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    Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines

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    U21ArtStanleyAssociationInthomDev.Pdf (1.881Mb)
    Date
    2021-12-17
    Author
    Stanley, A.E.
    Menkir, A.
    Ifie, B.E.
    Agre, A.P.
    Unachukwu, N.N.
    Meseka, S.K.
    Mengesha Abera, W.
    Bossey, B.
    Kwadwo, O.
    Tongoona, P.
    Oladejo, O.
    Sneller, C.
    Gedil, M.
    Type
    Journal Article
    Review Status
    Internal Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance was considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identifed thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize.
    https://dx.doi.org/10.1038/s41598-021-03566-4
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/7378
    IITA Authors ORCID
    https://orcid.org/
    https://orcid.org/
    https://orcid.org/
    https://orcid.org/
    https://orcid.org/
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.1038/s41598-021-03566-4
    Research Themes
    Biotech and Plant Breeding
    IITA Subjects
    Agronomy; Food Security; Genetic Improvement; Livelihoods; Maize; Pests of Plants; Plant Breeding; Plant Diseases; Plant Genetic Resources; Plant Production; Smallholder Farmers; Soil Fertility; Weeds
    Agrovoc Terms
    Parasitic Plants; Drought; Yields; Farmers; Genes; Breeding; Genotypes; Maize; Striga Hermonthica; Plant Growth; Weeds
    Regions
    Africa; West Africa
    Countries
    Nigeria
    Hubs
    Headquarters and Western Africa Hub
    Journals
    Scientific Reports
    Collections
    • Journal and Journal Articles4835
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