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Iosub IA, Wilkins OG, Ule J. Riboseq-flow: A streamlined, reliable pipeline for ribosome profiling data analysis and quality control. Wellcome Open Res 2024; 9:179. [PMID: 38846930 PMCID: PMC11153996 DOI: 10.12688/wellcomeopenres.21000.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/12/2024] [Indexed: 06/09/2024] Open
Abstract
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.
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Affiliation(s)
- Ira A. Iosub
- The Francis Crick Institute, London, England, UK
- UK Dementia Research Institute at King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Oscar G. Wilkins
- The Francis Crick Institute, London, England, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Jernej Ule
- The Francis Crick Institute, London, England, UK
- UK Dementia Research Institute at King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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2
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Qanmber G, You Q, Yang Z, Fan L, Zhang Z, Chai M, Gao B, Li F, Yang Z. Transcriptional and translational landscape fine-tune genome annotation and explores translation control in cotton. J Adv Res 2024; 58:13-30. [PMID: 37207930 PMCID: PMC10982868 DOI: 10.1016/j.jare.2023.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/10/2023] [Accepted: 05/12/2023] [Indexed: 05/21/2023] Open
Abstract
INTRODUCTION The unavailability of intergenic region annotation in whole genome sequencing and pan-genomics hinders efforts to enhance crop improvement. OBJECTIVES Despite advances in research, the impact of post-transcriptional regulation on fiber development and translatome profiling at different stages of fiber growth in cotton (G. hirsutum) remains unexplored. METHODS We utilized a combination of reference-guided de novo transcriptome assembly and ribosome profiling techniques to uncover the hidden mechanisms of translational control in eight distinct tissues of upland cotton. RESULTS Our study identified P-site distribution at three-nucleotide periodicity and dominant ribosome footprint at 27 nucleotides. Specifically, we have detected 1,589 small open reading frames (sORFs), including 1,376 upstream ORFs (uORFs) and 213 downstream ORFs (dORFs), as well as 552 long non-coding RNAs (lncRNAs) with potential coding functions, which fine-tune the annotation of the cotton genome. Further, we have identified novel genes and lncRNAs with strong translation efficiency (TE), while sORFs were found to affect mRNA transcription levels during fiber elongation. The reliability of these findings was confirmed by the high consistency in correlation and synergetic fold change between RNA-sequencing (RNA-seq) and Ribosome-sequencing (Ribo-seq) analyses. Additionally, integrated omics analysis of the normal fiber ZM24 and short fiber pag1 cotton mutant revealed several differentially expressed genes (DEGs), and fiber-specific expressed (high/low) genes associated with sORFs (uORFs and dORFs). These findings were further supported by the overexpression and knockdown of GhKCS6, a gene associated with sORFs in cotton, and demonstrated the potential regulation of the mechanism governing fiber elongation on both the transcriptional and post-transcriptional levels. CONCLUSION Reference-guided transcriptome assembly and the identification of novel transcripts fine-tune the annotation of the cotton genome and predicted the landscape of fiber development. Our approach provided a high-throughput method, based on multi-omics, for discovering unannotated ORFs, hidden translational control, and complex regulatory mechanisms in crop plants.
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Affiliation(s)
- Ghulam Qanmber
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China; National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Qi You
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou 225009, China
| | - Zhaoen Yang
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China; National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Liqiang Fan
- National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Zhibin Zhang
- National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Mao Chai
- National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China
| | - Baibai Gao
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China
| | - Fuguang Li
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China; National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China.
| | - Zuoren Yang
- Zhengzhou Research Base, National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China; National Key Laboratory of Cotton Bio‑breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China.
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3
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Goldkamp AK, Hagen DE. Implications of tRNA abundance on translation elongation across bovine tissues. Front Genet 2023; 14:1308048. [PMID: 38174049 PMCID: PMC10763252 DOI: 10.3389/fgene.2023.1308048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
Introduction: Translation is a crucial stage of gene expression. It may also act as an additional layer of regulation that plays an important role in gene expression and function. Highly expressed genes are believed to be codon-biased to support increased protein production, in which quickly translated codons correspond to highly abundant tRNAs. Synonymous SNPs, considered to be silent due to the degeneracy of the genetic code, may shift protein abundance and function through alterations in translational efficiency and suboptimal pairing to lowly abundant tRNAs. Methods: Here, we applied Quantitative Mature tRNA sequencing (QuantM-tRNAseq) and ribosome profiling across bovine tissues in order to investigate the relationship between tRNA expression and slowed translation. Results: Moreover, we have identified genes modulated at transcriptional and/or translational levels underlying tissue-specific biological processes. We have also successfully defined pausing sites that depict the regulatory information encoded within the open reading frame of transcripts, which could be related to translation rate and facilitate proper protein folding. This work offers an atlas of distinctive pausing sites across three bovine tissues, which provides an opportunity to predict codon optimality and understand tissue-specific mechanisms of regulating protein synthesis.
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Affiliation(s)
| | - Darren E. Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, United States
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4
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Ansari SA, Dantoft W, Ruiz-Orera J, Syed AP, Blachut S, van Heesch S, Hübner N, Uhlenhaut NH. Integrative analysis of macrophage ribo-Seq and RNA-Seq data define glucocorticoid receptor regulated inflammatory response genes into distinct regulatory classes. Comput Struct Biotechnol J 2022; 20:5622-5638. [PMID: 36284713 PMCID: PMC9582734 DOI: 10.1016/j.csbj.2022.09.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 11/03/2022] Open
Abstract
Glucocorticoids such as dexamethasone (Dex) are widely used to treat both acute and chronic inflammatory conditions. They regulate immune responses by dampening cell-mediated immunity in a glucocorticoid receptor (GR)-dependent manner, by suppressing the expression of pro-inflammatory cytokines and chemokines and by stimulating the expression of anti-inflammatory mediators. Despite its evident clinical benefit, the mechanistic underpinnings of the gene regulatory networks transcriptionally controlled by GR in a context-specific manner remain mysterious. Next generation sequencing methods such mRNA sequencing (RNA-seq) and Ribosome profiling (ribo-seq) provide tools to investigate the transcriptional and post-transcriptional mechanisms that govern gene expression. Here, we integrate matched RNA-seq data with ribo-seq data from human acute monocytic leukemia (THP-1) cells treated with the TLR4 ligand lipopolysaccharide (LPS) and with Dex, to investigate the global transcriptional and translational regulation (translational efficiency, ΔTE) of Dex-responsive genes. We find that the expression of most of the Dex-responsive genes are regulated at both the transcriptional and the post-transcriptional level, with the transcriptional changes intensified on the translational level. Overrepresentation pathway analysis combined with STRING protein network analysis and manual functional exploration, identified these genes to encode immune effectors and immunomodulators that contribute to macrophage-mediated immunity and to the maintenance of macrophage-mediated immune homeostasis. Further research into the translational regulatory network underlying the GR anti-inflammatory response could pave the way for the development of novel immunomodulatory therapeutic regimens with fewer undesirable side effects.
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Affiliation(s)
- Suhail A. Ansari
- Institute for Diabetes and Endocrinology (IDE), Helmholtz Center Munich (HMGU) and German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Widad Dantoft
- Institute for Diabetes and Endocrinology (IDE), Helmholtz Center Munich (HMGU) and German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jorge Ruiz-Orera
- Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Afzal P. Syed
- Institute for Diabetes and Endocrinology (IDE), Helmholtz Center Munich (HMGU) and German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Susanne Blachut
- Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Sebastiaan van Heesch
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS Utrecht, The Netherlands
| | - Norbert Hübner
- Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany,Charite-Universitätsmedizin Berlin, Berlin, Germany
| | - Nina Henriette Uhlenhaut
- Institute for Diabetes and Endocrinology (IDE), Helmholtz Center Munich (HMGU) and German Center for Diabetes Research (DZD), Neuherberg, Germany,Metabolic Programming, School of Life Sciences Weihenstephan, ZIEL – Institute for Food and Health, Technical University of Munich (TUM), Freising, Germany,Corresponding author.
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5
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Zhang Y, Zhang D, Xu Y, Qin Y, Gu M, Cai W, Bai Z, Zhang X, Chen R, Sun Y, Wu Y, Wang Z. Selection of Cashmere Fineness Functional Genes by Translatomics. Front Genet 2022; 12:775499. [PMID: 35096002 PMCID: PMC8790676 DOI: 10.3389/fgene.2021.775499] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/16/2021] [Indexed: 12/22/2022] Open
Abstract
Cashmere fineness is an important index to evaluate cashmere quality. Liaoning Cashmere Goat (LCG) has a large cashmere production and long cashmere fiber, but its fineness is not ideal. Therefore, it is important to find genes involved in cashmere fineness that can be used in future endeavors aiming to improve this phenotype. With the continuous advancement of research, the regulation of cashmere fineness has made new developments through high-throughput sequencing and genome-wide association analysis. It has been found that translatomics can identify genes associated with phenotypic traits. Through translatomic analysis, the skin tissue of LCG sample groups differing in cashmere fineness was sequenced by Ribo-seq. With these data, we identified 529 differentially expressed genes between the sample groups among the 27197 expressed genes. From these, 343 genes were upregulated in the fine LCG group in relation to the coarse LCG group, and 186 were downregulated in the same relationship. Through GO enrichment analysis and KEGG enrichment analysis of differential genes, the biological functions and pathways of differential genes can be found. In the GO enrichment analysis, 491 genes were significantly enriched, and the functional region was mainly in the extracellular region. In the KEGG enrichment analysis, the enrichment of the human papillomavirus infection pathway was seen the most. We found that the COL6A5 gene may affect cashmere fineness.
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Affiliation(s)
- Yu Zhang
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Dongyun Zhang
- International Business School and International Economics and Trade, Shenyang Normal University, Shenyang, China
| | - Yanan Xu
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yuting Qin
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Ming Gu
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Weidong Cai
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zhixian Bai
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Xinjiang Zhang
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Rui Chen
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yingang Sun
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Yanzhi Wu
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
| | - Zeying Wang
- College of Animal Science andVeterinary Medicine, Shenyang Agricultural University, Shenyang, China
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6
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A critical period of translational control during brain development at codon resolution. Nat Struct Mol Biol 2022; 29:1277-1290. [PMID: 36482253 PMCID: PMC9758057 DOI: 10.1038/s41594-022-00882-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 10/19/2022] [Indexed: 12/13/2022]
Abstract
Translation modulates the timing and amplification of gene expression after transcription. Brain development requires uniquely complex gene expression patterns, but large-scale measurements of translation directly in the prenatal brain are lacking. We measure the reactants, synthesis and products of mRNA translation spanning mouse neocortex neurogenesis, and discover a transient window of dynamic regulation at mid-gestation. Timed translation upregulation of chromatin-binding proteins like Satb2, which is essential for neuronal subtype differentiation, restricts protein expression in neuronal lineages despite broad transcriptional priming in progenitors. In contrast, translation downregulation of ribosomal proteins sharply decreases ribosome biogenesis, coinciding with a major shift in protein synthesis dynamics at mid-gestation. Changing activity of eIF4EBP1, a direct inhibitor of ribosome biogenesis, is concurrent with ribosome downregulation and affects neurogenesis of the Satb2 lineage. Thus, the molecular logic of brain development includes the refinement of transcriptional programs by translation. Modeling of the developmental neocortex translatome is provided as an open-source searchable resource at https://shiny.mdc-berlin.de/cortexomics .
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7
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Leininger SE, Rodriguez J, Vu QV, Jiang Y, Li MS, Deutsch C, O'Brien EP. Ribosome Elongation Kinetics of Consecutively Charged Residues Are Coupled to Electrostatic Force. Biochemistry 2021; 60:3223-3235. [PMID: 34652913 PMCID: PMC8916236 DOI: 10.1021/acs.biochem.1c00507] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
The speed of protein synthesis can dramatically change when consecutively charged residues are incorporated into an elongating nascent protein by the ribosome. The molecular origins of this class of allosteric coupling remain unknown. We demonstrate, using multiscale simulations, that positively charged residues generate large forces that move the P-site amino acid away from the A-site amino acid. Negatively charged residues generate forces of similar magnitude but move the A- and P-sites closer together. These conformational changes, respectively, increase and decrease the transition state barrier height to peptide bond formation, explaining how charged residues mechanochemically alter translation speed. This mechanochemical mechanism is consistent with in vivo ribosome profiling data exhibiting proportionality between translation speed and the number of charged residues, experimental data characterizing nascent chain conformations, and a previously published cryo-EM structure of a ribosome-nascent chain complex containing consecutive lysines. These results expand the role of mechanochemistry in translation and provide a framework for interpreting experimental results on translation speed.
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Affiliation(s)
- Sarah E Leininger
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, United States
| | - Judith Rodriguez
- Bioinformatics and Genomics Graduate Program, Huck Institutes of the Life Sciences, Penn State University, University Park, Pennsylvania 16802, United States
| | - Quyen V Vu
- Institute of Physics, Polish Academy of Sciences, Warsaw 02-668, Poland
| | - Yang Jiang
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, United States
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, Warsaw 02-668, Poland
- Institute for Computational Sciences and Technology, Ho Chi Minh City 700000, Vietnam
| | - Carol Deutsch
- Department of Physiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Edward P O'Brien
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, United States
- Bioinformatics and Genomics Graduate Program, Huck Institutes of the Life Sciences, Penn State University, University Park, Pennsylvania 16802, United States
- Institute for Computational and Data Sciences, Penn State University, University Park, Pennsylvania 16802, United States
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8
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Yadav V, Ullah Irshad I, Kumar H, Sharma AK. Quantitative Modeling of Protein Synthesis Using Ribosome Profiling Data. Front Mol Biosci 2021; 8:688700. [PMID: 34262940 PMCID: PMC8274658 DOI: 10.3389/fmolb.2021.688700] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/25/2021] [Indexed: 12/12/2022] Open
Abstract
Quantitative prediction on protein synthesis requires accurate translation initiation and codon translation rates. Ribosome profiling data, which provide steady-state distribution of relative ribosome occupancies along a transcript, can be used to extract these rate parameters. Various methods have been developed in the past few years to measure translation-initiation and codon translation rates from ribosome profiling data. In the review, we provide a detailed analysis of the key methods employed to extract the translation rate parameters from ribosome profiling data. We further discuss how these approaches were used to decipher the role of various structural and sequence-based features of mRNA molecules in the regulation of gene expression. The utilization of these accurate rate parameters in computational modeling of protein synthesis may provide new insights into the kinetic control of the process of gene expression.
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Affiliation(s)
- Vandana Yadav
- Department of Physics, Indian Institute of Technology Madras, Chennai, India
| | | | - Hemant Kumar
- School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
| | - Ajeet K Sharma
- Department of Physics, Indian Institute of Technology Jammu, Jammu, India
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9
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Tjeldnes H, Labun K, Torres Cleuren Y, Chyżyńska K, Świrski M, Valen E. ORFik: a comprehensive R toolkit for the analysis of translation. BMC Bioinformatics 2021; 22:336. [PMID: 34147079 PMCID: PMC8214792 DOI: 10.1186/s12859-021-04254-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND With the rapid growth in the use of high-throughput methods for characterizing translation and the continued expansion of multi-omics, there is a need for back-end functions and streamlined tools for processing, analyzing, and characterizing data produced by these assays. RESULTS Here, we introduce ORFik, a user-friendly R/Bioconductor API and toolbox for studying translation and its regulation. It extends GenomicRanges from the genome to the transcriptome and implements a framework that integrates data from several sources. ORFik streamlines the steps to process, analyze, and visualize the different steps of translation with a particular focus on initiation and elongation. It accepts high-throughput sequencing data from ribosome profiling to quantify ribosome elongation or RCP-seq/TCP-seq to also quantify ribosome scanning. In addition, ORFik can use CAGE data to accurately determine 5'UTRs and RNA-seq for determining translation relative to RNA abundance. ORFik supports and calculates over 30 different translation-related features and metrics from the literature and can annotate translated regions such as proteins or upstream open reading frames (uORFs). As a use-case, we demonstrate using ORFik to rapidly annotate the dynamics of 5' UTRs across different tissues, detect their uORFs, and characterize their scanning and translation in the downstream protein-coding regions. CONCLUSION In summary, ORFik introduces hundreds of tested, documented and optimized methods. ORFik is designed to be easily customizable, enabling users to create complete workflows from raw data to publication-ready figures for several types of sequencing data. Finally, by improving speed and scope of many core Bioconductor functions, ORFik offers enhancement benefiting the entire Bioconductor environment. AVAILABILITY http://bioconductor.org/packages/ORFik .
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Affiliation(s)
- Håkon Tjeldnes
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Kornel Labun
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Yamila Torres Cleuren
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.,Sars International Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway
| | - Katarzyna Chyżyńska
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Michał Świrski
- Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland
| | - Eivind Valen
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway. .,Sars International Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway.
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10
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Shao D, Ahmed N, Soni N, O'Brien EP. RiboA: a web application to identify ribosome A-site locations in ribosome profiling data. BMC Bioinformatics 2021; 22:156. [PMID: 33765913 PMCID: PMC7992832 DOI: 10.1186/s12859-021-04068-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 03/10/2021] [Indexed: 12/12/2022] Open
Abstract
Background Translation is a fundamental process in gene expression. Ribosome profiling is a method that enables the study of transcriptome-wide translation. A fundamental, technical challenge in analyzing Ribo-Seq data is identifying the A-site location on ribosome-protected mRNA fragments. Identification of the A-site is essential as it is at this location on the ribosome where a codon is translated into an amino acid. Incorrect assignment of a read to the A-site can lead to lower signal-to-noise ratio and loss of correlations necessary to understand the molecular factors influencing translation. Therefore, an easy-to-use and accurate analysis tool is needed to accurately identify the A-site locations. Results We present RiboA, a web application that identifies the most accurate A-site location on a ribosome-protected mRNA fragment and generates the A-site read density profiles. It uses an Integer Programming method that reflects the biological fact that the A-site of actively translating ribosomes is generally located between the second codon and stop codon of a transcript, and utilizes a wide range of mRNA fragment sizes in and around the coding sequence (CDS). The web application is containerized with Docker, and it can be easily ported across platforms. Conclusions The Integer Programming method that RiboA utilizes is the most accurate in identifying the A-site on Ribo-Seq mRNA fragments compared to other methods. RiboA makes it easier for the community to use this method via a user-friendly and portable web application. In addition, RiboA supports reproducible analyses by tracking all the input datasets and parameters, and it provides enhanced visualization to facilitate scientific exploration. RiboA is available as a web service at https://a-site.vmhost.psu.edu/. The code is publicly available at https://github.com/obrien-lab/aip_web_docker under the MIT license.
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Affiliation(s)
- Danying Shao
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, USA
| | - Nabeel Ahmed
- Department of Chemistry, Pennsylvania State University, University Park, USA
| | - Nishant Soni
- Department of Chemistry, Pennsylvania State University, University Park, USA
| | - Edward P O'Brien
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, USA. .,Department of Chemistry, Pennsylvania State University, University Park, USA.
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Nissley DA, Carbery A, Chonofsky M, Deane CM. Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains. Bioinformatics 2021; 37:1853-1859. [PMID: 33483722 PMCID: PMC8317121 DOI: 10.1093/bioinformatics/btab020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 12/11/2020] [Accepted: 01/12/2021] [Indexed: 02/05/2023] Open
Abstract
Motivation Protein synthesis is a non-equilibrium process, meaning that the speed of translation can influence the ability of proteins to fold and function. Assuming that structurally similar proteins fold by similar pathways, the profile of translation speed along an mRNA should be evolutionarily conserved between related proteins to direct correct folding and downstream function. The only evidence to date for such conservation of translation speed between homologous proteins has used codon rarity as a proxy for translation speed. There are, however, many other factors including mRNA structure and the chemistry of the amino acids in the A- and P-sites of the ribosome that influence the speed of amino acid addition. Results Ribosome profiling experiments provide a signal directly proportional to the underlying translation times at the level of individual codons. We compared ribosome occupancy profiles (extracted from five different large-scale yeast ribosome profiling studies) between related protein domains to more directly test if their translation schedule was conserved. Our analysis reveals that the ribosome occupancy profiles of paralogous domains tend to be significantly more similar to one another than to profiles of non-paralogous domains. This trend does not depend on domain length, structural classes, amino acid composition or sequence similarity. Our results indicate that entire ribosome occupancy profiles and not just rare codon locations are conserved between even distantly related domains in yeast, providing support for the hypothesis that translation schedule is conserved between structurally related domains to retain folding pathways and facilitate efficient folding. Availability and implementation Python3 code is available on GitHub at https://github.com/DanNissley/Compare-ribosome-occupancy. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Daniel A Nissley
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Anna Carbery
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
| | - Mark Chonofsky
- Department of Statistics, University of Oxford, Oxford, OX1 3LB, UK
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Genome-Wide Analysis of Actively Translated Open Reading Frames Using RiboTaper/ORFquant. Methods Mol Biol 2021; 2252:331-346. [PMID: 33765284 DOI: 10.1007/978-1-0716-1150-0_16] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Ribosome profiling, or Ribo-seq, provides precise information about the position of actively translating ribosomes. It can be used to identify open reading frames (ORFs) that are translated in a given sample. The RiboTaper pipeline, and the ORFquant R package, leverages the periodic distribution of such ribosomes along the ORF to perform a statistically robust test for translation which is insensitive to aperiodic noise and provides a statistically robust measure of translation. In addition to accounting for complex loci with overlapping ORFs, ORFquant is also able to use Ribo-seq as a tool for distinguishing actively translated transcripts from non-translated ones, within a given gene locus.
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Szavits-Nossan J, Ciandrini L. Inferring efficiency of translation initiation and elongation from ribosome profiling. Nucleic Acids Res 2020; 48:9478-9490. [PMID: 32821926 PMCID: PMC7515720 DOI: 10.1093/nar/gkaa678] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 07/29/2020] [Accepted: 08/15/2020] [Indexed: 01/13/2023] Open
Abstract
One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal}
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}{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.
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Affiliation(s)
- Juraj Szavits-Nossan
- SUPA, School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK
| | - Luca Ciandrini
- Centre de Biologie Structurale (CBS), CNRS, INSERM, Univ Montpellier, Montpellier 34090, France
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Sharma AK, Sormanni P, Ahmed N, Ciryam P, Friedrich UA, Kramer G, O’Brien EP. A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data. PLoS Comput Biol 2019; 15:e1007070. [PMID: 31120880 PMCID: PMC6559674 DOI: 10.1371/journal.pcbi.1007070] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 06/11/2019] [Accepted: 05/06/2019] [Indexed: 01/23/2023] Open
Abstract
Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.
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Affiliation(s)
- Ajeet K. Sharma
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Nabeel Ahmed
- Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Prajwal Ciryam
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Ulrike A. Friedrich
- Center for Molecular Biology of the Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Günter Kramer
- Center for Molecular Biology of the Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Edward P. O’Brien
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Institute for CyberScience, Pennsylvania State University, University Park, Pennsylvania, United States of America
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