Genome-Wide Association Analysis for Candidate Genes Contributing to Kernel-Related Traits in Maize

Overview

Journal Front Plant Sci

Date 2022 Jun 10

PMID 35685022

Authors

Zhibo Qu

Ying Wu

Die Hu

Ting Li

Hangyu Liang

Fan Ye

Jiquan Xue

Shutu Xu

Affiliations

Soon will be listed here.

Abstract

Maize grain size is the main factor determining grain yield. Dissecting the genetic basis of maize grain size may help reveal the regulatory mechanism of maize seed development and yield formation. In this study, two associated populations were used for genome-wide association analysis of kernel length, kernel width, kernel thickness, and hundred-kernel weight from multiple locations in AM122 and AM180, respectively. Then, genome-wide association mapping was performed based on the maize 6H90K SNP chip. A total of 139 loci were identified as associated with the four traits with < 1 × 10 using two models (FarmCPU and MLM). The transcriptome data showed that 15 of them were expressed differentially in two maize-inbred lines KB182 (small kernel) and KB020 (big kernel) during kernel development. These candidate genes were enriched in regulating peroxidase activity, oxidoreductase, and leaf senescence. The molecular function was major in binding and catalytic activity. This study provided important reference information for exploring maize kernel development mechanisms and applying molecular markers in high-yield breeding.

Citing Articles

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize.

Sahito J, Zhang H, Gishkori Z, Ma C, Wang Z, Ding D Int J Mol Sci. 2024; 25(3).

PMID: 38339196 PMC: 10855973. DOI: 10.3390/ijms25031918.

Unravelling the genetic framework associated with grain quality and yield-related traits in maize ( L.).

Sethi M, Saini D, Devi V, Kaur C, Singh M, Singh J Front Genet. 2023; 14:1248697.

PMID: 37609038 PMC: 10440565. DOI: 10.3389/fgene.2023.1248697.

Genome-Wide Association Study Identified Novel SNPs Associated with Chlorophyll Content in Maize.

Jin Y, Li D, Liu M, Cui Z, Sun D, Li C Genes (Basel). 2023; 14(5).

PMID: 37239370 PMC: 10218100. DOI: 10.3390/genes14051010.

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