Comparative transcriptome meta-analysis reveals a set of genes involved in the responses to multiple pathogens in maize

被引:9
作者
Wang, Yapeng [1 ,2 ,3 ]
Li, Ting [1 ,2 ,3 ]
Sun, Zedan [1 ,2 ,3 ]
Huang, Xiaojian [1 ,2 ,3 ]
Yu, Naibing [1 ,2 ,3 ]
Tai, Huanhuan [1 ,2 ,3 ]
Yang, Qin [1 ,2 ,3 ]
机构
[1] Northwest A&F Univ, State Key Lab Crop Stress Biol Arid Areas, Yangling, Peoples R China
[2] Northwest A&F Univ, Coll Agron, Yangling, Peoples R China
[3] Northwest A&F Univ, Key Lab Maize Biol & Genet Breeding Arid Area Nort, Minist Agr, Yangling, Peoples R China
来源
FRONTIERS IN PLANT SCIENCE | 2022年 / 13卷
基金
中国国家自然科学基金;
关键词
maize; pathogens; meta-analysis; multiple disease resistance; differentially expressed genes (DEGs); QUANTITATIVE DISEASE RESISTANCE; CONFERS RESISTANCE; TRIGGERED IMMUNITY; LEAF-BLIGHT; PLANT; TRANSPORTER; RECOGNITION; LOCUS; CYTOCHROME-P450; CONTRIBUTES;
D O I
10.3389/fpls.2022.971371
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Maize production is constantly threatened by the presence of different fungal pathogens worldwide. Genetic resistance is the most favorable approach to reducing yield losses resulted from fungal diseases. The molecular mechanism underlying disease resistance in maize remains largely unknown. The objective of this study was to identify key genes/pathways that are consistently associated with multiple fungal pathogen infections in maize. Here, we conducted a meta-analysis of gene expression profiles from seven publicly available RNA-seq datasets of different fungal pathogen infections in maize. We identified 267 common differentially expressed genes (co-DEGs) in the four maize leaf infection experiments and 115 co-DEGs in all the seven experiments. Functional enrichment analysis showed that the co-DEGs were mainly involved in the biosynthesis of diterpenoid and phenylpropanoid. Further investigation revealed a set of genes associated with terpenoid phytoalexin and lignin biosynthesis, as well as potential pattern recognition receptors and nutrient transporter genes, which were consistently up-regulated after inoculation with different pathogens. In addition, we constructed a weighted gene co-expression network and identified several hub genes encoding transcription factors and protein kinases. Our results provide valuable insights into the pathways and genes influenced by different fungal pathogens, which might facilitate mining multiple disease resistance genes in maize.
引用
收藏
页数:15
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