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

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-a...

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Autores principales: Badu-Apraku, Baffour, Adewale, S., Agre, P., Offornedo, Q.N., Gedil, Melaku A
Formato: Journal Article
Lenguaje:Inglés
Publicado: Frontiers Media 2023
Materias:
Acceso en línea:https://hdl.handle.net/10568/128480
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author Badu-Apraku, Baffour
Adewale, S.
Agre, P.
Offornedo, Q.N.
Gedil, Melaku A
author_browse Adewale, S.
Agre, P.
Badu-Apraku, Baffour
Gedil, Melaku A
Offornedo, Q.N.
author_facet Badu-Apraku, Baffour
Adewale, S.
Agre, P.
Offornedo, Q.N.
Gedil, Melaku A
author_sort Badu-Apraku, Baffour
collection Repository of Agricultural Research Outputs (CGSpace)
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.
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spelling CGSpace1284802025-12-08T10:29:22Z Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis Badu-Apraku, Baffour Adewale, S. Agre, P. Offornedo, Q.N. Gedil, Melaku A striga hermonthica disease resistance quantitative trait loci environment genes marker-assisted selection maize 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. 2023-01-12 2023-02-07T09:34:40Z 2023-02-07T09:34:40Z Journal Article https://hdl.handle.net/10568/128480 en Open Access application/pdf Frontiers Media 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.
spellingShingle striga hermonthica
disease resistance
quantitative trait loci
environment
genes
marker-assisted selection
maize
Badu-Apraku, Baffour
Adewale, S.
Agre, P.
Offornedo, Q.N.
Gedil, Melaku A
Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title_full Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title_fullStr Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title_full_unstemmed Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title_short Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis
title_sort mapping quantitative trait loci and predicting candidate genes for striga resistance in maize using resistance donor line derived from zea diploperennis
topic striga hermonthica
disease resistance
quantitative trait loci
environment
genes
marker-assisted selection
maize
url https://hdl.handle.net/10568/128480
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