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Glioblastoma is one of the most lethal brain diseases in humans. Although recent studies have shown reciprocal interactions between N6-methyladenosine (m6A) modifications and long noncoding RNAs (lncRNAs) in gliomagenesis and malignant progression, the mechanism of m6A-mediated lncRNA translational regulation in glioblastoma remains unclear. Herein, we profiled the transcriptomes, translatomes, and epitranscriptomics of glioma stem cells and differentiated glioma cells to investigate the role of m6A in lncRNA translation comprehensively. We found that lncRNAs with numerous m6A peaks exhibit reduced translation efficiency. Transcript-level expression analysis demonstrates an enrichment of m6A around short open reading frames (sORFs) of translatable lncRNA transcripts. Further comparison analysis of m6A modifications in different RNA regions indicates that m6A peaks downstream of sORFs inhibit lncRNA translation more than those upstream. Observations in glioma-associated lncRNAs H19 , LINC00467 , and GAS5 further confirm the negative effect of m6A methylation on lncRNA translation. Overall, these findings elucidate the dynamic profiles of the m6A methylome and enhance the understanding of the complexity of lncRNA translational regulation. [ABSTRACT FROM AUTHOR]

Simple Summary: Small open reading frames (sORFs; fewer than 300 nucleotides or fewer than 100 amino acids) are short DNA sequences that can regulate cellular processes or produce functional peptides. Identifying these sORFs, especially in non-genic regions, remains challenging despite advances in sequencing technology. To address this, we developed D-sORF, a machine-learning framework that predicts coding sORFs using the nucleotide context and motifs around start codons. D-sORF achieves 94.74% precision and 92.37% accuracy, outperforming experimental methods such as ribosome sequencing (Ribo-Seq) in identifying peptide-producing transcripts and filtering out false positives. Unlike traditional conservation-based methods, D-sORF's significant advantage is recognizing sORFs with low sequence similarity. Its robust prediction capabilities make it a valuable tool for researchers. It can enhance our understanding of sORFs' roles, potentially leading to discoveries in terms of gene regulation and new therapeutic targets. By accurately distinguishing small coding sequences from non-coding ones, D-sORF significantly contributes to genomic research and its applications in medicine and biotechnology. Small open reading frames (sORFs; <300 nucleotides or <100 amino acids) are widespread across all genomes, and an increasing variety of them appear to be translating from non-genic regions. Over the past few decades, peptides produced from sORFs have been identified as functional in various organisms, from bacteria to humans. Despite recent advances in next-generation sequencing and proteomics, accurate annotation and classification of sORFs remain a rate-limiting step toward reliable and high-throughput detection of small proteins from non-genic regions. Additionally, the cost of computational methods utilizing machine learning is lower than that of biological experiments, and they can be employed to detect sORFs, laying the groundwork for biological experiments. We present D-sORF, a machine-learning framework that integrates the statistical nucleotide context and motif information around the start codon to predict coding sORFs. D-sORF scores directly for coding identity and requires only the underlying genomic sequence, without incorporating parameters such as the conservation, which, in the case of sORFs, may increase the dispersion of scores within the significantly less conserved non-genic regions. D-sORF achieves 94.74% precision and 92.37% accuracy for small ORFs (using the 99 nt medium length window). When D-sORF is applied to sORFs associated with ribosomes, the identification of transcripts producing peptides (annotated by the Ensembl IDs) is similar to or superior to experimental methodologies based on ribosome-sequencing (Ribo-Seq) profiling. In parallel, the recognition of putative negative data, such as the intron-containing transcripts that associate with ribosomes, remains remarkably low, indicating that D-sORF could be efficiently applied to filter out false-positive sORFs from Ribo-Seq data because of the non-productive ribosomal binding or noise inherent in these protocols. [ABSTRACT FROM AUTHOR]

ABSTRACT Bombyx mori cypovirus (BmCPV), a member of the Reoviridae family, is a well-established research model for double-stranded RNA (dsRNA) viruses with segmented genomes. Despite its small genome size, the coding potential of BmCPV remains largely unexplored. In this study, we identified a novel small open reading frame within the S10 dsRNA genome, encoding a small viral peptide (VSP59) with 59 amino acid residues. Functional characterization revealed that VSP59 acts as a negative regulator of viral replication. VSP59 predominantly localizes to the cytoplasm, where it interacts with prohibitin 2 (PHB2), an inner membrane mitophagy receptor. This interaction targets mitochondria and triggers caspase 3-dependent apoptosis. Transient expression of vsp59 in BmN cells suppressed viral replication, an effect that was reversed by silencing PHB2 expression. Moreover, recombinant BmCPV with a mutated vsp59 exhibited reduced replication. Our findings demonstrate that VSP59 interacts with PHB2 on mitochondria, inducing apoptosis and thereby diminishing viral replication. This study expands our understanding of the genetic information encoded by the BmCPV genome and highlights the role of novel small peptides in host-virus interactions.IMPORTANCEA novel small open reading frame (sORF) from the viral genome was identified and characterized. The sORF could encode a small viral peptide (VSP59) that targeted mitochondria and induced prohibitin 2-related apoptosis, further attenuating Bombyx mori cypovirus replication.

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The biological functions of short open reading frame (sORF)‐encoded micropeptides remain largely unknown. Here, we report that LINC00998, a previously annotated lncRNA, was upregulated in multiple cancer types and the sORF on LINC00998 encoded a micropeptide named SMIM30. SMIM30 was localized in the membranes of the endoplasmic reticulum (ER) and mitochondria. Silencing SMIM30 inhibited the proliferation of hepatoma cells in vitro and suppressed the growth of tumor xenografts and N‐nitrosodiethylamine‐induced hepatoma. Overexpression of the 5′UTR‐sORF sequence of LINC00998, encoding wild‐type SMIM30, enhanced tumor cell growth, but this was abolished when a premature stop codon was introduced into the sORF via single‐base deletion. Gain‐ and loss‐of‐function studies revealed that SMIM30 peptide but not LINC00998 reduced cytosolic calcium level, increased CDK4, cyclin E2, phosphorylated‐Rb and E2F1, and promoted the G1/S phase transition and cell proliferation. The effect of SMIM30 silencing was attenuated by a calcium chelator or the agonist of sarco/endoplasmic reticulum calcium ATPase (SERCA) pump. These findings suggest a novel function of micropeptide SMIM30 in promoting G1/S transition and cell proliferation by enhancing SERCA activity and reducing cytosolic calcium level.

Small open reading frames (sORFs) are often overlooked features in genomes. In the past, they were labeled as noncoding or "transcriptional noise". However, accumulating evidence from recent years suggests that sORFs may be transcribed and translated to produce sORF-encoded polypeptides (SEPs) with less than 100 amino acids. The vigorous development of computational algorithms, ribosome profiling, and peptidome has facilitated the prediction and identification of many new SEPs. These SEPs were revealed to be involved in a wide range of basic biological processes, such as gene expression regulation, embryonic development, cellular metabolism, inflammation, and even carcinogenesis. To effectively understand the potential biological functions of SEPs, we discuss the history and development of the newly emerging research on sORFs and SEPs. In particular, we review a range of recently discovered bioinformatics tools for identifying, predicting, and validating SEPs as well as a variety of biochemical experiments for characterizing SEP functions. Lastly, this review underlines the challenges and future directions in identifying and validating sORFs and their encoded micropeptides, providing a significant reference for upcoming research on sORF-encoded peptides. [ABSTRACT FROM AUTHOR]

The biological functions of short open reading frame (sORF)‐encoded micropeptides remain largely unknown. Here, we report that LINC00998, a previously annotated lncRNA, was upregulated in multiple cancer types and the sORF on LINC00998 encoded a micropeptide named SMIM30. SMIM30 was localized in the membranes of the endoplasmic reticulum (ER) and mitochondria. Silencing SMIM30 inhibited the proliferation of hepatoma cells in vitro and suppressed the growth of tumor xenografts and N‐nitrosodiethylamine‐induced hepatoma. Overexpression of the 5′UTR‐sORF sequence of LINC00998, encoding wild‐type SMIM30, enhanced tumor cell growth, but this was abolished when a premature stop codon was introduced into the sORF via single‐base deletion. Gain‐ and loss‐of‐function studies revealed that SMIM30 peptide but not LINC00998 reduced cytosolic calcium level, increased CDK4, cyclin E2, phosphorylated‐Rb and E2F1, and promoted the G1/S phase transition and cell proliferation. The effect of SMIM30 silencing was attenuated by a calcium chelator or the agonist of sarco/endoplasmic reticulum calcium ATPase (SERCA) pump. These findings suggest a novel function of micropeptide SMIM30 in promoting G1/S transition and cell proliferation by enhancing SERCA activity and reducing cytosolic calcium level. [ABSTRACT FROM AUTHOR]

Primary transcripts of microRNAs (pri-miRNAs) were initially defined as long non-coding RNAs that host miRNAs further processed by the microRNA processor complex. A few years ago, however, it was discovered in plants that pri-miRNAs actually contain functional open reading frames (sORFs) that translate into small peptides called miPEPs, for microRNA-encoded peptides. Initially detected in Arabidopsis thaliana and Medicago truncatula, recent studies have revealed the presence of miPEPs in other pri-miRNAs as well as in other species ranging from various plant species to animals. This suggests that miPEP numbers remain largely underestimated and that they could be a common signature of pri-miRNAs. Here we present the most recent advances in miPEPs research and discuss how their discovery has broadened our vision of the regulation of gene expression by miRNAs, and how miPEPs could be interesting tools in sustainable agriculture or the treatment of certain human diseases. [ABSTRACT FROM AUTHOR]

In contrast to extensively studied prokaryotic 'small' transcriptomes (encompassing all small noncoding RNAs), small proteomes (here defined as including proteins ≤70 aa) are only now entering the limelight. The absence of a complete small protein catalogue in most prokaryotes precludes our understanding of how these molecules affect physiology. So far, archaeal genomes have not yet been analyzed broadly with a dedicated focus on small proteins. Here, we present a combinatorial approach, integrating experimental data from small protein-optimized mass spectrometry (MS) and ribosome profiling (Ribo-seq), to generate a high confidence inventory of small proteins in the model archaeon Haloferax volcanii. We demonstrate by MS and Ribo-seq that 67% of the 317 annotated small open reading frames (sORFs) are translated under standard growth conditions. Furthermore, annotation-independent analysis of Ribo-seq data showed ribosomal engagement for 47 novel sORFs in intergenic regions. A total of seven of these were also detected by proteomics, in addition to an eighth novel small protein solely identified by MS. We also provide independent experimental evidence in vivo for the translation of 12 sORFs (annotated and novel) using epitope tagging and western blotting, underlining the validity of our identification scheme. Several novel sORFs are conserved in Haloferax species and might have important functions. Based on our findings, we conclude that the small proteome of H. volcanii is larger than previously appreciated, and that combining MS with Ribo-seq is a powerful approach for the discovery of novel small protein coding genes in archaea. [ABSTRACT FROM AUTHOR]

Small open reading frames (sORFs) can encode functional polypeptides or act as cis-translational regulators in stress responses in eukaryotes. Their number and potential importance have only recently become clear in plants. In this study, we identified a novel sORF gene in sweet potato, IbEGF, which encoded the 83-amino acid polypeptide containing an EGF_CA domain. The expression of IbEGF was induced by PEG6000, H2O2, abscisic acid (ABA), methyl-jasmonate (MeJA) and brassinosteroid (BR). The IbEGF protein was localized to the nucleus and cell membrane. Under drought stress, overexpression of IbEGF enhanced drought tolerance, promoted the accumulation of ABA, MeJA, BR and proline and upregulated the genes encoding superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) in transgenic sweet potato. The IbEGF protein was found to interact with IbCOP9-5α, a regulator in the phytohormone signalling pathways. These results suggest that IbEGF interacting with IbCOP9-5α enhances drought tolerance by regulating phytohormone signalling pathways, increasing proline accumulation and further activating reactive oxygen species (ROS) scavenging system in transgenic sweet potato. [ABSTRACT FROM AUTHOR]

Accurate prediction of open reading frames (ORFs) is important for studying and using genome sequences. Ribosomes move along mRNA strands with a step of three nucleotides and datasets carrying this information can be used to predict ORFs. The ribosome-protected footprints (RPFs) feature a significant 3-nt periodicity on mRNAs and are powerful in predicting translating ORFs, including small ORFs (sORFs), but the application of RPFs is limited because they are too short to be accurately mapped in complex genomes. In this study, we found a significant 3-nt periodicity in the datasets of populational genomic variants in coding sequences, in which the nucleotide diversity increases every three nucleotides. We suggest that this feature can be used to predict ORFs and develop the Python package 'OrfPP', which recovers ~83% of the annotated ORFs in the tested genomes on average, independent of the population sizes and the complexity of the genomes. The novel ORFs, including sORFs, identified from single-nucleotide polymorphisms are supported by protein mass spectrometry evidence comparable to that of the annotated ORFs. The application of OrfPP to tetraploid cotton and hexaploid wheat genomes successfully identified 76.17% and 87.43% of the annotated ORFs in the genomes, respectively, as well as 4704 sORFs, including 1182 upstream and 2110 downstream ORFs in cotton and 5025 sORFs, including 232 upstream and 234 downstream ORFs in wheat. Overall, we propose an alternative and supplementary approach for ORF prediction that can extend the studies of sORFs to more complex genomes. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) were originally defined as non-coding RNAs (ncRNAs) which lack protein-coding ability. However, with the emergence of technologies such as ribosome profiling sequencing and ribosome-nascent chain complex sequencing, it has been demonstrated that most lncRNAs have short open reading frames hence the potential to encode functional micropeptides. Such micropeptides have been described to be widely involved in life-sustaining activities in several organisms, such as homeostasis regulation, disease, and tumor occurrence, and development, and morphological development of animals, and plants. In this review, we focus on the latest developments in the field of lncRNA-encoded micropeptides, and describe the relevant computational tools and techniques for micropeptide prediction and identification. This review aims to serve as a reference for future research studies on lncRNA-encoded micropeptides.

Most bacterial ORFs are identified by automated prediction algorithms. However, these algorithms often fail to identify ORFs lacking canonical features such as a length of >50 codons or the presence of an upstream Shine-Dalgarno sequence. Here, we use ribosome profiling approaches to identify actively translated ORFs in Mycobacterium tuberculosis. Most of the ORFs we identify have not been previously described, indicating that the M. tuberculosis transcriptome is pervasively translated. The newly described ORFs are predominantly short, with many encoding proteins of ≤50 amino acids. Codon usage of the newly discovered ORFs suggests that most have not been subject to purifying selection, and hence are unlikely to contribute to cell fitness. Nevertheless, we identify 90 new ORFs (median length of 52 codons) that bear the hallmarks of purifying selection. Thus, our data suggest that pervasive translation of short ORFs in Mycobacterium tuberculosis serves as a rich source for the evolution of new functional proteins.

Genomic studies of bacteria have long pointed toward widespread prevalence of small open reading frames (sORFs) encoding for short proteins, <100 amino acids in length. Despite the mounting genomic evidence of their robust expression, relatively little progress has been made in their mass spectrometry-based detection and various blanket statements have been used to explain this observed discrepancy. In this study, we provide a large-scale riboproteogenomics investigation of the challenging nature of proteomic detection of such small proteins as informed by conditional translation data. A panel of physiochemical properties alongside recently developed mass spectrometry detectability metrics was interrogated to provide a comprehensive evidence-based assessment of sORF-encoded polypeptide (SEP) detectability. Moreover, a large-scale proteomics and translatomics compendium of proteins produced by Salmonella Typhimurium (S. Typhimurium), a model human pathogen, across a panel of growth conditions is presented and used in support of our in silico SEP detectability analysis. This integrative approach is used to provide a data-driven census of small proteins expressed by S. Typhimurium across growth phases and infection-relevant conditions. Taken together, our study pinpoints current limitations in proteomics-based detection of novel small proteins currently missing from bacterial genome annotations. Integrative in silico proteome analysis and experimental riboproteogenomic data uncovers biases in mass spectrometric based detection of sORF-encoded small proteins. [ABSTRACT FROM AUTHOR]

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles., (© 2023 Wiley-VCH GmbH.)

Non-coding RNAs (ncRNAs) are not conventionally involved in protein encoding. However, recent findings indicate that ncRNAs possess the capacity to code for proteins or peptides. These ncRNA-encoded peptides (ncPEPs) are vital for diverse plant life processes and exhibit significant potential value. Despite their importance, research on plant ncPEPs is limited, with only a few studies conducted and less information on the underlying mechanisms, and the field remains in its nascent stage. This manuscript provides a comprehensive overview of ncPEPs mining methods in plants, focusing on prediction, identification, and functional analysis. We discuss the strengths and weaknesses of various techniques, identify future research directions in the ncPEPs domain, and elucidate the biological functions and agricultural application prospects of plant ncPEPs. By highlighting the immense potential and research value of ncPEPs, we aim to lay a solid foundation for more in-depth studies in plant science. [ABSTRACT FROM AUTHOR]

Small open reading frame-encoded peptides (SEPs) are microproteins with a length of 100 amino acids or less, which may play a critical role in maintaining cell homeostasis under stress. Therefore, we used mass spectrometry-based proteomics to explore microproteins potentially involved in cellular stress responses in Saccharomyces cerevisiae . A total of 225 microproteins with 1920 unique peptides were identified under six culture conditions: normal, oxidation, starvation, ultraviolet radiation, heat shock, and heat shock with starvation. Among these microproteins, we found 70 SEPs with 75 unique peptides. The annotated microproteins are involved in stress-related processes, such as cell redox reactions, cell wall modification, protein folding and degradation, and DNA damage repair. It suggests that SEPs may also play similar functions under stress conditions. For example, SEP IP&#95;008057, translated from a short coding sequence of YJL159W , may play a role in heat shock. This study identified stress-responsive SEPs in S. cerevisiae and provided valuable information to determine the functions of these proteins, which enrich the genome and proteome of S. cerevisiae and show clues to improving the stress tolerance of S. cerevisiae .

Small proteins of <51 amino acids are abundant across all domains of life, but they are often overlooked because their small size makes them difficult to predict computationally and they are refractory to standard proteomic approaches. Ribosome profiling has been used to infer the existence of small proteins by detecting the translation of the corresponding open reading frames (ORFs). Detection of translated short ORFs by ribosome profiling can be improved by treating cells with drugs that stall ribosomes at specific codons. Here, we combine the analysis of ribosome profiling data for Escherichia coli cells treated with antibiotics that stall ribosomes at either the start or stop codons. Thus, we identify ribosome-occupied start and stop codons with high sensitivity for ~400 novel putative ORFs. The newly discovered ORFs are mostly short, with 365 encoding proteins of <51 amino acids. We validate translation of several selected short ORFs and show that many likely encode unstable proteins. Moreover, we present evidence that most of the newly identified short ORFs are not under purifying selection, suggesting that they do not impact cell fitness, although a small subset have the hallmarks of functional ORFs. [ABSTRACT FROM AUTHOR]

Small proteins encoded by open reading frames (ORFs) shorter than 50 codons (small ORFs [sORFs]) are often overlooked by annotation engines and are difficult to characterize using traditional biochemical techniques. Ribosome profiling has tremendous potential to empirically improve the annotations of prokaryotic genomes. Recent improvements in ribosome profiling methods for bacterial model organisms have revealed many new sORFs in well-characterized genomes. Antibiotics that trap ribosomes just after initiation have played a key role in these developments by allowing the unambiguous identification of the start codons (and, hence, the reading frame) for novel ORFs. Here, we describe these new methods and highlight critical controls and considerations for adapting ribosome profiling to different prokaryotic species. [ABSTRACT FROM AUTHOR]