• Contact Us
    • Send Feedback
    • Login
    View Item 
    •   Home
    • Journal and Journal Articles
    • Journal and Journal Articles
    • View Item
    •   Home
    • Journal and Journal Articles
    • Journal and Journal Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    Whole Repository
    CollectionsIssue DateRegionCountryHubAffiliationAuthorsTitlesSubject
    This Sub-collection
    Issue DateRegionCountryHubAffiliationAuthorsTitlesSubject

    My Account

    Login

    Welcome to the International Institute of Tropical Agriculture Research Repository

    What would you like to view today?

    Training population optimization for prediction of cassava brown streak disease resistance in west African clones

    Thumbnail
    View/Open
    U18ArtOzimatiTrainingInthomDev(1).pdf (1.159Mb)
    Date
    2018
    Author
    Ozimati, A.
    Kawuki, R.
    Esuma, W.
    Kayondo, I.S.
    Wolfe, M.
    Lozano, R.
    Rabbi, I.
    Kulakow, P.
    Jannink, J.L
    Type
    Journal Article
    Target Audience
    Scientists
    Metadata
    Show full item record
    Abstract/Description
    Cassava production in the central, southern and eastern parts of Africa is under threat by cassava brown streak virus (CBSV). Yield losses of up to 100% occur in cases of severe infections of edible roots. Easy illegal movement of planting materials across African countries, and long-range movement of the virus vector (Bemisia tabaci) may facilitate spread of CBSV to West Africa. Thus, effort to pre-emptively breed for CBSD resistance in W. Africa is critical. Genomic selection (GS) has become the main approach for cassava breeding, as costs of genotyping per sample have declined. Using phenotypic and genotypic data (genotyping-by-sequencing), followed by imputation to whole genome sequence (WGS) for 922 clones from National Crops Resources Research Institute, Namulonge, Uganda as a training population (TP), we predicted CBSD symptoms for 35 genotyped W. African clones, evaluated in Uganda. The highest prediction accuracy (r = 0.44) was observed for cassava brown streak disease severity scored at three months (CBSD3s) in the W. African clones using WGS-imputed markers. Optimized TPs gave higher prediction accuracies for CBSD3s and CBSD6s than random TPs of the same size. Inclusion of CBSD QTL chromosome markers as kernels, increased prediction accuracies for CBSD3s and CBSD6s. Similarly, WGS imputation of markers increased prediction accuracies for CBSD3s and for cassava brown streak disease root severity (CBSDRs), but not for CBSD6s. Based on these results we recommend TP optimization, inclusion of CBSD QTL markers in genomic prediction models, and the use of high-density (WGS-imputed) markers for CBSD predictions across population.
    http://dx.doi.org/10.1534/g3.118.200710
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/5177
    Non-IITA Authors ORCID
    Ismail Rabbihttps://orcid.org/0000-0001-9966-2941
    Peter Kulakowhttps://orcid.org/0000-0002-7574-2645
    Jean-Luc Janninkhttps://orcid.org/0000-0003-4849-628X
    Digital Object Identifier (DOI)
    http://dx.doi.org/10.1534/g3.118.200710
    Research Themes
    BIOTECH & PLANT BREEDING
    IITA Subjects
    Cassava; Genetic Improvement; Plant Breeding; Plant Genetic Resources
    Agrovoc Terms
    Cassava; Genomics; Plant Diseases; Uganda; Tanzania; Genetics
    Regions
    Africa; East Africa
    Countries
    Tanzania; Uganda
    Journals
    G3-Genes Genomes Genetics
    Collections
    • Journal and Journal Articles4835
    copyright © 2019  IITASpace. All rights reserved.
    IITA | Open Access Repository