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Viral infection often triggers eukaryotic initiator factor 2α (eIF2α) phosphorylation, leading to global 5'-cap-dependent translation inhibition. RSV encodes messenger RNAs (mRNAs) mimicking 5'-cap structures of host mRNAs and thus inhibition of cap-dependent translation initiation would likely also reduce viral translation. We confirmed that RSV limits widespread translation initiation inhibition and unexpectedly found that the fraction of ribosomes within polysomes increases during infection, indicating higher ribosome loading on mRNAs during infection. We found that AU-rich host transcripts that are less efficiently translated under normal conditions become more efficient at recruiting ribosomes, similar to RSV transcripts. Viral transcripts are transcribed in cytoplasmic inclusion bodies, where the viral AU-rich binding protein M2-1 has been shown to bind viral transcripts and shuttle them into the cytoplasm. We further demonstrated that M2-1 is found on polysomes, and that M2-1 might deliver host AU-rich transcripts for translation.

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The degree to which translational control is specified by mRNA sequence is poorly understood in mammalian cells. Here, we constructed and leveraged a compendium of 3,819 ribosomal profiling datasets, distilling them into a transcriptome-wide atlas of translation efficiency (TE) measurements encompassing >140 human and mouse cell types. We subsequently developed RiboNN, a multitask deep convolutional neural network, and classic machine learning models to predict TEs in hundreds of cell types from sequence-encoded mRNA features, achieving state-of-the-art performance (r=0.79 in human and r=0.78 in mouse for mean TE across cell types). While the majority of earlier models solely considered 5' UTR sequence, RiboNN integrates contributions from the full-length mRNA sequence, learning that the 5' UTR, CDS, and 3' UTR respectively possess ~67%, 31%, and 2% per-nucleotide information density in the specification of mammalian TEs. Interpretation of RiboNN revealed that the spatial positioning of low-level di- and tri-nucleotide features (i.e., including codons) largely explain model performance, capturing mechanistic principles such as how ribosomal processivity and tRNA abundance control translational output. RiboNN is predictive of the translational behavior of base-modified therapeutic RNA, and can explain evolutionary selection pressures in human 5' UTRs. Finally, it detects a common language governing mRNA regulatory control and highlights the interconnectedness of mRNA translation, stability, and localization in mammalian organisms.

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Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

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Plants employ distinct mechanisms to respond to environmental changes. Modification of mRNA by N 6-methyladenosine (m6A), known to affect the fate of mRNA, may be one such mechanism to reprogram mRNA processing and translatability upon stress. However, it is difficult to distinguish a direct role from a pleiotropic effect for this modification due to its prevalence in RNA. Through characterization of the transient knockdown-mutants of m6A writer components and mutants of specific m6A readers, we demonstrate the essential role that m6A plays in basal resistance and pattern-triggered immunity (PTI). A global m6A profiling of mock and PTI-induced Arabidopsis plants as well as formaldehyde fixation and cross-linking immunoprecipitation-sequencing of the m6A reader, EVOLUTIONARILY CONSERVED C-TERMINAL REGION2 (ECT2) showed that while dynamic changes in m6A modification and binding by ECT2 were detected upon PTI induction, most of the m6A sites and their association with ECT2 remained static. Interestingly, RNA degradation assay identified a dual role of m6A in stabilizing the overall transcriptome while facilitating rapid turnover of immune-induced mRNAs during PTI. Moreover, polysome profiling showed that m6A enhances immune-associated translation by binding to the ECT2/3/4 readers. We propose that m6A plays a positive role in plant immunity by destabilizing defense mRNAs while enhancing their translation efficiency to create a transient surge in the production of defense proteins.

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BACKGROUND: This study is based on deep mining of Ribo-seq data for the identification of lncRNAs that have highly expressed sORFs in HCC. In this paper, dynamic prospects associated with sORFs acting as newly defined tumor-specific epitopes are discussed with possible improvement in strategies for tumor immunotherapy. OBJECTIVE: Using ribosome profiling to identify and characterize sORFs within lncRNAs in HCC, identify potential therapeutic targets and tumor-specific epitopes applicable for immunotherapy. METHODS: MetamORF performed the identification of sORFs with deep analysis of the data of ribosome profiling in lncRNAs associated with HCC. The translation efficiency in these molecules was estimated, and epitope prediction was done by pVACbind. Peptide search was done to check the presence of micropeptides translated from these identified sORFs. validated translational activity and identified potential epitopes. RESULTS: Higher translation efficiency was noted in the case of lncRNAs associated with HCC compared to normal tissues. Of particular note is ORF3418981, which results in the highest expression and has supporting experimental evidence at the protein level. Epitope prediction identified a putative epitope at the C-terminus of ORF3418981. CONCLUSIONS: This study uncovers the as-yet-unknown potential of lncRNA-derived sORFs as sources of tumor antigens, shifting the research focus from protein-coding genes to non-coding RNAs also in the HCC context. Moreover, this study highlights the contribution of a subset of lncRNAs, especially LINC00152, to the development of tumors and modulation of the immune response by its sORFs.

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In eukaryotes, the localization of small ribosomal subunits to mRNA transcripts requires the translation of Kozak elements at the starting site. The sequence of Kozak elements affects the translation efficiency of protein synthesis. However, whether the upstream nucleotide of Kozak sequence affects the expression of recombinant proteins in Chinese hamster ovary (CHO) cells remains unclear. In order to find the optimal sequence to enhance recombinant proteins expression in CHO cells, -10 to +4 sequences around ATG in 100 CHO genes were compared, and the extended Kozak elements with different translation intensities were constructed. Using the classic Kozak element as control, the effects of optimized extended Kozak elements on the secreted alkaline phosphatase (SEAP) and human serum albumin (HSA) gene were studied. The results showed that the optimized extended Kozak sequence can enhance the stable expression level of recombinant proteins in CHO cells. Furthermore, it was found that the increased expression level of the recombinant protein was not related with higher transcription level. In summary, optimizing extended Kozak elements can enhance the expression of recombinant proteins in CHO cells, which contributes to the construction of an efficient expression system for CHO cells.

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The 5' UTR, a regulatory region at the beginning of an mRNA molecule, plays a crucial role in regulating the translation process and impacts the protein expression level. Language models have showcased their effectiveness in decoding the functions of protein and genome sequences. Here, we introduced a language model for 5' UTR, which we refer to as the UTR-LM. The UTR-LM is pre-trained on endogenous 5' UTRs from multiple species and is further augmented with supervised information including secondary structure and minimum free energy. We fine-tuned the UTR-LM in a variety of downstream tasks. The model outperformed the best known benchmark by up to 5% for predicting the Mean Ribosome Loading, and by up to 8% for predicting the Translation Efficiency and the mRNA Expression Level. The model also applies to identifying unannotated Internal Ribosome Entry Sites within the untranslated region and improves the AUPR from 0.37 to 0.52 compared to the best baseline. Further, we designed a library of 211 novel 5' UTRs with high predicted values of translation efficiency and evaluated them via a wet-lab assay. Experiment results confirmed that our top designs achieved a 32.5% increase in protein production level relative to well-established 5' UTR optimized for therapeutics.

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BACKGROUND: RNA m5C methylation has been extensively implicated in the occurrence and development of tumors. As the main methyltransferase, NSUN2 plays a crucial regulatory role across diverse tumor types. However, the precise impact of NSUN2-mediated m5C modification on breast cancer (BC) remains unclear. Our study aims to elucidate the molecular mechanism underlying how NSUN2 regulates the target gene HGH1 (also known as FAM203) through m5C modification, thereby promoting BC progression. Additionally, this study targets at preliminarily clarifying the biological roles of NSUN2 and HGH1 in BC. METHODS: Tumor and adjacent tissues from 5 BC patients were collected, and the m5C modification target HGH1 in BC was screened through RNA sequencing (RNA-seq) and single-base resolution m5C methylation sequencing (RNA-BisSeq). Methylation RNA immunoprecipitation-qPCR (MeRIP-qPCR) and RNA-binding protein immunoprecipitation-qPCR (RIP-qPCR) confirmed that the methylation molecules NSUN2 and YBX1 specifically recognized and bound to HGH1 through m5C modification. In addition, proteomics, co-immunoprecipitation (co-IP), and Ribosome sequencing (Ribo-Seq) were used to explore the biological role of HGH1 in BC. RESULTS: As the main m5C methylation molecule, NSUN2 is abnormally overexpressed in BC and increases the overall level of RNA m5C. Knocking down NSUN2 can inhibit BC progression in vitro or in vivo. Combined RNA-seq and RNA-BisSeq analysis identified HGH1 as a potential target of abnormal m5C modifications. We clarified the mechanism by which NSUN2 regulates HGH1 expression through m5C modification, a process that involves interactions with the YBX1 protein, which collectively impacts mRNA stability and protein synthesis. Furthermore, this study is the first to reveal the binding interaction between HGH1 and the translation elongation factor EEF2, providing a comprehensive understanding of its ability to regulate transcript translation efficiency and protein synthesis in BC cells. CONCLUSIONS: This study preliminarily clarifies the regulatory role of the NSUN2-YBX1-m5C-HGH1 axis from post-transcriptional modification to protein translation, revealing the key role of abnormal RNA m5C modification in BC and suggesting that HGH1 may be a new epigenetic biomarker and potential therapeutic target for BC.

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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-ß 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. IMPORTANCE: 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.

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The Escherichia coli (E. coli)-based protein synthesis using recombinant elements (PURE) system is a cell-free protein synthesis system reconstituted from purified factors essential for E. coli translation. The PURE system is widely used for basic and synthetic biology applications. One of the major challenges associated with the PURE system is that the protein yield of the system varies depending on the protein. Studies have reported that the efficiency of translation is significantly affected by nucleotide and amino acid sequences, especially in the N-terminal region. Here, we investigated the inherent effect of various N-terminal sequences on protein synthesis using the PURE system. We found that a single amino acid substitution in the N-terminal region significantly altered translation efficiency in the PURE system, especially at low temperatures. This result gives us useful suggestions for the expression of the protein of interest in vitro and in vivo.

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Different bacterial species have dramatically different generation times, from 20-30 min in Escherichia coli to about two weeks in Mycobacterium leprae. The translation machinery in a cell needs to synthesize all proteins for a new cell in each generation. The three subprocesses of translation, i.e., initiation, elongation, and termination, are expected to be under stronger selection pressure to optimize in short-generation bacteria (SGB) such as Vibrio natriegens than in the long-generation Mycobacterium leprae. The initiation efficiency depends on the start codon decoded by the initiation tRNA, the optimal Shine-Dalgarno (SD) decoded by the anti-SD (aSD) sequence on small subunit rRNA, and the secondary structure that may embed the initiation signals and prevent them from being decoded. The elongation efficiency depends on the tRNA pool and codon usage. The termination efficiency in bacteria depends mainly on the nature of the stop codon and the nucleotide immediately downstream of the stop codon. By contrasting SGB with long-generation bacteria (LGB), we predict (1) SGB to have more ribosome RNA operons to produce ribosomes, and more tRNA genes for carrying amino acids to ribosomes, (2) SGB to have a higher percentage of genes using AUG as the start codon and UAA as the stop codon than LGB, (3) SGB to exhibit better codon and anticodon adaptation than LGB, and (4) SGB to have a weaker secondary structure near the translation initiation signals than LGB. These differences between SGB and LGB should be more pronounced in highly expressed genes than the rest of the genes. We present empirical evidence in support of these predictions.

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Haem oxygenase-1 (HO-1) is a ubiquitously expressed gene involved in cellular homoeostasis, and its imbalance in expression results in various disorders. To alleviate such disorders, HO-1 gene expression needs to be modulated. Codon usage bias results from evolutionary forces acting on any nucleotide sequence and determines the gene expression. Like codon usage bias, codon pair bias also exists, playing a role in gene expression. In the present study, HO-1 gene was recoded by manipulating codon and codon pair bias, and four such constructs were made through codon/codon pair deoptimization and codon/codon pair optimization to reduce and enhance the HO-1 gene expression. Codon usage analysis was done for these constructs for four tissues brain, heart, pancreas and liver. Based on codon usage in different tissues, gene expression of these tissues was determined in terms of the codon adaptation index. Based on the codon adaptation index, minimum free energy, and translation efficiency, constructs were evaluated for enhanced or decreased HO-1 expression. The analysis revealed that for enhancing gene expression, codon pair optimization, while for reducing gene expression, codon deoptimization is efficacious. The recoded constructs developed in the study could be used in gene therapy regimens to cure HO-1 over or underexpression-associated disorders.

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Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

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mRNA vaccines have been shown to be effective in combating the COVID-19 pandemic. The amount of research on the use of mRNAs as preventive and therapeutic modalities has undergone explosive growth in the last few years. Nonetheless, the issue of the stability of mRNA molecules and their translation efficiency remains incompletely resolved. These characteristics of mRNA directly affect the expression level of a desired protein. Regulatory elements of RNA-5' and 3' untranslated regions (UTRs)-are responsible for translation efficiency. An optimal combination of the regulatory sequences allows mRNA to significantly increase the target protein's expression. We assessed the translation efficiency of mRNA encoding of firefly luciferase with various 5' and 3'UTRs in vitro on cell lines DC2.4 and THP1. We found that mRNAs containing 5'UTR sequences from eukaryotic genes HBB, HSPA1A, Rabb, or H4C2, or from the adenoviral leader sequence TPL, resulted in higher levels of luciferase bioluminescence 4 h after transfection of DC2.4 cells as compared with 5'UTR sequences used in vaccines mRNA-1273 and BNT162b2 from Moderna and BioNTech. mRNA containing TPL as the 5'UTR also showed higher efficiency (as compared with the 5'UTR from Moderna) at generating a T-cell response in mice immunized with mRNA vaccines encoding a multiepitope antigen. By contrast, no effects of various 5'UTRs and 3'UTRs were detectable in THP1 cells, suggesting that the observed effects are cell type specific. Further analyses enabled us to identify potential cell type-specific RNA-binding proteins that differ in landing sites within mRNAs with various 5'UTRs and 3'UTRs. Taken together, our data indicate high translation efficiency of TPL as a 5'UTR, according to experiments on DC2.4 cells and C57BL/6 mice.

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Bacillus species, such as Bacillus subtilis and Bacillus licheniformis, are important industrial bacteria. However, there is a lack of standardized and predictable genetic tools for convenient and reproducible assembly of genetic modules in Bacillus species to realize their full potential. In this study, we constructed a Ribosome Binding Site (RBS) library in B. licheniformis, which provides incremental regulation of expression levels over a 104-fold range. Additionally, we developed a model to quantify the resulting translation rates. We successfully demonstrated the robust expression of various target genes using the RBS library and showed that the model accurately predicts the translation rates of arbitrary coding genes. Importantly, we also extended the use of the RBS library and prediction model to B. subtilis, B. thuringiensis, and B. amyloliquefacie. The versatility of the RBS library and its prediction model enables quantification of biological behavior, facilitating reliable forward engineering of gene expression.

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mRNA-based therapeutics have been found to be a promising treatment strategy in immunotherapy, gene therapy, and cancer treatments. Effectiveness of mRNA therapeutics depends on the level and duration of a desired protein's expression, which is determined by various cis- and trans-regulatory elements of the mRNA. Sequences of 5' and 3' untranslated regions (UTRs) are responsible for translational efficiency and stability of mRNA. An optimal combination of the regulatory sequences allows researchers to significantly increase the target protein's expression. Using both literature data and previously obtained experimental data, we chose six sequences of 5'UTRs (adenoviral tripartite leader [TPL], HBB, rabbit ß-globin [Rabb], H4C2, Moderna, and Neo2) and five sequences of 3'UTRs (mtRNR-EMCV, mtRNR-AES, mtRNR-mtRNR, BioNTech, and Moderna). By combining them, we constructed 30 in vitro transcribed RNAs encoding firefly luciferase with various combinations of 5'- and 3'UTRs, and the resultant bioluminescence was assessed in the DC2.4 cell line at 4, 8, 24, and 72 h after transfection. The cellular data enabled us to identify the best seven combinations of 5'- and 3'UTRs, whose translational efficiency was then assessed in BALB/c mice. Two combinations of 5'- and 3'UTRs (5'Rabb-3'mtRNR-EMCV and 5'TPL-3'Biontech) led to the most pronounced increase in the luciferase amount in the in vivo experiment in mice. Subsequent analysis of the stability of the mRNA indicated that the increase in luciferase expression is explained primarily by the efficiency of translation, not by the number of RNA molecules. Altogether, these findings suggest that 5'UTR-and-3'UTR combinations 5'Rabb-3'mtRNR- EMCV and 5'TPL-3'Biontech lead to high expression of target proteins and may be considered for use in preventive and therapeutic modalities based on mRNA.

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N4-Acetylcytidine (ac4C), a highly conserved post-transcriptional machinery with extensive existence for RNA modification, plays versatile roles in various cellular processes and functions. However, the molecular mechanism by which ac4C modification mediates neuropathic pain remains elusive. Here, it is found that the enhanced ac4C modification promotes the recruitment of polysome in Vegfa mRNA and strengthens the translation efficiency following SNI. Nerve injury increases the expression of NAT10 and the interaction between NAT10 and Vegfa mRNA in the dorsal horn neurons, and the gain and loss of NAT10 function further confirm that NAT10 is involved in the ac4C modification in Vegfa mRNA and pain behavior. Moreover, the ac4C-mediated VEGFA upregulation contributes to the central sensitivity and neuropathic pain induced by SNI or AAV-hSyn-NAT10. Finally, SNI promotes the binding of HNRNPK in Vegfa mRNA and subsequently recruits the NAT10. The enhanced interaction between HNRNPK and NAT10 contributes to the ac4C modification of Vegfa mRNA and neuropathic pain. These findings suggest that the enhanced interaction between HNRNPK and Vegfa mRNA upregulates the ac4C level by recruiting NAT10 and contributes to the central sensitivity and neuropathic pain following SNI. Blocking this cascade may be a novel therapeutic approach in patients with neuropathic pain.

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The expression of plant genes under salt stress at the transcriptional level has been extensively studied. However, less attention has been paid to gene translation regulation under salt stress. In this study, Ribo-seq and RNA-seq analyses were conducted in Medicago truncatula seedlings grown under normal and salt stress conditions. The results showed that salt stress significantly altered the gene expression at the transcriptional and translational levels, with 2755 genes showing significant changes only at the translational level. Salt stress significantly inhibited the gene translation efficiency. Small ORFs (including uORFs in the 5'UTR, dORFs in 3'UTRs, and sORFs in lncRNAs) were identified throughout the genome of M. truncatula. The efficiency of gene translation was simultaneously regulated by the uORFs, dORFs, and miRNAs. In summary, our results provide valuable information about translatomic resources and new insights into plant responses to salt stress.

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RNA accessibility is a useful RNA secondary structural feature for predicting RNA-RNA interactions and translation efficiency in prokaryotes. However, conventional accessibility calculation tools, such as Raccess, are computationally expensive and require considerable computational time to perform transcriptome-scale analysis. In this study, we developed DeepRaccess, which predicts RNA accessibility based on deep learning methods. DeepRaccess was trained to take artificial RNA sequences as input and to predict the accessibility of these sequences as calculated by Raccess. Simulation and empirical dataset analyses showed that the accessibility predicted by DeepRaccess was highly correlated with the accessibility calculated by Raccess. In addition, we confirmed that DeepRaccess could predict protein abundance in E.coli with moderate accuracy from the sequences around the start codon. We also demonstrated that DeepRaccess achieved tens to hundreds of times software speed-up in a GPU environment. The source codes and the trained models of DeepRaccess are freely available at https://github.com/hmdlab/DeepRaccess.

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Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.