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Mapping quantitative trait loci and predicting candidate genes for resistance in maize using resistance donor line derived from . | LitMetric

The parasitic weed, 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 mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four -adaptive traits and genotyped using the Diversity Arrays Technology (DArT) to determine the genomic regions responsible for 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 resistance traits were identified across four -infested environments with five stable QTLs (4, 2.1, 2.2, 5, and 6) detected in more than one environment. The variations explained by the QTLs ranged from 4.1% (2.3) to 14.4% (7.1). Six QTLs each with significant additive × environment interactions were also identified for grain yield and 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 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 resistant and high-yielding maize cultivars.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877281PMC
http://dx.doi.org/10.3389/fgene.2023.1012460DOI Listing

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