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      The Codon Statistics Database: A Database of Codon Usage Bias

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          Abstract

          We present the Codon Statistics Database, an online database that contains codon usage statistics for all the species with reference or representative genomes in RefSeq (over 15,000). The user can search for any species and access two sets of tables. One set lists, for each codon, the frequency, the Relative Synonymous Codon Usage, and whether the codon is preferred. Another set of tables lists, for each gene, its GC content, Effective Number of Codons, Codon Adaptation Index, and frequency of optimal codons. Equivalent tables can be accessed for (1) all nuclear genes, (2) nuclear genes encoding ribosomal proteins, (3) mitochondrial genes, and (4) chloroplast genes (if available in the relevant assembly). The user can also search for any taxonomic group (e.g., “primates”) and obtain a table comparing all the species in the group. The database is free to access without registration at http://codonstatsdb.unr.edu.

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          Most cited references13

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          The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

          P. Sharp, W Li (1987)
          A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the pattern of codon usage. In that respect it is useful for predicting the level of expression of a gene, for assessing the adaptation of viral genes to their hosts, and for making comparisons of codon usage in different organisms. The index may also give an approximate indication of the likely success of heterologous gene expression.
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            The 'effective number of codons' used in a gene.

            F Wright (1990)
            A simple measure is presented that quantifies how far the codon usage of a gene departs from equal usage of synonymous codons. This measure of synonymous codon usage bias, the 'effective number of codons used in a gene', Nc, can be easily calculated from codon usage data alone, and is independent of gene length and amino acid (aa) composition. Nc can take values from 20, in the case of extreme bias where one codon is exclusively used for each aa, to 61 when the use of alternative synonymous codons is equally likely. Nc thus provides an intuitively meaningful measure of the extent of codon preference in a gene. Codon usage patterns across genes can be investigated by the Nc-plot: a plot of Nc vs. G + C content at synonymous sites. Nc-plots are produced for Homo sapiens, Saccharomyces cerevisiae, Escherichia coli, Bacillus subtilis, Dictyostelium discoideum, and Drosophila melanogaster. A FORTRAN77 program written to calculate Nc is available on request.
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              Selection on codon bias.

              In a wide variety of organisms, synonymous codons are used with different frequencies, a phenomenon known as codon bias. Population genetic studies have shown that synonymous sites are under weak selection and that codon bias is maintained by a balance between selection, mutation, and genetic drift. It appears that the major cause for selection on codon bias is that certain preferred codons are translated more accurately and/or efficiently. However, additional and sometimes maybe even contradictory selective forces appear to affect codon usage as well. In this review, we discuss the current understanding of the ways in which natural selection participates in the creation and maintenance of codon bias. We also raise several open questions: (i) Is natural selection weak independently of the level of codon bias? It is possible that selection for preferred codons is weak only when codon bias approaches equilibrium and may be quite strong on genes with codon bias levels that are much lower and/or above equilibrium. (ii) What determines the identity of the major codons? (iii) How do shifts in codon bias occur? (iv) What is the exact nature of selection on codon bias? We discuss these questions in depth and offer some ideas on how they can be addressed using a combination of computational and experimental analyses.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Mol Biol Evol
                Mol Biol Evol
                molbev
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                August 2022
                21 July 2022
                21 July 2022
                : 39
                : 8
                : msac157
                Affiliations
                Biology Department, University of Nevada, Reno , Reno, NV 89557, USA
                Biology Department, University of Nevada, Reno , Reno, NV 89557, USA
                Biology Department, University of Nevada, Reno , Reno, NV 89557, USA
                Biology Department, University of Nevada, Reno , Reno, NV 89557, USA
                Author notes
                Corresponding author: E-mail: dap@ 123456unr.edu .

                Krishnamurthy Subramanian and Bryan Payne contributed equally to this work.

                Present address: Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
                Author information
                https://orcid.org/0000-0002-8729-1036
                Article
                msac157
                10.1093/molbev/msac157
                9372565
                35859338
                fdc2b1cf-fed7-4346-af30-f4aec36ff2f9
                © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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                Page count
                Pages: 3
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                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                codon bias,codon usage,database,synonymous codons
                Molecular biology
                codon bias, codon usage, database, synonymous codons

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