiology and disease pathology. However, it has been technically challenging to directly detect sORF-encoded peptides (SEPs). Here, we discuss the latest advances in methodologies for identifying SEPs with mass spectrometry, as well as the progress on functional studies of SEPs.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

The translational landscape of SARS-CoV-2 and infected cells

SARS-CoV-2 utilizes a number of strategies to modulate viral and host mRNA translation. Here, we used ribosome profiling in SARS-CoV-2 infected model cell lines and primary airway cells grown at the air-liquid interface to gain a deeper understanding of the translationally regulated events in response to virus replication. We find that SARS-CoV-2 mRNAs dominate the cellular mRNA pool but are not more efficiently translated than cellular mRNAs. SARS-CoV-2 utilized a highly efficient ribosomal frameshifting strategy in comparison to HIV-1, suggesting utilization of distinct structural elements. In the highly permissive cell models, although SARS-CoV-2 infection induced the transcriptional upregulation of numerous chemokines, cytokines and interferon stimulated genes, many of these mRNAs were not translated efficiently. Impact of SARS-CoV-2 on host mRNA translation was more subtle in primary cells, with marked transcriptional and translational upregulation of inflammatory and innate immune responses and downregulation of processes involved in ciliated cell function. Together, these data reveal the key role of mRNA translation in SARS-CoV-2 replication and highlight unique mechanisms for therapeutic development.

Widespread translational control regulates retinal development in mouse

Retinal development is tightly regulated to ensure the generation of appropriate cell types and the assembly of functional neuronal circuitry. Despite remarkable advances have been made in understanding regulation of gene expression during retinal development, how translational regulation guides retinogenesis is less understood. Here, we conduct a comprehensive translatome and transcriptome survey to the mouse retinogenesis from the embryonic to the adult stages. We discover thousands of genes that have dynamic changes at the translational level and pervasive translational regulation in a developmental stage-specific manner with specific biological functions. We further identify genes whose translational efficiencies are frequently controlled by changing usage in upstream open reading frame during retinal development. These genes are enriched for biological functions highly important to neurons, such as neuron projection organization and microtubule-based protein transport. Surprisingly, we discover hundreds of previously uncharacterized micropeptides, translated from putative long non-coding RNAs and circular RNAs. We validate their protein products in vitro and in vivo and demonstrate their potentials in regulating retinal development. Together, our study presents a rich and complex landscape of translational regulation and provides novel insights into their roles during retinogenesis.

SmProt: A Reliable Repository with Comprehensive Annotation of Small Proteins Identified from Ribosome Profiling

Small proteins specifically refer to proteins consisting of less than 100 amino acids translated from small open reading frames (sORFs), which were usually missed in previous genome annotation. The significance of small proteins has been revealed in current years, along with the discovery of their diverse functions. However, systematic annotation of small proteins is still insufficient. SmProt was specially developed to provide valuable information on small proteins for scientific community. Here we present the update of SmProt, which emphasizes reliability of translated sORFs, genetic variants in translated sORFs, disease-specific sORF translation events or sequences, and remarkably increased data volume. More components such as non-ATG translation initiation, function, and new sources are also included. SmProt incorporated 638,958 unique small proteins curated from 3,165,229 primary records, which were computationally predicted from 419 ribosome profiling (Ribo-seq) datasets or collected from literature and other sources from 370 cell lines or tissues in 8 species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Saccharomyces cerevisiae, Caenorhabditis elegans, and Escherichia coli). In addition, small protein families identified from human microbiomes were also collected. All datasets in SmProt are free to access, and available for browse, search, and bulk downloads at http://bigdata.ibp.ac.cn/SmProt/.

Exploring Evidence of Non-coding RNA Translation With Trips-Viz and GWIPS-Viz Browsers

Detection of translation in so-called non-coding RNA provides an opportunity for identification of novel bioactive peptides and microproteins. The main methods used for these purposes are ribosome profiling and mass spectrometry. A number of publicly available datasets already exist for a substantial number of different cell types grown under various conditions, and public data mining is an attractive strategy for identification of translation in non-coding RNAs. Since the analysis of publicly available data requires intensive data processing, several data resources have been created recently for exploring processed publicly available data, such as OpenProt, GWIPS-viz, and Trips-Viz. In this work we provide a detailed demonstration of how to use the latter two tools for exploring experimental evidence for translation of RNAs hitherto classified as non-coding. For this purpose, we use a set of transcripts with substantially different patterns of ribosome footprint distributions. We discuss how certain features of these patterns can be used as evidence for or against genuine translation. During our analysis we concluded that the MTLN mRNA, previously misannotated as lncRNA LINC00116, likely encodes only a short proteoform expressed from shorter RNA transcript variants.

Long intragenic non-coding RNA p53-induced transcript (LINC-PINT) as a novel prognosis indicator and therapeutic target in cancer

Cancer involves complex etiology factors, multiple stages, and intricate gene mutations. Long non-coding RNAs (lncRNAs) are implicated as molecular mechanisms underlying human genomic activity in various physiologic and pathophysiologic conditions. However, the sophisticated modifications and regulatory processes linking lncRNAs to cancer initiation and progression have not yet been fully explored. Long intragenic non-coding RNA p53-induced transcript (LINC-PINT) is an lncRNA that functions as a tumor suppressor gene involved in various tumors and malignant activities. LINC-PINT is downregulated in nasopharyngeal cancer, renal carcinoma, non-small cell lung cancer, glioblastoma, thyroid cancer, retinoblastoma, ovarian cancer, breast cancer, esophageal squamous cell carcinoma, osteosarcoma, melanoma, and gastric cancer. Furthermore, decreased LINC-PINT expression predicts poor prognosis and advanced clinical tumor stages. Together, these studies indicate that LINC-PINT could serve as a diagnostic and prognostic indicator in cancer. The specific lncRNA regulatory mechanism of LINC-PINT may also be a novel target for cancer therapies.

An Integrated Approach for Discovering Noncanonical MHC-I Peptides Encoded by Small Open Reading Frames

MHC-I peptides are a group of important immunopeptides presented by major histocompatibility complex (MHC) on the cell surface for immune recognition. The majority of reported MHC-I peptides are derived from protein coding sequences, and noncanonical peptides translated from small open reading frames (sORF) are largely unknown due to the lack of accurate and sensitive detection methods. Herein we report an efficient approach that implements complementary bioinformatic strategies to improve the identification of noncanonical MHC-I peptides. In a database search strategy, noncanonical immunopeptides mapping was optimized by combining three complementary pipelines to construct predicted sORF databases from Ribo-seq data. In a de novo peptide sequencing strategy, MS data search results were filtered against sORF databases to pin down additional noncanonical immunopeptides. In total, 308 noncanonical immunopeptides were identified from two tumor cell lines with selected ones vigorously validated. Our approach is a handy solution to identify noncanonical MHC peptides with Ribo-seq and MS data. Meanwhile, the novel noncanonical immunopeptides identified with this method could shed insights on fundamental immunology as well as cancer immunotherapies.

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.

Systematic functional interrogation of human pseudogenes using CRISPRi

BACKGROUND

The human genome encodes over 14,000 pseudogenes that are evolutionary relics of protein-coding genes and commonly considered as nonfunctional. Emerging evidence suggests that some pseudogenes may exert important functions. However, to what extent human pseudogenes are functionally relevant remains unclear. There has been no large-scale characterization of pseudogene function because of technical challenges, including high sequence similarity between pseudogene and parent genes, and poor annotation of transcription start sites.

RESULTS

To overcome these technical obstacles, we develop an integrated computational pipeline to design the first genome-wide library of CRISPR interference (CRISPRi) single-guide RNAs (sgRNAs) that target human pseudogene promoter-proximal regions. We perform the first pseudogene-focused CRISPRi screen in luminal A breast cancer cells and reveal approximately 70 pseudogenes that affect breast cancer cell fitness. Among the top hits, we identify a cancer-testis unitary pseudogene, MGAT4EP, that is predominantly localized in the nucleus and interacts with FOXA1, a key regulator in luminal A breast cancer. By enhancing the promoter binding of FOXA1, MGAT4EP upregulates the expression of oncogenic transcription factor FOXM1. Integrative analyses of multi-omic data from the Cancer Genome Atlas (TCGA) reveal many unitary pseudogenes whose expressions are significantly dysregulated and/or associated with overall/relapse-free survival of patients in diverse cancer types.

CONCLUSIONS

Our study represents the first large-scale study characterizing pseudogene function. Our findings suggest the importance of nuclear function of unitary pseudogenes and underscore their underappreciated roles in human diseases. The functional genomic resources developed here will greatly facilitate the study of human pseudogene function.

Combinatorial analysis of translation dynamics reveals eIF2 dependence of translation initiation at near-cognate codons

Although ribosome-profiling and translation initiation sequencing (TI-seq) analyses have identified many noncanonical initiation codons, the precise detection of translation initiation sites (TISs) remains a challenge, mainly because of experimental artifacts of such analyses. Here, we describe a new method, TISCA (TIS detection by translation Complex Analysis), for the accurate identification of TISs. TISCA proved to be more reliable for TIS detection compared with existing tools, and it identified a substantial number of near-cognate codons in Kozak-like sequence contexts. Analysis of proteomics data revealed the presence of methionine at the NH₂-terminus of most proteins derived from near-cognate initiation codons. Although eukaryotic initiation factor 2 (eIF2), eIF2A and eIF2D have previously been shown to contribute to translation initiation at near-cognate codons, we found that most noncanonical initiation events are most probably dependent on eIF2, consistent with the initial amino acid being methionine. Comprehensive identification of TISs by TISCA should facilitate characterization of the mechanism of noncanonical initiation.

HRIBO: high-throughput analysis of bacterial ribosome profiling data

MOTIVATION

Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50-100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs).

RESULTS

We present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization.

AVAILABILITY AND IMPLEMENTATION

HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO.

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.

Robust single-cell discovery of RNA targets of RNA-binding proteins and ribosomes

RNA-binding proteins (RBPs) are critical regulators of gene expression and RNA processing that are required for gene function. Yet the dynamics of RBP regulation in single cells is unknown. To address this gap in understanding, we developed STAMP (Surveying Targets by APOBEC-Mediated Profiling), which efficiently detects RBP-RNA interactions. STAMP does not rely on ultraviolet cross-linking or immunoprecipitation and, when coupled with single-cell capture, can identify RBP-specific and cell-type-specific RNA-protein interactions for multiple RBPs and cell types in single, pooled experiments. Pairing STAMP with long-read sequencing yields RBP target sites in an isoform-specific manner. Finally, Ribo-STAMP leverages small ribosomal subunits to measure transcriptome-wide ribosome association in single cells. STAMP enables the study of RBP-RNA interactomes and translational landscapes with unprecedented cellular resolution.

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.

RNA Dysregulation: An Expanding Source of Cancer Immunotherapy Targets

Cancer transcriptomes frequently exhibit RNA dysregulation. As the resulting aberrant transcripts may be translated into cancer-specific proteins, there is growing interest in exploiting RNA dysregulation as a source of tumor antigens (TAs) and thus novel immunotherapy targets. Recent advances in high-throughput technologies and rapid accumulation of multiomic cancer profiling data in public repositories have provided opportunities to systematically characterize RNA dysregulation in cancer and identify antigen targets for immunotherapy. However, given the complexity of cancer transcriptomes and proteomes, important conceptual and technological challenges exist. Here, we highlight the expanding repertoire of TAs arising from RNA dysregulation and introduce multiomic and big data strategies for identifying optimal immunotherapy targets. We discuss extant barriers for translating these targets into effective therapies as well as the implications for future research.

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.

Revisiting sORFs: overcoming challenges to identify and characterize functional microproteins

Short ORFs (sORFs), that is, occurrences of a start and stop codon within 100 codons or less, can be found in organisms of all domains of life, outnumbering annotated protein-coding ORFs by orders of magnitude. Even though functional proteins smaller than 100 amino acids are known, the coding potential of sORFs has often been overlooked, as it is not trivial to predict and test for functionality within the large number of sORFs. Recent advances in ribosome profiling and mass spectrometry approaches, together with refined bioinformatic predictions, have enabled a huge leap forward in this field and identified thousands of likely coding sORFs. A relatively low number of small proteins or microproteins produced from these sORFs have been characterized so far on the molecular, structural, and/or mechanistic level. These however display versatile and, in some cases, essential cellular functions, allowing for the exciting possibility that many more, previously unknown small proteins might be encoded in the genome, waiting to be discovered. This review will give an overview of the steadily growing microprotein field, focusing on eukaryotic small proteins. We will discuss emerging themes in the molecular action of microproteins, as well as advances and challenges in microprotein identification and characterization.

Translation elongation rate varies among organs and decreases with age

There has been a surge of interest towards targeting protein synthesis to treat diseases and extend lifespan. Despite the progress, few options are available to assess translation in live animals, as their complexity limits the repertoire of experimental tools to monitor and manipulate processes within organs and individual cells. It this study, we developed a labeling-free method for measuring organ- and cell-type-specific translation elongation rates in vivo. It is based on time-resolved delivery of translation initiation and elongation inhibitors in live animals followed by ribosome profiling. It also reports translation initiation sites in an organ-specific manner. Using this method, we found that the elongation rates differ more than 50% among mouse organs and determined them to be 6.8, 5.0 and 4.3 amino acids per second for liver, kidney, and skeletal muscle, respectively. We further found that the elongation rate is reduced by 20% between young adulthood and mid-life. Thus, translation, a major metabolic process in cells, is tightly regulated at the level of elongation of nascent polypeptide chains.

Global sequence features based translation initiation site prediction in human genomic sequences

Gene prediction has been increasingly important in genome annotation due to advancements in sequencing technology. Genome annotation further helps in determining the structure and function of these genes. Translation initiation site prediction (TIS) in human genomic sequences is one of the fundamental and essential steps in gene prediction. Thus, accurate prediction of TIS in these sequences is highly desirable. Although many computational methods were developed for this problem, none of them focused on finding these sites in human genomic sequences. In this paper, a new TIS prediction method is proposed by incorporating global sequence based features. Support vector machine is used to assess the prediction power of these features. The proposed method achieved accuracy of above 90% when tested for genomic as well as cDNA sequences. The experimental results indicate that the method works well for both genomic and cDNA sequences. The method can be integrated into gene prediction system in future.

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

Background

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

Results

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

Conclusions

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

Computational methods for ribosome profiling data analysis

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

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

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

RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data

Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers the user an HTML page to scan own data regarding the following aspects: periodicity, ligation and digestion of footprints; reproducibility and batch effects of replicates; drug-related artifacts; unbiased codon enrichment including variability between mRNAs, for A, P and E sites; mining of some causal or confounding factors. We expect our pipeline to allow an optimal use of the wealth of information provided by ribosome profiling experiments.

G-quadruplex located in the 5'UTR of the BAG-1 mRNA affects both its cap-dependent and cap-independent translation through global secondary structure maintenance

The anti-apoptotic BAG-1 protein isoforms are known to be overexpressed in colorectal tumors and are considered to be potential therapeutic targets. The isoforms are derived from alternative translation initiations occuring at four in-frame start codons of a single mRNA transcript. Its 5′UTR also contains an internal ribosome entry site (IRES) regulating the cap-independent translation of the transcript. An RNA G-quadruplex (rG4) is located at the 5′end of the BAG-1 5′UTR, upstream of the known cis-regulatory elements. Herein, we observed that the expression of BAG-1 isoforms is post-transcriptionally regulated in colorectal cancer cells and tumors, and that stabilisation of the rG4 by small molecules ligands reduces the expression of endogenous BAG-1 isoforms. We demonstrated a critical role for the rG4 in the control of both cap-dependent and independent translation of the BAG-1 mRNA in colorectal cancer cells. Additionally, we found an upstream ORF that also represses BAG-1 mRNA translation. The structural probing of the complete 5′UTR showed that the rG4 acts as a steric block which controls the initiation of translation at each start codon of the transcript and also maintains the global 5′UTR secondary structure required for IRES-dependent translation.

Non-canonical translation initiation in yeast generates a cryptic pool of mitochondrial proteins

Utilization of non-AUG alternative translation start sites is most common in bacteria and viruses, but it has been also reported in other organisms. This phenomenon increases proteome complexity by allowing expression of multiple protein isoforms from a single gene. In Saccharomyces cerevisiae, a few described cases concern proteins that are translated from upstream near-cognate start codons as N-terminally extended variants that localize to mitochondria. Using bioinformatics tools, we provide compelling evidence that in yeast the potential for producing alternative protein isoforms by non-AUG translation initiation is much more prevalent than previously anticipated and may apply to as many as a few thousand proteins. Several hundreds of candidates are predicted to gain a mitochondrial targeting signal (MTS), generating an unrecognized pool of mitochondrial proteins. We confirmed mitochondrial localization of a subset of proteins previously not identified as mitochondrial, whose standard forms do not carry an MTS. Our data highlight the potential of non-canonical translation initiation in expanding the capacity of the mitochondrial proteome and possibly also other cellular features.

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

BACKGROUND AND OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

uORF-Tools-Workflow for the determination of translation-regulatory upstream open reading frames

Ribosome profiling (ribo-seq) provides a means to analyze active translation by determining ribosome occupancy in a transcriptome-wide manner. The vast majority of ribosome protected fragments (RPFs) resides within the protein-coding sequence of mRNAs. However, commonly reads are also found within the transcript leader sequence (TLS) (aka 5’ untranslated region) preceding the main open reading frame (ORF), indicating the translation of regulatory upstream ORFs (uORFs). Here, we present a workflow for the identification of translation-regulatory uORFs. Specifically, uORF-Tools uses Ribo-TISH to identify uORFs within a given dataset and generates a uORF annotation file. In addition, a comprehensive human uORF annotation file, based on 35 ribo-seq files, is provided, which can serve as an alternative input file for the workflow. To assess the translation-regulatory activity of the uORFs, stimulus-induced changes in the ratio of the RPFs residing in the main ORFs relative to those found in the associated uORFs are determined. The resulting output file allows for the easy identification of candidate uORFs, which have translation-inhibitory effects on their associated main ORFs. uORF-Tools is available as a free and open Snakemake workflow at https://github.com/Biochemistry1-FFM/uORF-Tools. It is easily installed and all necessary tools are provided in a version-controlled manner, which also ensures lasting usability. uORF-Tools is designed for intuitive use and requires only limited computing times and resources.

Ribosome elongating footprints denoised by wavelet transform comprehensively characterize dynamic cellular translation events

Translation is dynamically regulated during cell development and stress response. In order to detect actively translated open reading frames (ORFs) and dynamic cellular translation events, we have developed a computational method, RiboWave, to process ribosome profiling data. RiboWave utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes and precisely locate their footprint denoted as Periodic Footprint P-site (PF P-site). Such high-resolution footprint is found to capture the full track of actively elongating ribosomes, from which translational landscape can be explicitly characterized. We compare RiboWave with several published methods, like RiboTaper, ORFscore and RibORF, and found that RiboWave outperforms them in both accuracy and usage when defining actively translated ORFs. Moreover, we show that PF P-site derived by RiboWave shows superior performance in characterizing the dynamics and complexity of cellular translatome by accurately estimating the abundance of protein levels, assessing differential translation and identifying dynamic translation frameshift.

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

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

The Circadian Protein Nocturnin Regulates Metabolic Adaptation in Brown Adipose Tissue

Fine-tuning of transcriptional responses can be critical for long-term outcomes in response to an environmental challenge. The circadian protein Nocturnin belongs to a family of proteins that include exonucleases, endonucleases, and phosphatases and is most closely related to the CCR4 family of deadenylases that regulate the cellular transcriptome via control of poly(A) tail length of RNA transcripts. In this study, we investigate the role of Nocturnin in regulating the transcriptional response and downstream metabolic adaptations during cold exposure in brown adipose tissue. We find that Nocturnin exhibits dual localization within the cytosol and mitochondria, and loss of Nocturnin causes changes in expression of networks of mRNAs involved in mitochondrial function. Furthermore, Nocturnin^−/− animals display significantly elevated levels of tricarboxylic acid cycle intermediates, indicating that they have distinct metabolic adaptations during a prolonged cold exposure. We conclude that cold-induced stimulation of Nocturnin levels can regulate long-term metabolic adaptations to environmental challenges.

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Nocturnin localizes to both the cytosol and the mitochondria

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Nocturnin is robustly induced in response to cold exposure in brown fat

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Regulation of mitochondrial metabolic genes is altered in Nocturnin^−/− brown fat

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Nocturnin regulates long-term metabolic adaptation to cold exposure in brown fat

Cap-specific terminal N 6-methylation of RNA by an RNA polymerase II-associated methyltransferase

N ⁶-methyladenosine (m⁶A), a major modification of messenger RNAs (mRNAs), plays critical roles in RNA metabolism and function. In addition to the internal m⁶A, N ⁶, 2'-O-dimethyladenosine (m⁶Am) is present at the transcription start nucleotide of capped mRNAs in vertebrates. However, its biogenesis and functional role remain elusive. Using a reverse genetics approach, we identified PCIF1, a factor that interacts with the serine-5-phosphorylated carboxyl-terminal domain of RNA polymerase II, as a cap-specific adenosine methyltransferase (CAPAM) responsible for N ⁶-methylation of m⁶Am. The crystal structure of CAPAM in complex with substrates revealed the molecular basis of cap-specific m⁶A formation. A transcriptome-wide analysis revealed that N ⁶-methylation of m⁶Am promotes the translation of capped mRNAs. Thus, a cap-specific m⁶A writer promotes translation of mRNAs starting from m⁶Am.

RibORF: Identifying Genome-Wide Translated Open Reading Frames Using Ribosome Profiling

Ribosome profiling identifies RNA fragments associated with translating ribosomes. The technology provides an opportunity to examine genome-wide translation events at single-nucleotide resolution and in an unbiased manner. Here I present a computational pipeline named RibORF to systematically identify translated open reading frames (ORFs), based on read distribution features representing active translation, including 3-nt periodicity and uniformness across codons. Analyses using the computational tool revealed pervasive translation in putative 'noncoding' regions, such as lncRNAs, pseudogenes, and 5'UTRs. The computational tool is useful for studying functional roles of non-canonical translation events in various biological processes. © 2018 by John Wiley & Sons, Inc.

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

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