CT-Based Phenotyping and Genome-Wide Association Analysis of the Internal Structure and Components of Maize Kernels

The structure of the maize kernels plays a critical role in determining maize yield and quality, and high-throughput, non-destructive microscope phenotypic characteristics acquisition and analysis are of great importance. In this study, Micro-CT technology was used to obtain images of maize kernels....

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Bibliographic Details
Published inAgronomy (Basel) Vol. 13; no. 4; p. 1078
Main Authors Li, Dazhuang, Wang, Jinglu, Zhang, Ying, Lu, Xianju, Du, Jianjun, Guo, Xinyu
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.04.2023
Subjects
Algorithms
Association analysis
Computed tomography
Corn
Crop yield
CT imaging
deep learning
Embryonic development
Embryos
Endosperm
Functional analysis
Genes
Genetic analysis
Genome-wide association studies
Genomes
Genomics
GWAS
Image analysis
Image processing
Inbreeding
Kernels
maize kernel
Medical imaging
micro-CT
microscopic phenotype
Morphology
Phenotypic variations
Phenotyping
Plant growth
Proteins
Single-nucleotide polymorphism
Software
three-dimensional structure
China
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Summary:The structure of the maize kernels plays a critical role in determining maize yield and quality, and high-throughput, non-destructive microscope phenotypic characteristics acquisition and analysis are of great importance. In this study, Micro-CT technology was used to obtain images of maize kernels. An automatic CT image analysis pipeline was then developed to extract 20 traits related to the three-dimensional structure of kernel, embryo, endosperm, and cavity. The determination coefficients for five volume-related traits (embryo, endosperm, silty endosperm, embryo cavity, and endosperm cavity) were 0.95, 0.95, 0.77, 0.73, and 0.94, respectively. Further, we analyzed the phenotypic variations among a group of 303 inbred lines and conducted genome-wide association studies (GWAS). A total of 26 significant SNP loci were associated with these traits that are closely related to kernel volume, and 62 candidate genes were identified. Functional analysis revealed that most candidate genes corresponding to cavity traits encoded stress resistance proteins, while those corresponding to embryo and endosperm traits encoded proteins involved in regulating plant growth and development. These results will improve the understanding of the phenotypic traits of maize kernels and will provide new theoretical support for in-depth analysis of the genetic mechanism of kernel structure traits.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy13041078