Genome-wide-association-analysis-based identification of genetic loci and candidate genes associated with seedling emergence rate in super-sweet corn (Zea mays L.)

Seed germination is the initial and critical stage of plant growth and development. This study conducted a genome-wide association study (GWAS) on seedling emergence rate (SER) and seedling length (SL) in super-sweet corn using a panel of 201 Chinese core germplasm accessions as the association population. Through multi-model GWAS integration of BLINK, FarmCPU and MLM approaches applied to 56 K maize SNP array data, 12, 18 and 19 significant SNPs were detected by each model respectively. Venn diagram analysis revealed significant overlaps among different models, ultimately identifying eight SNPs significantly associated with SER and two SNPs related to SL. Through functional annotation and literature analysis, 15 candidate genes were identified from an initial set of 49 annotated genes. Among these, 10 genes regulated SER, and 5 were linked to SL control, primarily functioning in protein biosynthesis, energy transduction, and cell division regulation. Allelic effect analysis demonstrated that the A/A and T/T genotypes represent key superior allelic variants regulating emergence rate. Through marker-assisted selection, pyramiding these favorable alleles can significantly enhance the seedling emergence rate in super-sweet corn. This study provides valuable genetic loci for marker-assisted breeding in super-sweet corn and offers an important reference for fine-mapping genes associated with seedling emergence rate characteristics.

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Publication Details

Journal
BMC Plant Biology
Published
2026-02-03
DOI
https://doi.org/10.1186/s12870-026-08228-z
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
Field-Weighted Citation Impact
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article

Genome-wide-association-analysis-based identification of genetic loci and candidate genes associated with seedling emergence rate in super-sweet corn (Zea mays L.)

Nini Cui, Yulin Yu, Xinxin Cheng, Ahmad Rizwan et al.
BMC Plant Biology
Genetic Mapping and Diversity in Plants and Animals
article

Genome-wide-association-analysis-based identification of genetic loci and candidate genes associated with seedling emergence rate in super-sweet corn (Zea mays L.)

Nini Cui, Yulin Yu, Xinxin Cheng, Ahmad Rizwan, Haibing Yu, Yongfu Wang, Yishuang Wang
article en

Abstract

Seed germination is the initial and critical stage of plant growth and development. This study conducted a genome-wide association study (GWAS) on seedling emergence rate (SER) and seedling length (SL) in super-sweet corn using a panel of 201 Chinese core germplasm accessions as the association population. Through multi-model GWAS integration of BLINK, FarmCPU and MLM approaches applied to 56 K maize SNP array data, 12, 18 and 19 significant SNPs were detected by each model respectively. Venn diagram analysis revealed significant overlaps among different models, ultimately identifying eight SNPs significantly associated with SER and two SNPs related to SL. Through functional annotation and literature analysis, 15 candidate genes were identified from an initial set of 49 annotated genes. Among these, 10 genes regulated SER, and 5 were linked to SL control, primarily functioning in protein biosynthesis, energy transduction, and cell division regulation. Allelic effect analysis demonstrated that the A/A and T/T genotypes represent key superior allelic variants regulating emergence rate. Through marker-assisted selection, pyramiding these favorable alleles can significantly enhance the seedling emergence rate in super-sweet corn. This study provides valuable genetic loci for marker-assisted breeding in super-sweet corn and offers an important reference for fine-mapping genes associated with seedling emergence rate characteristics.

BMC Plant BiologyVol. 26(1)
Anhui University of Science and Technology (CN), Shanghai Liangyou (China) (CN), Anhui Science and Technology University (CN), Chuzhou University (CN)
Openalex Percentile: Top 66%
Genetic Mapping and Diversity in Plants and Animals
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