Genome-wide identification and differential analysis of translational initiation

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.

Small open reading frame-encoded microproteins in cancer: identification, biological functions and clinical significance

The human genome harbors approximately twenty thousand protein-coding genes, and a significant portion of life science research focuses on elucidating their functions and the underlying mechanisms. Recent studies have revealed that small open reading frame (sORF), originating from non-coding RNAs or the 5' leader sequences of messenger RNAs, can be translated into small peptides called microproteins through cap-dependent or cap-independent mechanisms. These microproteins interact with diverse molecular partners to modulate gene expression at multiple regulatory levels, thereby playing critical roles in various biological processes. Notably, sORF-encoded microproteins exhibit aberrant expression patterns in cancer and are implicated in tumor initiation and progression, expanding our understanding of cancer biology. In this review, we introduce the translational mechanisms and identification methods of microproteins, summarize their dysregulation in cancer and their biological functions in regulating gene expression, and emphasize their roles in driving hallmark events of cancer. Furthermore, we discuss their clinical significance as diagnostic and prognostic biomarkers, as well as therapeutic targets.

A large-scale sORF screen identifies putative microproteins involved in cancer cell fitness

The human genome contains thousands of potentially coding short open reading frames (sORFs). While a growing set of microproteins translated from these sORFs have been demonstrated to mediate important cellular functions, the majority remains uncharacterized. In our study, we performed a high-throughput CRISPR-Cas9 knock-out screen targeting 11,776 sORFs to identify microproteins essential for cancer cell line growth. We show that the CENPBD2P gene encodes a translated sORF and promotes cell fitness. We selected five additional candidate sORFs encoding microproteins between 11 and 63 amino acids in length for further functional assessment. Green fluorescent protein fusion constructs of these microproteins localized to distinct subcellular compartments, and the majority showed reproducible biochemical interaction partners. Studying the fitness and transcriptome of sORF knock-outs and complementation with the corresponding microprotein, we identify rescuable phenotypes while also illustrating the limitations and caveats of our pipeline for sORF functional screening and characterization.

Extensive location bias of the GPCR-dependent translatome via site-selective activation of mTOR

G protein-coupled receptors (GPCRs) modulate various physiological functions by rewiring cellular gene expression in response to extracellular signals. Control of gene expression by GPCRs has been studied almost exclusively at the transcriptional level, neglecting an extensive amount of regulation that takes place translationally. Hence, little is known about the nature and mechanisms of gene-specific posttranscriptional regulation downstream of receptor activation. Here, we apply an unbiased multiomics approach to delineate an extensive translational regulatory program initiated by the prototypical beta2-adrenergic receptor (β2-AR) and provide mechanistic insights into how these processes are orchestrated. Using ribosome profiling (Ribo-seq), we identify nearly 120 gene targets of adrenergic receptor activity for which expression is exclusively regulated at the level of translation. We next show that all translational changes are induced selectively by endosomal β2-ARs and report that this proceeds through activation of the mammalian target of rapamycin (mTOR) pathway. Specifically, within the set of translational GPCR targets, we find significant enrichment of genes with 5' terminal oligopyrimidine (TOP) motifs, a gene class classically known to be translationally regulated by mTOR. We then demonstrate that endosomal β2-ARs are required for mTOR activation and subsequent mTOR-dependent TOP mRNA translation. This site-selective crosstalk between the pathways is observed in multiple cell models with native β2-ARs, across a range of endogenous and synthetic adrenergic agonists, and for other GPCRs with intracellular activity. Together, this comprehensive analysis of drug-induced translational regulation establishes a critical role for location-biased GPCR signaling in fine-tuning the cellular protein landscape.

Non-AUG HIV-1 uORF translation elicits specific T cell immune response and regulates viral transcript expression

Human immunodeficiency virus type-1 (HIV-1) is a complex retrovirus that relies on alternative splicing, translational, and post-translational mechanisms to produce over 15 functional proteins from its single ~10 kb transcriptional unit. Using ribosome profiling, nascent protein labeling, RNA sequencing, and whole-proteomics of infected CD4 + T lymphocytes, we characterized the transcriptional, translational, and post-translational landscape during infection. While viral infection exerts a significant impact on host transcript abundance, global translation rates are only modestly affected. Proteomics data reveal extensive transcriptional and post-translational regulation, with many genes showing opposing trends between transcript/ribosome profiling and protein abundance. These findings highlight a complex regulatory network orchestrating gene expression at multiple levels. Viral ribosome profiling further uncovered extensive non-AUG translation of small peptides from upstream open reading frames (uORFs) within the 5' long terminal repeat, which elicit specific T cell responses in people living with HIV. Conservation of uORF translation among retroviruses, along with TAR sequences, shapes DDX3 dependency for efficient translation of the main viral open reading frames.

Conserved GTPase OLA1 promotes efficient translation on D/E-rich mRNA

The TRAFAC (translation factors) GTPase OLA1 plays a critical role in various stress responses and is implicated in the regulation of tumor progression. It is conserved from bacteria to eukaryotes and regulates the translation through binding to the ribosome. Here, we report the cryo-electron microscopy structure of its Escherichia coli homolog, YchF, with the 50S subunit. In this structure, YchF is positioned at the side of the 50S subunit by engaging with uL14, bL19, and rRNA helix H62 through its helical and ATPase domains. We further demonstrate that the helical domain is essential for OLA1/YchF to function. A comprehensive analysis of the structure and Ribo-seq data points out that OLA1/YchF promotes the splitting of ribosomes into subunits on D/E-rich mRNA. Our findings provide crucial structural insights into the molecular mechanism of OLA1/YchF-associated translation-stalling regulation, which maintains the translation of genes involved in stress response and tumor progression.

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).

Deep learning to decode sites of RNA translation in normal and cancerous tissues

The biological process of RNA translation is fundamental to cellular life and has wide-ranging implications for human disease. Accurate delineation of RNA translation variation represents a significant challenge due to the complexity of the process and technical limitations. Here, we introduce RiboTIE, a transformer model-based approach designed to enhance the analysis of ribosome profiling data. Unlike existing methods, RiboTIE leverages raw ribosome profiling counts directly to robustly detect translated open reading frames (ORFs) with high precision and sensitivity, evaluated on a diverse set of datasets. We demonstrate that RiboTIE successfully recapitulates known findings and provides novel insights into the regulation of RNA translation in both normal brain and medulloblastoma cancer samples. Our results suggest that RiboTIE is a versatile tool that can significantly improve the accuracy and depth of Ribo-Seq data analysis, thereby advancing our understanding of protein synthesis and its implications in disease.

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.

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.

Transposable Elements Contribute to the Regulation of Long Noncoding RNAs in Drosophila melanogaster

Background: Transposable elements (TEs) and noncoding sequences are major components of the genome, yet their functional contributions to long noncoding RNAs (lncRNAs) are not well understood. Although many lncRNAs originating from TEs (TE-lncRNAs) have been identified across various organisms, their characteristics and regulatory roles, particularly in insects, remain largely unexplored. This study integrated multi-omics data to investigate TE-lncRNAs in D. melanogaster, focusing on the influence of transposons across different omics levels. Results: We identified 16,118 transposons overlapping with lncRNA sequences that constitute 2119 TE-lncRNAs (40.4% of all lncRNAs) using 256 public RNA-seq samples and 15 lncRNA-seq samples of Drosophila S2 cells treated with heavy metals. Of these, 67.2% of TE-lncRNAs contain more than one TE. The LTR/Gypsy family was the most common transposon insertion. Transposons preferred to insert into promoters, transcription starting sites, and intronic regions, especially in chromosome ends. Compared with lncRNAs, TE-lncRNAs showed longer lengths, a lower conservation, and lower levels but a higher specificity of expression. Multi-omics data analysis revealed positive correlations between transposon insertions and chromatin openness at the pre-transcriptional level. Notably, a total of 516 TE-lncRNAs provided transcriptional factor binding sites through transposon insertions. The regulatory network of a key transcription factor was rewired by transposons, potentially recruiting other transcription factors to exert regulatory functions under heavy metal stress. Additionally, 99 TE-lncRNAs were associated with m6A methylation modification sites, and 115 TE-lncRNAs potentially provided candidate small open reading frames through transposon insertions. Conclusions: Our data analysis demonstrated that TEs contribute to the regulation of lncRNAs. TEs not only promote the transcriptional regulation of lncRNAs, but also facilitate their post-transcriptional and epigenetic regulation.

Nuclear release of eIF1 restricts start-codon selection during mitosis

Regulated start-codon selection has the potential to reshape the proteome through the differential production of upstream open reading frames, canonical proteins, and alternative translational isoforms1-3. However, conditions under which start codon selection is altered remain poorly defined. Here, using transcriptome-wide translation-initiation-site profiling4, we reveal a global increase in the stringency of start-codon selection during mammalian mitosis. Low-efficiency initiation sites are preferentially repressed in mitosis, resulting in pervasive changes in the translation of thousands of start sites and their corresponding protein products. This enhanced stringency of start-codon selection during mitosis results from increased association between the 40S ribosome and the key regulator of start-codon selection, eIF1. We find that increased eIF1-40S ribosome interaction during mitosis is mediated by the release of a nuclear pool of eIF1 upon nuclear envelope breakdown. Selectively depleting the nuclear pool of eIF1 eliminates the change to translational stringency during mitosis, resulting in altered synthesis of thousands of protein isoforms. In addition, preventing mitotic translational rewiring results in substantially increased cell death and decreased mitotic slippage in cells that experience a mitotic delay induced by anti-mitotic chemotherapies. Thus, cells globally control stringency of translation initiation, which has critical roles during the mammalian cell cycle in preserving mitotic cell physiology.

Detection of host cell microprotein impurities in antibody drug products

Chinese hamster ovary (CHO) cells are used to produce almost 90% of therapeutic monoclonal antibodies (mAbs) and antibody fusion proteins (Fc-fusion). The annotation of non-canonical translation events in these cellular factories remains incomplete, limiting our ability to study CHO cell biology and detect host cell protein (HCP) impurities in the final antibody drug product. We utilised ribosome footprint profiling (Ribo-seq) to identify novel open reading frames (ORFs) including N-terminal extensions and thousands of short ORFs (sORFs) predicted to encode microproteins. Mass spectrometry-based HCP analysis of eight commercial antibody drug products (7 mAbs and 1 Fc-fusion protein) using the extended protein sequence database revealed the presence of microprotein impurities. We present evidence that microprotein abundance varies with growth phase and can be affected by the cell culture environment. In addition, our work provides a vital resource to facilitate future studies of non-canonical translation and the regulation of protein synthesis in CHO cell lines.

Genome-wide analysis reveals transcriptional and translational changes during diapause of the Asian corn borer (Ostrinia furnacalis)

BACKGROUND

Diapause, a pivotal phase in the insect life cycle, enables survival during harsh environmental conditions. Unraveling the gene expression profiles of the diapause process helps uncover the molecular mechanisms that underlying diapause, which is crucial for understanding physiological adaptations. In this study, we utilize RNA-seq and Ribo-seq data to examine differentially expressed genes (DEGs) and translational efficiency during diapause of Asian corn borer (Ostrinia furnacalis, ACB).

RESULTS

Our results unveil genes classified as "forwarded", "exclusive", "intensified", or "buffered" during diapause, shedding light on their transcription and translation regulation patterns. Furthermore, we explore the landscape of lncRNAs (long non-coding RNAs) during diapause and identify differentially expressed lncRNAs, suggesting their roles in diapause regulation. Comparative analysis of different types of diapause in insects uncovers shared and unique KEGG pathways. While shared pathways highlight energy balance, exclusive pathways in the ACB larvae indicate insect-specific adaptations related to nutrient utilization and stress response. Interestingly, our study also reveals dynamic changes in the HSP70 gene family and proteasome pathway during diapause. Manipulating HSP protein levels and proteasome pathway by HSP activator or inhibitor and proteasome inhibitor affects diapause, indicating their vital role in the process.

CONCLUSIONS

In summary, these findings enhance our knowledge of how insects navigate challenging conditions through intricate molecular mechanisms.

junctionCounts: comprehensive alternative splicing analysis and prediction of isoform-level impacts to the coding sequence

Alternative splicing (AS) is emerging as an important regulatory process for complex biological processes. Transcriptomic studies therefore commonly involve the identification and quantification of alternative processing events, but the need for predicting the functional consequences of changes to the relative inclusion of alternative events remains largely unaddressed. Many tools exist for the former task, albeit each constrained to its own event type definitions. Few tools exist for the latter task; each with significant limitations. To address these issues we developed junctionCounts, which captures both simple and complex pairwise AS events and quantifies them with straightforward exon-exon and exon-intron junction reads in RNA-seq data, performing competitively among similar tools in terms of sensitivity, false discovery rate and quantification accuracy. Its partner utility, cdsInsertion, identifies transcript coding sequence (CDS) information via in silico translation from annotated start codons, including the presence of premature termination codons. Finally, findSwitchEvents connects AS events with CDS information to predict the impact of individual events to the isoform-level CDS. We used junctionCounts to characterize splicing dynamics and NMD regulation during neuronal differentiation across four primates, demonstrating junctionCounts' capacity to robustly characterize AS in a variety of organisms and to predict its effect on mRNA isoform fate.

CRISPRware: an efficient method for contextual gRNA library design

We present CRISPRware, an efficient method for generating guide RNA (gRNA) libraries against transcribed, translated, and noncoding regions. CRISPRware leverages next-generation sequencing data to design context-specific gRNAs and accounts for genetic variation, which allows allele-specific guide design on a genome-wide scale. The latter ability holds promise for the development of gene therapy in the context of gene dosing and dominant negative mutations.

Extensive location bias of the GPCR-dependent translatome via site-selective activation of mTOR

G protein-coupled receptors (GPCRs) modulate various physiological functions by re-wiring cellular gene expression in response to extracellular signals. Control of gene expression by GPCRs has been studied almost exclusively at the transcriptional level, neglecting an extensive amount of regulation that takes place translationally. Hence, little is known about the nature and mechanisms of gene-specific post-transcriptional regulation downstream of receptor activation. Here, we apply an unbiased multiomics approach to delineate an extensive translational regulatory program initiated by the prototypical beta2-adrenergic receptor (β2-AR) and provide mechanistic insights into how these processes are orchestrated. Using ribosome profiling (Ribo-seq), we identify nearly 120 novel gene targets of adrenergic receptor activity which expression is exclusively regulated at the level of translation. We next show that all translational changes are induced selectively by endosomal β2-ARs. We further report that this proceeds through activation of the mammalian target of rapamycin (mTOR) pathway. Specifically, within the set of translational GPCR targets we discover significant enrichment of genes with 5' terminal oligopyrimidine (TOP) motifs, a gene class classically known to be translationally regulated by mTOR. We then demonstrate that endosomal β2-ARs are required for mTOR activation and subsequent mTOR-dependent TOP mRNA translation. Together, this comprehensive analysis of drug-induced translational regulation establishes a critical role for location-biased GPCR signaling in fine-tuning the cellular protein landscape.

Identification of genes associated with sperm storage capacity in hens at different times after insemination by RNA-seq and Ribo-seq

BACKGROUND

Sperm storage capacity (SSC) determines the duration of fertility in hens and is an important reproduction trait that cannot be ignored in production. Currently, the genetic mechanism of SSC is still unclear in hens. Therefore, to explore the genetic basis of SSC, we analyzed the uterus-vagina junction (UVJ) of hens with different SSC at different times after insemination by RNA-seq and Ribo-seq.

RESULTS

Our results showed that 589, 596, and 527 differentially expressed genes (DEGs), 730, 783, and 324 differentially translated genes (DTGs), and 804, 625, and 467 differential translation efficiency genes (DTEGs) were detected on the 5th, 10th, and 15th days after insemination, respectively. In transcription levels, we found that the differences of SSC at different times after insemination were mainly reflected in the transmission of information between cells, the composition of intercellular adhesion complexes, the regulation of ion channels, the regulation of cellular physiological activities, the composition of cells, and the composition of cell membranes. In translation efficiency (TE) levels, the differences of SSC were mainly related to the physiological and metabolic activities in the cell, the composition of the organelle membrane, the physiological activities of oxidation, cell components, and cell growth processes. According to pathway analysis, SSC was related to neuroactive ligand-receptor interaction, histidine metabolism, and PPAR signaling pathway at the transcriptional level and glutathione metabolism, oxidative phosphorylation, calcium signaling pathway, cell adhesion molecules, galactose metabolism, and Wnt signaling pathway at the TE level. We screened candidate genes affecting SSC at transcriptional levels (COL4A4, MUC6, MCHR2, TACR1, AVPR1A, COL1A1, HK2, RB1, VIPR2, HMGCS2) and TE levels(COL4A4, MUC6, CYCS, NDUFA13, CYTB, RRM2, CAMK4, HRH2, LCT, GCK, GALT). Among them, COL4A4 and MUC6 were the key candidate genes differing in transcription, translation, and translation efficiency.

CONCLUSIONS

Our study used the combined analysis of RNA-seq and Ribo-seq for the first time to investigate the SSC and reveal the physiological processes associated with SSC. The key candidate genes affecting SSC were screened, and the theoretical basis was provided for the analysis of the molecular regulation mechanism of SSC.

CodLncScape Provides a Self-Enriching Framework for the Systematic Collection and Exploration of Coding LncRNAs

Recent studies have revealed that numerous lncRNAs can translate proteins under specific conditions, performing diverse biological functions, thus termed coding lncRNAs. Their comprehensive landscape, however, remains elusive due to this field's preliminary and dispersed nature. This study introduces codLncScape, a framework for coding lncRNA exploration consisting of codLncDB, codLncFlow, codLncWeb, and codLncNLP. Specifically, it contains a manually compiled knowledge base, codLncDB, encompassing 353 coding lncRNA entries validated by experiments. Building upon codLncDB, codLncFlow investigates the expression characteristics of these lncRNAs and their diagnostic potential in the pan-cancer context, alongside their association with spermatogenesis. Furthermore, codLncWeb emerges as a platform for storing, browsing, and accessing knowledge concerning coding lncRNAs within various programming environments. Finally, codLncNLP serves as a knowledge-mining tool to enhance the timely content inclusion and updates within codLncDB. In summary, this study offers a well-functioning, content-rich ecosystem for coding lncRNA research, aiming to accelerate systematic studies in this field.

Association of long non-coding RNAs and ABO blood groups with acute lymphoblastic leukemia in Egyptian children

Acute lymphoblastic leukemia (ALL) is the most prevailing cancer among children. Despite extensive studies, ALL etiology is still an unsolved puzzle. Long non-coding RNAs (lncRNAs) emerged as key mediators in cancer etiology. Several lncRNAs are dysregulated in ALL, leading to oncogenic or tumor-suppressive activities. Additionally, a relation between ABO blood groups and hematological malignancies was proposed. The current study intended to explore the association of lncRNAs, ANRIL and LINC-PINT, and their downstream targets, CDKN2A and heme oxygenase-1 (HMOX1), with the incidence of ALL and treatment response, and to determine the distribution of blood groups across different childhood ALL phenotypes. Blood samples were taken from 66 ALL patients (at diagnosis and at the end of remission induction phase) and 39 healthy children. Whole blood was used for blood group typing. Expression of ANRIL, LINC-PINT and CDKN2A was analyzed in plasma by qRT-PCR. Serum HMOX1 was measured using ELISA. ANRIL and CDKN2A were upregulated, while LINC-PINT and HMOX1 were downregulated in newly diagnosed patients. All of which showed remarkable diagnostic performance, where HMOX1 was superior. HMOX1 was independent predictor of ALL as well. LINC-PINT and HMOX1 were significantly upregulated after treatment. Notably, ANRIL and LINC-PINT were associated with poor outcome. No significant difference in the distribution of ABO blood groups was observed between patients and controls. In conclusion, our results suggested an association of ANRIL and LINC-PINT with childhood ALL predisposition, at least in part, through altering CDKN2A and HMOX1 production. Furthermore, the impact of remission induction treatment was newly revealed.

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.

Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq

Accurate and comprehensive annotation of microprotein-coding small open reading frames (smORFs) is critical to our understanding of normal physiology and disease. Empirical identification of translated smORFs is carried out primarily using ribosome profiling (Ribo-seq). While effective, published Ribo-seq datasets can vary drastically in quality and different analysis tools are frequently employed. Here, we examine the impact of these factors on identifying translated smORFs. We compared five commonly used software tools that assess open reading frame translation from Ribo-seq (RibORFv0.1, RibORFv1.0, RiboCode, ORFquant, and Ribo-TISH) and found surprisingly low agreement across all tools. Only ~2% of smORFs were called translated by all five tools, and ~15% by three or more tools when assessing the same high-resolution Ribo-seq dataset. For larger annotated genes, the same analysis showed ~74% agreement across all five tools. We also found that some tools are strongly biased against low-resolution Ribo-seq data, while others are more tolerant. Analyzing Ribo-seq coverage revealed that smORFs detected by more than one tool tend to have higher translation levels and higher fractions of in-frame reads, consistent with what was observed for annotated genes. Together these results support employing multiple tools to identify the most confident microprotein-coding smORFs and choosing the tools based on the quality of the dataset and the planned downstream characterization experiments of the predicted smORFs.

Nuclear release of eIF1 globally increases stringency of start-codon selection to preserve mitotic arrest physiology

Regulated start-codon selection has the potential to reshape the proteome through the differential production of uORFs, canonical proteins, and alternative translational isoforms. However, conditions under which start-codon selection is altered remain poorly defined. Here, using transcriptome-wide translation initiation site profiling, we reveal a global increase in the stringency of start-codon selection during mammalian mitosis. Low-efficiency initiation sites are preferentially repressed in mitosis, resulting in pervasive changes in the translation of thousands of start sites and their corresponding protein products. This increased stringency of start-codon selection during mitosis results from increased interactions between the key regulator of start-codon selection, eIF1, and the 40S ribosome. We find that increased eIF1-40S ribosome interactions during mitosis are mediated by the release of a nuclear pool of eIF1 upon nuclear envelope breakdown. Selectively depleting the nuclear pool of eIF1 eliminates the changes to translational stringency during mitosis, resulting in altered mitotic proteome composition. In addition, preventing mitotic translational rewiring results in substantially increased cell death and decreased mitotic slippage following treatment with anti-mitotic chemotherapeutics. Thus, cells globally control translation initiation stringency with critical roles during the mammalian cell cycle to preserve mitotic cell physiology.

Implication of Stm1 in the protection of eIF5A, eEF2 and tRNA through dormant ribosomes

Background: Dormant ribosomes are typically associated with preservation factors to protect themselves from degradation under stress conditions. Stm1/SERBP1 is one such protein that anchors the 40S and 60S subunits together. Several proteins and tRNAs bind to this complex as well, yet the molecular mechanisms remain unclear. Methods: Here, we reported the cryo-EM structures of five newly identified Stm1/SERBP1-bound ribosomes. Results: These structures highlighted that eIF5A, eEF2, and tRNA might bind to dormant ribosomes under stress to avoid their own degradation, thus facilitating protein synthesis upon the restoration of growth conditions. In addition, Ribo-seq data analysis reflected the upregulation of nutrient, metabolism, and external-stimulus-related pathways in the ∆stm1 strain, suggesting possible regulatory roles of Stm1. Discussion: The knowledge generated from the present work will facilitate in better understanding the molecular mechanism of dormant ribosomes.

PABP-driven secondary condensed phase within RSV inclusion bodies activates viral mRNAs for ribosomal recruitment

Inclusion bodies (IBs) of respiratory syncytial virus (RSV) are formed by liquid-liquid phase separation (LLPS) and contain internal structures termed "IB-associated granules" (IBAGs), where anti-termination factor M2-1 and viral mRNAs are concentrated. However, the mechanism of IBAG formation and the physiological function of IBAGs are unclear. Here, we found that the internal structures of RSV IBs are actual M2-1-free viral messenger ribonucleoprotein (mRNP) condensates formed by secondary LLPS. Mechanistically, the RSV nucleoprotein (N) and M2-1 interact with and recruit PABP to IBs, promoting PABP to bind viral mRNAs transcribed in IBs by RNA-recognition motif and drive secondary phase separation. Furthermore, PABP-eIF4G1 interaction regulates viral mRNP condensate composition, thereby recruiting specific translation initiation factors (eIF4G1, eIF4E, eIF4A, eIF4B and eIF4H) into the secondary condensed phase to activate viral mRNAs for ribosomal recruitment. Our study proposes a novel LLPS-regulated translation mechanism during viral infection and a novel antiviral strategy via targeting on secondary condensed phase.

Deep learning to decode sites of RNA translation in normal and cancerous tissues

The biological process of RNA translation is fundamental to cellular life and has wide-ranging implications for human disease. Yet, accurately delineating the variation in RNA translation represents a significant challenge. Here, we develop RiboTIE, a transformer model-based approach to map global RNA translation. We find that RiboTIE offers unparalleled precision and sensitivity for ribosome profiling data. Application of RiboTIE to normal brain and medulloblastoma cancer samples enables high-resolution insights into disease regulation of RNA translation.

Modeling alternative translation initiation sites in plants reveals evolutionarily conserved cis-regulatory codes in eukaryotes

mRNA translation relies on identifying translation initiation sites (TISs) in mRNAs. Alternative TISs are prevalent across plant transcriptomes, but the mechanisms for their recognition are unclear. Using ribosome profiling and machine learning, we developed models for predicting alternative TISs in the tomato (Solanum lycopersicum). Distinct feature sets were predictive of AUG and nonAUG TISs in 5' untranslated regions and coding sequences, including a novel CU-rich sequence that promoted plant TIS activity, a translational enhancer found across dicots and monocots, and humans and viruses. Our results elucidate the mechanistic and evolutionary basis of TIS recognition, whereby cis-regulatory RNA signatures affect start site selection. The TIS prediction model provides global estimates of TISs to discover neglected protein-coding genes across plant genomes. The prevalence of cis-regulatory signatures across plant species, humans, and viruses suggests their broad and critical roles in reprogramming the translational landscape.

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.

Variants in the first methionine of RAD51C are homologous recombination proficient due to an alternative start site

In the 20+ years since the discovery of RAD51C, scientists have been perplexed as to how missense variants in this tumor suppressor gene impacts its function and pathogenicity. With a strong connection to breast and ovarian cancer, classifying these variants as pathogenic or benign aids in the diagnosis and treatment of patients with RAD51C variants. In particular, variants at translational starts sites are disruptive as they prevent protein expression. These variants are often classified as pathogenic, unless an alternative translational start is shown to produce a functional isoform to rescue protein expression. In this study, we utilized the ribosome profiling database GWIPS-VIZ to identify two active translational start sites in human RAD51C at methionine one and methionine ten. This second translational start at methionine ten is both conserved in 97 % of mammals and is the sole translational start in 80 % of mammals. Missense variants at either methionine have been identified in 47 individuals, preventing expression from one of these two start sites. Therefore, we stably expressed both wildtype isoforms, as well as the RAD51C M1 and M10 variants in a RAD51C CRISPR/Cas9 knockout U2OS cell and compared their homologous recombination function. Surprisingly, we find that expression of human RAD51C from either start site can equivalently rescue homologous recombination of RAD51C CRISPR/Cas9 knockout U2OS cells through a sister chromatid recombination assay. Similarly, each of our RAD51C CRISPR/Cas9 KO cells stably complemented with RAD51C missense variants at either M1 or M10 are homologous recombination proficient. Together, our data demonstrate that RAD51C has two translational start sites and that variants in either methionine result in homologous recombination proficiency. With this critical discovery, individuals with variants at M1 will be more accurately informed of their cancer risk upon reclassification of these variants.

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.

Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq

Accurate and comprehensive annotation of microprotein-coding small open reading frames (smORFs) is critical to our understanding of normal physiology and disease. Empirical identification of translated smORFs is carried out primarily using ribosome profiling (Ribo-seq). While effective, published Ribo-seq datasets can vary drastically in quality and different analysis tools are frequently employed. Here, we examine the impact of these factors on identifying translated smORFs. We compared five commonly used software tools that assess ORF translation from Ribo-seq (RibORFv0.1, RibORFv1.0, RiboCode, ORFquant, and Ribo-TISH), and found surprisingly low agreement across all tools. Only ~2% of smORFs were called translated by all five tools and ~15% by three or more tools when assessing the same high-resolution Ribo-seq dataset. For larger annotated genes, the same analysis showed ~72% agreement across all five tools. We also found that some tools are strongly biased against low-resolution Ribo-seq data, while others are more tolerant. Analyzing Ribo-seq coverage as a proxy for translation levels revealed that highly translated smORFs are more likely to be detected by more than one tool. Together these results support employing multiple tools to identify the most confident microprotein-coding smORFs, and choosing the tools based on the quality of the dataset and planned downstream characterization experiments of predicted smORFs.

ORFeus: a computational method to detect programmed ribosomal frameshifts and other non-canonical translation events

BACKGROUND

In canonical protein translation, ribosomes initiate translation at a specific start codon, maintain a single reading frame throughout elongation, and terminate at the first in-frame stop codon. However, ribosomal behavior can deviate at each of these steps, sometimes in a programmed manner. Certain mRNAs contain sequence and structural elements that cause ribosomes to begin translation at alternative start codons, shift reading frame, read through stop codons, or reinitiate on the same mRNA. These processes represent important translational control mechanisms that can allow an mRNA to encode multiple functional protein products or regulate protein expression. The prevalence of these events remains uncertain, due to the difficulty of systematic detection.

RESULTS

We have developed a computational model to infer non-canonical translation events from ribosome profiling data.

CONCLUSION

ORFeus identifies known examples of alternative open reading frames and recoding events across different organisms and enables transcriptome-wide searches for novel events.

CRISPR-Cas9-based functional interrogation of unconventional translatome reveals human cancer dependency on cryptic non-canonical open reading frames

Emerging evidence suggests that cryptic translation beyond the annotated translatome produces proteins with developmental or physiological functions. However, functions of cryptic non-canonical open reading frames (ORFs) in cancer remain largely unknown. To fill this gap and systematically identify colorectal cancer (CRC) dependency on non-canonical ORFs, we apply an integrative multiomic strategy, combining ribosome profiling and a CRISPR-Cas9 knockout screen with large-scale analysis of molecular and clinical data. Many such ORFs are upregulated in CRC compared to normal tissues and are associated with clinically relevant molecular subtypes. We confirm the in vivo tumor-promoting function of the microprotein SMIMP, encoded by a primate-specific, long noncoding RNA, the expression of which is associated with poor prognosis in CRC, is low in normal tissues and is specifically elevated in CRC and several other cancer types. Mechanistically, SMIMP interacts with the ATPase-forming domains of SMC1A, the core subunit of the cohesin complex, and facilitates SMC1A binding to cis-regulatory elements to promote epigenetic repression of the tumor-suppressive cell cycle regulators encoded by CDKN1A and CDKN2B. Thus, our study reveals a cryptic microprotein as an important component of cohesin-mediated gene regulation and suggests that the 'dark' proteome, encoded by cryptic non-canonical ORFs, may contain potential therapeutic or diagnostic targets.

Microproteins-Discovery, structure, and function

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.

Principles, challenges, and advances in ribosome profiling: from bulk to low-input and single-cell analysis

Ribosome profiling has revolutionized our understanding of gene expression regulation by providing a snapshot of global translation in vivo. This powerful technique enables the investigation of the dynamics of translation initiation, elongation, and termination, and has provided insights into the regulation of protein synthesis under various conditions. Despite its widespread adoption, challenges persist in obtaining high-quality ribosome profiling data. In this review, we discuss the fundamental principles of ribosome profiling and related methodologies, including selective ribosome profiling and translation complex profiling. We also delve into quality control to assess the reliability of ribosome profiling datasets, and the efforts to improve data quality by modifying the standard procedures. Additionally, we highlight recent advancements in ribosome profiling that enable the transition from bulk to low-input and single-cell applications. Single-cell ribosome profiling has emerged as a crucial tool for exploring translation heterogeneity within specific cell populations. However, the challenges of capturing mRNAs efficiently and the sparse nature of footprint reads in single-cell ribosome profiling present ongoing obstacles. The need to refine ribosome profiling techniques remains, especially when used at the single-cell level.

Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery

Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.

What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?

Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein coding."

MAVI1, an endoplasmic reticulum-localized microprotein, suppresses antiviral innate immune response by targeting MAVS on mitochondrion

Pattern recognition receptor-mediated innate immunity is critical for host defense against viruses. A growing number of coding and noncoding genes are found to encode microproteins. However, the landscape and functions of microproteins in responsive to virus infection remain uncharacterized. Here, we systematically identified microproteins that are responsive to vesicular stomatitis virus infection. A conserved and endoplasmic reticulum-localized membrane microprotein, MAVI1 (microprotein in antiviral immunity 1), was found to interact with mitochondrion-localized MAVS protein and inhibit MAVS aggregation and type I interferon signaling activation. The importance of MAVI1 was highlighted that viral infection was attenuated and survival rate was increased in Mavi1-knockout mice. A peptide inhibitor targeting the interaction between MAVI1 and MAVS activated the type I interferon signaling to defend viral infection. Our findings uncovered that microproteins play critical roles in regulating antiviral innate immune responses, and targeting microproteins might represent a therapeutic avenue for treating viral infection.

Shining in the dark: the big world of small peptides in plants

Small peptides represent a subset of dark matter in plant proteomes. Through differential expression patterns and modes of action, small peptides act as important regulators of plant growth and development. Over the past 20 years, many small peptides have been identified due to technical advances in genome sequencing, bioinformatics, and chemical biology. In this article, we summarize the classification of plant small peptides and experimental strategies used to identify them as well as their potential use in agronomic breeding. We review the biological functions and molecular mechanisms of small peptides in plants, discuss current problems in small peptide research and highlight future research directions in this field. Our review provides crucial insight into small peptides in plants and will contribute to a better understanding of their potential roles in biotechnology and agriculture.

Construction of a cuproptosis-associated lncRNA prognostic signature for bladder cancer and experimental validation of cuproptosis-related lncRNA UBE2Q1-AS1

Introduction

Bladder cancer (BLCA) is the ninth most common malignancy worldwide and the fourth most common cancer in men. Copper levels are significantly altered in patients with thyroid, breast, lung, cervical, ovarian, pancreatic, oral, gastric, bladder, and prostate cancers. Outcomes can be predicted by constructing signatures using lncRNA-related genes associated with outcomes.

Methods

We identified lncRNAs related to outcomes, those differentially expressed in bladder cancer, and cuproptosis-related lncRNAs from TCGA. We identified the intersection to obtain 12 genes and established a prognostic risk signature consisting of eight genes using LASSO-penalized multivariate Cox analysis. We constructed a training set, performed survival analysis on the high-and low-risk groups, and performed validation in the test and full sets. There existed a substantial contrast in the likelihood of survival among the cohorts of high and low risk. An in-depth analysis of the gene mutations associated with tumors was conducted to evaluate the risk of developing cancer. We also performed gene analysis on neoadjuvant chemotherapy. We conducted experimental validation on the key gene UBE2Q1-AS1 in our prognostic signature.

Results

The risk signature we constructed shows significant differences between the high-risk group and the low-risk group. Univariate survival analysis of the eight genes in our signature showed that each gene distinguished between high- and low-risk groups. Sub-group analysis revealed that our risk score differed significantly in tumor stage, age, and gender. The analysis results of the tumor mutation burden (TMB) showed a significant difference in the TMB between the low- and high-risk groups, which had a direct impact on the outcomes. These findings highlight the importance of TMB as a potential prognostic marker in cancer detection and prevention. We analyzed the immune microenvironment and found significant differences in immune function, validation responses, immunotherapy-related positive markers, and critical steps in the tumor immunity cycle between the high- and low-risk groups. We found that the effect of anti-CTLA4 and PD-1 was higher in the high-risk group than in the low-risk group.Gene analysis of neoadjuvant chemotherapy revealed that the treatment effect in the high-risk group was better than in the low-risk group. The key gene UBE2Q1-AS1 in our prognostic signature can significantly influence the cell viability, migration, and proliferation of cancer cells.

Discussion

We established a signature consisting of eight genes constructed from cuproptosis-related lncRNAs that have potential clinical applications for outcomes prediction, diagnosis, and treatment.

Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World

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.

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".

In brief

The human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.

Highlights

Combined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

CRISPR/Cas9 screen uncovers functional translation of cryptic lncRNA-encoded open reading frames in human cancer

Emerging evidence suggests that cryptic translation within long noncoding RNAs (lncRNAs) may produce novel proteins with important developmental/physiological functions. However, the role of this cryptic translation in complex diseases (e.g., cancer) remains elusive. Here, we applied an integrative strategy combining ribosome profiling and CRISPR/Cas9 screening with large-scale analysis of molecular/clinical data for breast cancer (BC) and identified estrogen receptor α-positive (ER+) BC dependency on the cryptic ORFs encoded by lncRNA genes that were upregulated in luminal tumors. We confirmed the in vivo tumor-promoting function of an unannotated protein, GATA3-interacting cryptic protein (GT3-INCP) encoded by LINC00992, the expression of which was associated with poor prognosis in luminal tumors. GTE-INCP was upregulated by estrogen/ER and regulated estrogen-dependent cell growth. Mechanistically, GT3-INCP interacted with GATA3, a master transcription factor key to mammary gland development/BC cell proliferation, and coregulated a gene expression program that involved many BC susceptibility/risk genes and impacted estrogen response/cell proliferation. GT3-INCP/GATA3 bound to common cis regulatory elements and upregulated the expression of the tumor-promoting and estrogen-regulated BC susceptibility/risk genes MYB and PDZK1. Our study indicates that cryptic lncRNA-encoded proteins can be an important integrated component of the master transcriptional regulatory network driving aberrant transcription in cancer, and suggests that the "hidden" lncRNA-encoded proteome might be a new space for therapeutic target discovery.

Ribosome profiling analysis reveals the roles of DDX41 in translational regulation

DDX41 mutation has been observed in myeloid malignancies including myelodysplastic syndromes and acute myeloid leukemia, but the underlying causative mechanisms of these diseases have not been fully elucidated. The DDX41 protein is an ATP-dependent RNA helicase with roles in RNA metabolism. We previously showed that DDX41 is involved in ribosome biogenesis by promoting the processing of newly transcribed pre-ribosomal RNA. To build on this finding, in this study, we leveraged ribosome profiling technology to investigate the involvement of DDX41 in translation. We found that DDX41 knockdown resulted in both translationally increased and decreased transcripts. Both gene set enrichment analysis and gene ontology analysis indicated that ribosome-associated genes were translationally promoted after DDX41 knockdown, in part because these transcripts had significantly shorter transcript length and higher transcriptional and translational levels. In addition, we found that transcripts with 5'-terminal oligopyrimidine motifs tended to be translationally upregulated when the DDX41 level was low. Our data suggest that a translationally regulated feedback mechanism involving DDX41 may exist for ribosome biogenesis.

Ribo-uORF: a comprehensive data resource of upstream open reading frames (uORFs) based on ribosome profiling

Upstream open reading frames (uORFs) are typically defined as translation sites located within the 5' untranslated region upstream of the main protein coding sequence (CDS) of messenger RNAs (mRNAs). Although uORFs are prevalent in eukaryotic mRNAs and modulate the translation of downstream CDSs, a comprehensive resource for uORFs is currently lacking. We developed Ribo-uORF (http://rnainformatics.org.cn/RiboUORF) to serve as a comprehensive functional resource for uORF analysis based on ribosome profiling (Ribo-seq) data. Ribo-uORF currently supports six species: human, mouse, rat, zebrafish, fruit fly, and worm. Ribo-uORF includes 501 554 actively translated uORFs and 107 914 upstream translation initiation sites (uTIS), which were identified from 1495 Ribo-seq and 77 quantitative translation initiation sequencing (QTI-seq) datasets, respectively. We also developed mRNAbrowse to visualize items such as uORFs, cis-regulatory elements, genetic variations, eQTLs, GWAS-based associations, RNA modifications, and RNA editing. Ribo-uORF provides a very intuitive web interface for conveniently browsing, searching, and visualizing uORF data. Finally, uORFscan and UTR5var were developed in Ribo-uORF to precisely identify uORFs and analyze the influence of genetic mutations on uORFs using user-uploaded datasets. Ribo-uORF should greatly facilitate studies of uORFs and their roles in mRNA translation and posttranscriptional control of gene expression.

Discovering microproteins: making the most of ribosome profiling data

Building a reference set of protein-coding open reading frames (ORFs) has revolutionized biological process discovery and understanding. Traditionally, gene models have been confirmed using cDNA sequencing and encoded translated regions inferred using sequence-based detection of start and stop combinations longer than 100 amino-acids to prevent false positives. This has led to small ORFs (smORFs) and their encoded proteins left un-annotated. Ribo-seq allows deciphering translated regions from untranslated irrespective of the length. In this review, we describe the power of Ribo-seq data in detection of smORFs while discussing the major challenge posed by data-quality, -depth and -sparseness in identifying the start and end of smORF translation. In particular, we outline smORF cataloguing efforts in humans and the large differences that have arisen due to variation in data, methods and assumptions. Although current versions of smORF reference sets can already be used as a powerful tool for hypothesis generation, we recommend that future editions should consider these data limitations and adopt unified processing for the community to establish a canonical catalogue of translated smORFs.

Cancer susceptibility 18 positively regulates NUAK Family Kinase 1 expression to promote migration and invasion via sponging of miR-5586-5p in cervical cancer cells

INTRODUCTION

Cervical squamous cell carcinoma (CESC) is the most common gynecological malignancy worldwide. Although the cancer susceptibility 18 (CASC18) gene was involved in the regulation of cancer biology, its specific role in CESC is not well characterized.

METHODS

CASC18-related axis was predicted by bioinformatic analyses, and the competing endogenous RNA (ceRNA) interaction was further validated using quantitative real-time PCR, western blotting, RNA pulldown, and luciferase reporter assays. Transwell and wound healing assays were performed to verify the effect of CASC18 on SiHa and HeLa cell motility.

RESULTS

We found that CASC18 was upregulated in CESC tissues. Moreover, interference with CASC18 attenuated NUAK1-mediated epithelial-mesenchymal transition (EMT) and thus suppressed cancer cell motility. Furthermore, the effects of CASC18 knockdown on CESC cells were partly rescued by transfection with the miR-5586-5p inhibitor. Additionally, our findings indicated that CASC18 acts as a ceRNA to enhance NUAK1 expression by sponging miR-5586-5p.

CONCLUSION

Our study showed a novel CASC18/miR-5586-5p/NUAK1 ceRNA axis that could regulate cell invasion and migration by modulating EMT in CESC. These findings suggest that CASC18 may potentially serve as a novel therapeutic target in CESC treatment.