CGSpaceA Repository of Agricultural Research Outputs
    View Item 
    •   CGSpace Home
    • Bioversity International
    • Bioversity Journal Articles
    • View Item
       
    • CGSpace Home
    • Bioversity International
    • Bioversity Journal Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A genome-wide association study on the seedless phenotype in banana (Musa spp.) reveals the potential of a selected panel to detect candidate genes in a vegetatively propagated crop

    Thumbnail
    View/Open
    Sardos_GWAS_Pone.PDF (2.660Mb)
    
    Authors
    Sardos, J.
    Rouard, M.
    Hueber, Y.
    Cenci, A.
    Hyma, K.E.
    van den Houwe, I.
    Hribova, E.
    Courtois, Brigitte
    Date
    2016
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    Accessibility
    Open Access
    Metadata
    Show full item record
    Share
    Citation
    Sardos, J.; Rouard, M.; Hueber, Y.; Cenci, A.; Hyma, K.E.; van den Houwe, I.; Hribova, E.; Courtois, B. (2016) A genome-wide association study on the seedless phenotype in banana (Musa spp.) reveals the potential of a selected panel to detect candidate genes in a vegetatively propagated crop. PLoS ONE 11(5): e0154448 ISSN: 1932-6203
    Permanent link to cite or share this item: http://hdl.handle.net/10568/73370
    DOI: https://dx.doi.org/10.1371/journal.pone.0154448
    Abstract/Description
    Banana (Musa sp.) is a vegetatively propagated, low fertility, potentially hybrid and polyploid crop. These qualities make the breeding and targeted genetic improvement of this crop a difficult and long process. The Genome-Wide Association Study (GWAS) approach is becoming widely used in crop plants and has proven efficient to detecting candidate genes for traits of interest, especially in cereals. GWAS has not been applied yet to a vegetatively propagated crop. However, successful GWAS in banana would considerably help unravel the genomic basis of traits of interest and therefore speed up this crop improvement. We present here a dedicated panel of 105 accessions of banana, freely available upon request, and their corresponding GBS data. A set of 5,544 highly reliable markers revealed high levels of admixture in most accessions, except for a subset of 33 individuals from Papua. A GWAS on the seedless phenotype was then successfully applied to the panel. By applying the Mixed Linear Model corrected for both kinship and structure as implemented in TASSEL, we detected 13 candidate genomic regions in which we found a number of genes potentially linked with the seedless phenotype (i.e. parthenocarpy combined with female sterility). An additional GWAS performed on the unstructured Papuan subset composed of 33 accessions confirmed six of these regions as candidate. Out of both sets of analyses, one strong candidate gene for female sterility, a putative orthologous gene to Histidine Kinase CKI1, was identified. The results presented here confirmed the feasibility and potential of GWAS when applied to small sets of banana accessions, at least for traits underpinned by a few loci. As phenotyping in banana is extremely space and time-consuming, this latest finding is of particular importance in the context of banana improvement.
    CGIAR Affiliations
    Roots, Tubers and Bananas
    AGROVOC Keywords
    BANANAS; GENOMES; CROPS; GENETICS; INTRONS; HETEROZYGOTES; VARIANTS; GENOTYPES
    Subjects
    GENOMES; CROPS; GENETICS; INTRONS; HETEROZYGOTES; VARIANTS; GENOTYPES;
    Related material
    Related data file: https://dx.doi.org/10.7910/DVN/2YAJPQ,
    Collections
    • RTB Journal Articles [665]
    • Bioversity Journal Articles [695]
    • Effective Genetic Resources Conservation and Use [285]

    AboutSend Feedback
     

    My Account

    LoginRegister

    Browse

    All of CGSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesBy AGROVOC keywordBy ILRI subjectBy CPWF subjectBy CCAFS subjectBy CIFOR subjectBy IWMI subjectBy RegionBy CountryBy SubregionBy CRP subjectBy River basinBy Output typeBy CTA subjectBy WLE subjectBy Bioversity subjectBy CIAT subjectBy CIP subjectBy animal breedBy CGIAR System subjectThis CollectionBy Issue DateAuthorsTitlesBy AGROVOC keywordBy ILRI subjectBy CPWF subjectBy CCAFS subjectBy CIFOR subjectBy IWMI subjectBy RegionBy CountryBy SubregionBy CRP subjectBy River basinBy Output typeBy CTA subjectBy WLE subjectBy Bioversity subjectBy CIAT subjectBy CIP subjectBy animal breedBy CGIAR System subject

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    AboutSend Feedback