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. 2022 Nov 16;13(11):2130.
doi: 10.3390/genes13112130.

WGCNA Analysis Revealed the Hub Genes Related to Soil Cadmium Stress in Maize Kernel (Zea mays L.)

Yongjin Li  1 , Ying Zhang  2 , Hongbing Luo  1   3 , Dan Lv  1 , Zhenxie Yi  1 , Meijuan Duan  1 , Min Deng  1   3
Affiliations

WGCNA Analysis Revealed the Hub Genes Related to Soil Cadmium Stress in Maize Kernel (Zea mays L.)

Yongjin Li et al. Genes (Basel). .

Abstract

Soil contamination by heavy metals has become a prevalent topic due to their widespread release from industry, agriculture, and other human activities. Great progress has been made in elucidating the uptake and translocation of cadmium (Cd) accumulation in rice. However, there is still little known about corresponding progress in maize. In the current study, we performed a comparative RNA-Seq-based approach to identify differentially expressed genes (DEGs) of maize immature kernel related to Cd stress. In total, 55, 92, 22, and 542 DEGs responsive to high cadmium concentration soil were identified between XNY22-CHS-8 vs. XNY22-YA-8, XNY22-CHS-24 vs. XNY22-YA-24, XNY27-CHS-8 vs. XNY27-YA-8, and XNY27-CHS-24 vs. XNY27-YA-24, respectively. The weighted gene co-expression network analysis (WGCNA) categorized the 9599 Cd stress-responsive hub genes into 37 different gene network modules. Combining the hub genes and DEGs, we obtained 71 candidate genes. Gene Ontology (GO) enrichment analysis of genes in the greenyellow module in XNY27-YA-24 and connectivity genes of these 71 candidate hub genes showed that the responses to metal ion, inorganic substance, abiotic stimulus, hydrogen peroxide, oxidative stress, stimulus, and other processes were enrichment. Moreover, five candidate genes that were responsive to Cd stress in maize kernel were detected. These results provided the putative key genes and pathways to response to Cd stress in maize kernel, and a useful dataset for unraveling the underlying mechanism of Cd accumulation in maize kernel.

Keywords: Cd stress; WGCNA; gene co-expression; maize; network.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Cd content in roots (A), stems (B), leaves (C), and kernels (D) of hybrid maize XNY22 and XNY27 at 8, 24, and 40 DAP in the CHS and YA locations.
Figure 2
Figure 2
The differentially expressed genes analysis. (A) The number of DEGs in four groups. (B) Venn diagram of hybrid maize XNY22 DEGs in two groups. (C) Venn diagram of hybrid maize XNY27 DEGs in two groups.
Figure 3
Figure 3
Module identification by weighted gene co-expression network analysis (WGCNA). (A,B) represent the soft threshold with scale independence and mean connectivity.
Figure 4
Figure 4
Hierarchical dendrogram reveals co-expression modules identified by WGCNA. A total of 37 modules were identified based on calculation of eigengenes; each module was decorated with a different color.
Figure 5
Figure 5
The correlation coefficient and correlation significance between the module and different kernel developmental stage hybrid of Cd stress. Each row in the table corresponds to a consensus module, and each column to different location, kernel developmental stage, and hybrid. The module name is shown on the y-axis, and the time point is shown on the x-axis.
Figure 6
Figure 6
GO term enrichment of genes in the greenyellow (A) and ivory (B).
Figure 7
Figure 7
Analysis of candidate hub genes network interaction in greenyellow module.
Figure 8
Figure 8
Analysis of candidate hub genes network interaction in the phenotypic significant enrichment module. The correlation network visualization of the interactions showed the connection between the top 20 genes with the highest connectivity in 71 candidate hub genes.
See this image and copyright information in PMC

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