Articles producció científica> Bioquímica i Biotecnologia

E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI)

  • Identification data

    Identifier: imarina:2083789
    Authors:
    Puigbo, PereBravo, Ignacio G.Garcia-Vallve, Santiago
    Abstract:
    The Codon Adaptation Index (CAI) is a measure of the synonymous codon usage bias for a DNA or RNA sequence. It quantifies the similarity between the synonymous codon usage of a gene and the synonymous codon frequency of a reference set. Extreme values in the nucleotide or in the amino acid composition have a large impact on differential preference for synonymous codons. It is thence essential to define the limits for the expected value of CAI on the basis of sequence composition in order to properly interpret the CAI and provide statistical support to CAI analyses. Though several freely available programs calculate the CAI for a given DNA sequence, none of them corrects for compositional biases or provides confidence intervals for CAI values.The E-CAI server, available at http://genomes.urv.es/CAIcal/E-CAI, is a web-application that calculates an expected value of CAI for a set of query sequences by generating random sequences with G+C and amino acid content similar to those of the input. An executable file, a tutorial, a Frequently Asked Questions (FAQ) section and several examples are also available. To exemplify the use of the E-CAI server, we have analysed the codon adaptation of human mitochondrial genes that codify a subunit of the mitochondrial respiratory chain (excluding those genes that lack a prokaryotic orthologue) and are encoded in the nuclear genome. It is assumed that these genes were transferred from the proto-mitochondrial to the nuclear genome and that its codon usage was then ameliorated.The E-CAI server provides a direct threshold value for discerning whether the differences in CAI are statistically significant or whether they are merely artifacts that arise from internal biases in the G+C composition and/or amino acid composition of the query seque
  • Others:

    Author, as appears in the article.: Puigbo, Pere; Bravo, Ignacio G.; Garcia-Vallve, Santiago;
    Department: Bioquímica i Biotecnologia
    URV's Author/s: Garcia Vallve, Santiago / PUIGBÒ AVALOS, PEDRO
    Keywords: Usage bias Sequences Selection Metabolism Human genome Highly expressed genes Evolution Escherichia-coli Database
    Abstract: The Codon Adaptation Index (CAI) is a measure of the synonymous codon usage bias for a DNA or RNA sequence. It quantifies the similarity between the synonymous codon usage of a gene and the synonymous codon frequency of a reference set. Extreme values in the nucleotide or in the amino acid composition have a large impact on differential preference for synonymous codons. It is thence essential to define the limits for the expected value of CAI on the basis of sequence composition in order to properly interpret the CAI and provide statistical support to CAI analyses. Though several freely available programs calculate the CAI for a given DNA sequence, none of them corrects for compositional biases or provides confidence intervals for CAI values.The E-CAI server, available at http://genomes.urv.es/CAIcal/E-CAI, is a web-application that calculates an expected value of CAI for a set of query sequences by generating random sequences with G+C and amino acid content similar to those of the input. An executable file, a tutorial, a Frequently Asked Questions (FAQ) section and several examples are also available. To exemplify the use of the E-CAI server, we have analysed the codon adaptation of human mitochondrial genes that codify a subunit of the mitochondrial respiratory chain (excluding those genes that lack a prokaryotic orthologue) and are encoded in the nuclear genome. It is assumed that these genes were transferred from the proto-mitochondrial to the nuclear genome and that its codon usage was then ameliorated.The E-CAI server provides a direct threshold value for discerning whether the differences in CAI are statistically significant or whether they are merely artifacts that arise from internal biases in the G+C composition and/or amino acid composition of the query sequences.
    Thematic Areas: Structural biology Saúde coletiva Química Molecular biology Medicina veterinaria Medicina ii Medicina i Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar Farmacia Engenharias iv Engenharias iii Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência da computação Biotecnología Biotechnology & applied microbiology Biodiversidade Biochemistry Biochemical research methods Applied mathematics
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 14712105
    Author's mail: santi.garcia-vallve@urv.cat
    Author identifier: 0000-0002-0348-7497
    Paper data publication: 2008-01-29
    Record's date: 2023-02-18
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-65
    Papper original source: Bmc Bioinformatics. 9 (65): 65-
    APA: Puigbo, Pere; Bravo, Ignacio G.; Garcia-Vallve, Santiago; (2008). E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI). Bmc Bioinformatics, 9(65), 65-. DOI: 10.1186/1471-2105-9-65
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1186/1471-2105-9-65
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2008
    Publication Type: Journal Publications
  • Keywords:

    Applied Mathematics,Biochemical Research Methods,Biochemistry,Biotechnology & Applied Microbiology,Computer Science Applications,Mathematical & Computational Biology,Molecular Biology,Structural Biology
    Usage bias
    Sequences
    Selection
    Metabolism
    Human genome
    Highly expressed genes
    Evolution
    Escherichia-coli
    Database
    Structural biology
    Saúde coletiva
    Química
    Molecular biology
    Medicina veterinaria
    Medicina ii
    Medicina i
    Mathematical & computational biology
    Matemática / probabilidade e estatística
    Interdisciplinar
    Farmacia
    Engenharias iv
    Engenharias iii
    Computer science applications
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biotechnology & applied microbiology
    Biodiversidade
    Biochemistry
    Biochemical research methods
    Applied mathematics
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