ArticlePlants (Basel, Switzerland)2025
Candidate Gene for Kernel-Related Traits in Maize Revealed by a Combination of GWAS and Meta-QTL Analyses.
Article in Plants (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- A genome-wide association study unveils the genetic architecture of morphological and biomass partitioning traits in maize under iron-deficient stress.Scientific reports · 2026Article
- Genome-wide association study identifies key loci and candidate genes for maize grain yield-related traits.BMC plant biology · 2026Article
- From development to yield: genetic and molecular regulation of agronomic traits in maize seeds.Frontiers in plant science · 2026Review
- Candidate genes for kernel ratio in maize identified via combined GWAS and QTL mapping across multiple environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genetic Architecture and Meta-QTL Identification of Yield Traits in Maize (Plants (Basel, Switzerland) · 2025Article
- Genetic Mapping of QTL Associated with 100-Kernel Weight Using a DH Population in Maize.Plants (Basel, Switzerland) · 2025Article
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Authors and funding
6 authors.
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Abstract
Maize kernel traits represent crucial agronomic characteristics that significantly determine yield potential. Analyzing the genetic basis of these traits is essential for yield improvement. In this study, we utilized 1283 maize inbred lines to investigate three kernel-related characteristics: kernel length (KL), kernel width (KW), and 100-kernel weight (HKW). We conducted a genome-wide association study (GWAS) on three kernel-related traits, resulting in the identification of 29 significantly associated SNPs and six candidate genes. Additionally, we compiled quantitative trait loci (QTL) information for 765 maize kernel-related traits from 56 studies, conducted a meta-analysis of QTL, and identified 65 meta-QTLs (MQTLs). Among the 23 MQTLs, we found 25 functional genes and reported candidate genes related to kernel traits. We identified 26 maize homologs across 19 MQTLs by utilizing 25 genes that affect rice grain traits. We compared the 29 significant SNPs detected with the physical locations of 65 MQTLs and found that 3 significant SNPs were located within these MQTL intervals, and another 10 significant SNPs were in proximity to these intervals, being less than 2 Mb away, although they were not included within the MQTL intervals. The results of this study provide a theoretical foundation for elucidating the genetic basis of maize kernel-related traits and advancing molecular marker-assisted breeding selection.
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