A Regression-Based Analysis of Ribosome-Profiling Data Reveals a Conserved Complexity to Mammalian Translation

ncRNAs: New Players in Mitochondrial Health and Disease?

The regulation of mitochondrial proteome is unique in that its components have origins in both mitochondria and nucleus. With the development of OMICS technologies, emerging evidence indicates an interaction between mitochondria and nucleus based not only on the proteins but also on the non-coding RNAs (ncRNAs). It is now accepted that large parts of the non‐coding genome are transcribed into various ncRNA species. Although their characterization has been a hot topic in recent years, the function of the majority remains unknown. Recently, ncRNA species microRNA (miRNA) and long-non coding RNAs (lncRNA) have been gaining attention as direct or indirect modulators of the mitochondrial proteome homeostasis. These ncRNA can impact mitochondria indirectly by affecting transcripts encoding for mitochondrial proteins in the cytoplasm. Furthermore, reports of mitochondria-localized miRNAs, termed mitomiRs, and lncRNAs directly regulating mitochondrial gene expression suggest the import of RNA to mitochondria, but also transcription from the mitochondrial genome. Interestingly, ncRNAs have been also shown to hide small open reading frames (sORFs) encoding for small functional peptides termed micropeptides, with several examples reported with a role in mitochondria. In this review, we provide a literature overview on ncRNAs and micropeptides found to be associated with mitochondrial biology in the context of both health and disease. Although reported, small study overlap and rare replications by other groups make the presence, transport, and role of ncRNA in mitochondria an attractive, but still challenging subject. Finally, we touch the topic of their potential as prognosis markers and therapeutic targets.

Comprehensive annotations of human herpesvirus 6A and 6B genomes reveal novel and conserved genomic features

Human herpesvirus-6 (HHV-6) A and B are ubiquitous betaherpesviruses, infecting the majority of the human population. They encompass large genomes and our understanding of their protein coding potential is far from complete. Here, we employ ribosome-profiling and systematic transcript-analysis to experimentally define HHV-6 translation products. We identify hundreds of new open reading frames (ORFs), including upstream ORFs (uORFs) and internal ORFs (iORFs), generating a complete unbiased atlas of HHV-6 proteome. By integrating systematic data from the prototypic betaherpesvirus, human cytomegalovirus, we uncover numerous uORFs and iORFs conserved across betaherpesviruses and we show uORFs are enriched in late viral genes. We identified three highly abundant HHV-6 encoded long non-coding RNAs, one of which generates a non-polyadenylated stable intron appearing to be a conserved feature of betaherpesviruses. Overall, our work reveals the complexity of HHV-6 genomes and highlights novel features conserved between betaherpesviruses, providing a rich resource for future functional studies.

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

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

DeepRibo: a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns

Annotation of gene expression in prokaryotes often finds itself corrected due to small variations of the annotated gene regions observed between different (sub)-species. It has become apparent that traditional sequence alignment algorithms, used for the curation of genomes, are not able to map the full complexity of the genomic landscape. We present DeepRibo, a novel neural network utilizing features extracted from ribosome profiling information and binding site sequence patterns that shows to be a precise tool for the delineation and annotation of expressed genes in prokaryotes. The neural network combines recurrent memory cells and convolutional layers, adapting the information gained from both the high-throughput ribosome profiling data and ribosome binding translation initiation sequence region into one model. DeepRibo is designed as a single model trained on a variety of ribosome profiling experiments, used for the identification of open reading frames in prokaryotes without a priori knowledge of the translational landscape. Through extensive validation of the model trained on various sets of data, multiple species sequence similarity, mass spectrometry and Edman degradation verified proteins, the effectiveness of DeepRibo is highlighted.

Not lost in host translation: The new roles of long noncoding RNAs in infectious diseases

Long non-coding RNAs (lncRNAs) play a central role in the regulation of gene expression. Although they were initially described as mRNA-like transcripts not encoding proteins, global approaches such as ribosome profiling have shown that they frequently associate with ribosomes, opening the possibility that lncRNAs are a source of cryptic translation events with functional roles. Recent studies have shed more light on small ORFs borne by lncRNAs and encoding short peptides potentially involved in infectious immunity. This review outlines the main strategies used to determine the coding potential of lncRNAs and discusses our emerging understanding of the implication of the encoded peptides in infectious diseases.

Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.

The Tomato Translational Landscape Revealed by Transcriptome Assembly and Ribosome Profiling

Recent applications of translational control in Arabidopsis (Arabidopsis thaliana) highlight the potential power of manipulating mRNA translation for crop improvement. However, to what extent translational regulation is conserved between Arabidopsis and other species is largely unknown, and the translatome of most crops remains poorly studied. Here, we combined de novo transcriptome assembly and ribosome profiling to study global mRNA translation in tomato (Solanum lycopersicum) roots. Exploiting features corresponding to active translation, we discovered widespread unannotated translation events, including 1,329 upstream open reading frames (uORFs) within the 5' untranslated regions of annotated coding genes and 354 small ORFs (sORFs) among unannotated transcripts. uORFs may repress translation of their downstream main ORFs, whereas sORFs may encode signaling peptides. Besides evolutionarily conserved sORFs, we uncovered 96 Solanaceae-specific sORFs, revealing the importance of studying translatomes directly in crops. Proteomic analysis confirmed that some of the unannotated ORFs generate stable proteins in planta. In addition to defining the translatome, our results reveal the global regulation by uORFs and microRNAs. Despite diverging over 100 million years ago, many translational features are well conserved between Arabidopsis and tomato. Thus, our approach provides a high-throughput method to discover unannotated ORFs, elucidates evolutionarily conserved and unique translational features, and identifies regulatory mechanisms hidden in a crop genome.

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.

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.

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

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

De novo annotation and characterization of the translatome with ribosome profiling data

By capturing and sequencing the RNA fragments protected by translating ribosomes, ribosome profiling provides snapshots of translation at subcodon resolution. The growing needs for comprehensive annotation and characterization of the context-dependent translatomes are calling for an efficient and unbiased method to accurately recover the signal of active translation from the ribosome profiling data. Here we present our new method, RiboCode, for such purpose. Being tested with simulated and real ribosome profiling data, and validated with cell type-specific QTI-seq and mass spectrometry data, RiboCode exhibits superior efficiency, sensitivity, and accuracy for de novo annotation of the translatome, which covers various types of ORFs in the previously annotated coding and non-coding regions. As an example, RiboCode was applied to assemble the context-specific translatomes of yeast under normal and stress conditions. Comparisons among these translatomes revealed stress-activated novel upstream and downstream ORFs, some of which are associated with translational dysregulations of the annotated main ORFs under the stress conditions.

A comprehensive catalog of predicted functional upstream open reading frames in humans

Upstream open reading frames (uORFs) latent in mRNA transcripts are thought to modify translation of coding sequences by altering ribosome activity. Not all uORFs are thought to be active in such a process. To estimate the impact of uORFs on the regulation of translation in humans, we first circumscribed the universe of all possible uORFs based on coding gene sequence motifs and identified 1.3 million unique uORFs. To determine which of these are likely to be biologically relevant, we built a simple Bayesian classifier using 89 attributes of uORFs labeled as active in ribosome profiling experiments. This allowed us to extrapolate to a comprehensive catalog of likely functional uORFs. We validated our predictions using in vivo protein levels and ribosome occupancy from 46 individuals. This is a substantially larger catalog of functional uORFs than has previously been reported. Our ranked list of likely active uORFs allows researchers to test their hypotheses regarding the role of uORFs in health and disease. We demonstrate several examples of biological interest through the application of our catalog to somatic mutations in cancer and disease-associated germline variants in humans.

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

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

Translational regulation contributes to the secretory response of chondrocytic cells following exposure to interleukin-1β

Osteoarthritis is a chronic disease characterized by the loss of articular cartilage in synovial joints through a process of extracellular matrix destruction that is strongly associated with inflammatory stimuli. Chondrocytes undergo changes to their protein translational capacity during osteoarthritis, but a study of how disease-relevant signals affect chondrocyte protein translation at the transcriptomic level has not previously been performed. In this study, we describe how the inflammatory cytokine interleukin 1-β (IL-1β) rapidly affects protein translation in the chondrocytic cell line SW1353. Using ribosome profiling we demonstrate that IL-1β induced altered translation of inflammatory-associated transcripts such as NFKB1, TNFAIP2, MMP13, CCL2, and CCL7, as well as a number of ribosome-associated transcripts, through differential translation and the use of multiple open reading frames. Proteomic analysis of the cellular layer and the conditioned media of these cells identified changes in a number of the proteins that were differentially translated. Translationally regulated secreted proteins included a number of chemokines and cytokines, underlining the rapid, translationally mediated inflammatory cascade that is initiated by IL-1β. Although fewer cellular proteins were found to be regulated in both ribosome profiling and proteomic data sets, we did find increased levels of SOD2, indicative of redox changes within SW1353 cells being modulated at the translational level. In conclusion, we have produced combined ribosome profiling and proteomic data sets that provide a valuable resource in understanding the processes that occur during cytokine stimulation of chondrocytic cells.

c-MYC regulates mRNA translation efficiency and start-site selection in lymphoma

The oncogenic c-MYC (MYC) transcription factor has broad effects on gene expression and cell behavior. We show that MYC alters the efficiency and quality of mRNA translation into functional proteins. Specifically, MYC drives the translation of most protein components of the electron transport chain in lymphoma cells, and many of these effects are independent from proliferation. Specific interactions of MYC-sensitive RNA-binding proteins (e.g., SRSF1/RBM42) with 5'UTR sequence motifs mediate many of these changes. Moreover, we observe a striking shift in translation initiation site usage. For example, in low-MYC conditions, lymphoma cells initiate translation of the CD19 mRNA from a site in exon 5. This results in the truncation of all extracellular CD19 domains and facilitates escape from CD19-directed CAR-T cell therapy. Together, our findings reveal MYC effects on the translation of key metabolic enzymes and immune receptors in lymphoma cells.

Survey of the translation shifts in hepatocellular carcinoma with ribosome profiling

Despite the critical position of translation in the multilevel gene expression regulation program, high-resolution and genome-wide view of the landscape of RNA translation in solid tumors is still limited. Methods: With a ribosome profiling procedure optimized for solid tissue samples, we profiled the translatomes of liver tumors and their adjacent noncancerous normal liver tissues from 10 patients with hepatocellular carcinoma (HCC). A set of bioinformatics tools was then applied to these data for the mining of novel insights into the translation shifts in HCC. Results: This is the first translatome data resource for dissecting dysregulated translation in HCC at the sub-codon resolution. Based on our data, quantitative comparisons of mRNA translation rates yielded the genes and processes that were subjected to patient specific or universal dysregulations of translation efficiencies in tumors. For example, multiple proteins involved in extracellular matrix organization exhibited significant translational upregulation in tumors. We then experimentally validated the tumor-promoting functions of two such genes as examples: AGRN and VWA1. In addition, the data was also used for de novo annotation of the translatomes in tumors and normal tissues, including multiple types of novel non-canonical small ORFs, which would be a resource for further functional studies. Conclusions: The present study generates the first survey of the HCC translatome with ribosome profiling, which is an insightful data resource for dissecting the translatome shift in liver cancer, at sub-codon resolution.

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

BACKGROUND

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

RESULTS

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

CONCLUSION

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

Ribosome Profiling: Global Views of Translation

The translation of messenger RNA (mRNA) into protein and the folding of the resulting protein into an active form are prerequisites for virtually every cellular process and represent the single largest investment of energy by cells. Ribosome profiling-based approaches have revolutionized our ability to monitor every step of protein synthesis in vivo, allowing one to measure the rate of protein synthesis across the proteome, annotate the protein coding capacity of genomes, monitor localized protein synthesis, and explore cotranslational folding and targeting. The rich and quantitative nature of ribosome profiling data provides an unprecedented opportunity to explore and model complex cellular processes. New analytical techniques and improved experimental protocols will provide a deeper understanding of the factors controlling translation speed and its impact on protein function and cell physiology as well as the role of ribosomal RNA and mRNA modifications in regulating translation.

Identifying Small Proteins by Ribosome Profiling with Stalled Initiation Complexes

Small proteins consisting of 50 or fewer amino acids have been identified as regulators of larger proteins in bacteria and eukaryotes. Despite the importance of these molecules, the total number of small proteins remains unknown because conventional annotation pipelines usually exclude small open reading frames (smORFs). We previously identified several dozen small proteins in the model organism Escherichia coli using theoretical bioinformatic approaches based on sequence conservation and matches to canonical ribosome binding sites. Here, we present an empirical approach for discovering new proteins, taking advantage of recent advances in ribosome profiling in which antibiotics are used to trap newly initiated 70S ribosomes at start codons. This approach led to the identification of many novel initiation sites in intergenic regions in E. coli We tagged 41 smORFs on the chromosome and detected protein synthesis for all but three. Not only are the corresponding genes intergenic but they are also found antisense to other genes, in operons, and overlapping other open reading frames (ORFs), some impacting the translation of larger downstream genes. These results demonstrate the utility of this method for identifying new genes, regardless of their genomic context.IMPORTANCE Proteins comprised of 50 or fewer amino acids have been shown to interact with and modulate the functions of larger proteins in a range of organisms. Despite the possible importance of small proteins, the true prevalence and capabilities of these regulators remain unknown as the small size of the proteins places serious limitations on their identification, purification, and characterization. Here, we present a ribosome profiling approach with stalled initiation complexes that led to the identification of 38 new small proteins.

Mining for missed sORF-encoded peptides

INTRODUCTION

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

Ribosomal Proteins Regulate MHC Class I Peptide Generation for Immunosurveillance

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

Translation of Small Open Reading Frames: Roles in Regulation and Evolutionary Innovation

The translatome can be defined as the sum of the RNA sequences that are translated into proteins in the cell by the ribosomal machinery. Until recently, it was generally assumed that the translatome was essentially restricted to evolutionary conserved proteins encoded by the set of annotated protein-coding genes. However, it has become increasingly clear that it also includes small regulatory open reading frames (ORFs), functional micropeptides, de novo proteins, and the pervasive translation of likely nonfunctional proteins. Many of these ORFs have been discovered thanks to the development of ribosome profiling, a technique to sequence ribosome-protected RNA fragments. To fully capture the diversity of translated ORFs, we propose a comprehensive classification that includes the new types of translated ORFs in addition to standard proteins.

Peptides/Proteins Encoded by Non-coding RNA: A Novel Resource Bank for Drug Targets and Biomarkers

Non-coding RNAs (ncRNAs) are defined as RNA molecules that do not encode proteins, but recent evidence has proven that peptides/proteins encoded by ncRNAs do indeed exist and usually contain less than 100 amino acids. These peptides/proteins play an important role in regulating tumor energy metabolism, epithelial to mesenchymal transition of cancer cells, the stability of the c-Myc oncoprotein, and the ubiquitination and degradation of proliferating cell nuclear antigen (PCNA). These peptides/proteins represent promising drug targets for fighting against tumor growth or biomarkers for predicting the prognosis of cancer patients. In this review, we summarize the characteristics of peptides/proteins that have recently been identified as putative ncRNA translation products and their outlook for small molecule peptide drugs, drug targets, and biomarkers.

Disruption of TWIST1 translation by 5' UTR variants in Saethre-Chotzen syndrome

Saethre-Chotzen syndrome (SCS), one of the most common forms of syndromic craniosynostosis (premature fusion of the cranial sutures), results from haploinsufficiency of TWIST1, caused by deletions of the entire gene or loss-of-function variants within the coding region. To determine whether non-coding variants also contribute to SCS, we screened 14 genetically undiagnosed SCS patients using targeted capture sequencing, and identified novel single nucleotide variants (SNVs) in the 5' untranslated region (UTR) of TWIST1 in two unrelated SCS cases. We show experimentally that these variants, which create translation start sites in the TWIST1 leader sequence, reduce translation from the main open reading frame (mORF). This is the first demonstration that non-coding SNVs of TWIST1 can cause SCS, and highlights the importance of screening the 5' UTR in clinically diagnosed SCS patients without a coding mutation. Similar 5' UTR variants, particularly of haploinsufficient genes, may represent an under-ascertained cause of monogenic disease.

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

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

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.

Genome-wide maps of ribosomal occupancy provide insights into adaptive evolution and regulatory roles of uORFs during Drosophila development

Upstream open reading frames (uORFs) play important roles in regulating the main coding DNA sequences (CDSs) via translational repression. Despite their prevalence in the genomes, uORFs are overall discriminated against by natural selection. However, it remains unclear why in the genomes there are so many uORFs more conserved than expected under the assumption of neutral evolution. Here, we generated genome-wide maps of translational efficiency (TE) at the codon level throughout the life cycle of Drosophila melanogaster. We identified 35,735 uORFs that were expressed, and 32,224 (90.2%) of them showed evidence of ribosome occupancy during Drosophila development. The ribosome occupancy of uORFs is determined by genomic features, such as optimized sequence contexts around their start codons, a shorter distance to CDSs, and higher coding potentials. Our population genomic analysis suggests the segregating mutations that create or disrupt uORFs are overall deleterious in D. melanogaster. However, we found for the first time that many (68.3% of) newly fixed uORFs that are associated with ribosomes in D. melanogaster are driven by positive Darwinian selection. Our findings also suggest that uORFs play a vital role in controlling the translational program in Drosophila. Moreover, we found that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner, suggesting that selective transcription or translation of uORFs could potentially modulate the TE of the downstream CDSs during Drosophila development.

Upstream open reading frames (uORFs) in the 5′ untranslated regions (UTRs) of messenger RNAs can potentially inhibit translation of the downstream regions that encode proteins by sequestering protein-making machinery the ribosome. Moreover, mutations that destroy existing uORFs or create new ones are known to cause human disease. Although mutations that create new uORFs are generally deleterious and are selected against, many uORFs are evolutionarily conserved across eukaryotic species. To resolve this dilemma, we used extensive mRNA-Seq and ribosome profiling to generate high-resolution genome-wide maps of ribosome occupancy and translational efficiency (TE) during the life cycle of the fruit fly D. melanogaster. This allowed us to identify the sequence features of uORFs that influence their ability to associate with ribosomes. We demonstrate for the first time that the majority of the newly fixed uORFs in D. melanogaster, especially the translated ones, are under positive Darwinian selection. We also show that uORFs exert widespread repressive effects on the translation of the downstream protein-coding region. We find that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner. Our results suggest that during Drosophila development, changes in the TE of uORFs, as well as the inclusion/exclusion of uORFs, are frequently exploited to inversely influence the translation of the downstream protein-coding regions. Our study provides novel insights into the molecular mechanisms and functional consequences of uORF-mediated regulation.

Methods for monitoring and measurement of protein translation in time and space

Regulation of protein translation constitutes a crucial step in control of gene expression. Here we review recent methods for system-wide monitoring and measurement of protein translation.

Regulation of protein translation constitutes a crucial step in control of gene expression. In comparison to transcriptional regulation, however, translational control has remained a significantly under-studied layer of gene expression. This trend is now beginning to shift thanks to recent advances in next-generation sequencing, proteomics, and microscopy based methodologies which allow accurate monitoring of protein translation rates, from single target messenger RNA molecules to genome-wide scale studies. In this review, we summarize these recent advances, and discuss how they are enabling researchers to study translational regulation in a wide variety of in vitro and in vivo biological systems, with unprecedented depth and spatiotemporal resolution.

The exon-intron gene structure upstream of the initiation codon predicts translation efficiency

Introns in mRNA leaders are common in complex eukaryotes, but often overlooked. These introns are spliced out before translation, leaving exon-exon junctions in the mRNA leaders (leader EEJs). Our multi-omic approach shows that the number of leader EEJs inversely correlates with the main protein translation, as does the number of upstream open reading frames (uORFs). Across the five species studied, the lowest levels of translation were observed for mRNAs with both leader EEJs and uORFs (29%). This class of mRNAs also have ribosome footprints on uORFs, with strong triplet periodicity indicating uORF translation. Furthermore, the positions of both leader EEJ and uORF are conserved between human and mouse. Thus, the uORF, in combination with leader EEJ predicts lower expression for nearly one-third of eukaryotic proteins.

Battling for Ribosomes: Translational Control at the Forefront of the Antiviral Response

In the early stages of infection, gaining control of the cellular protein synthesis machinery including its ribosomes is the ultimate combat objective for a virus. To successfully replicate, viruses unequivocally need to usurp and redeploy this machinery for translation of their own mRNA. In response, the host triggers global shutdown of translation while paradoxically allowing swift synthesis of antiviral proteins as a strategy to limit collateral damage. This fundamental conflict at the level of translational control defines the outcome of infection. As part of this special issue on molecular mechanisms of early virus-host cell interactions, we review the current state of knowledge regarding translational control during viral infection with specific emphasis on protein kinase RNA-activated and mammalian target of rapamycin-mediated mechanisms. We also describe recent technological advances that will allow unprecedented insight into how viruses and host cells battle for ribosomes.

Following Ribosome Footprints to Understand Translation at a Genome Wide Level

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

Viral Short ORFs and Their Possible Functions

Definition of functional genomic elements is one of the greater challenges of the genomic era. Traditionally, putative short open reading frames (sORFs) coding for less than 100 amino acids were disregarded due to computational and experimental limitations; however, it has become clear over the past several years that translation of sORFs is pervasive and serves diverse functions. The development of ribosome profiling, allowing identification of translated sequences genome wide, revealed wide spread, previously unidentified translation events. New computational methodologies as well as improved mass spectrometry approaches also contributed to the task of annotating translated sORFs in different organisms. Viruses are of special interest due to the selective pressure on their genome size, their rapid and confining evolution, and the potential contribution of novel peptides to the host immune response. Indeed, many functional viral sORFs were characterized to date, and ribosome profiling analyses suggest that this may be the tip of the iceberg. Our computational analyses of sORFs identified by ribosome profiling in DNA viruses demonstrate that they may be enriched in specific features implying that at least some of them are functional. Combination of systematic genome editing strategies with synthetic tagging will take us into the next step-elucidation of the biological relevance and function of this intriguing class of molecules.

Improved Ribo-seq enables identification of cryptic translation events

Ribosome profiling has been used to predict thousands of short open reading frames (sORFs) in eukaryotic cells, but it suffers from substantial levels of noise. PRICE (https://github.com/erhard-lab/price) is a computational method that models experimental noise to enable researchers to accurately resolve overlapping sORFs and noncanonical translation initiation. We experimentally validated translation using major histocompatibility complex class I (MHC I) peptidomics and observed that sORF-derived peptides efficiently enter the MHC I presentation pathway and thus constitute a substantial fraction of the antigen repertoire.

Micropeptides Encoded in Transcripts Previously Identified as Long Noncoding RNAs: A New Chapter in Transcriptomics and Proteomics

Integrative analysis using omics-based technologies results in the identification of a large number of putative short open reading frames (sORFs) with protein-coding capacity within transcripts previously identified as long noncoding RNAs (lncRNAs) or transcripts of unknown function (TUFs). sORFs were previously overlooked because of their diminutive size and the difficulty of identification by bioinformatics analyses. There is now growing evidence of the existence of potentially functional micropeptides produced from sORFs within cells of diverse species. Recent characterization of a few of these revealed their significant divergent roles in many fundamental biological processes, where some also show important relationships with pathogenesis. Recent works therefore provide new insights for exploring the wealth of information that may lie within sORF-encoded short proteins. Here, we summarize the current progress and view of micropeptides encoded in sORFs of protein-coding genes.

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship

Technological advances promise unprecedented opportunities for whole exome sequencing and proteomic analyses of populations. Currently, data from genome and exome sequencing or proteomic studies are searched against reference genome annotations. This provides the foundation for research and clinical screening for genetic causes of pathologies. However, current genome annotations substantially underestimate the proteomic information encoded within a gene. Numerous studies have now demonstrated the expression and function of alternative (mainly small, sometimes overlapping) ORFs within mature gene transcripts. This has important consequences for the correlation of phenotypes and genotypes. Most alternative ORFs are not yet annotated because of a lack of evidence, and this absence from databases precludes their detection by standard proteomic methods, such as mass spectrometry. Here, we demonstrate how current approaches tend to overlook alternative ORFs, hindering the discovery of new genetic drivers and fundamental research. We discuss available tools and techniques to improve identification of proteins from alternative ORFs and finally suggest a novel annotation system to permit a more complete representation of the transcriptomic and proteomic information contained within a gene. Given the crucial challenge of distinguishing functional ORFs from random ones, the suggested pipeline emphasizes both experimental data and conservation signatures. The addition of alternative ORFs in databases will render identification less serendipitous and advance the pace of research and genomic knowledge. This review highlights the urgent medical and research need to incorporate alternative ORFs in current genome annotations and thus permit their inclusion in hypotheses and models, which relate phenotypes and genotypes.

A Comprehensive Analysis of Transcript-Supported De Novo Genes in Saccharomyces sensu stricto Yeasts

Novel genes arising from random DNA sequences (de novo genes) have been suggested to be widespread in the genomes of different organisms. However, our knowledge about the origin and evolution of de novo genes is still limited. To systematically understand the general features of de novo genes, we established a robust pipeline to analyze >20,000 transcript-supported coding sequences (CDSs) from the budding yeast Saccharomyces cerevisiae. Our analysis pipeline combined phylogeny, synteny, and sequence alignment information to identify possible orthologs across 20 Saccharomycetaceae yeasts and discovered 4,340 S. cerevisiae-specific de novo genes and 8,871 S. sensu stricto-specific de novo genes. We further combine information on CDS positions and transcript structures to show that >65% of de novo genes arose from transcript isoforms of ancient genes, especially in the upstream and internal regions of ancient genes. Fourteen identified de novo genes with high transcript levels were chosen to verify their protein expressions. Ten of them, including eight transcript isoform-associated CDSs, showed translation signals and five proteins exhibited specific cytosolic localizations. Our results suggest that de novo genes frequently arise in the S. sensu stricto complex and have the potential to be quickly integrated into ancient cellular network.

RNA surveillance by the nuclear RNA exosome: mechanisms and significance

The nuclear RNA exosome is an essential and versatile machinery that regulates maturation and degradation of a huge plethora of RNA species. The past two decades have witnessed remarkable progress in understanding the whole picture of its RNA substrates and the structural basis of its functions. In addition to the exosome itself, recent studies focusing on associated co-factors have been elucidating how the exosome is directed towards specific substrates. Moreover, it has been gradually realized that loss-of-function of exosome subunits affect multiple biological processes such as the DNA damage response, R-loop resolution, maintenance of genome integrity, RNA export, translation and cell differentiation. In this review, we summarize the current knowledge of the mechanisms of nuclear exosome-mediated RNA metabolism and discuss their physiological significance.

Understanding biopharmaceutical production at single nucleotide resolution using ribosome footprint profiling

Biopharmaceuticals such as monoclonal antibodies have revolutionised the treatment of a variety of diseases. The production of recombinant therapeutic proteins, however, remains expensive due to the manufacturing complexity of mammalian expression systems and the regulatory burden associated with administrating these medicines to patients in a safe and efficacious manner. In recent years, academic and industrial groups have begun to develop a greater understanding of the biology of host cell lines, such as Chinese hamster ovary (CHO) cells and utilise that information for process development and cell line engineering. In this review, we focus on ribosome footprint profiling (RiboSeq), an exciting next generation sequencing (NGS) method that provides genome-wide information on translation, and discuss how its application can transform our understanding of therapeutic protein production.

Discovering Putative Peptides Encoded from Noncoding RNAs in Ribosome Profiling Data of Arabidopsis thaliana

Most noncoding RNAs are considered by their expression at low levels and as having a limited phylogenetic distribution in the cytoplasm, indicating that they may be only involved in specific biological processes. However, recent studies showed the protein-coding potential of ncRNAs, indicating that they might be a source of some special proteins. Although there are increasing noncoding RNAs identified to be able to code proteins, it is challenging to distinguish coding RNAs from previously annotated ncRNAs, and to detect the proteins from their translation. In this article, we designed a pipeline to identify these noncoding RNAs in Arabidopsis thaliana from three NCBI GEO data sets with coding potential and predict their translation products. 31 311 noncoding RNAs were predicted to be translated into peptides, and they showed lower conservation rate than common proteins. In addition, we built an interaction network between these peptides and annotated Arabidopsis proteins using BIPS, which included 69 peptides from noncoding RNAs. Peptides in the interaction network showed different characteristics from other noncoding RNA-derived peptides, and they participated in several crucial biological processes, such as photorespiration and stress-responses. All the information of putative ncPEPs and their interaction with proteins predicted above are finally integrated in a database, PncPEPDB ( http://bis.zju.edu.cn/PncPEPDB ). These results showed that peptides derived from noncoding RNAs may play important roles in noncoding RNA regulation, which provided another hypothesis that noncoding RNA may regulate the metabolism via their translation products.

Exploiting non-canonical translation to identify new targets for T cell-based cancer immunotherapy

Cryptic MHC I-associated peptides (MAPs) are produced via two mechanisms: translation of protein-coding genes in non-canonical reading frames and translation of allegedly non-coding sequences. In general, cryptic MAPs are coded by relatively short open reading frames whose translation can be regulated at the level of initiation, elongation or termination. In contrast to conventional MAPs, the processing of cryptic MAPs is frequently proteasome independent. The existence of cryptic MAPs derived from allegedly non-coding regions enlarges the scope of CD8 T cell immunosurveillance from a mere ~2% to as much as ~75% of the human genome. Considering that 99% of cancer-specific mutations are located in those allegedly non-coding regions, cryptic MAPs could furthermore represent a particularly rich source of tumor-specific antigens. However, extensive proteogenomic analyses will be required to determine the breath as well as the temporal and spatial plasticity of the cryptic MAP repertoire in normal and neoplastic cells.

Conserved non-AUG uORFs revealed by a novel regression analysis of ribosome profiling data

Upstream open reading frames (uORFs), located in transcript leaders (5' UTRs), are potent cis-acting regulators of translation and mRNA turnover. Recent genome-wide ribosome profiling studies suggest that thousands of uORFs initiate with non-AUG start codons. Although intriguing, these non-AUG uORF predictions have been made without statistical control or validation; thus, the importance of these elements remains to be demonstrated. To address this, we took a comparative genomics approach to study AUG and non-AUG uORFs. We mapped transcription leaders in multiple Saccharomyces yeast species and applied a novel machine learning algorithm (uORF-seqr) to ribosome profiling data to identify statistically significant uORFs. We found that AUG and non-AUG uORFs are both frequently found in Saccharomyces yeasts. Although most non-AUG uORFs are found in only one species, hundreds have either conserved sequence or position within Saccharomyces uORFs initiating with UUG are particularly common and are shared between species at rates similar to that of AUG uORFs. However, non-AUG uORFs are translated less efficiently than AUG-uORFs and are less subject to removal via alternative transcription initiation under normal growth conditions. These results suggest that a subset of non-AUG uORFs may play important roles in regulating gene expression.

Rethinking Unconventional Translation in Neurodegeneration

Eukaryotic translation is tightly regulated to ensure that protein production occurs at the right time and place. Recent studies on abnormal repeat proteins, especially in age-dependent neurodegenerative diseases caused by nucleotide repeat expansion, have highlighted or identified two forms of unconventional translation initiation: usage of AUG-like sites (near cognates) or repeat-associated non-AUG (RAN) translation. We discuss how repeat proteins may differ due to not just unconventional initiation, but also ribosomal frameshifting and/or imperfect repeat DNA replication, expansion, and repair, and we highlight how research on translation of repeats may uncover insights into the biology of translation and its contribution to disease.

Comparative ribosome profiling uncovers a dominant role for translational control in Toxoplasma gondii

Background

The lytic cycle of the protozoan parasite Toxoplasma gondii, which involves a brief sojourn in the extracellular space, is characterized by defined transcriptional profiles. For an obligate intracellular parasite that is shielded from the cytosolic host immune factors by a parasitophorous vacuole, the brief entry into the extracellular space is likely to exert enormous stress. Due to its role in cellular stress response, we hypothesize that translational control plays an important role in regulating gene expression in Toxoplasma during the lytic cycle. Unlike transcriptional profiles, insights into genome-wide translational profiles of Toxoplasma gondii are lacking.

Methods

We have performed genome-wide ribosome profiling, coupled with high throughput RNA sequencing, in intracellular and extracellular Toxoplasma gondii parasites to investigate translational control during the lytic cycle.

Results

Although differences in transcript abundance were mostly mirrored at the translational level, we observed significant differences in the abundance of ribosome footprints between the two parasite stages. Furthermore, our data suggest that mRNA translation in the parasite is potentially regulated by mRNA secondary structure and upstream open reading frames.

Conclusion

We show that most of the Toxoplasma genes that are dysregulated during the lytic cycle are translationally regulated.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4362-6) contains supplementary material, which is available to authorized users.

Mining for Small Translated ORFs

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

REPARATION: ribosome profiling assisted (re-)annotation of bacterial genomes

Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated methods depend heavily on sequence composition and often underestimate the complexity of the proteome. We developed RibosomeE Profiling Assisted (re-)AnnotaTION (REPARATION), a de novo machine learning algorithm that takes advantage of experimental protein synthesis evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation (https://github.com/Biobix/REPARATION). REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds based on a growth curve model to screen for spurious ORFs. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel (small) ORFs including variants of previously annotated ORFs and >70% of all (variants of) annotated protein coding ORFs were predicted by REPARATION to be translated. Our predictions are supported by matching mass spectrometry proteomics data, sequence composition and conservation analysis. REPARATION is unique in that it makes use of experimental translation evidence to intrinsically perform a de novo ORF delineation in bacterial genomes irrespective of the sequence features linked to open reading frames.

Non-AUG translation: a new start for protein synthesis in eukaryotes

This review by Kearse and Wilusz discusses the profound impact of non-AUG start codons in eukaryotic translation. It describes how misregulation of non-AUG initiation events contributes to multiple human diseases, including cancer and neurodegeneration, and how modulation of non-AUG usage may represent a novel therapeutic strategy.

Although it was long thought that eukaryotic translation almost always initiates at an AUG start codon, recent advancements in ribosome footprint mapping have revealed that non-AUG start codons are used at an astonishing frequency. These non-AUG initiation events are not simply errors but instead are used to generate or regulate proteins with key cellular functions; for example, during development or stress. Misregulation of non-AUG initiation events contributes to multiple human diseases, including cancer and neurodegeneration, and modulation of non-AUG usage may represent a novel therapeutic strategy. It is thus becoming increasingly clear that start codon selection is regulated by many trans-acting initiation factors as well as sequence/structural elements within messenger RNAs and that non-AUG translation has a profound impact on cellular states.

Genome-wide identification and differential analysis of translational initiation

Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5'UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data.

The functions and unique features of long intergenic non-coding RNA

Long intergenic non-coding RNA (lincRNA) genes have diverse features that distinguish them from mRNA-encoding genes and exercise functions such as remodelling chromatin and genome architecture, RNA stabilization and transcription regulation, including enhancer-associated activity. Some genes currently annotated as encoding lincRNAs include small open reading frames (smORFs) and encode functional peptides and thus may be more properly classified as coding RNAs. lincRNAs may broadly serve to fine-tune the expression of neighbouring genes with remarkable tissue specificity through a diversity of mechanisms, highlighting our rapidly evolving understanding of the non-coding genome.