Evidence map›Paper›PMID 41634575›Full record

ArticleBMC plant biology2026

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, Yishuang Wang, Yulin Yu, Ahmad Rizwan, Haibing Yu, Yongfu Wang, Xinxin Cheng

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Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Nini Cui *College of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China.
Yishuang Wang *College of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China.
Yulin YuCollege of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China.
Ahmad RizwanCollege of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China.
Haibing YuCollege of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China.
Yongfu WangCollege of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China. wangyongfu@ahstu.edu.cn.
Xinxin ChengCollege of Agriculture, Anhui Science and Technology University, No. 9, Donghua Road, Chuzhou, Anhui Province, 233100, China. chengxx@ahstu.edu.cn.

Funding

Emergency Management of the National Natural Science Foundation of China 31440066
6 · The paper itself

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.

Indexed as

SeedlingsZea maysGenes, PlantGenetic LociGenome-Wide Association StudyGenotypePolymorphism, Single NucleotideCandidate geneGenome-wide association analysisSeedling emergence rateSeedling lengthSuper-sweet corn

Identifiers

PMID41634575
PMCPMC12958539

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