Translation of mRNAs into proteins is a key cellular process. Ribosome binding sites and stop codons provide signals to initiate and terminate translation, while stable secondary mRNA structures can ...induce translational recoding events. Fluorescent proteins are commonly used to characterize such elements but require the modification of a part's natural context and allow only a few parameters to be monitored concurrently. Here, we combine Ribo‐seq with quantitative RNA‐seq to measure at nucleotide resolution and in absolute units the performance of elements controlling transcriptional and translational processes during protein synthesis. We simultaneously measure 779 translation initiation rates and 750 translation termination efficiencies across the Escherichia coli transcriptome, in addition to translational frameshifting induced at a stable RNA pseudoknot structure. By analyzing the transcriptional and translational response, we discover that sequestered ribosomes at the pseudoknot contribute to a σ32‐mediated stress response, codon‐specific pausing, and a drop in translation initiation rates across the cell. Our work demonstrates the power of integrating global approaches toward a comprehensive and quantitative understanding of gene regulation and burden in living cells.
Synopsis
A sequencing‐based method is developed to quantify transcriptional and translational processes, enabling high‐throughput measurements in absolute units of genetic regulatory components and the burden synthetic genetic constructs place on the host cell.
Quantitative transcription and translation profiles are generated from combined RNA‐seq and Ribo‐seq data to capture the steady‐state flux of RNA polymerases and ribosomes across the genome at a nucleotide resolution.
Mathematical models are used to infer the performance of genetic parts controlling translation.
This approach is used to simultaneously characterize ribosome bindings sites (RBSs) and stop codons across the E. coli transcriptome, dissect the transcriptional/translational response to expression of a strong heterologous RNA pseudoknot that stalls and frameshifts ribosomes, and measure the burden synthetic genetic constructs place on the host cell.
A sequencing‐based method is developed to quantify transcriptional and translational processes, enabling high‐throughput measurements in absolute units of genetic regulatory components and the burden synthetic genetic constructs place on the host cell.
Deep sequencing of ribosome footprints (ribosome profiling) maps and quantifies mRNA translation. Because ribosomes decode mRNA every 3 nt, the periodic property of ribosome footprints could be used ...to identify novel translated ORFs. However, due to the limited resolution of existing methods, the 3-nt periodicity is observed mostly in a global analysis, but not in individual transcripts. Here, we report a protocol applied to Arabidopsis that maps over 90% of the footprints to the main reading frame and thus offers super-resolution profiles for individual transcripts to precisely define translated regions. The resulting data not only support many annotated and predicted noncanonical translation events but also uncover small ORFs in annotated noncoding RNAs and pseudogenes. A substantial number of these unannotated ORFs are evolutionarily conserved, and some produce stable proteins. Thus, our study provides a valuable resource for plant genomics and an efficient optimization strategy for ribosome profiling in other organisms.
Initial light reception after germination is a dramatic life event when a seedling starts proper morphogenesis. Blue light contains a range of light wavelengths that plants can perceive. A previous ...report suggested that the chemical compound 3-bromo-7-nitroindazole (3B7N) inhibits blue light-mediated suppression of hypocotyl elongation by physically interacting with the blue light receptor Cryptochrome 1 (CRY1). We previously examined changes of genome-wide gene expression in Arabidopsis seedlings germinated in the dark and then exposed to blue light by RNA-seq and Ribo-seq analyses. The expression of ribosome-related genes was translationally upregulated in response to the initial blue light exposure, depending on signals from both the nucleus and chloroplasts. Here, we re-analyzed our previous data and examined the effect of 3B7N treatment on changes in gene expression upon blue light exposure. The results showed that 3B7N negatively affected translation of ribosome-related genes and, interestingly, the effects were similar to not only those in cry1cry2 mutants but also plants under suppression of photosynthesis. We propose an apparent crosstalk between chloroplast function and blue light signaling.
By mapping the positions of millions of translating ribosomes in the cell, ribosome profiling (Ribo-seq) has established its role as a powerful tool to study gene expression. Several laboratories ...have introduced modifications to the experimental protocol and expanded the repertoire of biochemical methods to study translation transcriptome-wide. However, the diversity of protocols highlights a need for standardization. At the same time, different computational analysis strategies have used Ribo-seq data to identify the set of translated sequences with high confidence. In this review we present an overview of such methodologies, outlining their assumptions, data requirements, and availability. At the interface between RNA and proteins, Ribo-seq can complement data from multiple omics approaches, zooming in on the central role of translation in the molecular cell.
Ribo-seq has become an established protocol to identify translated transcript regions via deep sequencing, closing the gap between RNA sequencing and proteomics.
Recently developed Ribo-seq data analysis strategies use different features as hallmarks of translation. Specifically, the ability to monitor the positions of translating ribosomes with single-nucleotide precision has driven the development of computational tools that rely on ‘subcodon resolution’. Knowing the concrete assumptions and precise goals of different approaches is crucial.
In addition to addressing translation-focused questions, from defining open reading frames to identifying alternative translation initiation sites and estimating differential translation rates, Ribo-seq data show great promise for integrative efforts combining additional omics approaches.
Long non-coding RNA (lncRNA) was originally defined as the representative of the non-coding RNAs and unable to encode. However, recent reports suggest that some lncRNAs actually contain open reading ...frames that encode peptides. These coding products play important roles in the pathogenesis of many diseases. Here, we summarize the regulatory pathways of mammalian lncRNA-encoded peptides in influencing muscle function, mRNA stability, gene expression, and so on. We also address the promoting and inhibiting functions of the peptides in different cancers and other diseases. Then we introduce the computational predicting methods and data resources to predict the coding ability of lncRNA. The intention of this review is to provide references for further coding research and contribute to reveal the potential prospects for targeted tumor therapy.
Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the ...mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation.
Turnip mosaic virus (TuMV) constitutes one of the primary diseases affecting Brassica rapa, severely impacting its production and resulting in crop failures in various regions worldwide. Recent ...research has demonstrated the significance of plant translation initiation factors, specifically the eIF4E and eIF4G family genes, as essential recessive disease resistance genes. In our study, we conducted evolutionary and gene expression studies, leading us to identify eIF(iso)4E.c as a potential TuMV-resistant gene. Leveraging CRISPR/Cas9 technology, we obtained mutant B. rapa plants with edited eIF(iso)4E.c gene. We confirmed eIF(iso)4E.c confers resistance against TuMV through phenotypic observations and virus content evaluations. Furthermore, we employed ribosome profiling assays on eif(iso)4e.c mutant seedlings to unravel the translation landscape in response to TuMV. Interestingly, we observed a moderate correlation between the fold changes in gene expression at the transcriptional and translational levels (R2 = 0.729). Comparative analysis of ribosome profiling and RNA-seq data revealed that plant–pathogen interaction, and MAPK signaling pathway–plant pathways were involved in eIF(iso)4E.c-mediated TuMV resistance. Further analysis revealed that sequence features, coding sequence length, and normalized minimal free energy, influenced the translation efficiency of genes. Our study highlights that the loss of eIF(iso)4E.c can result in a highly intricate translation mechanism, acting synergistically with transcription to confer resistance against TuMV.
smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of ...transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP.
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.”
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•Ribo-seq paired with proteomics-based methods optimally detects noncanonical ORFs.•Data quality and analytical pipelines impact the output of a Ribo-seq experiment.•Noncanonical ORF catalogs variably report both high- and low-stringency nominations.•A framework for standardized noncanonical ORF evidence will advance the field.
The human genome encodes thousands of noncanonical ORFs along with protein-coding genes. As a nascent field, many questions about them remain: How many exist? Do they encode proteins? What evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-Seq) to discern genome-wide ribosome occupancy and immunopeptidomics to detect peptides presented by major histocompatibility complex molecules. This article synthesizes the current state of noncanonical ORF research and proposes standards for their future investigation and reporting.
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