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

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.

Abstract W P73: Feasibility and Preliminary Results of Whole Blood RNA-Sequencing Analysis in Patients With Intracranial Aneurysms

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Blake Haas ◽  
Nestor R Gonzalez ◽  
Elina Nikkola ◽  
Mark Connolly ◽  
William Hsu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Rna Sequencing ◽  
Whole Blood ◽  
Intracranial Aneurysms ◽  
Small Sample Size ◽  
Expression Patterns ◽  
Small Sample ◽  
Cellular Respiration ◽  
Sequencing Analysis

Introduction: Intracranial aneurysms (IA) growth and rupture have been associated with chronic remodeling of the arterial wall. However, the pathobiology of this process remains poorly understood. The objective of the present study was to evaluate the feasibility of analyzing gene expression patterns in peripheral blood of patients with ruptured and unruptured saccular IAs. Materials and Methods: We analyzed human whole blood transcriptomes by performing paired-end, 100 bp RNA-sequencing (RNAseq) using the Illumina platform. We used STAR to align reads to the genome, HTSeq to count reads, and DESeq to normalize counts across samples. Self-reported patient information was used to correct expression values for ancestry, age, and sex. We utilized weighted gene co-expression network analysis (WGCNA) to identify gene expression network modules associated with IA size and rupture. The DAVID tool was employed to search for Gene Ontology enrichment in relevant modules. Results: Samples from 12 patients (9 females, age 57.6 +/-12) with IAs were analyzed. Four had ruptured aneurysms. RNA isolation and application of the methodology described above was successful in all samples. Although the small sample size prevents us from drawing definite conclusions, we observed promising novel co-expression networks for IAs: WCGNA analysis showed down-regulation of two transcript modules associated with ruptured IA status (r=-0.78, p=0.008 and r=-0.77, p=0.009), and up-regulation of two modules associated with aneurysm size (r=0.86, p=0.002 and r=0.9, p=4e-04), respectively. DAVID analyses showed that genes upregulated in an IA size-associated module were enriched with genes involved in cellular respiration and translation, while genes involved in transcription were down-regulated in a module associated with ruptured IAs. Conclusions: Whole blood RNAseq analysis is a feasible tool to capture transcriptome dynamics and achieve a better understanding of the pathophysiology of IAs. Further longitudinal studies of patients with IAs using network analysis are justified.

scholarly journals Indirubin attenuates mouse psoriasis-like skin lesion in a CD274-dependent manner: an achievement of RNA sequencing

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Xiaochun Xue ◽  
Jianhua Wu ◽  
Junhui Li ◽  
Jianguo Xu ◽  
Haiying Dai ◽  
...  
Keyword(s):  
Network Analysis ◽  
Skin Lesion ◽  
Candidate Genes ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Regulatory Mechanisms ◽  
Epidermal Keratinocytes ◽  
Dependent Manner ◽  
Human Epidermal Keratinocytes ◽  
Ifn Γ

It was previously reported that the expression of CD274 was down-regulated in psoriatic epidermis, leading to immune disorders of psoriasis. However, the regulatory mechanisms of CD274 were rarely elucidated. We aimed to explore the regulatory mechanisms of CD274. Skin samples were collected from 18 patients with psoriasis vulgaris and 9 healthy participants for RNA sequencing. Candidate genes were chosen based on degree and k-core difference of genes in the co-expression network. The relations between candidate genes and CD274 were validated by flow cytometry and real-time PCR in primary human epidermal keratinocytes. The therapeutic effect of indirubin was assessed in an imiquimod-treated mouse model. Interferon-γ (IFN-γ), cyclin-dependent kinase (CDK) 1, Toll-like receptor 3 (TLR3), TLR4 and interleukin (IL)-17A were considered as candidate genes. In primary human epidermal keratinocytes, the level of CD274 was obviously increased under the stimulation of IFN-γ and CDK1 inhibitor (indirubin), independent of TLR4, TLR3 or IL-17A. Indirubin alleviated the severity of psoriatic mice in a CD274-dependent manner. Co-expression network analysis served as an effective method for the exploration of molecular mechanisms. We demonstrated for the first time that CD274 was the regulator of indirubin-mediated effect on mouse psoriasis-like skin lesion based on co-expression network analysis, contributing to the alleviation of mouse psoriasis-like skin lesion.

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.

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
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