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    Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis

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    Journal Article (1.445Mb)
    Authors
    Badu-Apraku, B.
    Adewale, S.
    Agre, P.
    Offornedo, Q.N.
    Gedil, M.
    Date Issued
    2023-01
    Date Online
    2023-01
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    ISI journal
    Accessibility
    Open Access
    Usage rights
    CC-BY-4.0
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    Citation
    Badu-Apraku, B., Adewale, S., Agre, P., Offornedo, Q. & Gedil, M. (2023). Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis. Frontiers in Genetics, 14: 1012460, 1-14.
    Permanent link to cite or share this item: https://hdl.handle.net/10568/128480
    DOI: https://doi.org/10.3389/fgene.2023.1012460
    Abstract/Description
    The parasitic weed, Striga is a major biological constraint to cereal production in sub-Saharan Africa (SSA) and threatens food and nutrition security. Two hundred and twenty-three (223) F2:3 mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four Striga-adaptive traits and genotyped using the Diversity Arrays Technology (DArT) to determine the genomic regions responsible for Striga resistance in maize. After removing distorted SNP markers, a genetic linkage map was constructed using 1,918 DArTseq markers which covered 2092.1 cM. Using the inclusive composite interval mapping method in IciMapping, twenty-three QTLs influencing Striga resistance traits were identified across four Striga-infested environments with five stable QTLs (qGY4, qSC2.1, qSC2.2, qSC5, and qSC6) detected in more than one environment. The variations explained by the QTLs ranged from 4.1% (qSD2.3) to 14.4% (qSC7.1). Six QTLs each with significant additive × environment interactions were also identified for grain yield and Striga damage. Gene annotation revealed candidate genes underlying the QTLs, including the gene models GRMZM2G077002 and GRMZM2G404973 which encode the GATA transcription factors, GRMZM2G178998 and GRMZM2G134073 encoding the NAC transcription factors, GRMZM2G053868 and GRMZM2G157068 which encode the nitrate transporter protein and GRMZM2G371033 encoding the SBP-transcription factor. These candidate genes play crucial roles in plant growth and developmental processes and defense functions. This study provides further insights into the genetic mechanisms of resistance to Striga parasitism in maize. The QTL detected in more than one environment would be useful for further fine-mapping and marker-assisted selection for the development of Striga resistant and high-yielding maize cultivars.
    CGIAR Author ORCID iDs
    BAFFOUR BADU-APRAKUhttps://orcid.org/0000-0003-0113-5487
    Samuel Adewalehttps://orcid.org/0000-0002-0331-7201
    Paterne AGREhttps://orcid.org/0000-0003-1231-2530
    Melaku Gedilhttps://orcid.org/0000-0002-6258-6014
    CGIAR Impact Areas
    Nutrition, health and food security
    Other CGIAR Affiliations
    Maize; Roots, Tubers and Bananas
    Contributes to SDGs
    SDG 1 - No poverty; SDG 2 - Zero hunger
    AGROVOC Keywords
    striga hermonthica; disease resistance; quantitative trait loci; environment; genes; marker-assisted selection; maize
    Subjects
    AGRONOMY; DISEASE CONTROL; FOOD SECURITY; MAIZE; PLANT BREEDING; PLANT DISEASES; PLANT PRODUCTION
    Countries
    Nigeria
    Regions
    Africa; Western Africa
    Organizations Affiliated to the Authors
    International Institute of Tropical Agriculture
    Investors/sponsors
    Bill & Melinda Gates Foundation
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    • IITA Journal Articles [4998]

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