scholarly journals Metabolic Profiling and Metabolite Correlation Network Analysis Reveal That Fusarium solani Induces Differential Metabolic Responses in Lotus japonicus and Lotus tenuis against Severe Phosphate Starvation

2021 ◽  
Vol 7 (9) ◽  
pp. 765
Author(s):  
Amira Susana Nieva ◽  
Fernando Matías Romero ◽  
Alexander Erban ◽  
Pedro Carrasco ◽  
Oscar Adolfo Ruiz ◽  
...  
Keyword(s):  
Network Analysis ◽  
Fusarium Solani ◽  
Plant Nutrition ◽  
Lotus Japonicus ◽  
Correlation Network ◽  
Stressful Situation ◽  
Mild Stress ◽  
Differential Outcomes ◽  
Pi Starvation ◽  
Fungal Interactions

Root fungal endophytes are essential mediators of plant nutrition under mild stress conditions. However, variations in the rhizosphere environment, such as nutrient depletion, could result in a stressful situation for both partners, shifting mutualistic to nonconvenient interactions. Mycorrhizal fungi and dark septate endophytes (DSEs) have demonstrated their ability to facilitate phosphate (Pi) acquisition. However, few studies have investigated other plant–fungal interactions that take place in the root environment with regard to phosphate nutrition. In the present research work, we aimed to analyze the effect of extreme Pi starvation and the fungal endophyte Fusarium solani on the model Lotus japonicus and the crop L. tenuis. We conducted metabolomics analysis based on gas chromatography-mass spectrometry (GC-MS) on plant tissues under optimal conditions, severe Pi starvation and F.solani presence. By combining statistical and correlation network analysis strategies, we demonstrated the differential outcomes of the two plant species against the combination of treatments. The combination of nutritional stress and Fusarium presence activated significant modifications in the metabolism of L. japonicus affecting the levels of sugars, polyols and some amino acids. Our results display potential markers for further inspection of the factors related to plant nutrition and plant–fungal interactions.

scholarly journals Lipidomic Network of Mild Cognitive Impairment from the Mayo Clinic Study of Aging

2021 ◽  
pp. 1-11
Author(s):  
Xuewei Wang ◽  
Hai Bui ◽  
Prashanthi Vemuri ◽  
Jonathan Graff-Radford ◽  
Clifford R. Jack Jr ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Network Analysis ◽  
Mayo Clinic ◽  
Plasma Lipids ◽  
Amyloid Β ◽  
Cognitive Status ◽  
Correlation Network ◽  
Lipid Species ◽  
Clinic Study

Background: Lipid alterations contribute to Alzheimer’s disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. Objective: To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groups Methods: Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Results: Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Conclusion: Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

scholarly journals The Use of RNA Sequencing and Correlation Network Analysis to Study Potential Regulators of Crabapple Leaf Color Transformation

2018 ◽  
Vol 59 (5) ◽  
pp. 1027-1042 ◽  
Author(s):  
Tuo Yang ◽  
Keting Li ◽  
Suxiao Hao ◽  
Jie Zhang ◽  
Tingting Song ◽  
...  
Keyword(s):  
Network Analysis ◽  
Rna Sequencing ◽  
Correlation Network ◽  
Leaf Color ◽  
Color Transformation

Correlation Network Analysis and Knowledge Integration

2011 ◽  
pp. 251-280 ◽  
Author(s):  
Thomas N. Plasterer ◽  
Robert Stanley ◽  
Erich Gombocz
Keyword(s):  
Network Analysis ◽  
Knowledge Integration ◽  
Correlation Network

A network analysis of political incivility dimensions

2019 ◽  
Vol 4 (3) ◽  
pp. 204-223
Author(s):  
Toby Hopp
Keyword(s):  
Network Analysis ◽  
Partial Correlation ◽  
Precise Definition ◽  
Correlation Network ◽  
Political Discussion ◽  
Relational Dynamics ◽  
Communication Processes ◽  
Democratic Communication ◽  
Scholarly Inquiry

Although online political incivility has increasingly become an object of scholarly inquiry, there exists little agreement on the construct’s precise definition. The goal of this work was therefore to explore the relational dynamics among previously identified dimensions of online political incivility. The results of a regularized partial correlation network indicated that a communicator’s desire to exclude attitude-discrepant others from discussion played an especially influential role in the variable network. The data also suggested that certain facets of incivility may be likely to be deployed together. Specifically, the data suggested the existence of two identifiable groupings of incivility factors: (1) variables pertaining to violation of speech-based norms and (2) variables pertaining to the violation of the inclusion-based norms that underlie democratic communication processes. These results are discussed in the context of political discussion and deliberation.

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