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Updated: Sep 16, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Mining candidate genes for maize plant height based on a GWAS, Meta-QTL, and WGCNA
Fu Qian1, Zhanqin Zhang2, Shubin Chen2
1The Key Laboratory of Oasis Eco-Agriculture, College of Agriculture, Shihezi University, Shihezi, China.
Introduction:
In maize, plant height (PH) is one of the most important agronomic traits that directly influences planting density and yield. Therefore, identifying candidate genes related to PH will help manipulate maize yield indirectly.
Methods:
The present research carried out a genome-wide association study (GWAS) of PH using a natural population of 580 maize inbred lines. Further, after collecting the published transcriptome data of maize B73, tissue-specific gene co-expression modules related to PH were generated using weighted gene co-expression network analysis (WGCNA). Furthermore, a meta-analysis of the already reported PH-related quantitative trait loci (QTLs).
Results:
The integrated analysis of the results based on the different approaches screened three candidate genes: Zm00001d031796, encoding AP2-EREBP transcription factor 172; Zm00001d009918, encoding Phytochrome A-associated F-box protein; and Zm00001d042454, encoding plastid specific ribosomal protein 4.
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