MicroRNAs are short, non-coding RNAs that repress gene expression in both plants and animals and have diverse functions related to growth, development, and stress responses. The ribonuclease, DICER-LIKE1 (DCL1) is required for two steps in plant miRNA biogenesis: cleavage of the primary miRNAs (pri-miRNAs) to release a hairpin structure, called the precursor miRNA (pre-miRNA) and cleavage of the pre-miRNA to generate the miRNA/miRNA* duplex. The mature miRNA guides the RNA-induced silencing complex to target RNAs with complementary sequences, resulting in translational repression and/or RNA cleavage of target mRNAs. However, the relative contribution of translational repression versus mRNA degradation by miRNAs remains unknown at the genome-level in crops, especially in maize. The maize fuzzy tassel (fzt) mutant contains a hypomorphic mutation in DCL1 resulting in broad developmental defects. While most miRNAs are reduced in fzt, the levels of miRNA-targeted mRNAs are not dramatically increased, suggesting that translational regulation by miRNAs may be common. To gain insight into the repression mechanism of plant miRNAs, we combined ribosome profiling and RNA-sequencing to globally survey miRNA activities in maize. Our data indicate that translational repression contributes significantly to regulation of most miRNA targets and that approximately one-third of miRNA targets are regulated primarily at the translational level. Surprisingly, ribosomes appear altered in fzt mutants suggesting that DCL1 may also have a role in ribosome biogenesis. Thus, DICER-LIKE1 shapes the translational landscape in plants through both miRNA-dependent and miRNA-independent mechanisms.

Viruses have evolved a range of strategies to utilize or manipulate the host\'s cellular translational machinery for efficient infection, although the mechanisms by which infectious bronchitis virus (IBV) manipulates the host translation machinery remain unclear. In this study, we firstly demonstrate that IBV infection causes host shutoff, although viral protein synthesis is not affected. We then screened 23 viral proteins, and identified that more than one viral protein is responsible for IBV-induced host shutoff, the inhibitory effects of proteins Nsp15 were particularly pronounced. Ribosome profiling was used to draw the landscape of viral mRNA and cellular genes expression model, and the results showed that IBV mRNAs gradually dominated the cellular mRNA pool, the translation efficiency of the viral mRNAs was lower than the median efficiency (about 1) of cellular mRNAs. In the analysis of viral transcription and translation, higher densities of RNA sequencing (RNA-seq) and ribosome profiling (Ribo-seq) reads were observed for structural proteins and 5\' untranslated regions, which conformed to the typical transcriptional characteristics of nested viruses. Translational halt events and the number of host genes increased significantly after viral infection. The translationally paused genes were enriched in translation, unfolded-protein-related response, and activation of immune response pathways. Immune- and inflammation-related mRNAs were inefficiently translated in infected cells, and IBV infection delayed the production of IFN-β and IFN-λ. Our results describe the translational landscape of IBV-infected cells and demonstrate new strategies by which IBV induces host gene shutoff to promote its replication.
OBJECTIVE: Infectious bronchitis virus (IBV) is a γ-coronavirus that causes huge economic losses to the poultry industry. Understanding how the virus manipulates cellular biological processes to facilitate its replication is critical for controlling viral infections. Here, we used Ribo-seq to determine how IBV infection remodels the host\'s biological processes and identified multiple viral proteins involved in host gene shutoff. Immune- and inflammation-related mRNAs were inefficiently translated, the translation halt of unfolded proteins and immune activation-related genes increased significantly, benefitting IBV replication. These data provide new insights into how IBV modulates its host\'s antiviral responses.

BACKGROUND: Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses.
RESULTS: In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.
METHODS: Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.

Ribosome profiling is a powerful technique to study translation at a transcriptome-wide level. However, ensuring good data quality is paramount for accurate interpretation, as is ensuring that the analyses are reproducible. We introduce a new Nextflow DSL2 pipeline, riboseq-flow, designed for processing and comprehensive quality control of ribosome profiling experiments. Riboseq-flow is user-friendly, versatile and upholds high standards in reproducibility, scalability, portability, version control and continuous integration. It enables users to efficiently analyse multiple samples in parallel and helps them evaluate the quality and utility of their data based on the detailed metrics and visualisations that are automatically generated. Riboseq-flow is available at https://github.com/iraiosub/riboseq-flow.
Ribosome profiling is a cutting-edge method that provides a detailed view of protein synthesis across the entire set of RNA molecules within cells. To ensure the reliability of such studies, high-quality data and the ability to replicate analyses are crucial. To address this, we present riboseq-flow, a new tool built with Nextflow DSL2, tailored for analysing data from ribosome profiling experiments. This pipeline stands out for its ease of use, flexibility, and commitment to high reproducibility standards. It\'s designed to handle multiple samples simultaneously, ensuring efficient analysis for large-scale studies. Moreover, riboseq-flow automatically generates detailed reports and visual representations to assess the data quality, enhancing researchers\' understanding of their experiments and guiding future decisions. This valuable resource is freely accessible at https://github.com/iraiosub/riboseq-flow.

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.

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.

Cellular iron homeostasis is regulated by iron regulatory proteins (IRP1 and IRP2) that sense iron levels (and other metabolic cues) and modulate mRNA translation or stability via interaction with iron regulatory elements (IREs). IRP2 is viewed as the primary regulator in the liver, yet our previous datasets showing diurnal rhythms for certain IRE-containing mRNAs suggest a nuanced temporal control mechanism. The purpose of this study is to gain insights into the daily regulatory dynamics across IRE-bearing mRNAs, specific IRP involvement, and underlying systemic and cellular rhythmicity cues in mouse liver.
We uncover high-amplitude diurnal oscillations in the regulation of key IRE-containing transcripts in the liver, compatible with maximal IRP activity at the onset of the dark phase. Although IRP2 protein levels also exhibit some diurnal variations and peak at the light-dark transition, ribosome profiling in IRP2-deficient mice reveals that maximal repression of target mRNAs at this timepoint still occurs. We further find that diurnal regulation of IRE-containing mRNAs can continue in the absence of a functional circadian clock as long as feeding is rhythmic.
Our findings suggest temporally controlled redundancy in IRP activities, with IRP2 mediating regulation of IRE-containing transcripts in the light phase and redundancy, conceivably with IRP1, at dark onset. Moreover, we highlight the significance of feeding-associated signals in driving rhythmicity. Our work highlights the dynamic nature and regulatory complexity in a metabolic pathway that had previously been considered well-understood.

Translational regulation plays the most critical role in gene expression. Ribosome profiling sequencing (Ribo-Seq) is one of the methods to study translation and its regulation. It is a high throughput technology based on deep sequencing, which targets ribosome protected mRNA fragments to produce a \'global snapshot\' of translatome. There has been an annual increase in the number of publications incorporating Ribo-seq technology. Because of its importance, we used PubMed database to conduct a comprehensive bibliometric analysis on Ribo-seq. We identified 2744 published articles that utilized the term \'Ribo-seq\' between 2009 and Jan 2024, and 684 articles that contained both Ribo-seq and RNA-seq terms. Based on keywords correlation analysis, we discovered that the primary focus of Ribo-seq articles lies in the areas of translation, transcriptome, and ribosome in the past few years and other topics such as single-cell ribo-seq and crispr within two years, reflecting current areas of interests in Ribo-seq research. The Ribo-seq data analysis applications were also explored and summarized, providing a guide for researchers to choose corresponding tools for different types of analysis. Overall, we highlighted the advances made by Ribo-seq technologies, and the possibilities of utilizing machine learning models to unravel information from multi-omics data. The integration of Ribo-seq with other omics data, such as RNA-seq, is essential to understand the gene expression in complex biological systems.

Tumor MYCN amplification is seen in high-risk neuroblastoma, yet direct targeting of this oncogenic transcription factor has been challenging. Here, we take advantage of the dependence of MYCN-amplified neuroblastoma cells on increased protein synthesis to inhibit the activity of eukaryotic translation initiation factor 4A1 (eIF4A1) using an amidino-rocaglate, CMLD012824. Consistent with the role of this RNA helicase in resolving structural barriers in 5\' untranslated regions (UTRs), CMLD012824 increased eIF4A1 affinity for polypurine-rich 5\' UTRs, including that of the MYCN and associated transcripts with critical roles in cell proliferation. CMLD012824-mediated clamping of eIF4A1 spanned the full lengths of mRNAs, while translational inhibition was mediated through 5\' UTR binding in a cap-dependent and -independent manner. Finally, CMLD012824 led to growth inhibition in MYCN-amplified neuroblastoma models without generalized toxicity. Our studies highlight the key role of eIF4A1 in MYCN-amplified neuroblastoma and demonstrate the therapeutic potential of disrupting its function.

Genome-wide measurement of ribosome occupancy on mRNAs has enabled empirical identification of translated regions, but high-confidence detection of coding regions that overlap annotated coding regions has remained challenging. Here, we report a sensitive and robust algorithm that revealed the translation of 388 N-terminally truncated proteins in budding yeast-more than 30-fold more than previously known. We extensively experimentally validated them and defined two classes. The first class lacks large portions of the annotated protein and tends to be produced from a truncated transcript. We show that two such cases, Yap5truncation and Pus1truncation, have condition-specific regulation and distinct functions from their respective annotated isoforms. The second class of truncated protein isoforms lacks only a small region of the annotated protein and is less likely to be produced from an alternative transcript isoform. Many display different subcellular localizations than their annotated counterpart, representing a common strategy for dual localization of otherwise functionally identical proteins. A record of this paper\'s transparent peer review process is included in the supplemental information.