Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat

Lv, Liangjie; Zhang, Wenying; Sun, Lijing; Zhao, Aiju; Zhang, Yingjun; Wang, Limei; Liu, Yuping; Li, Ziqian; Chen, Xiyong

doi:10.1371/journal.pone.0236186

Cited by 29 publications

(22 citation statements)

References 67 publications

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“…WGCNA was used to detect the genes which co-express (Lin et al, 2019). The relationship between trait and module identifies the most vital hub genes, which supports an efficacious way to explore the in-depth mechanism of complex traits (Lv et al, 2020). Considering the importance of fungal inoculants against the control of O. furnacalis, plant yield, and maize defense through augmented production of enzymatic and non-enzymatic antioxidants.…”

Section: Discussionmentioning

confidence: 99%

Myco-Synergism Boosts Herbivory-Induced Maize Defense by Triggering Antioxidants and Phytohormone Signaling

et al. 2022

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BackgroundBiocontrol strategies are the best possible and eco-friendly solution to develop resistance against O furnacalis and improve the maize yield. However, the knowledge about underlying molecular mechanisms, metabolic shifts, and hormonal signaling is limited.MethodsHere, we used an axenic and a consortium of entomopathogenic Beauveria bassiana OFDH1-5 and a pathogen-antagonistic Trichoderma asperellum GDFS1009 in maize and observed that consortium applications resulted in higher chlorophyll contents and antioxidants activities [superoxide dismutase (SOD), peroxidase (POD), proline, protease, and polyphenol oxidase (PPO)] with a decrease in O. furnacalis survival. We performed a comprehensive transcriptome and an untargeted metabolome profiling for the first time at a vegetative stage in fungal inoculated maize leaves at 0-, 12-, 24-, 48-, and 72-h post insect infestation.ResultsThe consortium of B. bassiana and T. asperellum leads to 80–95% of O. furnacalis mortality. A total of 13,156 differentially expressed genes were used for weighted gene coexpression network analysis. We identified the six significant modules containing thirteen candidate genes [protein kinase (GRMZM2G025459), acyl-CoA dehydrogenase (GRMZM5G864319), thioredoxin gene (GRMZM2G091481), glutathione S-transferase (GRMZM2G116273), patatin-like phospholipase gene (GRMZM2G154523), cytochrome P450 (GRMZM2G139874), protease inhibitor (GRMZM2G004466), (AC233926.1_FG002), chitinase (GRMZM2G453805), defensin (GRMZM2G392863), peroxidase (GRMZM2G144153), GDSL- like lipase (AC212068.4_FG005), and Beta-glucosidase (GRMZM2G031660)], which are not previously reported that are highly correlated with Jasmonic acid - Ethylene (JA-ET) signaling pathway and antioxidants. We detected a total of 130 negative and 491 positive metabolomic features using a ultrahigh-performance liquid chromatography ion trap time-of-flight mass spectrometry (UHPLC-QTOF-MS). Intramodular significance and real time-quantitative polymerase chain reaction (RT-qPCR) expressions showed that these genes are the true candidate genes. Consortium treated maize had higher jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) levels.ConclusionOur results provide insights into the genetics, biochemicals, and metabolic diversity and are useful for future biocontrol strategies against ACB attacks.

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Section: Discussionmentioning

confidence: 99%

Myco-Synergism Boosts Herbivory-Induced Maize Defense by Triggering Antioxidants and Phytohormone Signaling

et al. 2022

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“…Gene association analysis is widely used to envision how genes work cooperatively in regulatory systems under prevailing conditions 9 , 10 . It has enabled insights into plant regulatory responses to stress, for example the responses of Arabidopsis 32 and apple 28 to bacterial infection and cotton 33 and wheat 34 to drought stress. Gene co-expression networks facilitate the holistic inference of associations based upon concurrence between gene expression patterns.…”

Section: Discussionmentioning

confidence: 99%

Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava

Jaemthaworn

Kalapanulak

Saithong

2021

Sci Rep

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Robustness, a naïve property of biological systems, enables organisms to maintain functions during perturbation and is crucial for improving the resilience of crops to prevailing stress conditions and diseases, guaranteeing food security. Most studies of robustness in crops have focused on genetic superiority based upon individual genes, overlooking the collaborative actions of multiple responsive genes and the regulatory network topology. This research aims to uncover patterns of gene cooperation leading to organismal robustness by studying the topology of gene co-expression networks (GCNs) of both CBSV virus resistant and susceptible cassava cultivars. The resulting GCNs show higher topological clustering of cooperative genes in the resistant cultivar, suggesting that the network architecture is central to attaining robustness. Despite a reduction in the number of hub genes in the resistant cultivar following the perturbation, essential biological functions contained in the network were maintained through neighboring genes that withstood the shock. The susceptible cultivar seemingly coped by inducing more gene actions in the network but could not maintain the functions required for plant growth. These findings underscore the importance of regulatory network architecture in ensuring phenotypic robustness and deepen our understanding of transcriptional regulation.

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“…Furthermore, this crisis of crop productivity is further exacerbated by global climate change and future water shortages [3]. Since water is essential at all stages of growth and development, a subtle variation in water potential during critical growth phases can adversely impact the yield of agronomically important crops [2,5,6]. For instance, drought-related water scarcity can reduce 40% and 50% of wheat and tomato production, respectively [5,7].…”

Section: Introductionmentioning

confidence: 99%

“…Since water is essential at all stages of growth and development, a subtle variation in water potential during critical growth phases can adversely impact the yield of agronomically important crops [2,5,6]. For instance, drought-related water scarcity can reduce 40% and 50% of wheat and tomato production, respectively [5,7]. Likewise, it was projected that climate change-related water deficiency can reduce potato production by 18-32% in the next four decades [4].…”

Section: Introductionmentioning

confidence: 99%

Network Biology Analyses and Dynamic Modeling of Gene Regulatory Networks Under Drought Stress Reveal Major Transcriptional Regulators in Arabidopsis

Kumar¹,

Mishra²,

Liu³

et al. 2022

Preprint

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Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on the plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of highly-priority transcription factors (TFs) dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We revealed distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficients nodes. Dynamic transcriptional regulatory modeling on integrated TF-target and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that can potentially be used in future genetic crop engineering programs.

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Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat

Cited by 29 publications

References 67 publications

Myco-Synergism Boosts Herbivory-Induced Maize Defense by Triggering Antioxidants and Phytohormone Signaling

Myco-Synergism Boosts Herbivory-Induced Maize Defense by Triggering Antioxidants and Phytohormone Signaling

Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava

Network Biology Analyses and Dynamic Modeling of Gene Regulatory Networks Under Drought Stress Reveal Major Transcriptional Regulators in Arabidopsis

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