Comparative transcriptomics and WGCNA reveal candidate genes involved in petaloid stamens in <i>Paeonia lactiflora</i>

Fan, Yongming; Yanyi, Zheng; Silva, Jaime A. Teixeira da; Yu, Xiaonan

doi:10.1080/14620316.2021.1892535

Cited by 16 publications

(8 citation statements)

References 65 publications

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“…Admittedly, our approach also has a certain limitation. Due to factors such as experimental cost and social ethics, the number of patient samples experienced in this study is very limited 39 . In addition, our research lacks the validation of animal or cell experiments.…”

Section: Discussionmentioning

confidence: 99%

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking

Huo

Liu³

2021

Sci Rep

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Yixinyin, the traditional Chinese medicine, has the effects of replenishing righteous qi, and promoting blood circulation to eliminate blood stagnation. It is often used to treat patients with acute myocardial infarction (MI). The purpose of our study is to explore the key components and targets of Yixinyin in the treatment of MI. In this study, we analyzed gene expression data and clinical information from 248 samples of MI patients with the GSE34198, GSE29111 and GSE66360 data sets. By constructing a weighted gene co-expression network, gene modules related to myocardial infarction are obtained. These modules can be mapped in Yixinyin PPI network. By integrating differential genes of healthy/MI and unstable angina/MI, key targets of Yixinyin for the treatment of myocardial infarction were screened. We validated the key objectives with external data sets. GSEA analysis is used to identify the biological processes involved in key targets. Through molecular docking screening, active components that can combine with key targets in Yixinyin were obtained. In the treatment of myocardial infarction, we have obtained key targets of Yixinyin, which are ALDH2, C5AR1, FOS, IL1B, TLR2, TXNRD1. External data sets prove that they behave differently in the healthy and MI (P < 0.05). GSEA enrichment analysis revealed that they are mainly involved in pathways associated with myocardial infarction, such as viral myocarditis, VEGF signaling pathway and type I diabetes mellitus. The docking results showed that the components that can be combined with key targets in YixinYin are Supraene, Prostaglandin B1, isomucronulatol-7,2′-di-O-glucosiole, angusifolin B, Linolenic acid ethyl ester, and Mandenol. For that matter, they may be active ingredients of Yixinyin in treating MI. These findings provide a basis for the preliminary research of myocardial infarction therapy in traditional Chinese medicine and provide ideas for the design of related drugs.

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Section: Discussionmentioning

confidence: 99%

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking

Huo

Liu³

2021

Sci Rep

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“…In recent years, transcriptome sequencing has become an efficient, fast, and low-cost high-throughput sequencing technology that is widely used in numerous studies [ 18 , 19 , 20 , 21 , 42 ]. RNA-Seq technology was used to identify and characterize the expression of a large number of genes, and algorithms were combined to develop genome-wide coexpression networks to provide new genes for molecular breeding.…”

Section: Discussionmentioning

confidence: 99%

“…RNA-seq technology has been widely used in the study of various biotic or abiotic stresses. Based on microarray or RNA-seq expression data, weighted gene co-expression network analysis (WGCNA) constructs a scale-free topological overlap matrix to describe relationships between genes and then divides genes with similar expression patterns into groups in a gene expression module [ 19 ]. WGCNA is used to study the biological correlation between co-expressed gene modules relate to target traits and to explore core genes in gene co-expression networks.…”

Section: Introductionmentioning

confidence: 99%

Mining Candidate Genes Related to Heavy Metals in Mature Melon (Cucumis melo L.) Peel and Pulp Using WGCNA

Shen

Tao

et al. 2022

Genes

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The content of metal ions in fruits is inseparable from plant intake of trace elements and health effects in the human body. To understand metal ion content in the fruit and pericarp of melon (Cucumis melo L.) and the candidate genes responsible for controlling this process, we analyzed the metal ion content in distinct parts of melon fruit and pericarp and performed RNA-seq. The results showed that the content of metal ions in melon fruit tissue was significantly higher than that in the pericarp. Based on transcriptome expression profiling, we found that the fruit and pericarp contained elevated levels of DEGs. GO functional annotations included cell surface receptor signaling, signal transduction, organic substance metabolism, carbohydrate derivative binding, and hormone-mediated signaling pathways. KEGG pathways included pectate lyase, pentose and glucuronate interconversions, H+-transporting ATPase, oxidative phosphorylation, plant hormone signal transduction, and MAPK signaling pathways. We also analyzed the expression patterns of genes and transcription factors involved in hormone biosynthesis and signal transduction. Using weighted gene co-expression network analysis (WGCNA), a co-expression network was constructed to identify a specific module that was significantly correlated with the content of metal ions in melon, after which the gene expression in the module was measured. Connectivity and qRT–PCR identified five candidate melon genes, LOC103501427, LOC103501539, LOC103503694, LOC103504124, and LOC107990281, associated with metal ion content. This study provides a theoretical basis for further understanding the molecular mechanism of heavy metal ion content in melon fruit and peel and provides new genetic resources for the study of heavy metal ion content in plant tissues.

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“…The TOM similarity was used to derive two useful metrics of weights and distances. The dynamic tree-cut algorithm was employed to pinpoint the gene coexpression module with minModuleSize of 50 and mergeCutHeight of 0.01 [ 12 ]. Module eigengene (ME) is an important component for each gene module that represents the overall level of gene expression.…”

Section: Methodsmentioning

confidence: 99%

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

Zhou

Zhang

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. This study is aimed at screening out effective active compounds of Qizhen capsule (QZC) and exploring the underlying mechanisms against gastric cancer (GACA) by combining both bioinformatic analysis and experimental approaches. Weighted gene coexpression network analysis (WGCNA), network pharmacology, molecular docking simulation, survival analysis, and data-based differential gene and protein expression analysis were employed to predict QZC’s potential targets and explore the underlying mechanisms. Subsequently, multiple experiments, including cell viability, apoptosis, and protein expression analyses, were conducted to validate the bioinformatics-predicted therapeutic targets. The results indicated that luteolin, rutin, quercetin, and kaempferol were vital active compounds, and TP53, MAPK1, and AKT1 were key targets. Molecular docking simulation showed that the four abovementioned active compounds had high binding affinities to the three main targets. Enrichment analysis showed that vital active compounds exerted therapeutic effects on GACA through regulating the TP53 pathway, MAPK pathway, and PI3K/AKT pathway. Furthermore, data-based gene expression analysis revealed that TP53 and JUN genes were not only differentially expressed between normal and GACA tissues but also correlated with clinical stages. In parallel, in vitro experimental results suggested that QZC exerted therapeutic effects on GACA by decreasing IC50 values, downregulating AKT expression, upregulating TP53 and MAPK expression, and increasing apoptosis of SGC-7901 cells. This study highlights the potential candidate biomarkers, therapeutic targets, and basic mechanisms of QZC in treating GACA, providing a foundation for new drug development, target mining, and related animal studies in GACA.

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Comparative transcriptomics and WGCNA reveal candidate genes involved in petaloid stamens in Paeonia lactiflora

Cited by 16 publications

References 65 publications

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking

Exploring the mechanism of Yixinyin for myocardial infarction by weighted co-expression network and molecular docking

Mining Candidate Genes Related to Heavy Metals in Mature Melon (Cucumis melo L.) Peel and Pulp Using WGCNA

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

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