scholarly journals Gene co-expression network analysis reveals key pathways and hub genes in Chinese cabbage (Brassica rapa L.) during vernalization

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yun Dai ◽  
Xiao Sun ◽  
Chenggang Wang ◽  
Fei Li ◽  
Shifan Zhang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Brassica Rapa ◽  
Leaf Senescence ◽  
Chinese Cabbage ◽  
Gene Networks ◽  
Gene Annotation ◽  
Function Analysis ◽  
Hub Genes ◽  
Comprehensive Overview ◽  
Bolting And Flowering

Abstract Background Vernalization is a type of low temperature stress used to promote rapid bolting and flowering in plants. Although rapid bolting and flowering promote the reproduction of Chinese cabbages (Brassica rapa L. ssp. pekinensis), this process causes their commercial value to decline. Clarifying the mechanisms of vernalization is essential for its further application. We performed RNA sequencing of gradient-vernalization in order to explore the reasons for the different bolting process of two Chinese cabbage accessions during vernalization. Results There was considerable variation in gene expression between different-bolting Chinese cabbage accessions during vernalization. Comparative transcriptome analysis and weighted gene co-expression network analysis (WGCNA) were performed for different-bolting Chinese cabbage during different vernalization periods. The biological function analysis and hub gene annotation of highly relevant modules revealed that shoot system morphogenesis and polysaccharide and sugar metabolism caused early-bolting ‘XBJ’ to bolt and flower faster; chitin, ABA and ethylene-activated signaling pathways were enriched in late-bolting ‘JWW’; and leaf senescence and carbohydrate metabolism enrichment were found in the two Chinese cabbage-related modules, indicating that these pathways may be related to bolting and flowering. The high connectivity of hub genes regulated vernalization, including MTHFR2, CPRD49, AAP8, endoglucanase 10, BXLs, GATLs, and WRKYs. Additionally, five genes related to flower development, BBX32 (binds to the FT promoter), SUS1 (increases FT expression), TSF (the closest homologue of FT), PAO and NAC029 (plays a role in leaf senescence), were expressed in the two Chinese cabbage accessions. Conclusion The present work provides a comprehensive overview of vernalization-related gene networks in two different-bolting Chinese cabbages during vernalization. In addition, the candidate pathways and hub genes related to vernalization identified here will serve as a reference for breeders in the regulation of Chinese cabbage production.

scholarly journals Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
Author(s):  
Aliakbar Hasankhani ◽  
Abolfazl Bahrami ◽  
Negin Sheybani ◽  
Behzad Aria ◽  
Behzad Hemati ◽  
...  
Keyword(s):  
Network Analysis ◽  
Gene Networks ◽  
Information Transfer ◽  
Molecular Mechanisms ◽  
Topological Analysis ◽  
Therapeutic Targets ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Ppi Networks ◽  
Recent Emergence

BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.MethodsRNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19’s main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Gene co-expression network analysis of the heat-responsive core transcriptome identifies hub genes in Brassica rapa

Planta ◽  
2021 ◽  
Vol 253 (5) ◽  
Author(s):  
Lixin Yue ◽  
Guoliang Li ◽  
Yun Dai ◽  
Xiao Sun ◽  
Fei Li ◽  
...  
Keyword(s):  
Network Analysis ◽  
Brassica Rapa ◽  
Hub Genes

Genome-wide identification and expression analysis of the PTP family in Chinese cabbage (Brassica rapa subsp. pekinensis)

Botany ◽  
2019 ◽  
Vol 97 (11) ◽  
pp. 599-614
Author(s):  
Mingfeng Liu ◽  
Jie Ren ◽  
Xueling Ye ◽  
Xin Jiang ◽  
Qingqing Li ◽  
...  
Keyword(s):  
Gene Family ◽  
Brassica Rapa ◽  
Gene Structure ◽  
Chinese Cabbage ◽  
Protein Function ◽  
Tandem Repeats ◽  
Function Analysis ◽  
Expression Patterns ◽  
Protein Tyrosine Phosphatases ◽  
Protein Domain

Protein tyrosine phosphatases (PTPs) are signaling enzymes that play an important role in plant growth and development. Bioinformatics was used to analyze the PTP gene family of Brassica rapa subsp. pekinensis. Forty-six BrPTP family members were identified. These families were divided into eight subfamilies according to the protein domain. The relationship between gene structure and evolution was determined by comparing gene structure with the evolutionary tree. The 46 BrPTP genes were unevenly distributed across the chromosomes, and two pairs were identified to be tandem repeats. The BrPTP domain contained eight important motifs. Motifs of the same subfamily were basically identical, whereas that of each subfamily differed. These common motifs in these subfamilies are essential for PTP protein function. Analysis of BrPTP by quantitative reverse-transcription PCR revealed tissue-specific differences in expression. Most of the BrPTP genes were expressed in the five tissues examined, but not all. Expression patterns under stress showed that most genes were involved in the stress response. Further study of the PTP gene family may reveal more of its functions in Chinese cabbage.

scholarly journals Identification of Biomarkers and Pathogenesis in Severe Asthma by Co-expression Network Analysis

2020 ◽  
Author(s):  
Zeyi Zhang ◽  
Ou Chen ◽  
Jingjing Wang
Keyword(s):  
Network Analysis ◽  
Severe Asthma ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Area Under The Curve ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Asthma Severity ◽  
Functional Enrichment ◽  
Hub Genes

Abstract BackgroundSevere asthma is a heterogeneous inflammatory disease. The rise of precise immunotherapy for severe asthmatics underlines more understanding of molecular mechanisms and biomarkers. In this study, we aim to identify underlying mechanisms and hub genes that define asthma severity.MethodsDifferentially expressed genes were screened out based on bronchial epithelial brushings from mild and severe asthmatics. Then, the weighted gene co-expression network analysis was adopted to identify gene networks and the most significant module associated with asthma severity. Meanwhile, hub genes screening and functional enrichment analysis was performed. Receiver operating characteristic was conducted to validate the hub genes.ResultsWeighted gene co-expression network analysis identified 6 modules associated with asthma severity. Three modules were positively correlated (P < 0.001) with asthma severity, containing genes upregulated in severe asthmatics. Functional enrichment analysis found genes in the highlighted module mainly enriched in neutrophil degranulation and activation, leukocyte migration and chemotaxis. Hub genes identified in the module were CXCR1, CXCR2, CCR1, CCR7, TLR2, FPR1, FCGR3B, FCGR2A, ITGAM, and PLEK. Combining these hub genes possessed a moderate ability for discriminating between severe asthmatics and mild-moderate asthmatics with an area under the curve of 0.75.ConclusionOur results identified biomarkers and potential pathogenesis of severe asthma, which provides sight into treatment targets and prognostic markers.

scholarly journals Weighted gene co-expression network analysis identified underlying hub genes and mechanisms in the occurrence and development of viral myocarditis

2020 ◽  
Vol 8 (21) ◽  
pp. 1348-1348
Author(s):  
Zetao Ma ◽  
Zhida Shen ◽  
Yingchao Gong ◽  
Jiaqi Zhou ◽  
Xiaoou Chen ◽  
...  
Keyword(s):  
Network Analysis ◽  
Viral Myocarditis ◽  
Hub Genes

scholarly journals Identification of key modules and hub genes in glioblastoma multiforme based on co‐expression network analysis

FEBS Open Bio ◽  
2021 ◽  
Author(s):  
Chun Li ◽  
Bangming Pu ◽  
Long Gu ◽  
Mingwei Zhang ◽  
Hongping Shen ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Network Analysis ◽  
Hub Genes

scholarly journals Comprehensive Analysis of the Histone Deacetylase Gene Family in Chinese Cabbage (Brassica rapa): From Evolution and Expression Pattern to Functional Analysis of BraHDA3

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 244
Author(s):  
Seung Hee Eom ◽  
Tae Kyung Hyun
Keyword(s):  
Functional Analysis ◽  
Brassica Rapa ◽  
Chinese Cabbage ◽  
Stress Responses ◽  
Histone Deacetylases ◽  
Expression Patterns ◽  
Evolutionary Relationship ◽  
Gene Families ◽  
Physiological Processes ◽  
Lysine Residues

Histone deacetylases (HDACs) are known as erasers that remove acetyl groups from lysine residues in histones. Although plant HDACs play essential roles in physiological processes, including various stress responses, our knowledge concerning HDAC gene families and their evolutionary relationship remains limited. In Brassica rapa genome, we identified 20 HDAC genes, which are divided into three major groups: RPD3/HDA1, HD2, and SIR2 families. In addition, seven pairs of segmental duplicated paralogs and one pair of tandem duplicated paralogs were identified in the B. rapa HDAC (BraHDAC) family, indicating that segmental duplication is predominant for the expansion of the BraHDAC genes. The expression patterns of paralogous gene pairs suggest a divergence in the function of BraHDACs under various stress conditions. Furthermore, we suggested that BraHDA3 (homologous of Arabidopsis HDA14) encodes the functional HDAC enzyme, which can be inhibited by Class I/II HDAC inhibitor SAHA. As a first step toward understanding the epigenetic responses to environmental stresses in Chinese cabbage, our results provide a solid foundation for functional analysis of the BraHDAC family.

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