1
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Oelschlaeger P. Molecular Mechanisms and the Significance of Synonymous Mutations. Biomolecules 2024; 14:132. [PMID: 38275761 PMCID: PMC10813300 DOI: 10.3390/biom14010132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/15/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
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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Affiliation(s)
- Peter Oelschlaeger
- Department of Biotechnology and Pharmaceutical Sciences, College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
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2
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Abrhámová K, Groušlová M, Valentová A, Hao X, Liu B, Převorovský M, Gahura O, Půta F, Sunnerhagen P, Folk P. Truncating the spliceosomal 'rope protein' Prp45 results in Htz1 dependent phenotypes. RNA Biol 2024; 21:1-17. [PMID: 38711165 PMCID: PMC11085953 DOI: 10.1080/15476286.2024.2348896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/24/2024] [Indexed: 05/08/2024] Open
Abstract
Spliceosome assembly contributes an important but incompletely understood aspect of splicing regulation. Prp45 is a yeast splicing factor which runs as an extended fold through the spliceosome, and which may be important for bringing its components together. We performed a whole genome analysis of the genetic interaction network of the truncated allele of PRP45 (prp45(1-169)) using synthetic genetic array technology and found chromatin remodellers and modifiers as an enriched category. In agreement with related studies, H2A.Z-encoding HTZ1, and the components of SWR1, INO80, and SAGA complexes represented prominent interactors, with htz1 conferring the strongest growth defect. Because the truncation of Prp45 disproportionately affected low copy number transcripts of intron-containing genes, we prepared strains carrying intronless versions of SRB2, VPS75, or HRB1, the most affected cases with transcription-related function. Intron removal from SRB2, but not from the other genes, partly repaired some but not all the growth phenotypes identified in the genetic screen. The interaction of prp45(1-169) and htz1Δ was detectable even in cells with SRB2 intron deleted (srb2Δi). The less truncated variant, prp45(1-330), had a synthetic growth defect with htz1Δ at 16°C, which also persisted in the srb2Δi background. Moreover, htz1Δ enhanced prp45(1-330) dependent pre-mRNA hyper-accumulation of both high and low efficiency splicers, genes ECM33 and COF1, respectively. We conclude that while the expression defects of low expression intron-containing genes contribute to the genetic interactome of prp45(1-169), the genetic interactions between prp45 and htz1 alleles demonstrate the sensitivity of spliceosome assembly, delayed in prp45(1-169), to the chromatin environment.
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Affiliation(s)
- Kateřina Abrhámová
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
| | - Martina Groušlová
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
| | - Anna Valentová
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
| | - Xinxin Hao
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Beidong Liu
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Martin Převorovský
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
| | - Ondřej Gahura
- Institute of Parasitology, Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic
| | - František Půta
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
| | - Per Sunnerhagen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Petr Folk
- Department of Cell Biology, Faculty of Science, Charles University, Praha, Czech Republic
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3
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Liu L, Zhao Y, Siepel A. DNA-sequence and epigenomic determinants of local rates of transcription elongation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572932. [PMID: 38187771 PMCID: PMC10769381 DOI: 10.1101/2023.12.21.572932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Across all branches of life, transcription elongation is a crucial, regulated phase in gene expression. Many recent studies in eukaryotes have focused on the regulation of promoter-proximal pausing of RNA Polymerase II (Pol II), but rates of productive elongation also vary substantially throughout the gene body, both within and across genes. Here, we introduce a probabilistic model for systematically evaluating potential determinants of the local elongation rate based on nascent RNA sequencing (NRS) data. Our model is derived from a unified model for both the kinetics of Pol II movement along the DNA template and the generation of NRS read counts at steady state. It allows for a continuously variable elongation rate along the gene body, with the rate at each nucleotide defined by a generalized linear relationship with nearby genomic and epigenomic features. High-dimensional feature vectors are accommodated through a sparse-regression extension. We show with simulations that the model allows accurate detection of associated features and accurate prediction of local elongation rates. In an analysis of public PRO-seq and epigenomic data, we identify several features that are strongly associated with reductions in the local elongation rate, including DNA methylation, splice sites, RNA stem-loops, CTCF binding sites, and several histone marks, including H3K36me3 and H4K20me1. By contrast, low-complexity sequences and H3K79me2 marks are associated with increases in elongation rate. In an analysis of DNA k -mers, we find that cytosine nucleotides are strongly associated with reductions in local elongation rate, particularly when preceded by guanines and followed by adenines or thymines. Increases in elongation rate are associated with thymines and A+T-rich k -mers. These associations are generally shared across cell types, and by considering them our model is effective at predicting features of held-out PRO-seq data. Overall, our analysis is the first to permit genome-wide predictions of relative nucleotide-specific elongation rates based on complex sets of genomic and epigenomic covariates. We have made predictions available for the K562, CD14+, MCF-7, and HeLa-S3 cell types in a UCSC Genome Browser track.
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Affiliation(s)
- Lingjie Liu
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
- Graduate Program in Genetics, Stony Brook University, Stony Brook, NY
| | - Yixin Zhao
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
- Graduate Program in Genetics, Stony Brook University, Stony Brook, NY
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4
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Wienecke AN, Barry ML, Pollard DA. Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae. Genetics 2023; 224:iyad113. [PMID: 37310925 PMCID: PMC10411576 DOI: 10.1093/genetics/iyad113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 04/10/2023] [Accepted: 05/15/2023] [Indexed: 06/15/2023] Open
Abstract
Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest that the influence of these 2 mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1,620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed-effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found that codon bias and mF interact synergistically in a positive association with logPPR, and this interaction explains almost all the effects of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain-encoding and 3' coding sequences, while mF acts most significantly through coding sequences with weaker effects from untranslated regions. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.
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Affiliation(s)
- Anastacia N Wienecke
- Biology Department, Western Washington University, Bellingham, WA 98225, USA
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Margaret L Barry
- Biology Department, Western Washington University, Bellingham, WA 98225, USA
| | - Daniel A Pollard
- Biology Department, Western Washington University, Bellingham, WA 98225, USA
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5
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Liu K, Ouyang Y, Lin R, Ge C, Zhou M. Strong negative correlation between codon usage bias and protein structural disorder impedes protein expression after codon optimization. J Biotechnol 2022; 343:15-24. [PMID: 34763006 DOI: 10.1016/j.jbiotec.2021.11.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 10/14/2021] [Accepted: 11/04/2021] [Indexed: 11/18/2022]
Abstract
As a common phenomenon existing in almost all genomes, codon usage bias has been studied for a long time. Codon optimization is a frequently used strategy to accelerate protein synthesis rate. Besides regulating protein translation speed, codon usage bias has also be reported to affect co-translation folding and transcription. P. pastoris is a well-developed expression system, whose efficiency is tightly correlated with commercial value. However, few studies focus on the role of codon usage bias in affecting protein expression in P. pastoris. Besides, many genes in P. pastoris genome show significant negative correlation between codon usage bias and protein structural disorder tendency. It's not known whether this feature is important for their expression. In order to answer these questions, we picked 4P. pastoris gene candidates with strong negative correlation between codon usage bias and protein structural disorder. We then performed full-length codon optimization which completely eliminated the correlation. Protein and RNA assays were then used to compare protein and mRNA levels before and after codon optimization. As a result, codon optimization failed to elevate their protein expression levels, and even resulted in a decrease. As represented by the trypsin sensitivity assays, codon optimization also altered the protein structure of 0616 and 0788. Besides protein, codon optimization also affected mRNA levels. Shown by in vitro and in vivo RNA degradation assays, the mRNA stability of 0616, 0788 and 0135 were also altered by codon optimization. For each gene, the detailed effect may be related with its specific sequence and protein structure. Our results suggest that codon usage bias is an important factor to regulate gene expression level, as well as mRNA and protein stabilities in P. pastoris. "Extreme" codon optimization in genes with strong negative correlation between codon usage bias and protein structural disorder tendency may not be favored. Compromised strategies should be tried if expression is not successful. Besides, codon optimization may affect protein structural conformation more severely in structural disordered proteins.
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Affiliation(s)
- Kunshan Liu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Yaqi Ouyang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Ru Lin
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Chenyu Ge
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Mian Zhou
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China.
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6
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Gutman T, Goren G, Efroni O, Tuller T. Estimating the predictive power of silent mutations on cancer classification and prognosis. NPJ Genom Med 2021; 6:67. [PMID: 34385450 PMCID: PMC8361094 DOI: 10.1038/s41525-021-00229-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023] Open
Abstract
In recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.
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Affiliation(s)
- Tal Gutman
- Department of Biomedical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv, Israel
| | - Guy Goren
- Department of Electrical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv, Israel
| | - Omri Efroni
- Department of Electrical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv, Israel.
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7
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Gedeon T, Davis L, Weber K, Thorenson J. Trade-offs among transcription elongation rate, number, and duration of ubiquitous pauses on highly transcribed bacterial genes. J Bioinform Comput Biol 2021; 19:2150020. [PMID: 34353243 DOI: 10.1142/s0219720021500207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In this paper, we study the limitations imposed on the transcription process by the presence of short ubiquitous pauses and crowding. These effects are especially pronounced in highly transcribed genes such as ribosomal genes (rrn) in fast growing bacteria. Our model indicates that the quantity and duration of pauses reported for protein-coding genes is incompatible with the average elongation rate observed in rrn genes. When maximal elongation rate is high, pause-induced traffic jams occur, increasing promoter occlusion, thereby lowering the initiation rate. This lowers average transcription rate and increases average transcription time. Increasing maximal elongation rate in the model is insufficient to match the experimentally observed average elongation rate in rrn genes. This suggests that there may be rrn-specific modifications to RNAP, which then experience fewer pauses, or pauses of shorter duration than those in protein-coding genes. We identify model parameter triples (maximal elongation rate, mean pause duration time, number of pauses) which are compatible with experimentally observed elongation rates. Average transcription time and average transcription rate are the model outputs investigated as proxies for cell fitness. These fitness functions are optimized for different parameter choices, opening up a possibility of differential control of these aspects of the elongation process, with potential evolutionary consequences. As an example, a gene's average transcription time may be crucial to fitness when the surrounding medium is prone to abrupt changes. This paper demonstrates that a functional relationship among the model parameters can be estimated using a standard statistical analysis, and this functional relationship describes the various trade-offs that must be made in order for the gene to control the elongation process and achieve a desired average transcription time. It also demonstrates the robustness of the system when a range of maximal elongation rates can be balanced with transcriptional pause data in order to maintain a desired fitness.
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Affiliation(s)
- Tomáš Gedeon
- Department of Mathematical Sciences, Montana State University, P.O. Box 172400, Bozeman, MT 59717-2400, USA
| | - Lisa Davis
- Department of Mathematical Sciences, Montana State University, P.O. Box 172400, Bozeman, MT 59717-2400, USA
| | - Katelyn Weber
- Department of Statistics, London School of Economics and Political Science, London, UK
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8
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Muniz L, Nicolas E, Trouche D. RNA polymerase II speed: a key player in controlling and adapting transcriptome composition. EMBO J 2021; 40:e105740. [PMID: 34254686 PMCID: PMC8327950 DOI: 10.15252/embj.2020105740] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 05/01/2021] [Accepted: 05/10/2021] [Indexed: 12/19/2022] Open
Abstract
RNA polymerase II (RNA Pol II) speed or elongation rate, i.e., the number of nucleotides synthesized per unit of time, is a major determinant of transcriptome composition. It controls co‐transcriptional processes such as splicing, polyadenylation, and transcription termination, thus regulating the production of alternative splice variants, circular RNAs, alternatively polyadenylated transcripts, or read‐through transcripts. RNA Pol II speed itself is regulated in response to intra‐ and extra‐cellular stimuli and can in turn affect the transcriptome composition in response to these stimuli. Evidence points to a potentially important role of transcriptome composition modification through RNA Pol II speed regulation for adaptation of cells to a changing environment, thus pointing to a function of RNA Pol II speed regulation in cellular physiology. Analyzing RNA Pol II speed dynamics may therefore be central to fully understand the regulation of physiological processes, such as the development of multicellular organisms. Recent findings also raise the possibility that RNA Pol II speed deregulation can be detrimental and participate in disease progression. Here, we review initial and current approaches to measure RNA Pol II speed, as well as providing an overview of the factors controlling speed and the co‐transcriptional processes which are affected. Finally, we discuss the role of RNA Pol II speed regulation in cell physiology.
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Affiliation(s)
- Lisa Muniz
- MCD, Centre de Biologie Integrative (CBI), CNRS, UPS, University of Toulouse, Toulouse, France
| | - Estelle Nicolas
- MCD, Centre de Biologie Integrative (CBI), CNRS, UPS, University of Toulouse, Toulouse, France
| | - Didier Trouche
- MCD, Centre de Biologie Integrative (CBI), CNRS, UPS, University of Toulouse, Toulouse, France
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9
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Bahiri-Elitzur S, Tuller T. Codon-based indices for modeling gene expression and transcript evolution. Comput Struct Biotechnol J 2021; 19:2646-2663. [PMID: 34025951 PMCID: PMC8122159 DOI: 10.1016/j.csbj.2021.04.042] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 04/17/2021] [Accepted: 04/18/2021] [Indexed: 11/21/2022] Open
Abstract
Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.
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Affiliation(s)
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
- The Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv, Israel
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10
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Tian T, Li S, Lang P, Zhao D, Zeng J. Full-length ribosome density prediction by a multi-input and multi-output model. PLoS Comput Biol 2021; 17:e1008842. [PMID: 33770074 PMCID: PMC8026034 DOI: 10.1371/journal.pcbi.1008842] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 04/07/2021] [Accepted: 03/01/2021] [Indexed: 11/29/2022] Open
Abstract
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS. Translation elongation is a process in which amino acids are linked into proteins by ribosomes in cells. Translation elongation rates along the mRNAs are not constant, and are regulated by a series of mechanisms, such as codon rarity and mRNA stability. In this study, we modeled the translation elongation process at a full-length coding sequence level and developed a deep learning based approach to predict the translation elongation rates from mRNA sequences, through extracting the regulatory codes of elongation rates from the contextual sequences. The analyses, based on our interpretable metric named codon impact score, for the first time (to the best of our knowledge), revealed that in addition to the neighboring codons of the ribosomal A sites, the remote codons may also have an important impact on the translation elongation rates. This new finding may stimulate additional experiments and shed light on the regulatory mechanisms of protein synthesis.
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Affiliation(s)
- Tingzhong Tian
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Shuya Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Peng Lang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
- * E-mail: (DZ); (JZ)
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China
- * E-mail: (DZ); (JZ)
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11
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Hia F, Takeuchi O. The effects of codon bias and optimality on mRNA and protein regulation. Cell Mol Life Sci 2021; 78:1909-1928. [PMID: 33128106 PMCID: PMC11072601 DOI: 10.1007/s00018-020-03685-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 10/05/2020] [Accepted: 10/12/2020] [Indexed: 12/25/2022]
Abstract
The central dogma of molecular biology entails that genetic information is transferred from nucleic acid to proteins. Notwithstanding retro-transcribing genetic elements, DNA is transcribed to RNA which in turn is translated into proteins. Recent advancements have shown that each stage is regulated to control protein abundances for a variety of essential physiological processes. In this regard, mRNA regulation is essential in fine-tuning or calibrating protein abundances. In this review, we would like to discuss one of several mRNA-intrinsic features of mRNA regulation that has been gaining traction of recent-codon bias and optimality. Specifically, we address the effects of codon bias with regard to codon optimality in several biological processes centred on translation, such as mRNA stability and protein folding among others. Finally, we examine how different organisms or cell types, through this system, are able to coordinate physiological pathways to respond to a variety of stress or growth conditions.
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Affiliation(s)
- Fabian Hia
- Department of Medical Chemistry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Osamu Takeuchi
- Department of Medical Chemistry, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
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12
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McKinnon LM, Miller JB, Whiting MF, Kauwe JSK, Ridge PG. A comprehensive analysis of the phylogenetic signal in ramp sequences in 211 vertebrates. Sci Rep 2021; 11:622. [PMID: 33436653 PMCID: PMC7803996 DOI: 10.1038/s41598-020-78803-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 11/23/2020] [Indexed: 01/24/2023] Open
Abstract
Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Ramp sequences were compared from 247 vertebrates (114 Mammalian and 133 non-mammalian), where the presence and absence of ramp sequences was analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life synthetic tree to determine the number of parallelisms and reversals that occurred, and those results were compared to random permutations. Parsimony and maximum likelihood analyses of the presence and absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, 81% of vertebrate mammalian ramps and 81.2% of other vertebrate ramps had less parallelisms and reversals than the mean from 1000 randomly permuted trees. A chi-square analysis of completely orthologous ramp sequences resulted in a p-value < 0.001 as compared to random chance. Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches if many orthologs are taken into account. However, phylogenomic methods utilizing few orthologs should be cautious in incorporating ramp sequences because individual ramp sequences may provide conflicting signals.
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Affiliation(s)
- Lauren M McKinnon
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Justin B Miller
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Michael F Whiting
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
- Monte L. Bean Museum, Brigham Young University, Provo, UT, 84602, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Perry G Ridge
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA.
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13
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Slobodin B, Dikstein R. So close, no matter how far: multiple paths connecting transcription to mRNA translation in eukaryotes. EMBO Rep 2020; 21:e50799. [PMID: 32803873 PMCID: PMC7507372 DOI: 10.15252/embr.202050799] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/22/2020] [Accepted: 07/23/2020] [Indexed: 12/15/2022] Open
Abstract
Transcription of DNA into mRNA and translation of mRNA into proteins are two major processes underlying gene expression. Due to the distinct molecular mechanisms, timings, and locales of action, these processes are mainly considered to be independent. During the last two decades, however, multiple factors and elements were shown to coordinate transcription and translation, suggesting an intricate level of synchronization. This review discusses the molecular mechanisms that impact both processes in eukaryotic cells of different origins. The emerging global picture suggests evolutionarily conserved regulation and coordination between transcription and mRNA translation, indicating the importance of this phenomenon for the fine-tuning of gene expression and the adjustment to constantly changing conditions.
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Affiliation(s)
- Boris Slobodin
- Department of Biomolecular SciencesThe Weizmann Institute of ScienceRehovotIsrael
| | - Rivka Dikstein
- Department of Biomolecular SciencesThe Weizmann Institute of ScienceRehovotIsrael
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14
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Interplay between Position-Dependent Codon Usage Bias and Hydrogen Bonding at the 5' End of ORFeomes. mSystems 2020; 5:5/4/e00613-20. [PMID: 32788408 PMCID: PMC7426154 DOI: 10.1128/msystems.00613-20] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Codon usage bias exerts control over a wide variety of molecular processes. The positioning of synonymous codons within coding sequences (CDSs) dictates protein expression by mechanisms such as local translation efficiency, mRNA Gibbs free energy, and protein cotranslational folding. In this work, we explore how codon usage affects the position-dependent content of hydrogen bonding, which in turn influences energy requirements for unwinding double-stranded DNA (dsDNA). We categorized codons according to their hydrogen bond content and found differential effects on hydrogen bonding encoded by codon variants. The specific positional disposition of codon variants within CDSs creates a ramp of hydrogen bonding at the 5' end of the ORFeome in Escherichia coli CDSs occupying the first position of operons are subjected to selective pressure that reduces their hydrogen bonding compared to internal CDSs, and highly transcribed CDSs demand a lower maximum capacity of hydrogen bonds per codon, suggesting that the energetic requirement for unwinding the dsDNA in highly transcribed CDSs has evolved to be minimized in E. coli Subsequent analysis of over 14,000 ORFeomes showed a pervasive ramp of hydrogen bonding at the 5' end in Bacteria and Archaea that positively correlates with the probability of mRNA secondary structure formation. Both the ramp and the correlation were not found in Fungi The position-dependent hydrogen bonding might be part of the mechanism that contributes to the coordination between transcription and translation in Bacteria and Archaea A Web-based application to analyze the position-dependent hydrogen bonding of ORFeomes has been developed and is publicly available (https://juanvillada.shinyapps.io/hbonds/).IMPORTANCE Redundancy of the genetic code creates a vast space of alternatives to encode a protein. Synonymous codons exert control over a variety of molecular and physiological processes of cells mainly through influencing protein biosynthesis. Recent findings have shown that synonymous codon choice affects transcription by controlling mRNA abundance, mRNA stability, transcription termination, and transcript biosynthesis cost. In this work, by analyzing thousands of Bacteria, Archaea, and Fungi genomes, we extend recent findings by showing that synonymous codon choice, corresponding to the number of hydrogen bonds in a codon, can also have an effect on the energetic requirements for unwinding double-stranded DNA in a position-dependent fashion. This report offers new perspectives on the mechanism behind the transcription-translation coordination and complements previous hypotheses on the resource allocation strategies used by Bacteria and Archaea to manage energy efficiency in gene expression.
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15
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Diament A, Weiner I, Shahar N, Landman S, Feldman Y, Atar S, Avitan M, Schweitzer S, Yacoby I, Tuller T. ChimeraUGEM: unsupervised gene expression modeling in any given organism. Bioinformatics 2020; 35:3365-3371. [PMID: 30715207 DOI: 10.1093/bioinformatics/btz080] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 01/07/2019] [Accepted: 01/30/2019] [Indexed: 01/06/2023] Open
Abstract
MOTIVATION Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. RESULTS To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. AVAILABILITY AND IMPLEMENTATION Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Alon Diament
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel
| | - Iddo Weiner
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Noam Shahar
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shira Landman
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Yael Feldman
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shimshi Atar
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel
| | - Meital Avitan
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shira Schweitzer
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Iftach Yacoby
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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16
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Galili M, Tuller T. CSN: unsupervised approach for inferring biological networks based on the genome alone. BMC Bioinformatics 2020; 21:190. [PMID: 32414319 PMCID: PMC7227238 DOI: 10.1186/s12859-020-3479-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 03/31/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Most organisms cannot be cultivated, as they live in unique ecological conditions that cannot be mimicked in the lab. Understanding the functionality of those organisms' genes and their interactions by performing large-scale measurements of transcription levels, protein-protein interactions or metabolism, is extremely difficult and, in some cases, impossible. Thus, efficient algorithms for deciphering genome functionality based only on the genomic sequences with no other experimental measurements are needed. RESULTS In this study, we describe a novel algorithm that infers gene networks that we name Common Substring Network (CSN). The algorithm enables inferring novel regulatory relations among genes based only on the genomic sequence of a given organism and partial homolog/ortholog-based functional annotation. It can specifically infer the functional annotation of genes with unknown homology. This approach is based on the assumption that related genes, not necessarily homologs, tend to share sub-sequences, which may be related to common regulatory mechanisms, similar functionality of encoded proteins, common evolutionary history, and more. We demonstrate that CSNs, which are based on S. cerevisiae and E. coli genomes, have properties similar to 'traditional' biological networks inferred from experiments. Highly expressed genes tend to have higher degree nodes in the CSN, genes with similar protein functionality tend to be closer, and the CSN graph exhibits a power-law degree distribution. Also, we show how the CSN can be used for predicting gene interactions and functions. CONCLUSIONS The reported results suggest that 'silent' code inside the transcript can help to predict central features of biological networks and gene function. This approach can help researchers to understand the genome of novel microorganisms, analyze metagenomic data, and can help to decipher new gene functions. AVAILABILITY Our MATLAB implementation of CSN is available at https://www.cs.tau.ac.il/~tamirtul/CSN-Autogen.
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Affiliation(s)
- Maya Galili
- Biomedical Engineering Department, Tel Aviv University, Tel-Aviv, Israel
- Department of Molecular Microbiology & Biotechnology, Tel Aviv University, Tel-Aviv, Israel
| | - Tamir Tuller
- Biomedical Engineering Department, Tel Aviv University, Tel-Aviv, Israel
- The Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel
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17
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Abstract
Messenger RNAs (mRNAs) consist of a coding region (open reading frame (ORF)) and two untranslated regions (UTRs), 5'UTR and 3'UTR. Ribosomes travel along the coding region, translating nucleotide triplets (called codons) to a chain of amino acids. The coding region was long believed to mainly encode the amino acid content of proteins, whereas regulatory signals reside in the UTRs and in other genomic regions. However, in recent years we have learned that the ORF is expansively populated with various regulatory signals, or codes, which are related to all gene expression steps and additional intracellular aspects. In this paper, we review the current knowledge related to overlapping codes inside the coding regions, such as the influence of synonymous codon usage on translation speed (and, in turn, the effect of translation speed on protein folding), ribosomal frameshifting, mRNA stability, methylation, splicing, transcription and more. All these codes come together and overlap in the ORF sequence, ensuring production of the right protein at the right time.
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Affiliation(s)
- Shaked Bergman
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
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18
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Lai RW, Lu R, Danthi PS, Bravo JI, Goumba A, Sampathkumar NK, Benayoun BA. Multi-level remodeling of transcriptional landscapes in aging and longevity. BMB Rep 2019. [PMID: 30526773 PMCID: PMC6386224 DOI: 10.5483/bmbrep.2019.52.1.296] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
In multi-cellular organisms, the control of gene expression is key not only for development, but also for adult cellular homeostasis, and gene expression has been observed to be deregulated with aging. In this review, we discuss the current knowledge on the transcriptional alterations that have been described to occur with age in metazoans. First, we discuss age-related transcriptional changes in protein-coding genes, the expected functional impact of such changes, and how known pro-longevity interventions impact these changes. Second, we discuss the changes and impact of emerging aspects of transcription in aging, including age-related changes in splicing, lncRNAs and circRNAs. Third, we discuss the changes and potential impact of transcription of transposable elements with aging. Fourth, we highlight small ncRNAs and their potential impact on the regulation of aging phenotypes. Understanding the aging transcriptome will be key to identify important regulatory targets, and ultimately slow-down or reverse aging and extend healthy lifespan in humans.
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Affiliation(s)
- Rochelle W Lai
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Ryan Lu
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Prakroothi S Danthi
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Juan I Bravo
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089; Graduate program in the Biology of Aging, University of Southern California, Los Angeles, CA 90089, USA
| | - Alexandre Goumba
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | | | - Bérénice A Benayoun
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089; USC Norris Comprehensive Cancer Center, Epigenetics and Gene Regulation, Los Angeles, CA 90089; USC Stem Cell Initiative, Los Angeles, CA 90089, USA
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19
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Shahar N, Weiner I, Stotsky L, Tuller T, Yacoby I. Prediction and large-scale analysis of primary operons in plastids reveals unique genetic features in the evolution of chloroplasts. Nucleic Acids Res 2019; 47:3344-3352. [PMID: 30828719 PMCID: PMC6468310 DOI: 10.1093/nar/gkz151] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 01/30/2019] [Accepted: 02/21/2019] [Indexed: 11/14/2022] Open
Abstract
While bacterial operons have been thoroughly studied, few analyses of chloroplast operons exist, limiting the ability to study fundamental elements of these structures and utilize them for synthetic biology. Here, we describe the creation of a plastome-specific operon database (link provided below) achieved by combining experimental tools and predictive modeling. Using a Reverse-Transcription-PCR based method and published data, we determined the transcription-state of 213 gene pairs from four plastomes of evolutionary distinct organisms. By analyzing sequence-based features computed for our dataset, we were able to highlight fundamental characteristics differentiating between operon pairs and non-operon pairs. These include an interesting tendency toward maintaining similar messenger RNA-folding profiles in operon gene pairs, a feature that failed to yield any informative separation in cyanobacteria, suggesting that it catches unique traits of operon gene expression, which have evolved post-endosymbiosis. Subsequently, we used this feature set to train a random-forest classifier for operon prediction. As our results demonstrate the ability of our predictor to obtain accurate (84%) and robust predictions on unlabeled datasets, we proceeded to building operon maps for 2018 sequenced plastids. Our database may now present new opportunities for promoting metabolic engineering and synthetic biology in chloroplasts.
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Affiliation(s)
- Noam Shahar
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
| | - Iddo Weiner
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Lior Stotsky
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Iftach Yacoby
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
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20
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Nanikashvili I, Zarai Y, Ovseevich A, Tuller T, Margaliot M. Networks of ribosome flow models for modeling and analyzing intracellular traffic. Sci Rep 2019; 9:1703. [PMID: 30737417 PMCID: PMC6368613 DOI: 10.1038/s41598-018-37864-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 12/17/2018] [Indexed: 11/20/2022] Open
Abstract
The ribosome flow model with input and output (RFMIO) is a deterministic dynamical system that has been used to study the flow of ribosomes during mRNA translation. The input of the RFMIO controls its initiation rate and the output represents the ribosome exit rate (and thus the protein production rate) at the 3′ end of the mRNA molecule. The RFMIO and its variants encapsulate important properties that are relevant to modeling ribosome flow such as the possible evolution of “traffic jams” and non-homogeneous elongation rates along the mRNA molecule, and can also be used for studying additional intracellular processes such as transcription, transport, and more. Here we consider networks of interconnected RFMIOs as a fundamental tool for modeling, analyzing and re-engineering the complex mechanisms of protein production. In these networks, the output of each RFMIO may be divided, using connection weights, between several inputs of other RFMIOs. We show that under quite general feedback connections the network has two important properties: (1) it admits a unique steady-state and every trajectory converges to this steady-state; and (2) the problem of how to determine the connection weights so that the network steady-state output is maximized is a convex optimization problem. These mathematical properties make these networks highly suitable as models of various phenomena: property (1) means that the behavior is predictable and ordered, and property (2) means that determining the optimal weights is numerically tractable even for large-scale networks. For the specific case of a feed-forward network of RFMIOs we prove an additional useful property, namely, that there exists a spectral representation for the network steady-state, and thus it can be determined without any numerical simulations of the dynamics. We describe the implications of these results to several fundamental biological phenomena and biotechnological objectives.
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Affiliation(s)
- Itzik Nanikashvili
- School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel
| | - Yoram Zarai
- Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel
| | - Alexander Ovseevich
- Ishlinsky Institute for Problems in Mechanics, Russian Academy of Sciences and the Russian Quantum Center, Moscow, Russia
| | - Tamir Tuller
- Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, 69978, Israel. .,Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel.
| | - Michael Margaliot
- School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel.,Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, 69978, Israel
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21
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Mioduser O, Goz E, Tuller T. Significant differences in terms of codon usage bias between bacteriophage early and late genes: a comparative genomics analysis. BMC Genomics 2017; 18:866. [PMID: 29132309 PMCID: PMC5683454 DOI: 10.1186/s12864-017-4248-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 10/31/2017] [Indexed: 11/13/2022] Open
Abstract
Background Viruses undergo extensive evolutionary selection for efficient replication which effects, among others, their codon distribution. In the current study, we aimed at understanding the way evolution shapes the codon distribution in early vs. late viral genes in terms of their expression during different stages in the viral replication cycle. To this end we analyzed 14 bacteriophages and 11 human viruses with available information about the expression phases of their genes. Results We demonstrated evidence of selection for distinct composition of synonymous codons in early and late viral genes in 50% of the analyzed bacteriophages. Among others, this phenomenon may be related to the time specific adaptation of the viral genes to the translation efficiency factors involved at different bacteriophage developmental stages. Specifically, we showed that the differences in codon composition in different temporal gene groups cannot be explained only by phylogenetic proximities between the analyzed bacteriophages, and can be partially explained by differences in the adaptation to the host tRNA pool, nucleotide bias, GC content and more. In contrast, no difference in temporal regulation of synonymous codon usage was observed in human viruses, possibly because of a stronger selection pressure due to a larger effective population size in bacteriophages and their bacterial hosts. Conclusions The codon distribution in large fractions of bacteriophage genomes tend to be different in early and late genes. This phenomenon seems to be related to various aspects of the viral life cycle, and to various intracellular processes. We believe that the reported results should contribute towards better understanding of viral evolution and may promote the development of relevant procedures in synthetic virology. Electronic supplementary material The online version of this article (10.1186/s12864-017-4248-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Oriah Mioduser
- Department of Biomedical Engineering, Tel-Aviv University, Ramat Aviv, Israel
| | - Eli Goz
- Department of Biomedical Engineering, Tel-Aviv University, Ramat Aviv, Israel.,SynVaccineLtd. Ramat Hachayal, Tel Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel-Aviv University, Ramat Aviv, Israel. .,SynVaccineLtd. Ramat Hachayal, Tel Aviv, Israel. .,Sagol School of Neuroscience, Tel-Aviv University, Ramat Aviv, Israel.
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22
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Ding L, Wang M, Sun D, Li A. A novel method for identifying potential disease-related miRNAs via a disease–miRNA–target heterogeneous network. MOLECULAR BIOSYSTEMS 2017; 13:2328-2337. [DOI: 10.1039/c7mb00485k] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
MicroRNAs (miRNAs), as a kind of important small endogenous single-stranded non-coding RNA, play critical roles in a large number of human diseases.
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Affiliation(s)
- Liang Ding
- School of Information Science and Technology
- University of Science and Technology of China
- Hefei AH230027
- People's Republic of China
| | - Minghui Wang
- School of Information Science and Technology
- University of Science and Technology of China
- Hefei AH230027
- People's Republic of China
- Centers for Biomedical Engineering
| | - Dongdong Sun
- School of Information Science and Technology
- University of Science and Technology of China
- Hefei AH230027
- People's Republic of China
| | - Ao Li
- School of Information Science and Technology
- University of Science and Technology of China
- Hefei AH230027
- People's Republic of China
- Centers for Biomedical Engineering
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