CONCUR: quick and robust calculation of codon usage from ribosome profiling data.
Ontology highlight
ABSTRACT: Summary
CONCUR is a standalone tool for codon usage analysis in ribosome profiling experiments. CONCUR uses the aligned reads in BAM format to estimate codon counts at the ribosome E-, P- and A-sites and at flanking positions.Availability and implementation
CONCUR is written in Perl and is freely available at https://github.com/susbo/concur.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Frye M
PROVIDER: S-EPMC8097682 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
CONCUR: quick and robust calculation of codon usage from ribosome profiling data.
Frye Michaela M Bornelöv Susanne S
Bioinformatics (Oxford, England) 20210501 5
<h4>Summary</h4>CONCUR is a standalone tool for codon usage analysis in ribosome profiling experiments. CONCUR uses the aligned reads in BAM format to estimate codon counts at the ribosome E-, P- and A-sites and at flanking positions.<h4>Availability and implementation</h4>CONCUR is written in Perl and is freely available at https://github.com/susbo/concur.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online. ...[more]
Similar Datasets
Project description:Protein translation depends on mRNA-specific initiation, elongation, and termination rates. While the regulation of ribosome elongation is well studied in bacteria and yeast, less is known in higher eukaryotes. Here, we combined ribosome and tRNA profiling to investigate the relations between ribosome elongation rates, (aminoacyl-) tRNA levels and codon usage in mammals. We modeled codon-specific ribosome dwell times and translation fluxes from ribosome profiling, considering pair-interactions between ribosome sites. In mouse liver, the model revealed site and codon specific dwell times, as well as codon pair-interactions clustering by amino acids. While translation fluxes varied significantly across diurnal time and feeding regimen, codon dwell times were highly stable, and conserved in human. Fasting had no effect on codon dwell times in mouse liver. Profiling of total and aminoacylated tRNAs revealed highly heterogeneous levels with specific isoacceptor patterns and a correlation with codon usage. tRNAs for isoleucine, asparagine, aspartate and arginine were lowly loaded and conserved in fasted mice. Finally, codons with low levels of charged tRNAs and high codon usage relative to tRNA abundance exhibited long dwell times. Together, these analyses pave the way towards understanding the complex relation between tRNA loading, codon usage and ribosome dwell times in mammals.
2020-03-26 | GSE126383 | GEO
Project description:Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. Experimental results on four microbial genomes indicate that the new method is well-suited for the analysis of horizontal gene transfer and translational selection. As compared with the widely-used correspondence analysis, our method did not suffer from outlier sensitivity and showed a better clustering of putative alien genes in most cases.
| S-EPMC1526732 | biostudies-literature
Project description:Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the F9 gene, both of which are translated into identical proteins in terms of their amino acid sequences. However, these F9 genes vary drastically in their codon usage and predicted mRNA structure. We also provide the pipeline that we used to analyze the data. Further analyzing this dataset holds great potential as it can be used i) to unveil insights into the composition and regulation of the transcriptome, ii) for comparison with other ribosome profiling datasets, iii) to measure the rate of protein synthesis across the proteome and identify differences in elongation rates, iv) to discover previously unidentified translation of peptides, v) to explore the effects of codon usage or codon context in translational kinetics and vi) to investigate cotranslational folding. Importantly, a unique feature of this dataset, compared to other available ribosome profiling data, is the presence of the F9 gene in two very distinct coding sequences.
| S-EPMC7509596 | biostudies-literature
Project description:Most genomes are heterogeneous in codon usage, so a codon usage study should start by defining the codon usage that is typical to the genome. Although this is commonly taken to be the genomewide average, we propose that the mode-the codon usage that matches the most genes-provides a more useful approximation of the typical codon usage of a genome. We provide a method for estimating the modal codon usage, which utilizes a continuous approximation to the number of matching genes and a simplex optimization. In a survey of bacterial and archaeal genomes, as many as 20% more of the genes in a given genome match the modal codon usage than the average codon usage. We use the mode to examine the evolution of the multireplicon genomes of Agrobacterium tumefaciens C58 and Borrelia burgdorferi B31. In A. tumefaciens, the circular and linear chromosomes are characterized by a common "chromosome-like" codon usage, whereas both plasmids share a distinct "plasmid-like" codon usage. In B. burgdorferi, in addition to different codon-usage biases on the leading and lagging strands of DNA replication found by McInerney (McInerney JO. 1998. Replicational and transcriptional selection on codon usage in Borrelia burgdorferi. Proc Natl Acad Sci USA. 95:10698-10703), we also detect a codon-usage similarity between linear plasmid lp38 and the leading strand of the chromosome and a high similarity among the cp32 family of plasmids.
| S-EPMC2839124 | biostudies-literature
Project description:Codon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants and animals. Different species have consistent and characteristic codon biases. Codon bias varies not only with species, family or group within kingdom, but also between the genes within an organism. Codon usage bias has evolved through mutation, natural selection, and genetic drift in various organisms. Genome composition, GC content, expression level and length of genes, position and context of codons in the genes, recombination rates, mRNA folding, and tRNA abundance and interactions are some factors influencing codon bias. The factors shaping codon bias may also be involved in evolution of the universal genetic code. Codon-usage bias is critical factor determining gene expression and cellular function by influencing diverse processes such as RNA processing, protein translation and protein folding. Codon usage bias reflects the origin, mutation patterns and evolution of the species or genes. Investigations of codon bias patterns in genomes can reveal phylogenetic relationships between organisms, horizontal gene transfers, molecular evolution of genes and identify selective forces that drive their evolution. Most important application of codon bias analysis is in the design of transgenes, to increase gene expression levels through codon optimization, for development of transgenic crops. The review gives an overview of deviations of genetic code, factors influencing codon usage or bias, codon usage bias of nuclear and organellar genes, computational methods to determine codon usage and the significance as well as applications of codon usage analysis in biological research, with emphasis on plants.
| S-EPMC8613526 | biostudies-literature
Project description:A key goal in molecular evolution is to extract mechanistic insights from signatures of selection. A case study is codon usage, where despite many recent advances and hypotheses, two longstanding problems remain: the relative contribution of selection and mutation in determining codon frequencies and the relative contribution of translational speed and accuracy to selection. The relevant targets of selection--the rate of translation and of mistranslation of a codon per unit time in the cell--can only be related to mechanistic properties of the translational apparatus if the number of transcripts per cell is known, requiring use of gene expression measurements. Perhaps surprisingly, different gene-expression data sets yield markedly different estimates of selection. We show that this is largely due to measurement noise, notably due to differences between studies rather than instrument error or biological variability. We develop an analytical framework that explicitly models noise in expression in the context of the population-genetic model. Estimates of mutation and selection strength in budding yeast produced by this method are robust to the expression data set used and are substantially higher than estimates using a noise-blind approach. We introduce per-gene selection estimates that correlate well with previous scoring systems, such as the codon adaptation index, while now carrying an evolutionary interpretation. On average, selection for codon usage in budding yeast is weak, yet our estimates show that genes range from virtually unselected to average per-codon selection coefficients above the inverse population size. Our analytical framework may be generally useful for distinguishing biological signals from measurement noise in other applications that depend upon measurements of gene expression.
| S-EPMC3649678 | biostudies-literature
Project description:Protein translation depends on mRNA-specific initiation, elongation, and termination rates. While the regulation of ribosome elongation is well studied in bacteria and yeast, less is known in higher eukaryotes. Here, we combined ribosome and tRNA profiling to investigate the relations between ribosome elongation rates, (aminoacyl-) tRNA levels and codon usage in mammals. We modeled codon-specific ribosome dwell times and translation fluxes from ribosome profiling, considering pair-interactions between ribosome sites. In mouse liver, the model revealed site and codon specific dwell times, as well as codon pair-interactions clustering by amino acids. While translation fluxes varied significantly across diurnal time and feeding regimen, codon dwell times were highly stable, and conserved in human. Fasting had no effect on codon dwell times in mouse liver. Profiling of total and aminoacylated tRNAs revealed highly heterogeneous levels with specific isoacceptor patterns and a correlation with codon usage. tRNAs for isoleucine, asparagine, aspartate and arginine were lowly loaded and conserved in fasted mice. Finally, codons with low levels of charged tRNAs and high codon usage relative to tRNA abundance exhibited long dwell times. Together, these analyses pave the way towards understanding the complex relation between tRNA loading, codon usage and ribosome dwell times in mammals.
2020-03-26 | GSE126382 | GEO
Project description:Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26-34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.
| S-EPMC7319539 | biostudies-literature
Project description:Ribosomes can read through stop codons in a regulated manner, elongating rather than terminating the nascent peptide. Stop codon readthrough is essential to diverse viruses, and phylogenetically predicted to occur in a few hundred genes in Drosophila melanogaster, but the importance of regulated readthrough in eukaryotes remains largely unexplored. Here, we present a ribosome profiling assay (deep sequencing of ribosome-protected mRNA fragments) for Drosophila melanogaster, and provide the first genome-wide experimental analysis of readthrough. Readthrough is far more pervasive than expected: the vast majority of readthrough events evolved within D. melanogaster and were not predicted phylogenetically. The resulting C-terminal protein extensions show evidence of selection, contain functional subcellular localization signals, and their readthrough is regulated, arguing for their importance. We further demonstrate that readthrough occurs in yeast and humans. Readthrough thus provides general mechanisms both to regulate gene expression and function, and to add plasticity to the proteome during evolution. DOI: http://dx.doi.org/10.7554/eLife.01179.001.
| S-EPMC3840789 | biostudies-literature
Project description:Codon Usage Preferences (CUPrefs) describe the unequal usage of synonymous codons at the gene, chromosome, or genome levels. Numerous indices have been developed to evaluate CUPrefs, either in absolute terms or with respect to a reference. We introduce the normalized index COUSIN (for COdon Usage Similarity INdex), that compares the CUPrefs of a query against those of a reference and normalizes the output over a Null Hypothesis of random codon usage. The added value of COUSIN is to be easily interpreted, both quantitatively and qualitatively. An eponymous software written in Python3 is available for local or online use (http://cousin.ird.fr). This software allows for an easy and complete analysis of CUPrefs via COUSIN, includes seven other indices, and provides additional features such as statistical analyses, clustering, and CUPrefs optimization for gene expression. We illustrate the flexibility of COUSIN and highlight its advantages by analyzing the complete coding sequences of eight divergent genomes. Strikingly, COUSIN captures a bimodal distribution in the CUPrefs of human and chicken genes hitherto unreported with such precision. COUSIN opens new perspectives to uncover CUPrefs specificities in genomes in a practical, informative, and user-friendly way.
| S-EPMC6934141 | biostudies-literature