Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs

Bowen Luo; Jiaqian Li; Binyang Li; Haiying Zhang; Ting Yu; Guidi Zhang; Shuhao Zhang; Javed Hussain Sahito; Xiao Zhang; Dan Liu; Ling Wu; Duojiang Gao; Shiqiang Gao; Shibin Gao

doi:10.3389/fpls.2022.1013598

Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs

Front Plant Sci. 2022 Oct 28:13:1013598. doi: 10.3389/fpls.2022.1013598. eCollection 2022.

Authors

Bowen Luo^{1

2

3}, Jiaqian Li^{2

3}, Binyang Li^{2

3}, Haiying Zhang^{2

3}, Ting Yu^{2

3}, Guidi Zhang^{2

3}, Shuhao Zhang^{2

3}, Javed Hussain Sahito^{2

4}, Xiao Zhang^{2

3}, Dan Liu^{2

3}, Ling Wu^{2

3}, Duojiang Gao^{2

3}, Shiqiang Gao^{2

3}, Shibin Gao^{1

2

3}

Affiliations

¹ State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, Sichuan, China.
² Maize Research Institute, Sichuan Agricultural University, Chengdu, Sichuan, China.
³ Key laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Chengdu, Sichuan, China.
⁴ Key Laboratory of Wheat and Maize Crops Science, College of Agronomy, Henan Agricultural University, Zhengzhou, China.

Abstract

Nutrient restrictions and large-scale emergence of diseases are threatening the maize production. Recent findings demonstrated that there is a certain synergistic interaction between nutrition and diseases pathways in model plants, however there are few studies on the synergistic genes of nutrients and diseases in maize. Thus, the transcriptome data of nitrogen (N) and phosphorus (P) nutrients and diseases treatments in maize, rice, wheat and Arabidopsis thaliana were collected in this study, and four and 22 weighted co-expression modules were obtained by using Weighted Gene Co-expression Network Analysis (WGCNA) in leaf and root tissues, respectively. With a total of 5252 genes, MFUZZ cluster analysis screened 26 clusters with the same expression trend under nutrition and disease treatments. In the meantime, 1427 genes and 22 specific consensus quantitative trait loci (scQTLs) loci were identified by meta-QTL analysis of nitrogen and phosphorus nutrition and disease stress in maize. Combined with the results of cluster analysis and scQTLs, a total of 195 consistent genes were screened, of which six genes were shown to synergistically respond to nutrition and disease both in roots and leaves. Moreover, the six candidate genes were found in scQTLs associated with gray leaf spot (GLS) and corn leaf blight (CLB). In addition, subcellular localization and bioinformatics analysis of the six candidate genes revealed that they were primarily expressed in endoplasmic reticulum, mitochondria, nucleus and plasma membrane, and were involved in defense and stress, MeJA and abscisic acid response pathways. The fluorescence quantitative PCR confirmed their responsiveness to nitrogen and phosphorus nutrition as well as GLS treatments. Taken together, findings of this study indicated that the nutrition and disease have a significant synergistic response in maize.

Keywords: Nutrition utilization; cQTLs; co-expression network; disease resistance; maize; synergistic genes.