Impact of eIF2α phosphorylation on the translational landscape of mouse embryonic stem cells.

The integrated stress response (ISR) is critical for cell survival under stress. In response to diverse environmental cues, eIF2α becomes phosphorylated, engendering a dramatic change in mRNA translation. The activation of ISR plays a pivotal role in the early embryogenesis, but the eIF2-dependent translational landscape in pluripotent embryonic stem cells (ESCs) is largely unexplored. We employ a multi-omics approach consisting of ribosome profiling, proteomics, and metabolomics in wild-type (eIF2α+/+) and phosphorylation-deficient mutant eIF2α (eIF2αA/A) mouse ESCs (mESCs) to investigate phosphorylated (p)-eIF2α-dependent translational control of naive pluripotency. We show a transient increase in p-eIF2α in the naive epiblast layer of E4.5 embryos. Absence of eIF2α phosphorylation engenders an exit from naive pluripotency following 2i (two chemical inhibitors of MEK1/2 and GSK3α/ß) withdrawal. p-eIF2α controls translation of mRNAs encoding proteins that govern pluripotency, chromatin organization, and glutathione synthesis. Thus, p-eIF2α acts as a key regulator of the naive pluripotency gene regulatory network.

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.

Development of a ribosome profiling protocol to study translation in Kluyveromyces marxianus.

Kluyveromyces marxianus is an interesting and important yeast because of particular traits such as thermotolerance and rapid growth, and for applications in food and industrial biotechnology. For both understanding its biology and developing bioprocesses, it is important to understand how K. marxianus responds and adapts to changing environments. For this, a full suite of omics tools to measure and compare global patterns of gene expression and protein synthesis is needed. We report here the development of a ribosome profiling method for K. marxianus, which allows codon resolution of translation on a genome-wide scale by deep sequencing of ribosome locations on mRNAs. To aid in the analysis and sharing of ribosome profiling data, we added the K. marxianus genome as well as transcriptome and ribosome profiling data to the publicly accessible GWIPS-viz and Trips-Viz browsers. Users are able to upload custom ribosome profiling and RNA-Seq data to both browsers, therefore allowing easy analysis and sharing of data. We also provide a set of step-by-step protocols for the experimental and bioinformatic methods that we developed.

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.

Trips-Viz: an environment for the analysis of public and user-generated ribosome profiling data.

Trips-Viz (https://trips.ucc.ie/) is an interactive platform for the analysis and visualization of ribosome profiling (Ribo-Seq) and shotgun RNA sequencing (RNA-seq) data. This includes publicly available and user generated data, hence Trips-Viz can be classified as a database and as a server. As a database it provides access to many processed Ribo-Seq and RNA-seq data aligned to reference transcriptomes which has been expanded considerably since its inception. Here, we focus on the server functionality of Trips-viz which also has been greatly improved. Trips-viz now enables visualisation of proteomics data from a large number of processed mass spectrometry datasets. It can be used to support translation inferred from Ribo-Seq data. Users are now able to upload a custom reference transcriptome as well as data types other than Ribo-Seq/RNA-Seq. Incorporating custom data has been streamlined with RiboGalaxy (https://ribogalaxy.ucc.ie/) integration. The other new functionality is the rapid detection of translated open reading frames (ORFs) through a simple easy to use interface. The analysis of differential expression has been also improved via integration of DESeq2 and Anota2seq in addition to a number of other improvements of existing Trips-viz features.

eIF2α controls memory consolidation via excitatory and somatostatin neurons.

An important tenet of learning and memory is the notion of a molecular switch that promotes the formation of long-term memory1-4. The regulation of proteostasis is a critical and rate-limiting step in the consolidation of new memories5-10. One of the most effective and prevalent ways to enhance memory is by regulating the synthesis of proteins controlled by the translation initiation factor eIF211. Phosphorylation of the α-subunit of eIF2 (p-eIF2α), the central component of the integrated stress response (ISR), impairs long-term memory formation in rodents and birds11-13. By contrast, inhibiting the ISR by mutating the eIF2α phosphorylation site, genetically11 and pharmacologically inhibiting the ISR kinases14-17, or mimicking reduced p-eIF2α with the ISR inhibitor ISRIB11, enhances long-term memory in health and disease18. Here we used molecular genetics to dissect the neuronal circuits by which the ISR gates cognitive processing. We found that learning reduces eIF2α phosphorylation in hippocampal excitatory neurons and a subset of hippocampal inhibitory neurons (those that express somatostatin, but not parvalbumin). Moreover, ablation of p-eIF2α in either excitatory or somatostatin-expressing (but not parvalbumin-expressing) inhibitory neurons increased general mRNA translation, bolstered synaptic plasticity and enhanced long-term memory. Thus, eIF2α-dependent mRNA translation controls memory consolidation via autonomous mechanisms in excitatory and somatostatin-expressing inhibitory neurons.

Unusually efficient CUG initiation of an overlapping reading frame in POLG mRNA yields novel protein POLGARF.

While near-cognate codons are frequently used for translation initiation in eukaryotes, their efficiencies are usually low (<10% compared to an AUG in optimal context). Here, we describe a rare case of highly efficient near-cognate initiation. A CUG triplet located in the 5' leader of POLG messenger RNA (mRNA) initiates almost as efficiently (∼60 to 70%) as an AUG in optimal context. This CUG directs translation of a conserved 260-triplet-long overlapping open reading frame (ORF), which we call POLGARF (POLG Alternative Reading Frame). Translation of a short upstream ORF 5' of this CUG governs the ratio between POLG (the catalytic subunit of mitochondrial DNA polymerase) and POLGARF synthesized from a single POLG mRNA. Functional investigation of POLGARF suggests a role in extracellular signaling. While unprocessed POLGARF localizes to the nucleoli together with its interacting partner C1QBP, serum stimulation results in rapid cleavage and secretion of a POLGARF C-terminal fragment. Phylogenetic analysis shows that POLGARF evolved ∼160 million y ago due to a mammalian-wide interspersed repeat (MIR) transposition into the 5' leader sequence of the mammalian POLG gene, which became fixed in placental mammals. This discovery of POLGARF unveils a previously undescribed mechanism of de novo protein-coding gene evolution.

Selection Shapes Synonymous Stop Codon Use in Mammals.

Phylogenetic models of the evolution of protein-coding sequences can provide insights into the selection pressures that have shaped them. In the application of these models synonymous nucleotide substitutions, which do not alter the encoded amino acid, are often assumed to have limited functional consequences and used as a proxy for the neutral rate of evolution. The ratio of nonsynonymous to synonymous substitution rates is then used to categorize the selective regime that applies to the protein (e.g., purifying selection, neutral evolution, diversifying selection). Here, we extend the Muse and Gaut model of codon evolution to explore the extent of purifying selection acting on substitutions between synonymous stop codons. Using a large collection of coding sequence alignments, we estimate that a high proportion (approximately 57%) of mammalian genes are affected by selection acting on stop codon preference. This proportion varies substantially by codon, with UGA stop codons far more likely to be conserved. Genes with evidence of selection acting on synonymous stop codons have distinctive characteristics, compared to unconserved genes with the same stop codon, including longer [Formula: see text] untranslated regions (UTRs) and shorter mRNA half-life. The coding regions of these genes are also much more likely to be under strong purifying selection pressure. Our results suggest that the preference for UGA stop codons found in many multicellular eukaryotes is selective rather than mutational in origin.

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.

Cellular Gene Expression during Hepatitis C Virus Replication as Revealed by Ribosome Profiling.

BACKGROUND: Hepatitis C virus (HCV) infects human liver hepatocytes, often leading to liver cirrhosis and hepatocellular carcinoma (HCC). It is believed that chronic infection alters host gene expression and favors HCC development. In particular, HCV replication in Endoplasmic Reticulum (ER) derived membranes induces chronic ER stress. How HCV replication affects host mRNA translation and transcription at a genome wide level is not yet known. METHODS: We used Riboseq (Ribosome Profiling) to analyze transcriptome and translatome changes in the Huh-7.5 hepatocarcinoma cell line replicating HCV for 6 days. RESULTS: Established viral replication does not cause global changes in host gene expression-only around 30 genes are significantly differentially expressed. Upregulated genes are related to ER stress and HCV replication, and several regulated genes are known to be involved in HCC development. Some mRNAs (PPP1R15A/GADD34, DDIT3/CHOP, and TRIB3) may be subject to upstream open reading frame (uORF) mediated translation control. Transcriptional downregulation mainly affects mitochondrial respiratory chain complex core subunit genes. CONCLUSION: After establishing HCV replication, the lack of global changes in cellular gene expression indicates an adaptation to chronic infection, while the downregulation of mitochondrial respiratory chain genes indicates how a virus may further contribute to cancer cell-like metabolic reprogramming ("Warburg effect") even in the hepatocellular carcinoma cells used here.

Trips-Viz: a transcriptome browser for exploring Ribo-Seq data.

Ribosome profiling (Ribo-Seq) is a technique that allows for the isolation and sequencing of mRNA fragments protected from nuclease digestion by actively translating ribosomes. Mapping these ribosome footprints to a genome or transcriptome generates quantitative information on translated regions. To provide access to publicly available ribosome profiling data in the context of transcriptomes we developed Trips-Viz (transcriptome-wide information on protein synthesis-visualized). Trips-Viz provides a large range of graphical tools for exploring global properties of translatomes and of individual transcripts. It enables analysis of aligned footprints to evaluate datasets quality, differential gene expression detection, visual identification of upstream ORFs and alternative proteoforms. Trips-Viz is available at https://trips.ucc.ie.

The GWIPS-viz Browser.

GWIPS-viz is a publicly available browser that provides Genome Wide Information on Protein Synthesis through the visualization of ribosome profiling data. Ribosome profiling (Ribo-seq) is a high-throughput technique which isolates fragments of messenger RNA that are protected by the ribosome. The alignment of the ribosome-protected fragments or footprint sequences to the corresponding reference genome and their visualization using GWIPS-viz allows for unique insights into the genome loci that are expressed as potentially translated RNA. The GWIPS-viz browser hosts both Ribo-seq data and corresponding mRNA-seq data from publicly available studies across a number of genomes, avoiding the need for computational processing on the user side. Since its initial publication in 2014, over 1885 tracks have been produced across 24 genomes. This unit describes the navigation of the GWIPS-viz genome browser, the uploading of custom tracks, and the downloading of the Ribo-seq/mRNA-seq alignment data. © 2018 by John Wiley & Sons, Inc.

TASEP modelling provides a parsimonious explanation for the ability of a single uORF to derepress translation during the integrated stress response.

Translation initiation is the rate-limiting step of protein synthesis that is downregulated during the Integrated Stress Response (ISR). Previously, we demonstrated that most human mRNAs that are resistant to this inhibition possess translated upstream open reading frames (uORFs), and that in some cases a single uORF is sufficient for the resistance. Here we developed a computational model of Initiation Complexes Interference with Elongating Ribosomes (ICIER) to gain insight into the mechanism. We explored the relationship between the flux of scanning ribosomes upstream and downstream of a single uORF depending on uORF features. Paradoxically, our analysis predicts that reducing ribosome flux upstream of certain uORFs increases initiation downstream. The model supports the derepression of downstream translation as a general mechanism of uORF-mediated stress resistance. It predicts that stress resistance can be achieved with long slowly decoded uORFs that do not favor translation reinitiation and that start with initiators of low leakiness.

AMD1 mRNA employs ribosome stalling as a mechanism for molecular memory formation.

In addition to acting as template for protein synthesis, messenger RNA (mRNA) often contains sensory sequence elements that regulate this process. Here we report a new mechanism that limits the number of complete protein molecules that can be synthesized from a single mRNA molecule of the human AMD1 gene encoding adenosylmethionine decarboxylase 1 (AdoMetDC). A small proportion of ribosomes translating AMD1 mRNA stochastically read through the stop codon of the main coding region. These readthrough ribosomes then stall close to the next in-frame stop codon, eventually forming a ribosome queue, the length of which is proportional to the number of AdoMetDC molecules that were synthesized from the same AMD1 mRNA. Once the entire spacer region between the two stop codons is filled with queueing ribosomes, the queue impinges upon the main AMD1 coding region halting its translation. Phylogenetic analysis suggests that this mechanism is highly conserved in vertebrates and existed in their common ancestor. We propose that this mechanism is used to count and limit the number of protein molecules that can be synthesized from a single mRNA template. It could serve to safeguard from dysregulated translation that may occur owing to errors in transcription or mRNA damage.

GWIPS-viz: 2018 update.

The GWIPS-viz browser (http://gwips.ucc.ie/) is an on-line genome browser which is tailored for exploring ribosome profiling (Ribo-seq) data. Since its publication in 2014, GWIPS-viz provides Ribo-seq data for an additional 14 genomes bringing the current total to 23. The integration of new Ribo-seq data has been automated thereby increasing the number of available tracks to 1792, a 10-fold increase in the last three years. The increase is particularly substantial for data derived from human sources. Following user requests, we added the functionality to download these tracks in bigWig format. We also incorporated new types of data (e.g. TCP-seq) as well as auxiliary tracks from other sources that help with the interpretation of Ribo-seq data. Improvements in the visualization of the data have been carried out particularly for bacterial genomes where the Ribo-seq data are now shown in a strand specific manner. For higher eukaryotic datasets, we provide characteristics of individual datasets using the RUST program which includes the triplet periodicity, sequencing biases and relative inferred A-site dwell times. This information can be used for assessing the quality of Ribo-seq datasets. To improve the power of the signal, we aggregate Ribo-seq data from several studies into Global aggregate tracks for each genome.