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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

dc.contributor.authorBadu-Apraku, B.
dc.contributor.authorAdewale, S.
dc.contributor.authorAgre, P.
dc.contributor.authorOffornedo, Q.
dc.contributor.authorGedil, M.
dc.date.accessioned2023-02-08T12:08:32Z
dc.date.available2023-02-08T12:08:32Z
dc.date.issued2023-01-12
dc.identifier.citationBadu-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.
dc.identifier.issn1664-8021
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8039
dc.description.abstractThe 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.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-14
dc.language.isoen
dc.subjectStriga Hermonthica
dc.subjectDisease Resistance
dc.subjectQuantitative Trait Loci
dc.subjectEnvironment
dc.subjectGenes
dc.subjectMarker-Assisted Selection
dc.subjectMaize
dc.titleMapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
dc.typeJournal Article
cg.contributor.crpMaize
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidAPRAKU:2023
cg.isijournalISI Journal
cg.authorship.typesCGIAR Single Centre
cg.iitasubjectAgronomy
cg.iitasubjectDisease Control
cg.iitasubjectFood Security
cg.iitasubjectMaize
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Diseases
cg.iitasubjectPlant Production
cg.journalFrontiers in Genetics
cg.notesOpen Access Journal; Published online: 12 Jan 2023
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.3389/fgene.2023.1012460
cg.iitaauthor.identifierBAFFOUR BADU-APRAKU: 0000-0003-0113-5487
cg.iitaauthor.identifierSamuel Adewale: 0000-0002-0331-7201
cg.iitaauthor.identifierPaterne AGRE: 0000-0003-1231-2530
cg.iitaauthor.identifierMelaku Gedil: 0000-0002-6258-6014
cg.futureupdate.requiredNo
cg.identifier.issue1012460
cg.identifier.volume14
cg.contributor.acknowledgementsThe authors are also grateful to the IITA Maize Improvement Programme and Bioscience staff for providing technical assistance.


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