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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

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) F(2:3) mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four Striga...

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Autores principales: Badu-Apraku, B., Adewale, S., Paterne, A., Offornedo, Q., Gedil, M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877281/
https://www.ncbi.nlm.nih.gov/pubmed/36713079
http://dx.doi.org/10.3389/fgene.2023.1012460
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author Badu-Apraku, B.
Adewale, S.
Paterne, A.
Offornedo, Q.
Gedil, M.
author_facet Badu-Apraku, B.
Adewale, S.
Paterne, A.
Offornedo, Q.
Gedil, M.
author_sort Badu-Apraku, B.
collection PubMed
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) F(2:3) 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 pubmed-98772812023-01-27 Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis Badu-Apraku, B. Adewale, S. Paterne, A. Offornedo, Q. Gedil, M. Front Genet Genetics 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) F(2:3) 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. Frontiers Media S.A. 2023-01-12 /pmc/articles/PMC9877281/ /pubmed/36713079 http://dx.doi.org/10.3389/fgene.2023.1012460 Text en Copyright © 2023 Badu-Apraku, Adewale, Paterne, Offornedo and Gedil. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Badu-Apraku, B.
Adewale, S.
Paterne, A.
Offornedo, Q.
Gedil, M.
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 Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877281/
https://www.ncbi.nlm.nih.gov/pubmed/36713079
http://dx.doi.org/10.3389/fgene.2023.1012460
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