Detecting actively translated open reading frames in ribosome profiling data

Unveiling the regulatory role of GRP7 in ABA signal-mediated mRNA translation efficiency regulation

Abscisic acid (ABA) is a crucial phytohormone involved in plant growth and stress responses. While the transcriptional regulation triggered by ABA is well-documented, its effects on translational regulation have been less studied. Through Ribo-seq and RNA-seq analyses, we find that ABA treatment not only influences gene expression at the mRNA level but also significantly impacts mRNA translation efficiency (TE) in Arabidopsis thaliana. ABA inhibits global mRNA translation via its core signaling pathway, which includes ABA receptors, protein phosphatase 2Cs (PP2Cs), and SNF1-related protein kinase 2 s (SnRK2s). Upon ABA treatment, Glycine-rich RNA-binding proteins 7 and 8 (GRP7&8) protein levels decrease due to both reduced mRNA level and decreased TE, which diminishes their association with polysomes and leads to a global decline in mRNA TE. The absence of GRP7&8 results in a global impairment of ABA-regulated translational changes, linking ABA signaling to GRP7-dependent modulation of mRNA translation. The regulation of GRP7 on TE relies significantly on its direct binding to target mRNAs. Moreover, mRNA translation efficiency under drought stress is partially dependent on the ABA-GRP7&8 pathways. Collectively, our study reveals GRP7's role downstream of SnRK2s in mediating translation regulation in ABA signaling, offering a model for ABA-triggered multi-route regulation of environmental adaptation.

tRNA modifications tune m6A-dependent mRNA decay

Chemically modified nucleotides in mRNA are critical regulators of gene expression, primarily through interactions with reader proteins that bind to these modifications. Here, we present a mechanism by which the epitranscriptomic mark N6-methyladenosine (m6A) is read by tRNAs during translation. Codons that are modified with m6A are decoded inefficiently by the ribosome, rendering them "non-optimal" and inducing ribosome collisions on cellular transcripts. This couples mRNA translation to decay. 5-Methoxycarbonylmethyl-2-thiouridine (mcm5s2U) in the tRNA anticodon loop counteracts this effect. This unanticipated link between the mRNA and tRNA epitranscriptomes enables the coordinated decay of mRNA regulons, including those encoding oncogenic signaling pathways. In cancer, dysregulation of the m6A and mcm5s2U biogenesis pathways-marked by a shift toward more mcm5s2U-is associated with more aggressive tumors and poor prognosis. Overall, this pan-epitranscriptomic interaction represents a novel mechanism of post-transcriptional gene regulation with implications for human health.

Chloroplast precursor protein preClpD overaccumulation triggers multilevel reprogramming of gene expression and a heat shock-like response

Thousands of nucleus-encoded chloroplast proteins are synthesized as precursors on cytosolic ribosomes and posttranslationally imported into chloroplasts. Cytosolic accumulation of unfolded chloroplast precursor proteins (e.g., under stress conditions) is hazardous to the cell. The global cellular responses and regulatory pathways involved in triggering appropriate responses are largely unknown. Here, by inducible and constitutive overexpression of ClpD-GFP to result in precursor protein overaccumulation, we present a comprehensive picture of multilevel reprogramming of gene expression in response to chloroplast precursor overaccumulation stress (cPOS), reveal a critical role of translational activation in the expression of cytosolic chaperones (heat-shock proteins, HSPs), and demonstrate that chloroplast-derived reactive oxygen species act as retrograde signal for the transcriptional activation of small HSPs. Furthermore, we reveal an important role of the chaperone ClpB1/HOT1 in maintaining cellular proteostasis upon cPOS. Together, our observations uncover a cytosolic heat shock-like response to cPOS and provide insights into the underlying molecular mechanisms.

RiboParser/RiboShiny: an integrated platform for comprehensive analysis and visualization of Ribo-seq data

Translation is a crucial step in gene expression. Over the past decade, the development and application of Ribosome profiling (Ribo-seq) have significantly advanced our understanding of translational regulation in vivo. However, the analysis and visualization of Ribo-seq data remain challenging. Despite the availability of various analytical pipelines, improvements in comprehensiveness, accuracy, and user-friendliness are still necessary. In this study, we develop RiboParser/RiboShiny, a robust framework for analyzing and visualizing Ribo-seq data. Building on published methods, we optimize ribosome structure-based and start/stop-based models to improve the accuracy and stability of P-site detection, even in species with a high proportion of leaderless transcripts. Leveraging these improvements, RiboParser offers comprehensive analyses, including quality control, gene-level analysis, codon-level analysis, and the analysis of Ribo-seq variants. Meanwhile, RiboShiny provides a user-friendly and adaptable platform for data visualization, facilitating deeper insights into the translational landscape. Furthermore, the integration of standardized genome annotation renders our platform universally applicable to various organisms with sequenced genomes. This framework has the potential to significantly improve the precision and efficiency of Ribo-seq data interpretation, thereby deepening our understanding of translational regulation.

RIBOSS detects novel translational events by combining long- and short-read transcriptome and translatome profiling

Ribosome profiling is a high-throughput sequencing technique that captures the positions of translating ribosomes on RNAs. Recent advancements in ribosome profiling include achieving highly phased ribosome footprints for plant translatomes and more recently for bacterial translatomes. This substantially increases the specificity of detecting open reading frames (ORFs) that can be translated, such as small ORFs located upstream and downstream of the annotated ORFs. However, most genomes (e.g. bacterial genomes) lack the annotations for the transcription start and termination sites. This hinders the systematic discovery of novel ORFs in the 'untranslated' regions in ribosome profiling data. Here, we develop a new computational pipeline called RIBOSS to discover noncanonical ORFs and assess their translational potential against annotated ORFs. The RIBOSS Python modules are versatile, and we use them to analyse both prokaryotic and eukaryotic data. We present a resulting list of noncanonical ORFs with high translational potential in Homo sapiens, Arabidopsis thaliana, and Salmonella enterica. We further illustrate RIBOSS utility when studying organisms with incomplete transcriptome annotations. We leverage long-read and short-read data for reference-guided transcriptome assembly and highly phased ribosome profiling data for detecting novel translational events in the assembled transcriptome for S. enterica. In sum, RIBOSS is the first integrated computational pipeline for noncanonical ORF detection and translational potential assessment that incorporates long- and short-read sequencing technologies to investigate translation. RIBOSS is freely available at https://github.com/lcscs12345/riboss.

Ribosome profiling reveals dynamic translational landscape following X-ray irradiation

X-ray irradiation induces widespread changes in gene expression. Positioned at the bottom of the central dogma, translational regulation responds swiftly to environmental stimuli, fine-tuning protein levels. However, the global view of mRNA translation following X-ray exposure remains unclear. In this study, we systematically investigated X-ray-induced translational alternation using ribosome profiling. Our study revealed a temporary translation inhibition in HEK293T cells following X-ray treatment. A subset of mRNAs experienced translational upregulation by bypassing upstream open reading frames (uORFs). The upregulated genes were enriched in the MAPK signaling pathway, such as MAPKBP1. Suppression of MAPKBP1 inhibited X-ray-induced cell apoptosis. Furthermore, we identified the induction of novel peptides encoded by small open reading frames (smORFs) within long non-coding RNAs (lncRNAs) upon X-ray treatment. Overall, our findings provide a comprehensive overview of the translational landscape within eukaryotic cells following X-ray treatment, offering new insights into DNA damage response.

Comprehensive discovery and functional characterization of the noncanonical proteome

The systematic identification and functional characterization of noncanonical translation products, such as novel peptides, will facilitate the understanding of the human genome and provide new insights into cell biology. Here, we constructed a high-coverage peptide sequencing reference library with 11,668,944 open reading frames and employed an ultrafiltration tandem mass spectrometry assay to identify novel peptides. Through these methods, we discovered 8945 previously unannotated peptides from normal gastric tissues, gastric cancer tissues and cell lines, nearly half of which were derived from noncoding RNAs. Moreover, our CRISPR screening revealed that 1161 peptides are involved in tumor cell proliferation. The presence and physiological function of a subset of these peptides, selected based on screening scores, amino acid length, and various indicators, were verified through Flag-knockin and multiple other methods. To further characterize the potential regulatory mechanisms involved, we constructed a framework based on artificial intelligence structure prediction and peptide‒protein interaction network analysis for the top 100 candidates and revealed that these cancer-related peptides have diverse subcellular locations and participate in organelle-specific processes. Further investigation verified the interacting partners of pep1-nc-OLMALINC, pep5-nc-TRHDE-AS1, pep-nc-ZNF436-AS1 and pep2-nc-AC027045.3, and the functions of these peptides in mitochondrial complex assembly, energy metabolism, and cholesterol metabolism, respectively. We showed that pep5-nc-TRHDE-AS1 and pep2-nc-AC027045.3 had substantial impacts on tumor growth in xenograft models. Furthermore, the dysregulation of these four peptides is closely correlated with clinical prognosis. Taken together, our study provides a comprehensive characterization of the noncanonical proteome, and highlights critical roles of these previously unannotated peptides in cancer biology.

ggRibo: a ggplot-based single-gene viewer for visualizing Ribo-seq and related omics datasets

Visualizing periodic Ribo-seq data within genes of interest is a powerful approach to studying mRNA translation, but its application is limited by a lack of robust tools. Here, we introduce ggRibo, a user-friendly R package for visualizing individual gene expression, integrating Ribo-seq, RNA-seq, and other genome-wide datasets with flexible scaling options. ggRibo presents the 3-nucleotide periodicity, a hallmark of translating ribosomes, within a gene-structure context, including introns and untranslated regions, enabling the study of novel ORFs, isoform translation, and mechanisms of translational regulation. ggRibo can plot multiple Ribo-seq/RNA-seq datasets from different conditions for comparison. Additionally, it supports the visualization of other omics datasets that could also be presented with single-nucleotide resolution, such as RNA degradome, transcription start sites, and translation initiation sites. Through its intuitive and flexible platform, ggRibo enables parallel comparisons of multi-omic datasets, facilitating a comprehensive understanding of gene expression regulation and promoting hypothesis generation. We demonstrate its utility with examples of upstream ORFs, downstream ORFs, isoform translation, and multi-omic comparison in humans and Arabidopsis. In summary, ggRibo is an advanced single-gene viewer that enhances the interpretation of translatome and related genome-wide datasets, offering a valuable resource for studying gene expression regulation. ggRibo is available on GitHub (https://github.com/hsinyenwu/ggRibo).

Microproteins in cancer: identification, biological functions, and clinical implications

Cancer continues to be a major global health challenge, accounting for 10 million deaths annually worldwide. Since the inception of genome-wide cancer sequencing studies 20 years ago, a core set of ~700 oncogenes and tumor suppressor genes has become the basis for cancer research. However, this research has been based largely on an understanding that the human genome encodes ~19 500 protein-coding genes. Complementing this genomic landscape, recent advances have described numerous microproteins which are now poised to redefine our understanding of oncogenic processes and open new avenues for therapeutic intervention. This review explores the emerging evidence for microprotein involvement in cancer mechanisms and discusses potential therapeutic applications, with an emphasis on highlighting recent advances in the field.

Micropeptides derived from long non-coding RNAs: Computational analysis and functional roles in breast cancer and other diseases

Long non-coding RNAs (lncRNAs), once thought to be mere transcriptional noise, are now revealing a hidden code. Recent advancements like ribosome sequencing have unveiled that many lncRNAs harbor small open reading frames and can potentially encode functional micropeptides. Emerging research suggests these micropeptides, not the lncRNAs themselves, play crucial roles in regulating homeostasis, inflammation, metabolism, and especially in breast cancer progression. This review delves into the rapidly evolving computational tools used to predict and validate lncRNA-encoded micropeptides. We then explore the diverse functions and mechanisms of action of these micropeptides in breast cancer pathogenesis, with a focus on their roles in various species. Ultimately, this review aims to illuminate the functional landscape of lncRNA-encoded micropeptides and their potential as therapeutic targets in cancer.

Unlocking the secrets of the immunopeptidome: MHC molecules, ncRNA peptides, and vesicles in immune response

The immunopeptidome, a diverse set of peptides presented by Major Histocompatibility Complex (MHC) molecules, is a critical component of immune recognition and response. This review article delves into the mechanisms of peptide presentation by MHC molecules, particularly emphasizing the roles of ncRNA-derived peptides and extracellular vesicles (EVs) in shaping the immunopeptidome landscape. We explore established and emerging insights into MHC molecule interactions with peptides, including the dynamics of peptide loading, transport, and the influence of cellular and genetic variations. The article highlights novel research on non-coding RNA (ncRNA)-derived peptides, which challenge conventional views of antigen processing and presentation and the role of EVs in transporting these peptides, thereby modulating immune responses at remote body sites. This novel research not only challenges conventional views but also opens up new avenues for understanding immune responses. Furthermore, we discuss the implications of these mechanisms in developing therapeutic strategies, particularly for cancer immunotherapy. By conducting a comprehensive analysis of current literature and advanced methodologies in immunopeptidomics, this review aims to deepen the understanding of the complex interplay between MHC peptide presentation and the immune system, offering new perspectives on potential diagnostic and therapeutic applications. Additionally, the interactions between ncRNA-derived peptides and EVs provide a mechanism for the enhanced surface presentation of these peptides and highlight a novel pathway for their systemic distribution, potentially altering immune surveillance and therapeutic landscapes.

RiboSeq.Org: an integrated suite of resources for ribosome profiling data analysis and visualization

Ribosome profiling (Ribo-Seq) has revolutionised our understanding of translation, but the increasing complexity and volume of Ribo-Seq data present challenges for its reuse. Here, we formally introduce RiboSeq.Org, an integrated suite of resources designed to facilitate Ribo-Seq data analysis and visualisation within a web browser. RiboSeq.Org comprises several interconnected tools: GWIPS-viz for genome-wide visualisation, Trips-Viz for transcriptome-centric analysis, RiboGalaxy for data processing and the newly developed RiboSeq data portal (RDP) for centralised dataset identification and access. The RDP currently hosts preprocessed datasets corresponding to 14840 sequence libraries (samples) from 969 studies across 96 species, in various file formats along with standardised metadata. RiboSeq.Org addresses key challenges in Ribo-Seq data reuse through standardised sample preprocessing, semi-automated metadata curation and programmatic information access via a REST API and command-line utilities. RiboSeq.Org enhances the accessibility and utility of public Ribo-Seq data, enabling researchers to gain new insights into translational regulation and protein synthesis across diverse organisms and conditions. By providing these integrated, user-friendly resources, RiboSeq.Org aims to lower the barrier to reproducible research in the field of translatomics and promote more efficient utilisation of the wealth of available Ribo-Seq data.

Evaluation of Eukaryotic mRNA Coding Potential

It is widely discussed that eukaryotic mRNAs can encode several functional polypeptides. Recent progress in NGS and proteomics techniques has resulted in a huge volume of information on potential alternative translation initiation sites and open reading frames (altORFs). However, these data are still incomprehensive, and the vast majority of eukaryotic mRNAs annotated in conventional databases (e.g., GenBank) contain a single ORF (CDS) encoding a protein larger than some arbitrary threshold (commonly 100 amino acid residues). Indeed, some gene functions may relate to the polypeptides encoded by unannotated altORFs, and insufficient information in nucleotide sequence databanks may limit the interpretation of genomics and transcriptomics data. However, despite the need for special experiments to predict altORFs accurately, there are some simple methods for their preliminary mapping.

Transcriptome and translatome profiling of Col-0 and grp7grp8 under ABA treatment in Arabidopsis

Abscisic acid (ABA) is a crucial phytohormone that regulates plant growth and stress responses. While substantial knowledge exists about transcriptional regulation, the molecular mechanisms underlying ABA-triggered translational regulation remain unclear. Recent advances in deep sequencing of ribosome footprints (Ribo-seq) enable the mapping and quantification of mRNA translation efficiency. Additionally, RNA-binding proteins (RBPs) play essential roles in translational regulation by interacting with target RNA molecules, making the identification of binding sites via UV crosslinking and immunoprecipitation (CLIP) critical for understanding RBP function. Glycine-rich RNA-binding proteins (GRPs), a prominent class of RBPs in plants, are responsive to ABA. In this study, RNA-seq and Ribo-seq analyses were conducted on 3-day-old Col-0 and grp7grp8 seedlings of Arabidopsis thaliana, treated with either ABA or mock solutions. These analyses facilitated deep sequencing of total mRNA and mRNA fragments protected by translating ribosomes. Additionally, CLIP-seq analysis of pGRP7::GRP7-GFP grp7-1 identified RNA bound by GRP7. This multi-omics dataset allows for a comprehensive investigation of the plant's response to ABA from various perspectives, providing a significant resource for studying ABA-regulated mRNA translation efficiency.

Transposable element exonization generates a reservoir of evolving and functional protein isoforms

Alternative splicing enhances protein diversity in different ways, including through exonization of transposable elements (TEs). Recent transcriptomic analyses identified thousands of unannotated spliced transcripts with exonizing TEs, but their contribution to the proteome and biological relevance remains unclear. Here, we use transcriptome assembly, ribosome profiling, and proteomics to describe a population of 1,227 unannotated TE exonizing isoforms generated by mRNA splicing and recurrent in human populations. Despite being shorter and lowly expressed, these isoforms are shared between individuals and efficiently translated. Functional analyses show stable expression, specific cellular localization, and, in some cases, modified functions. Exonized TEs are rich in ancient genes, whereas the involved splice sites are recent and can be evolutionarily conserved. In addition, exonized TEs contribute to the secondary structure of the emerging isoforms, supporting their functional relevance. We conclude that TE-spliced isoforms represent a diversity reservoir of functional proteins on which natural selection can act.

AthRiboNC: an Arabidopsis database for ncRNAs with coding potential revealed from ribosome profiling

Non-coding RNAs (ncRNAs) are traditionally considered incapable of encoding proteins, but new evidence suggests that small open reading frames (sORFs) within ncRNAs can actually encode biologically functional small peptides. Despite growing recognition of their importance, a systematic exploration of plant ncRNAs with coding potential has remained largely uncharted territory, especially in the context of their translational activities. By collecting and analyzing Ribo-Seq data from 226 Arabidopsis thaliana samples, we have integrated extensive information on Arabidopsis ncRNAs with coding potential and developed the AthRiboNC database, a novel and dedicated database that consolidates extensive information on ncRNAs with coding potential in Arabidopsis. AthRiboNC covers detailed information on 2743 long non-coding RNAs, 255 microRNAs, and 1871 circular RNA in Arabidopsis, along with 40 162 ORFs identified from these ncRNAs. The database also constructs co-expression networks for ncRNAs with coding potential, revealing correlations and potential biological function interpretations. With a commitment to accessibility and ease-of-use, AthRiboNC features a clear and intuitive interface. We hope that AthRiboNC will serve as a valuable resource for exploring the coding potential of plant ncRNAs. Database URL: https://bis.zju.edu.cn/athribonc.

Exploring the potential of large language model-based chatbots in challenges of ribosome profiling data analysis: a review

Ribosome profiling (Ribo-seq) provides transcriptome-wide insights into protein synthesis dynamics, yet its analysis poses challenges, particularly for nonbioinformatics researchers. Large language model-based chatbots offer promising solutions by leveraging natural language processing. This review explores their convergence, highlighting opportunities for synergy. We discuss challenges in Ribo-seq analysis and how chatbots mitigate them, facilitating scientific discovery. Through case studies, we illustrate chatbots' potential contributions, including data analysis and result interpretation. Despite the absence of applied examples, existing software underscores the value of chatbots and the large language model. We anticipate their pivotal role in future Ribo-seq analysis, overcoming limitations. Challenges such as model bias and data privacy require attention, but emerging trends offer promise. The integration of large language models and Ribo-seq analysis holds immense potential for advancing translational regulation and gene expression understanding.

Recent Advances in Peptide Drug Discovery: Novel Strategies and Targeted Protein Degradation

Recent technological advancements, including computer-assisted drug discovery, gene-editing techniques, and high-throughput screening approaches, have greatly expanded the palette of methods for the discovery of peptides available to researchers. These emerging strategies, driven by recent advances in bioinformatics and multi-omics, have significantly improved the efficiency of peptide drug discovery when compared with traditional in vitro and in vivo methods, cutting costs and improving their reliability. An added benefit of peptide-based drugs is the ability to precisely target protein-protein interactions, which are normally a particularly challenging aspect of drug discovery. Another recent breakthrough in this field is targeted protein degradation through proteolysis-targeting chimeras. These revolutionary compounds represent a noteworthy advancement over traditional small-molecule inhibitors due to their unique mechanism of action, which allows for the degradation of specific proteins with unprecedented specificity. The inclusion of a peptide as a protein-of-interest-targeting moiety allows for improved versatility and the possibility of targeting otherwise undruggable proteins. In this review, we discuss various novel wet-lab and computational multi-omic methods for peptide drug discovery, provide an overview of therapeutic agents discovered through these cutting-edge techniques, and discuss the potential for the therapeutic delivery of peptide-based drugs.

HOT3/eIF5B1 confers Kozak motif-dependent translational control of photosynthesis-associated nuclear genes for chloroplast biogenesis

Photosynthesis requires chloroplasts, in which most proteins are nucleus-encoded and produced via cytoplasmic translation. The translation initiation factor eIF5B gates the transition from initiation (I) to elongation (E), and the Kozak motif is associated with translation efficiency, but their relationship is previously unknown. Here, with ribosome profiling, we determined the genome-wide I-E transition efficiencies. We discovered that the most prevalent Kozak motif is associated with high I-E transition efficiency in Arabidopsis, rice, and wheat, thus implicating the potential of the Kozak motif in facilitating the I-E transition. Indeed, the effects of Kozak motifs in promoting translation depend on HOT3/eIF5B1 in Arabidopsis. HOT3 preferentially promotes the translation of photosynthesis-associated nuclear genes in a Kozak motif-dependent manner, which explains the chloroplast defects and reduced photosynthesis activity of hot3 mutants. Our study linked the Kozak motif to eIF5B-mediated I-E transition during translation and uncovered the function of HOT3 in the cytoplasmic translational control of chloroplast biogenesis and photosynthesis.

Interpreting deep neural networks for the prediction of translation rates

BACKGROUND

The 5' untranslated region of mRNA strongly impacts the rate of translation initiation. A recent convolutional neural network (CNN) model accurately quantifies the relationship between massively parallel synthetic 5' untranslated regions (5'UTRs) and translation levels. However, the underlying biological features, which drive model predictions, remain elusive. Uncovering sequence determinants predictive of translation output may allow us to develop a more detailed understanding of translation regulation at the 5'UTR.

RESULTS

Applying model interpretation, we extract representations of regulatory logic from CNNs trained on synthetic and human 5'UTR reporter data. We reveal a complex interplay of regulatory sequence elements, such as initiation context and upstream open reading frames (uORFs) to influence model predictions. We show that models trained on synthetic data alone do not sufficiently explain translation regulation via the 5'UTR due to differences in the frequency of regulatory motifs compared to natural 5'UTRs.

CONCLUSIONS

Our study demonstrates the significance of model interpretation in understanding model behavior, properties of experimental data and ultimately mRNA translation. By combining synthetic and human 5'UTR reporter data, we develop a model (OptMRL) which better captures the characteristics of human translation regulation. This approach provides a general strategy for building more successful sequence-based models of gene regulation, as it combines global sampling of random sequences with the subspace of naturally occurring sequences. Ultimately, this will enhance our understanding of 5'UTR sequences in disease and our ability to engineer translation output.

An AI Agent for Fully Automated Multi-Omic Analyses

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle bioinformatics analysis continues to grow. In response to this need, Automated Bioinformatics Analysis (AutoBA) is introduced, an autonomous AI agent designed explicitly for fully automated multi-omic analyses based on large language models (LLMs). AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. AutoBA's unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA offers multiple LLM backends, with options for both online and local usage, prioritizing data security and user privacy. In comparison to ChatGPT and open-source LLMs, an automated code repair (ACR) mechanism in AutoBA is designed to improve its stability in automated end-to-end bioinformatics analysis tasks. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents an advanced and convenient tool, offering robustness and adaptability for conventional multi-omic analyses.

Human DCP1 is crucial for mRNA decapping and possesses paralog-specific gene regulating functions

The mRNA 5'-cap structure removal by the decapping enzyme DCP2 is a critical step in gene regulation. While DCP2 is the catalytic subunit in the decapping complex, its activity is strongly enhanced by multiple factors, particularly DCP1, which is the major activator in yeast. However, the precise role of DCP1 in metazoans has yet to be fully elucidated. Moreover, in humans, the specific biological functions of the two DCP1 paralogs, DCP1a and DCP1b, remain largely unknown. To investigate the role of human DCP1, we generated cell lines that were deficient in DCP1a, DCP1b, or both to evaluate the importance of DCP1 in the decapping machinery. Our results highlight the importance of human DCP1 in decapping process and show that the EVH1 domain of DCP1 enhances the mRNA-binding affinity of DCP2. Transcriptome and metabolome analyses outline the distinct functions of DCP1a and DCP1b in human cells, regulating specific endogenous mRNA targets and biological processes. Overall, our findings provide insights into the molecular mechanism of human DCP1 in mRNA decapping and shed light on the distinct functions of its paralogs.

Upstream open reading frames may contain hundreds of novel human exons

Several recent studies have presented evidence that the human gene catalogue should be expanded to include thousands of short open reading frames (ORFs) appearing upstream or downstream of existing protein-coding genes, each of which might create an additional bicistronic transcript in humans. Here we explore an alternative hypothesis that would explain the translational and evolutionary evidence for these upstream ORFs without the need to create novel genes or bicistronic transcripts. We examined 2,199 upstream ORFs that have been proposed as high-quality candidates for novel genes, to determine if they could instead represent protein-coding exons that can be added to existing genes. We checked for the conservation of these ORFs in four recently sequenced, high-quality human genomes, and found a large majority (87.8%) to be conserved in all four as expected. We then looked for splicing evidence that would connect each upstream ORF to the downstream protein-coding gene at the same locus, thus creating a novel splicing variant using the upstream ORF as its first exon. These protein coding exon candidates were further evaluated using protein structure predictions of the protein sequences that included the proposed new exons. We determined that 541 out of 2,199 upstream ORFs have strong evidence that they can form protein coding exons that are part of an existing gene, and that the resulting protein is predicted to have similar or better structural quality than the currently annotated isoform.

Long non-coding RNA-encoded micropeptides: functions, mechanisms and implications

Long non-coding RNAs (lncRNAs) are typically described as RNA transcripts exceeding 200 nucleotides in length, which do not code for proteins. Recent advancements in technology, including ribosome RNA sequencing and ribosome nascent-chain complex sequencing, have demonstrated that many lncRNAs retain small open reading frames and can potentially encode micropeptides. Emerging studies have revealed that these micropeptides, rather than lncRNAs themselves, are responsible for vital functions, including but not limited to regulating homeostasis, managing inflammation and the immune system, moderating metabolism, and influencing tumor progression. In this review, we initially outline the rapidly advancing computational analytical methods and public tools to predict and validate the potential encoding of lncRNAs. We then focus on the diverse functions of micropeptides and their underlying mechanisms in the pathogenesis of disease. This review aims to elucidate the functions of lncRNA-encoded micropeptides and explore their potential applications as therapeutic targets in cancer.

Multi-Omic Approaches in Cancer-Related Micropeptide Identification

Despite the advances in modern cancer therapy, malignant diseases are still a leading cause of morbidity and mortality worldwide. Conventional treatment methods frequently lead to side effects and drug resistance in patients, highlighting the need for novel therapeutic approaches. Recent findings have identified the existence of non-canonical micropeptides, an additional layer of the proteome complexity, also called the microproteome. These small peptides are a promising class of therapeutic agents with the potential to address the limitations of current cancer treatments. The microproteome is encoded by regions of the genome historically annotated as non-coding, and its existence has been revealed thanks to recent advances in proteomic and bioinformatic technology, which dramatically improved the understanding of proteome complexity. Micropeptides have been shown to be biologically active in several cancer types, indicating their therapeutic role. Furthermore, they are characterized by low toxicity and high target specificity, demonstrating their potential for the development of better tolerated drugs. In this review, we survey the current landscape of known micropeptides with a role in cancer progression or treatment, discuss their potential as anticancer agents, and describe the methodological challenges facing the proteome field of research.

Experimental approaches to studying translation in plant semi-autonomous organelles

Plant mitochondria and chloroplasts are semi-autonomous organelles originated from free-living bacteria that have retained reduced genomes during evolution. As a consequence, relatively few of the mitochondrial and chloroplast proteins are encoded in the organellar genomes and synthesized by the organellar ribosomes. Since both organellar genomes encode mainly components of the energy transduction systems, oxidative phosphorylation in mitochondria and photosynthetic apparatus in chloroplasts, understanding organellar translation is critical for a thorough comprehension of key aspects of mitochondrial and chloroplast activity affecting plant growth and development. Recent studies have clearly shown that translation is a key regulatory node in the expression of plant organellar genes, underscoring the need for an adequate methodology to study this unique stage of gene expression. The organellar translatome can be analysed by studying newly synthesized proteins or the mRNA pool recruited to the organellar ribosomes. In this review, we present experimental approaches used for studying translation in plant bioenergetic organelles. Their benefits and limitations, as well as the critical steps, are discussed. Additionally, we briefly mention several recently developed strategies to study organellar translation that have not yet been applied to plants.

SMYD5 is a ribosomal methyltransferase that catalyzes RPL40 lysine methylation to enhance translation output and promote hepatocellular carcinoma

While lysine methylation is well-known for regulating gene expression transcriptionally, its implications in translation have been largely uncharted. Trimethylation at lysine 22 (K22me3) on RPL40, a core ribosomal protein located in the GTPase activation center, was first reported 27 years ago. Yet, its methyltransferase and role in translation remain unexplored. Here, we report that SMYD5 has robust in vitro activity toward RPL40 K22 and primarily catalyzes RPL40 K22me3 in cells. The loss of SMYD5 and RPL40 K22me3 leads to reduced translation output and disturbed elongation as evidenced by increased ribosome collisions. SMYD5 and RPL40 K22me3 are upregulated in hepatocellular carcinoma (HCC) and negatively correlated with patient prognosis. Depleting SMYD5 renders HCC cells hypersensitive to mTOR inhibition in both 2D and 3D cultures. Additionally, the loss of SMYD5 markedly inhibits HCC development and growth in both genetically engineered mouse and patient-derived xenograft (PDX) models, with the inhibitory effect in the PDX model further enhanced by concurrent mTOR suppression. Our findings reveal a novel role of the SMYD5 and RPL40 K22me3 axis in translation elongation and highlight the therapeutic potential of targeting SMYD5 in HCC, particularly with concurrent mTOR inhibition. This work also conceptually broadens the understanding of lysine methylation, extending its significance from transcriptional regulation to translational control.

Current limitations in predicting mRNA translation with deep learning models

BACKGROUND

The design of nucleotide sequences with defined properties is a long-standing problem in bioengineering. An important application is protein expression, be it in the context of research or the production of mRNA vaccines. The rate of protein synthesis depends on the 5' untranslated region (5'UTR) of the mRNAs, and recently, deep learning models were proposed to predict the translation output of mRNAs from the 5'UTR sequence. At the same time, large data sets of endogenous and reporter mRNA translation have become available.

RESULTS

In this study, we use complementary data obtained in two different cell types to assess the accuracy and generality of currently available models for predicting translational output. We find that while performing well on the data sets on which they were trained, deep learning models do not generalize well to other data sets, in particular of endogenous mRNAs, which differ in many properties from reporter constructs.

CONCLUSIONS

These differences limit the ability of deep learning models to uncover mechanisms of translation control and to predict the impact of genetic variation. We suggest directions that combine high-throughput measurements and machine learning to unravel mechanisms of translation control and improve construct design.

Rp3: Ribosome profiling-assisted proteogenomics improves coverage and confidence during microprotein discovery

There has been a dramatic increase in the identification of non-canonical translation and a significant expansion of the protein-coding genome. Among the strategies used to identify unannotated small Open Reading Frames (smORFs) that encode microproteins, Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple genomic sites are removed since they cannot be unambiguously assigned to a specific genomic location. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of multi-mapping alignments, such that smORFs residing in these regions cannot be identified by Ribo-Seq. Moreover, it has been challenging to identify protein evidence for Ribo-Seq. To solve this, we developed Rp3, a pipeline that integrates proteogenomics and Ribosome profiling to provide unambiguous evidence for a subset of microproteins missed by current Ribo-Seq pipelines. Here, we show that Rp3 maximizes proteomics detection and confidence of microprotein-encoding smORFs.

Human DDX6 regulates translation and decay of inefficiently translated mRNAs

Recent findings indicate that the translation elongation rate influences mRNA stability. One of the factors that has been implicated in this link between mRNA decay and translation speed is the yeast DEAD-box helicase Dhh1p. Here, we demonstrated that the human ortholog of Dhh1p, DDX6, triggers the deadenylation-dependent decay of inefficiently translated mRNAs in human cells. DDX6 interacts with the ribosome through the Phe-Asp-Phe (FDF) motif in its RecA2 domain. Furthermore, RecA2-mediated interactions and ATPase activity are both required for DDX6 to destabilize inefficiently translated mRNAs. Using ribosome profiling and RNA sequencing, we identified two classes of endogenous mRNAs that are regulated in a DDX6-dependent manner. The identified targets are either translationally regulated or regulated at the steady-state-level and either exhibit signatures of poor overall translation or of locally reduced ribosome translocation rates. Transferring the identified sequence stretches into a reporter mRNA caused translation- and DDX6-dependent degradation of the reporter mRNA. In summary, these results identify DDX6 as a crucial regulator of mRNA translation and decay triggered by slow ribosome movement and provide insights into the mechanism by which DDX6 destabilizes inefficiently translated mRNAs.

The blue light signaling inhibitor 3-bromo-7-nitroindazole affects gene translation at the initial reception of blue light in young Arabidopsis seedlings

Initial light reception after germination is a dramatic life event when a seedling starts proper morphogenesis. Blue light contains a range of light wavelengths that plants can perceive. A previous report suggested that the chemical compound 3-bromo-7-nitroindazole (3B7N) inhibits blue light-mediated suppression of hypocotyl elongation by physically interacting with the blue light receptor Cryptochrome 1 (CRY1). We previously examined changes of genome-wide gene expression in Arabidopsis seedlings germinated in the dark and then exposed to blue light by RNA-seq and Ribo-seq analyses. The expression of ribosome-related genes was translationally upregulated in response to the initial blue light exposure, depending on signals from both the nucleus and chloroplasts. Here, we re-analyzed our previous data and examined the effect of 3B7N treatment on changes in gene expression upon blue light exposure. The results showed that 3B7N negatively affected translation of ribosome-related genes and, interestingly, the effects were similar to not only those in cry1cry2 mutants but also plants under suppression of photosynthesis. We propose an apparent crosstalk between chloroplast function and blue light signaling.

Next generation sequencing technologies to address aberrant mRNA translation in cancer

In this review, we explore the transformative impact of next generation sequencing technologies in the realm of translatomics (the study of how translational machinery acts on a genome-wide scale). Despite the expectation of a direct correlation between mRNA and protein content, the complex regulatory mechanisms that affect this relationship remark the limitations of standard RNA-seq approaches. Then, the review characterizes crucial techniques such as polysome profiling, ribo-seq, trap-seq, proximity-specific ribosome profiling, rnc-seq, tcp-seq, qti-seq and scRibo-seq. All these methods are summarized within the context of cancer research, shedding light on their applications in deciphering aberrant translation in cancer cells. In addition, we encompass databases and bioinformatic tools essential for researchers that want to address translatome analysis in the context of cancer biology.

Thylakoid protein FPB1 synergistically cooperates with PAM68 to promote CP47 biogenesis and Photosystem II assembly

In chloroplasts, insertion of proteins with multiple transmembrane domains (TMDs) into thylakoid membranes usually occurs in a co-translational manner. Here, we have characterized a thylakoid protein designated FPB1 (Facilitator of PsbB biogenesis1) which together with a previously reported factor PAM68 (Photosynthesis Affected Mutant68) is involved in assisting the biogenesis of CP47, a subunit of the Photosystem II (PSII) core. Analysis by ribosome profiling reveals increased ribosome stalling when the last TMD segment of CP47 emerges from the ribosomal tunnel in fpb1 and pam68. FPB1 interacts with PAM68 and both proteins coimmunoprecipitate with SecY/E and Alb3 as well as with some ribosomal components. Thus, our data indicate that, in coordination with the SecY/E translocon and the Alb3 integrase, FPB1 synergistically cooperates with PAM68 to facilitate the co-translational integration of the last two CP47 TMDs and the large loop between them into thylakoids and the PSII core complex.

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy

With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor-specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the "dark matter" of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine-learning-supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.

Transcriptional and translational landscape fine-tune genome annotation and explores translation control in cotton

INTRODUCTION

The unavailability of intergenic region annotation in whole genome sequencing and pan-genomics hinders efforts to enhance crop improvement.

OBJECTIVES

Despite advances in research, the impact of post-transcriptional regulation on fiber development and translatome profiling at different stages of fiber growth in cotton (G. hirsutum) remains unexplored.

METHODS

We utilized a combination of reference-guided de novo transcriptome assembly and ribosome profiling techniques to uncover the hidden mechanisms of translational control in eight distinct tissues of upland cotton.

RESULTS

Our study identified P-site distribution at three-nucleotide periodicity and dominant ribosome footprint at 27 nucleotides. Specifically, we have detected 1,589 small open reading frames (sORFs), including 1,376 upstream ORFs (uORFs) and 213 downstream ORFs (dORFs), as well as 552 long non-coding RNAs (lncRNAs) with potential coding functions, which fine-tune the annotation of the cotton genome. Further, we have identified novel genes and lncRNAs with strong translation efficiency (TE), while sORFs were found to affect mRNA transcription levels during fiber elongation. The reliability of these findings was confirmed by the high consistency in correlation and synergetic fold change between RNA-sequencing (RNA-seq) and Ribosome-sequencing (Ribo-seq) analyses. Additionally, integrated omics analysis of the normal fiber ZM24 and short fiber pag1 cotton mutant revealed several differentially expressed genes (DEGs), and fiber-specific expressed (high/low) genes associated with sORFs (uORFs and dORFs). These findings were further supported by the overexpression and knockdown of GhKCS6, a gene associated with sORFs in cotton, and demonstrated the potential regulation of the mechanism governing fiber elongation on both the transcriptional and post-transcriptional levels.

CONCLUSION

Reference-guided transcriptome assembly and the identification of novel transcripts fine-tune the annotation of the cotton genome and predicted the landscape of fiber development. Our approach provided a high-throughput method, based on multi-omics, for discovering unannotated ORFs, hidden translational control, and complex regulatory mechanisms in crop plants.

Upstream open reading frames may contain hundreds of novel human exons

Several recent studies have presented evidence that the human gene catalogue should be expanded to include thousands of short open reading frames (ORFs) appearing upstream or downstream of existing protein-coding genes, each of which would comprise an additional bicistronic transcript in humans. Here we explore an alternative hypothesis that would explain the translational and evolutionary evidence for these upstream ORFs without the need to create novel genes or bicistronic transcripts. We examined 2,199 upstream ORFs that have been proposed as high-quality candidates for novel genes, to determine if they could instead represent protein-coding exons that can be added to existing genes. We checked for the conservation of these ORFs in four recently sequenced, high-quality human genomes, and found a large majority (87.8%) to be conserved in all four as expected. We then looked for splicing evidence that would connect each upstream ORF to the downstream protein-coding gene at the same locus, thus creating a novel splicing variant using the upstream ORF as its first exon. These protein coding exon candidates were further evaluated using protein structure predictions of the protein sequences that included the proposed new exons. We determined that 582 out of 2,199 upstream ORFs have strong evidence that they can form protein coding exons that are part of an existing gene, and that the resulting protein is predicted to have similar or better structural quality than the currently annotated isoform.

sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data

Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data.

The RNA m6A reader IGF2BP3 regulates NFAT1/IRF1 axis-mediated anti-tumor activity in gastric cancer

N6-methyladenosine (m6A) and its associated reader protein insulin like growth factor 2 mRNA binding protein 3 (IGF2BP3) are involved in tumor initiation and progression via regulating RNA metabolism. This study aims to investigate the biological function and clinical significance of IGF2BP3 in gastric cancer (GC). The clinical significance of IGF2BP3 was evaluated using tumor related databases and clinical tissues. The biological role and molecular mechanism of IGF2BP3 in GC progression were investigated by multi-omics analysis including Ribosome sequence (Ribo-seq), RNA sequence (RNA-seq) and m6A sequence (m6A-seq) combined with gain- and loss- of function experiments. IGF2BP3 expression is significantly elevated in GC tissues and associated with poor prognosis of GC patients. Knockdown of IGF2BP3 significantly weakens the migration and clonogenic ability, promotes the apoptosis, inhibits translation, and suppresses in vitro growth and progression of GC cells. Mechanistically, IGF2BP3 regulates the mRNA stability and translation of the nuclear factor of activated T cells 1(NFAT1) in a m6A dependent manner. Then NFAT1 induced by IGF2BP3 acts as a transcription factor (TF) to negatively regulates the promoter activities of interferon regulatory factor 1 (IRF1) to inhibit its expression. Inhibition of IGF2BP3-induced expression of IRF1 activates interferon (IFN) signaling pathway and then exerts its anti-tumor effect. Elevated IGF2BP3 promotes in vivo and in vitro GC progression via regulation of NFAT1/IRF1 pathways. Targeted inhibition of IGF2BP3 might be a potential therapeutic approach for GC treatment.

Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features

Studies have revealed dozens of functional peptides in putative 'noncoding' regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the probability that the encoded peptide is stable in humans. Systematic ectopic expression validates PepScore and shows that stable complex-associating microproteins can be encoded in 5'/3' untranslated regions and overlapping coding regions of mRNAs besides annotated noncoding RNAs. Stable noncanonical proteins follow conventional rules and localize to different subcellular compartments. Inhibition of proteasomal/lysosomal degradation pathways can stabilize some peptides especially those with moderate PepScores, but cannot rescue the expression of short ones with low PepScores suggesting they are directly degraded by cellular proteases. The majority of human noncanonical peptides with high PepScores show longer lengths but low conservation across species/mammals, and hundreds contain trait-associated genetic variants. Our study presents a statistical framework to identify stable noncanonical peptides in the genome and provides a valuable resource for functional characterization of noncanonical translation during development and disease.

Origin of functional de novo genes in humans from "hopeful monsters"

For a long time, it was believed that new genes arise only from modifications of preexisting genes, but the discovery of de novo protein-coding genes that originated from noncoding DNA regions demonstrates the existence of a "motherless" origination process for new genes. However, the features, distributions, expression profiles, and origin modes of these genes in humans seem to support the notion that their origin is not a purely "motherless" process; rather, these genes arise preferentially from genomic regions encoding preexisting precursors with gene-like features. In such a case, the gene loci are typically not brand new. In this short review, we will summarize the definition and features of human de novo genes and clarify their process of origination from ancestral non-coding genomic regions. In addition, we define the favored precursors, or "hopeful monsters," for the origin of de novo genes and present a discussion of the functional significance of these young genes in brain development and tumorigenesis in humans. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas

Ribosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq yields genome-wide insight into translational dynamics and post-transcriptional control of gene expression. Here, we provide details on the Ribo-seq method and the subsequent analysis with the unicellular model alga Chlamydomonas reinhardtii (Chlamydomonas) for generating high-resolution data covering more than 10 000 different transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5' and 3' sections of transcripts and characteristics of eukaryotic translation termination, which are fundamentally distinct for chloroplast translation. In chloroplasts, a heterogeneous RPF size distribution along the coding sequence indicates specific regulatory phases during protein synthesis. For example, local accumulation of small RPFs correlates with local slowdown of psbA translation, possibly uncovering an uncharacterized regulatory step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light-harvesting complex proteins, LHCs. By providing high-quality datasets for all subcellular genomes and attaching our data to the Chlamydomonas reference genome, we aim to make ribosome profiles easily accessible for the broad research community. The data can be browsed without advanced bioinformatic background knowledge for translation output levels of specific genes and their splice variants and for monitoring genome annotation.

Translatome and Transcriptome Analyses Reveal the Mechanism that Underlies the Enhancement of Salt Stress by the Small Peptide Ospep5 in Plants

Salt stress significantly impedes plant growth and the crop yield. This study utilized de novo transcriptome assembly and ribosome profiling to explore mRNA translation's role in rice salt tolerance. We identified unrecognized translated open reading frames (ORFs), including 42 upstream transcripts and 86 unannotated transcripts. A noteworthy discovery was the role of a small ORF, Ospep5, in conferring salt tolerance. Overexpression of Ospep5 in plants increased salt tolerance, while its absence led to heightened sensitivity. This hypothesis was corroborated by the findings that exogenous application of the synthetic small peptide Ospep5 bolstered salt tolerance in both rice and Arabidopsis. We found that the mechanism underpinning the Ospep5-mediated salt tolerance involves the maintenance of intracellular Na+/K+ homeostasis, facilitated by upregulation of high-affinity potassium transporters (HKT) and Na+/H+ exchangers (SOS1). Furthermore, a comprehensive multiomics approach, particularly ribosome profiling, is instrumental in uncovering unannotated ORFs and elucidating their functions in plant stress responses.

Improved super-resolution ribosome profiling reveals prevalent translation of upstream ORFs and small ORFs in Arabidopsis

A crucial step in functional genomics is identifying actively translated ORFs and linking them to biological functions. The challenge lies in identifying short ORFs, as their identification is greatly influenced by data quality and depth. Here, we improved the coverage of super-resolution Ribo-seq in Arabidopsis (Arabidopsis thaliana), revealing uncharacterized translation events for nuclear, chloroplastic, and mitochondrial genes. Assisted by a transcriptome assembly, we identified 7,751 unconventional translation events, comprising 6,996 upstream ORFs (uORFs) and 209 downstream ORFs on annotated protein-coding genes, as well as 546 ORFs in presumed noncoding RNAs. Proteomic data confirmed the production of stable proteins from some of these unannotated translation events. We present evidence of active translation from primary transcripts of trans-acting small interfering RNAs (TAS1-4) and microRNAs (pri-MIR163 and pri-MIR169) and periodic ribosome stalling supporting cotranslational decay. Additionally, we developed a method for identifying extremely short uORFs, including 370 minimum uORFs (AUG-stop), and 2,921 tiny uORFs (2 to 10 amino acids) and 681 uORFs that overlap with each other. Remarkably, these short uORFs exhibit strong translational repression as do longer uORFs. We also systematically discovered 594 uORFs regulated by alternative splicing, suggesting widespread isoform-specific translational control. Finally, these prevalent uORFs are associated with numerous important pathways. In summary, our improved Arabidopsis translational landscape provides valuable resources to study gene expression regulation.

No country for old methods: New tools for studying microproteins

Microproteins encoded by small open reading frames (sORFs) have emerged as a fascinating frontier in genomics. Traditionally overlooked due to their small size, recent technological advancements such as ribosome profiling, mass spectrometry-based strategies and advanced computational approaches have led to the annotation of more than 7000 sORFs in the human genome. Despite the vast progress, only a tiny portion of these microproteins have been characterized and an important challenge in the field lies in identifying functionally relevant microproteins and understanding their role in different cellular contexts. In this review, we explore the recent advancements in sORF research, focusing on the new methodologies and computational approaches that have facilitated their identification and functional characterization. Leveraging these new tools hold great promise for dissecting the diverse cellular roles of microproteins and will ultimately pave the way for understanding their role in the pathogenesis of diseases and identifying new therapeutic targets.

Making sense of mRNA translational "noise"

The importance of translation fidelity has been apparent since the discovery of genetic code. It is commonly believed that translation deviating from the main coding region is to be avoided at all times inside cells. However, ribosome profiling and mass spectrometry have revealed pervasive noncanonical translation. Both the scope and origin of translational "noise" are just beginning to be appreciated. Although largely overlooked, those translational "noises" are associated with a wide range of cellular functions, such as producing unannotated protein products. Furthermore, the dynamic nature of translational "noise" is responsive to stress conditions, highlighting the beneficial effect of translational "noise" in stress adaptation. Mechanistic investigation of translational "noise" will provide better insight into the mechanisms of translational regulation. Ultimately, they are not "noise" at all but represent a signature of cellular activities under pathophysiological conditions. Deciphering translational "noise" holds the therapeutic and diagnostic potential in a wide spectrum of human diseases.

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/β) 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.

Ribosome Profiling of Plants

Translation is a key step in control of gene expression, yet most analyses of global responses to a stimulus focus on transcription and the transcriptome. For RNA viruses in particular, which have no DNA-templated transcriptional control, control of viral and host translation is crucial. Here, we describe the method of ribosome profiling (ribo-seq) in plants, applied to virus infection. Ribo-seq is a deep sequencing technique that reveals the translatome by presenting a snapshot of the positions and relative amounts of translating ribosomes on all mRNAs in the cell. In contrast to RNA-seq, a crude cell extract is first digested with ribonuclease to degrade all mRNA not protected by a translating 80S ribosome. The resulting ribosome-protected fragments (RPFs) are deep sequenced. The number of reads mapping to a specific mRNA compared to the standard RNA-seq reads reveals the translational efficiency of that mRNA. Moreover, the precise positions of ribosome pause sites, previously unknown translatable open reading frames, and noncanonical translation events can be characterized quantitatively using ribo-seq. As this technique requires meticulous technique, here we present detailed step-by-step instructions for cell lysate preparation by flash freezing of samples, nuclease digestion of cell lysate, monosome collection by sucrose cushion ultracentrifugation, size-selective RNA extraction and rRNA depletion, library preparation for sequencing and finally quality control of sequenced data. These experimental methods apply to many plant systems, with minor nuclease digestion modifications depending on the plant tissue and species. This protocol should be valuable for studies of plant virus gene expression, and the global translational response to virus infection, or any other biotic or abiotic stress, by the host plant.

Synonymous codon usage regulates translation initiation

Nonoptimal synonymous codons repress gene expression, but the underlying mechanisms are poorly understood. We and others have previously shown that nonoptimal codons slow translation elongation speeds and thereby trigger messenger RNA (mRNA) degradation. Nevertheless, transcript levels are often insufficient to explain protein levels, suggesting additional mechanisms by which codon usage regulates gene expression. Using reporters in human and Drosophila cells, we find that transcript levels account for less than half of the variation in protein abundance due to codon usage. This discrepancy is explained by translational differences whereby nonoptimal codons repress translation initiation. Nonoptimal transcripts are also less bound by the translation initiation factors eIF4E and eIF4G1, providing a mechanistic explanation for their reduced initiation rates. Importantly, translational repression can occur without mRNA decay and deadenylation, and it does not depend on the known nonoptimality sensor, CNOT3. Our results reveal a potent mechanism of regulation by codon usage where nonoptimal codons repress further rounds of translation.

Discovery of regulatory motifs in 5' untranslated regions using interpretable multi-task learning models

The sequence in the 5' untranslated regions (UTRs) is known to affect mRNA translation rates. However, the underlying regulatory grammar remains elusive. Here, we propose MTtrans, a multi-task translation rate predictor capable of learning common sequence patterns from datasets across various experimental techniques. The core premise is that common motifs are more likely to be genuinely involved in translation control. MTtrans outperforms existing methods in both accuracy and the ability to capture transferable motifs across species, highlighting its strength in identifying evolutionarily conserved sequence motifs. Our independent fluorescence-activated cell sorting coupled with deep sequencing (FACS-seq) experiment validates the impact of most motifs identified by MTtrans. Additionally, we introduce "GRU-rewiring," a technique to interpret the hidden states of the recurrent units. Gated recurrent unit (GRU)-rewiring allows us to identify regulatory element-enriched positions and examine the local effects of 5' UTR mutations. MTtrans is a powerful tool for deciphering the translation regulatory motifs.