scholarly journals Transcriptomic Profiling of Young Cotyledons Response to Chilling Stress in Two Contrasting Cotton (Gossypium hirsutum L.) Genotypes at the Seedling Stage

2020 ◽  
Vol 21 (14) ◽  
pp. 5095
Author(s):  
Gongmin Cheng ◽  
Longyan Zhang ◽  
Hantao Wang ◽  
Jianhua Lu ◽  
Hengling Wei ◽  
...  
Keyword(s):  
Cold Tolerance ◽  
Chilling Stress ◽  
Chilling Injury ◽  
Membrane Damage ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Future Research ◽  
Ros Scavenging ◽  
Hub Genes ◽  
Cell Membrane Damage

Young cotyledons of cotton seedlings are most susceptible to chilling stress. To gain insight into the potential mechanism of cold tolerance of young cotton cotyledons, we conducted physiological and comparative transcriptome analysis of two varieties with contrasting phenotypes. The evaluation of chilling injury of young cotyledons among 74 cotton varieties revealed that H559 was the most tolerant and YM21 was the most sensitive. The physiological analysis found that the ROS scavenging ability was lower, and cell membrane damage was more severe in the cotyledons of YM21 than that of H559 under chilling stress. RNA-seq analysis identified a total of 44,998 expressed genes and 19,982 differentially expressed genes (DEGs) in young cotyledons of the two varieties under chilling stress. Weighted gene coexpression network analysis (WGCNA) of all DEGs revealed four significant modules with close correlation with specific samples. The GO-term enrichment analysis found that lots of genes in H559-specific modules were involved in plant resistance to abiotic stress. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that pathways such as plant hormone signal transduction, MAPK signaling, and plant–pathogen interaction were related to chilling stress response. A total of 574 transcription factors and 936 hub genes in these modules were identified. Twenty hub genes were selected for qRT-PCR verification, revealing the reliability and accuracy of transcriptome data. These findings will lay a foundation for future research on the molecular mechanism of cold tolerance in cotyledons of cotton.

scholarly journals Weighted Gene Correlation Network Analysis Identifies Specific Functional Modules and Genes in Esophageal Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Xu ◽  
Jian Xu ◽  
Zhiqiang Wang ◽  
Yuequan Jiang
Keyword(s):  
Esophageal Cancer ◽  
Network Analysis ◽  
Cell Cycle Progression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Future Research ◽  
Hub Genes ◽  
Pathological Staging

Objective. Esophageal cancer (ESCA) is one of the most aggressive malignancies globally with an undesirable five-year survival rate. Here, this study was conducted for determining specific functional genes linked with ESCA initiation and progression. Methods. Gene expression profiling of ESCA was curated from TCGA (containing 160 ESCA and 11 nontumor specimens) and GSE38129 (30 paired ESCA and nontumor tissues) datasets. Differential expression analysis was conducted between ESCA and nontumor tissues with adjusted p value <0.05 and |log2fold-change|>1. Weighted gene coexpression network analysis (WGCNA) was conducted for determining the ESCA-specific coexpression modules and genes. Thereafter, ESCA-specific differentially expressed genes (DEGs) were intersected. Functional enrichment analysis was then presented with clusterProfiler package. Protein-protein interaction was conducted, and hub genes were determined. Association of hub genes with pathological staging was evaluated, and survival analysis was presented among ESCA patients. Results. This study determined 91 ESCA-specific DEGs following intersection of DEGs and ESCA-specific genes in TCGA and GSE38129 datasets. They were remarkably linked to cell cycle progression and carcinogenic pathways like the p53 signaling pathway, cellular senescence, and apoptosis. Ten ESCA-specific hub genes were determined, containing ASPM, BUB1B, CCNA2, CDC20, CDK1, DLGAP5, KIF11, KIF20 A, TOP2A, and TPX2. They were prominently associated with pathological staging. Among them, KIF11 upregulation was in relation to undesirable prognosis of ESCA patients. Conclusion. Collectively, we determined ESCA-specific coexpression modules and hub genes, which offered the foundation for future research concerning the mechanistic basis of ESCA.

scholarly journals Identification of the Crucial Gene in Overflow Arteriovenous Fistula by Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhengde Zhao ◽  
Qining Fu ◽  
Liangzhu Hu ◽  
Yangdong Liu
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Intimal Hyperplasia ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Biological Processes ◽  
Hub Genes ◽  
Av Fistula ◽  
Core Genes

Objective: The aim was to study the preliminary screening of the crucial genes in intimal hyperplasia in the venous segment of arteriovenous (AV) fistula and the underlying potential molecular mechanisms of intimal hyperplasia with bioinformatics analysis.Methods: The gene expression profile data (GSE39488) was analyzed to identify differentially expressed genes (DEGs). We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of DEGs. Gene set enrichment analysis (GSEA) was used to understand the potential activated signaling pathway. The protein–protein interaction (PPI) network was constructed with the STRING database and Cytoscape software. The Venn diagram between 10 hub genes and gene sets of 4 crucial signaling pathways was used to obtain core genes and relevant potential pathways. Furthermore, GSEAs were performed to understand their biological functions.Results: A total of 185 DEGs were screened in this study. The main biological function of the 111 upregulated genes in AV fistula primarily concentrated on cell proliferation and vascular remodeling, and the 74 downregulated genes in AV fistula were enriched in the biological function mainly relevant to inflammation. GSEA found four signaling pathways crucial for intimal hyperplasia, namely, MAPK, NOD-like, Cell Cycle, and TGF-beta signaling pathway. A total of 10 hub genes were identified, namely, EGR1, EGR2, EGR3, NR4A1, NR4A2, DUSP1, CXCR4, ATF3, CCL4, and CYR61. Particularly, DUSP1 and NR4A1 were identified as core genes that potentially participate in the MAPK signaling pathway. In AV fistula, the biological processes and pathways were primarily involved with MAPK signaling pathway and MAPK-mediated pathway with the high expression of DUSP1 and were highly relevant to cell proliferation and inflammation with the low expression of DUSP1. Besides, the biological processes and pathways in AV fistula with the high expression of NR4A1 similarly included the MAPK signaling pathway and the pathway mediated by MAPK signaling, and it was mainly involved with inflammation in AV fistula with the low expression of NR4A1.Conclusion: We screened four potential signaling pathways relevant to intimal hyperplasia and identified 10 hub genes, including two core genes (i.e., DUSP1 and NR4A1). Two core genes potentially participate in the MAPK signaling pathway and might serve as the therapeutic targets of intimal hyperplasia to prevent stenosis after AV fistula creation.

A new morphological method to identify cold tolerance of melon at seedling stage

2020 ◽  
Vol 47 (1) ◽  
pp. 80
Author(s):  
Meng Li ◽  
Xiaoyu Duan ◽  
Qian Wang ◽  
Wei Chen ◽  
Hongyan Qi
Keyword(s):  
Cold Tolerance ◽  
Chilling Stress ◽  
Chilling Injury ◽  
Accurate Method ◽  
Seedling Stage ◽  
Leaf Angle ◽  
Injury Index ◽  
Spad Value ◽  
Yield And Quality ◽  
Rate Maximum

Low temperature restrains the growth and development of melons, as well as severely impairing the yield and quality. To obtain a rapid and accurate method for evaluating cold tolerance of melon, 10 genotypes were selected to investigate their cold tolerance at seedling stage. Chilling stress (15°C/6°C, day/night) increased leaf angles and caused leaves wilted: the phenotypes of the 10 genotypes were obviously different. Thus, a new predicted method for chilling injury index (CII) of melon was constructed based on the change of leaf angle and leaf state. The CII showed significant correlation with survival rate, maximum photochemical quantum yield of PSII (Fv/Fm) and changes of SPAD value. Moreover, the validity of the method was further verified by seedlings growth, photosynthesis, membrane permeability and metabolites accumulation of four screened genotypes. Taken together, this work provides a morphological and accurate method for evaluating cold tolerance in melon.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

scholarly journals Deciphering the Underlying Mechanism of Eucommiae Cortex against Osteoporotic Fracture by Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yongming Shuai ◽  
Zhili Jiang ◽  
Qiuwen Yuan ◽  
Shuqiang Tu ◽  
Fanhui Zeng
Keyword(s):  
Osteoporotic Fractures ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Ovariectomized Rats ◽  
Network Pharmacology ◽  
Future Research ◽  
Ppi Network ◽  
Hub Genes ◽  
Traditional Chinese Herbal Medicine ◽  
Kegg Pathways

Background. Du Zhong (DZ), or Eucommiae Cortex, a traditional Chinese herbal medicine, has been used to treat osteoporosis. Although it has been reported that DZ can improve bone mass in ovariectomized rats, its pharmacological mechanisms in treating osteoporotic fractures (OPF) remain unclear. Methods. In this study, we used a network pharmacological manner to explore its potential complicated mechanism in treating OPF. We obtained DZ compounds from TCMSP and BATMAN-TCM databases and collected potential targets of these compounds through target fishing based on TCMSP and BATMAN-TCM databases. Next, we collected the OPF targets by using CTD, GeneCards, OMIM, HPO, and GenCLiP 3 databases. And then the overlapping genes between DZ potential targets and OPF targets were used to build up the protein-protein interaction (PPI) network and to analyze their interactions and find out the big hub genes in this network. Subsequently, clusterProfiler package in R language was utilized to conduct the enrichment of Gene Ontology biological process and KEGG pathways. Results. There were totally 93 active compounds and 916 related targets in DZ. After the enrichment analysis, we collected top 25 cellular biological processes and top 25 pathways based on the adjusted P value and found that the DZ anti-OPF effect was mainly associated with the regulation of ROS and inflammatory response. Furthermore, 64 hub genes in PPI network, such as MAPK1 (degree = 41), SRC (degree = 39), PIK3R1 (degree = 36), VEGFA (degree = 31), TP53 (degree = 29), EGFR (degree = 29), JUN (degree = 29), AGT (degree = 29), MAPK1, SRC, PIK3R1, VEGFA, and TP53, were considered as potential therapeutic targets, implying the underlying mechanisms of DZ acting on OPF. Conclusion. We investigated the possible therapeutic mechanisms of DZ from a systemic perspective. These key targets and pathways provided promising directions for the future research to reveal the exact regulating mechanisms of DZ in treating OPF.

scholarly journals Identification of Neuropeptides as Potential Crosstalks Linking Down Syndrome and Periodontitis Revealed by Transcriptomic Analyses

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yue Chen ◽  
Xiaofei Yu ◽  
Jia Kong
Keyword(s):  
Down Syndrome ◽  
Signaling Pathway ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Future Research ◽  
Biological Processes

Background. This bioinformatics study was aimed to investigate the relationship between periodontitis (PD) and Down Syndrome (DS) regarding potential crosstalk genes, related neuropeptides, and biological processes. Methods. Data for PD (GSE23586, GSE10334 and GSE16134) and DS (GSE35665) were downloaded from NCBI Gene Expression Omnibus (GEO). Following normalization and merging of PD data, differential expression analysis was performed ( p value < 0.05 and ∣ log   FC ∣ ≥ 0.5 ). The common deregulated genes between PD and DS were considered as crosstalk genes. The significantly differentially expressed genes were used to construct the coexpression network and to further identify coexpression gene modules. To acquire the significant modules, the significant expression level of genes in the module was used to analyze the enrichment of genes in each module. Neuropeptides were assessed from NeuroPedia database. Neuropeptide genes and crosstalk genes were merged and mapped into PPI network, and the correlation coefficient (Spearman) was determined for the crosstalk genes. Results. 138 crosstalk genes were predicted. According to the functional enrichment analysis, these genes significantly regulated different biological processes and pathways. In enrichment analysis, the significant module of DS was pink module, and turquoise module was significant in PD. Four common crosstalk genes were acquired, i.e., CD19, FCRL5, FCRLA, and HLA-DOB. In the complex network, INS and IGF2 interacted with CASP3 and TP53, which commonly regulated the MAPK signaling pathway. Moreover, the results showed that TP53 interacted with IGF2 and INS inducing the dysregulation of PI3K-Akt signaling pathway. UBL was positively correlated with crosstalk genes in both diseases. LEP was revealed to be both a neuropeptide and crosstalk gene and was positively correlated with other crosstalk genes. Conclusion. Different crosstalk genes, related neuropeptides, and biological pathways and processes were revealed between PD and DS, which can serve as a theoretical basis for future research.

Ectopic Expression of a Novel Cold-resistance Protein 1 (BoCRP1) from Brassica Oleracea Promotes Tolerance to Cold via Modulating Stress Associated Components

2021 ◽  
Author(s):  
Umer Majeed Wani ◽  
Tahir Majeed Sheikh ◽  
Vaseem Raja ◽  
Zubair Ahmad Wani ◽  
Nelofer Jan ◽  
...  
Keyword(s):  
Cold Stress ◽  
Brassica Oleracea ◽  
Chilling Stress ◽  
Membrane Damage ◽  
Ectopic Expression ◽  
Ros Scavenging ◽  
Effective Strategies ◽  
Protective Shield ◽  
Scavenging Enzymes ◽  
Susceptible Tomato

Abstract Cold stress is considered as a major environmental factor that adversely affect the plant growth and distribution. Therefore, there arises an immediate need to cultivate effective strategies aimed at developing stress-tolerant crops that would boost the production and minimise the risks associated with cold stress. In this study, a novel cold-responsive protein1 isolated from Brassica oleracea (BoCRP1) was ectopically expressed in a cold susceptible tomato genotype Shalimar 1 and its function was investigated in response to chilling stress. BoCRP1 was constitutively expressed in all the tissues of B. oleracea including leaf, root and stem however, its expression was found to be significantly increased in response to cold stress. Moreover, transgenic tomato plants expressing BoCRP1 exhibited increased tolerance to chilling stress (4oC) with an overall improved rate of seed germination, increased root length, reduced membrane damage and increase in accumulation of osmoprotectants. Furthermore, we observed increased transcript levels of stress responsive genes and enhanced accumulation of ROS scavenging enzymes in transgenic on exposure to chilling stress. These results are therefore strongly in support of the role of BoCRP1 in offering the plant a protective shield and heightened resilience to chilling stress by maintaining osmotic balance, utilising the cellular antioxidant system and enhancing the transcription of cold responsive genes.

scholarly journals Novel Signature Genes for Human Left Ventricle Cardiomyopathies Identified by Weighted Co-expression Network Analysis (WGCNA)

2020 ◽  
Author(s):  
Jiao Tian ◽  
Zhengyuan Wu ◽  
Yaqi Zhang ◽  
Yingying He ◽  
SHUBAI LIU
Keyword(s):  
Post Partum ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Clinical Diagnostics ◽  
Hub Genes ◽  
Signature Genes ◽  
Ppi Networks ◽  
The Common ◽  
Human Left Ventricle ◽  
Key Pathways

Abstract BackgroundCardiomyopathy, a heart disease that arises from different etiologies, brings a huge healthcare burden to the global society. Identification of biomarkers can be very useful for early diagnosis of cardiomyopathy, interruption of the disease procession to heart failure, and decrement of the mortality. MethodsClinical cases of cardiomyopathy were screened out of independently investigations from the genomic database. Exploration of its whole transcription disorder pattern by WGCNA (Weighted Gene Co-expression Network Analysis) to discover the signature genes for different subtypes of cardiomyopathy. The hub genes and key pathways, which are correlated to cardiomyopathy traits, were identified through co-expression and protein-protein interaction (PPI) networks enrichment analysis. Discovered hub genes were blast through the Cardiovascular Disease Portal to verify functions related to human cardiomyopathies.ResultsThree common axes of signature genes were discovered for five subtypes of cardiomyopathy: 1) Four genes (MDM4, CFLAR, RPS6KB1, PKD1L2) were common for ischemic and ischemic cardiomyopathy subgroups; 2) Subtypes of cardiomyopathy (ischemic, post. partum, familiar and idiopathic) shared eight genes (MAPK1, MAPK11, MAPK14, LMNA, RAC1, PECAM1, XIAP, CREB1); 3) TFAM and RHEB were the common signature genes for subtypes of cardiomyopathy (viral, post. partum, familiar, and idiopathic). Major pathways enriched were including MAPK signaling pathway, the pathway of protein processing in endoplasmic reticulum, and pathway of regulatory actin cytoskeleton. Aberrant in these pathways caused disorders metabolic process and cellular malfunctions that generally contributes to cardiac dysregulation and functional relapse into cardiomyopathies.ConclusionThis study identified the key signaling pathways, functions and biological process related to cardiomyopathies and will give a light to better understand the molecular mechanism of processes of cardiomyopathies and figure out the rational clinical interference way to cure the patients. Therein, these novel signature genes may work as potential promising biomarkers for cardiomyopathy diagnosis, and will benefit for the better clinical diagnostics and outcome for patients with cardiomyopathies. 


Weighted Gene Co-expression Network Analysis Identifies Specific Modules and Hub Genes Related to Alzheimer's Disease

2020 ◽  
Author(s):  
Kang Yang ◽  
Bin Deng ◽  
Liju Xie ◽  
Dandan Bo ◽  
Jingsong Mao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Biological Significance ◽  
Mapk Signaling ◽  
Future Research ◽  
Hub Genes ◽  
Efficient System ◽  
Hub Gene ◽  
Differential Expression Genes ◽  
Gene Modules

Abstract Background: Alzheimer's disease (AD) is the most common cause of dementia. We used Weighted gene co-expression network (WGCNA) to construct a gene co-expression network to analyze AD-related genes and find biomarkers of AD. An AD RNA chip expression data was downloaded from NCBI's GEO database. The construction of the gene co-expression network was completed by the WGCNA package of R software. Functional annotation of genes was performed by gene ontology and Kyoto Encyclopedia Gene and Genomic pathway analysis.Results: We used WGCNA to construct a co-expression network of 2713 differential expression genes in 56 AD patients and 44 healthy controls, and finally identified 7 gene modules, ranging in size from 32 to 1619. Correlation analysis of gene modules and disease showed that the turquoise module and the brown module were significantly associated with age. The turquoise module has obvious biological significance. The hub gene in this module is ATL1, which is involved in synaptic signaling and MAPK signaling pathways. The hub gene in the Brown module is CIRBP, which may be related to the regeneration of synapses.Conclusions: This study used WGCNA, an efficient system biology algorithm, to analyze the hub genes related to AD for the first time and provide a new direction for the future research of AD.

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