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Updated: Jun 13, 2026

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
Published on: March 28, 2025
Application of NGS Technology, Association Mapping, and Physical Mapping Technologies to Identify Candidate Genes
Jan Bocianowski1, Agnieszka Tomkowiak2, Ewelina Wagner3
1Department of Mathematical and Statistical Methods, Faculty of Agriculture, Horticulture and Biotechnology, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland.
Abstract:
Maize (Zea mays L.) is one of the most important cereal crops worldwide, with yield being a complex quantitative trait controlled by multiple genetic factors. The aim of this study was to identify molecular markers associated with maize yield using next-generation sequencing (NGS), association mapping, and physical mapping approaches. A total of 122 maize hybrids were evaluated under field conditions in a randomized complete block design with three replications. Phenotypic data were collected for grain yield, while genotypic data were obtained using DArTseq technology, resulting in the identification of 60,436 SilicoDArT and 32,178 SNP markers. After quality filtering, 25,078 markers were used for further analyses. Analysis of variance revealed statistically significant differences among hybrids in terms of yield (p < 0.001), with values ranging from 12.67 to 18.52 kg/10 m2. Genetic similarity among hybrids ranged from 0.434 to 0.957, indicating substantial genetic diversity. Cluster analyses based on phenotypic and genotypic data showed a lack of correspondence between yield performance and genetic similarity. Genome-wide association studies (GWAS) identified 2478 markers significantly associated with yield, including 47 highly significant markers (Logarithm of the Odds - LOD > 4.0). Individual markers explained between 2.4% and 18.7% of yield variation. Ten markers with the highest contribution to yield variability (13.30-18.70%) were selected as the most promising candidates for further breeding applications. These markers represent promising candidates for marker-assisted selection and genomic selection (GS) of high-yielding maize genotypes. These are some of the first positive results. The integration of phenotypic evaluation with high-throughput genotyping and association mapping provides valuable insights into the genetic architecture of yield and offers practical tools for the development of high-yielding maize cultivars.
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