scholarly journals Petal Color-Transition in Lonicera japonica is Mainly Associated with Increase of the Carotenoid Content and Carotenoid Biosynthetic Gene Expression

2020 ◽  
Author(s):  
Yan Xia ◽  
Weiwei Chen ◽  
Weibo Xiang ◽  
Dan Wang ◽  
Baogui Xue ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Lonicera Japonica ◽  
Carotenoid Content ◽  
Signal Pathways ◽  
Carotenoid Cleavage Dioxygenase ◽  
Endogenous Hormones ◽  
Metabolome Analysis ◽  
Color Transition ◽  
Flower Petal

Abstract Background: Plants have remarkable diversity in petal color through the biosynthesis and accumulation of various pigments. To better understand the mechanisms regulating the petal pigmentation, we used multiple approaches to investigate the changes of carotenoids, gene expression dynamics and endogenous hormones in Lonicera japonica during petal color transitions, i.e. green bud petal (GB_Pe), white flower petal (WF_Pe) and yellow flower petal (YF_Pe). Results: Metabolome analysis showed that YF_Pe had a much higher content of carotenoids than white petals, with violaxanthin identified as the major carotenoid compound in YF_Pe. Comparative transcriptome analysis revealed that the key differentially expressed genes (DEGs) involved in carotenoid biosynthesis, such as phytoene synthase, phytoene desaturase and ζ-carotene desaturase, were significantly up-regulated in YF_Pe. However, expression levels of the carotenoid degradation-related genes, including abscisic-aldehyde oxidase 3 and carotenoid cleavage dioxygenase 4, were significantly down-regulated in YF_Pe. The results indicated that upregulated carotenoids concentrations and carotenoids biosynthesis-related genes promote the color transition. Furthermore, enrichment analysis of DEGs was mainly associated with the metabolic pathways of hormone signal transduction during petal color transitions. The DEGs were mainly involved in the auxin, cytokinin, gibberellin (GA), brassinosteroid (BR), jasmonic acid and abscisic acid (ABA) signal pathways. Accordingly, analyses of changes in indoleacetic acid, zeatin riboside, GA, BR, methyl jasmonate and ABA levels indicated that the color transitions are regulated by endogenous hormones. Conclusion: Our results provide new insight into the regulatory mechanisms underlying the petal color transitions during flower development process in L. japonica.

scholarly journals Integrated metabolic profiling and transcriptome analysis of pigment accumulation in Lonicera japonica flower petals during colour-transition

2020 ◽  
Author(s):  
Yan Xia ◽  
Weiwei Chen ◽  
Weibo Xiang ◽  
Dan Wang ◽  
Baogui Xue ◽  
...  
Keyword(s):  
Transcriptome Analysis ◽  
Carotenoid Biosynthesis ◽  
Zeatin Riboside ◽  
Lonicera Japonica ◽  
Endogenous Hormones ◽  
Metabolome Analysis ◽  
Yellow Colour ◽  
Petal Colour ◽  
Gene Expression Dynamics ◽  
Pigment Accumulation

Abstract Background: Plants have remarkable diversity in petal colour through the biosynthesis and accumulation of various pigments. To better understand the mechanisms regulating petal pigmentation in Lonicera japonica, we used multiple approaches to investigate the changes in carotenoids, anthocyanins, endogenous hormones and gene expression dynamics during petal colour transitions, i.e., green bud petals (GB_Pe), white flower petals (WF_Pe) and yellow flower petals (YF_Pe). Results: Metabolome analysis showed that YF_Pe contained a much higher content of carotenoids than GB_Pe and WF_Pe, with α-carotene, zeaxanthin, violaxanthin and γ-carotene identified as the major carotenoid compounds in YF_Pe. Comparative transcriptome analysis revealed that the key differentially expressed genes (DEGs) involved in carotenoid biosynthesis, such as phytoene synthase, phytoene desaturase and ζ-carotene desaturase, were significantly upregulated in YF_Pe. The results indicated that upregulated carotenoid concentrations and carotenoid biosynthesis-related genes predominantly promote colour transition. Meanwhile, two anthocyanins (pelargonidin and cyanidin) were significantly increased in YF_Pe, and the expression level of an anthocyanidin synthase gene was significantly upregulated, suggesting that anthocyanins may contribute to vivid yellow colour in YF_Pe. Furthermore, analyses of changes in indoleacetic acid, zeatin riboside, gibberellin (GA), brassinosteroid (BR), methyl jasmonate and abscisic acid (ABA) levels indicated that colour transitions are regulated by endogenous hormones. The DEGs involved in the auxin, cytokinin, GA, BR, jasmonic acid and ABA signalling pathways were enriched and associated with petal colour transitions.Conclusion: Our results provide global insight into the pigment accumulation and the regulatory mechanisms underlying petal colour transitions during the flower development process in L. japonica.

scholarly journals Integrated metabolic profiling and transcriptome analysis of pigment accumulation in Lonicera japonica flower petals during colour-transition

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Xia ◽  
Weiwei Chen ◽  
Weibo Xiang ◽  
Dan Wang ◽  
Baogui Xue ◽  
...  
Keyword(s):  
Transcriptome Analysis ◽  
Carotenoid Biosynthesis ◽  
Zeatin Riboside ◽  
Lonicera Japonica ◽  
Endogenous Hormones ◽  
Metabolome Analysis ◽  
Yellow Colour ◽  
Petal Colour ◽  
Gene Expression Dynamics ◽  
Pigment Accumulation

Abstract Background Plants have remarkable diversity in petal colour through the biosynthesis and accumulation of various pigments. To better understand the mechanisms regulating petal pigmentation in Lonicera japonica, we used multiple approaches to investigate the changes in carotenoids, anthocyanins, endogenous hormones and gene expression dynamics during petal colour transitions, i.e., green bud petals (GB_Pe), white flower petals (WF_Pe) and yellow flower petals (YF_Pe). Results Metabolome analysis showed that YF_Pe contained a much higher content of carotenoids than GB_Pe and WF_Pe, with α-carotene, zeaxanthin, violaxanthin and γ-carotene identified as the major carotenoid compounds in YF_Pe. Comparative transcriptome analysis revealed that the key differentially expressed genes (DEGs) involved in carotenoid biosynthesis, such as phytoene synthase, phytoene desaturase and ζ-carotene desaturase, were significantly upregulated in YF_Pe. The results indicated that upregulated carotenoid concentrations and carotenoid biosynthesis-related genes predominantly promote colour transition. Meanwhile, two anthocyanins (pelargonidin and cyanidin) were significantly increased in YF_Pe, and the expression level of an anthocyanidin synthase gene was significantly upregulated, suggesting that anthocyanins may contribute to vivid yellow colour in YF_Pe. Furthermore, analyses of changes in indoleacetic acid, zeatin riboside, gibberellic acid, brassinosteroid (BR), methyl jasmonate and abscisic acid (ABA) levels indicated that colour transitions are regulated by endogenous hormones. The DEGs involved in the auxin, cytokinin, gibberellin, BR, jasmonic acid and ABA signalling pathways were enriched and associated with petal colour transitions. Conclusion Our results provide global insight into the pigment accumulation and the regulatory mechanisms underlying petal colour transitions during the flower development process in L. japonica.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

GLIOBLASTOMA MULTIFORME: PATHOGENESIS AND MOLECULAR MARKERS

2017 ◽  
Vol 63 (5) ◽  
pp. 695-702
Author(s):  
Oleg Kit ◽  
Dmitriy Vodolazhskiy ◽  
Yelena Frantsiyants ◽  
Svetlana Panina ◽  
E. Rastorguev ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Tumor ◽  
Molecular Markers ◽  
Glioblastoma Multiforme ◽  
Somatic Mutations ◽  
Web Of Science ◽  
Molecular Subtypes ◽  
Regulation Of Gene Expression ◽  
Signal Pathways ◽  
Poorly Differentiated

Glioblastoma multiforme (GBM) is the most common and invasive poorly differentiated brain tumor with nearly 100 % rate of recurrence and unfavorable prognosis. The aim of the present review is to analyze recent studies and experimental results (Scopus, Web of Science, PubMed) concerning somatic mutations in glioblastoma, aberrant regulation of gene expression of signal pathways including EGFR, TGFß, etc. and markers for GBM progression. Particularly the molecular subtypes of glioblastoma and NGS results are considered in this review.

scholarly journals Identification of potential biomarkers for abdominal pain in IBS patients by bioinformatics approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhongyuan Lin ◽  
Yimin Wang ◽  
Shiqing Lin ◽  
Decheng Liu ◽  
Guohui Mo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Irritable Bowel Syndrome ◽  
Abdominal Pain ◽  
Gastrointestinal Disease ◽  
Rectal Mucosa ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Irritable Bowel ◽  
Potential Biomarkers

Abstract Background Irritable bowel syndrome (IBS) is the most common functional gastrointestinal disease characterized by chronic abdominal discomfort and pain. The mechanisms of abdominal pain, as a relevant symptom, in IBS are still unclear. We aimed to explore the key genes and neurobiological changes specially involved in abdominal pain in IBS. Methods Gene expression data (GSE36701) was downloaded from Gene Expression Omnibus database. Fifty-three rectal mucosa samples from 27 irritable bowel syndrome with diarrhea (IBS-D) patients and 40 samples from 21 healthy volunteers as controls were included. Differentially expressed genes (DEGs) between two groups were identified using the GEO2R online tool. Functional enrichment analysis of DEGs was performed on the DAVID database. Then a protein–protein interaction network was constructed and visualized using STRING database and Cytoscape. Results The microarray analysis demonstrated a subset of genes (CCKBR, CCL13, ACPP, BDKRB2, GRPR, SLC1A2, NPFF, P2RX4, TRPA1, CCKBR, TLX2, MRGPRX3, PAX2, CXCR1) specially involved in pain transmission. Among these genes, we identified GRPR, NPFF and TRPA1 genes as potential biomarkers for irritating abdominal pain of IBS patients. Conclusions Overexpression of certain pain-related genes (GRPR, NPFF and TRPA1) may contribute to chronic visceral hypersensitivity, therefore be partly responsible for recurrent abdominal pain or discomfort in IBS patients. Several synapses modification and biological process of psychological distress may be risk factors of IBS.

scholarly journals Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1821
Author(s):  
Ujjwal Mukund Mahajan ◽  
Ahmed Alnatsha ◽  
Qi Li ◽  
Bettina Oehrle ◽  
Frank-Ulrich Weiss ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Enrichment Analysis ◽  
Response Prediction ◽  
Ductal Adenocarcinoma ◽  
Pathway Enrichment Analysis ◽  
Metabolome Analysis ◽  
Dismal Prognosis ◽  
Chemotherapeutic Response ◽  
Plasma Metabolome ◽  
Metabolome Profiling

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

scholarly journals Study on potential differentially expressed genes in stroke by bioinformatics analysis

2021 ◽  
Author(s):  
Xitong Yang ◽  
Pengyu Wang ◽  
Shanquan Yan ◽  
Guangming Wang
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Normal Control ◽  
Enrichment Analysis ◽  
Normal Control Group ◽  
Control Group ◽  
Ppi Network ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Key Genes

AbstractStroke is a sudden cerebrovascular circulatory disorder with high morbidity, disability, mortality, and recurrence rate, but its pathogenesis and key genes are still unclear. In this study, bioinformatics was used to deeply analyze the pathogenesis of stroke and related key genes, so as to study the potential pathogenesis of stroke and provide guidance for clinical treatment. Gene Expression profiles of GSE58294 and GSE16561 were obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IS and normal control group. The different expression genes (DEGs) between IS and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), the function and pathway enrichment analysis of DEGS were performed. Then, a protein–protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. A total of 85 DEGs were screened out in this study, including 65 upward genes and 20 downward genes. In addition, 3 KEGG pathways, cytokine − cytokine receptor interaction, hematopoietic cell lineage, B cell receptor signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the PPI network and CytoHubba, 10 hub genes including CEACAM8, CD19, MMP9, ARG1, CKAP4, CCR7, MGAM, CD79A, CD79B, and CLEC4D were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including hsa-mir-146a-5p, hsa-mir-7-5p, hsa-mir-335-5p, and hsa-mir-27a- 3p, were predicted as possibly the key miRNAs. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of ischemic stroke, and provide a new strategy for clinical therapy.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals Identification of ferroptosis genes in immune infiltration and prognosis in thyroid papillary carcinoma using network analysis

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruoting Lin ◽  
Conor E. Fogarty ◽  
Bowei Ma ◽  
Hejie Li ◽  
Guoying Ni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Carcinoma ◽  
Risk Score ◽  
Immune Cells ◽  
Survival Curve ◽  
Enrichment Analysis ◽  
Papillary Thyroid ◽  
Hub Genes ◽  
Cox Analysis ◽  
Cluster 2

Abstract Background Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. While many patients survive, a portion of PTC cases display high aggressiveness and even develop into refractory differentiated thyroid carcinoma. This may be alleviated by developing a novel model to predict the risk of recurrence. Ferroptosis is an iron-dependent form of regulated cell death (RCD) driven by lethal accumulation of lipid peroxides, is regulated by a set of genes and shows a variety of metabolic changes. To elucidate whether ferroptosis occurs in PTC, we analyse the gene expression profiles of the disease and established a new model for the correlation. Methods The thyroid carcinoma (THCA) datasets were downloaded from The Cancer Genome Atlas (TCGA), UCSC Xena and MisgDB, and included 502 tumour samples and 56 normal samples. A total of 60 ferroptosis related genes were summarised from MisgDB database. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) were used to analyse pathways potentially involving PTC subtypes. Single sample GSEA (ssGSEA) algorithm was used to analyse the proportion of 28 types of immune cells in the tumour immune infiltration microenvironment in THCA and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells. Spearman correlation analysis was performed on the ferroptosis gene expression and the correlation between immune infiltrating cells proportion. We established the WGCNA to identify genes modules that are highly correlated with the microenvironment of immune invasion. DEseq2 algorithm was further used for differential analysis of sequencing data to analyse the functions and pathways potentially involving hub genes. GO and KEGG enrichment analysis was performed using Clusterprofiler to explore the clinical efficacy of hub genes. Univariate Cox analysis was performed for hub genes combined with clinical prognostic data, and the results was included for lasso regression and constructed the risk regression model. ROC curve and survival curve were used for evaluating the model. Univariate Cox analysis and multivariate Cox analysis were performed in combination with the clinical data of THCA and the risk score value, the clinical efficacy of the model was further evaluated. Results We identify two subtypes in PTC based on the expression of ferroptosis related genes, with the proportion of cluster 1 significantly higher than cluster 2 in ferroptosis signature genes that are positively associated. The mutations of Braf and Nras are detected as the major mutations of cluster 1 and 2, respectively. Subsequent analyses of TME immune cells infiltration indicated cluster 1 is remarkably richer than cluster 2. The risk score of THCA is in good performance evaluated by ROC curve and survival curve, in conjunction with univariate Cox analysis and multivariate Cox analysis results based on the clinical data shows that the risk score of the proposed model could be used as an independent prognostic indicator to predict the prognosis of patients with papillary thyroid cancer. Conclusions Our study finds seven crucial genes, including Ac008063.2, Apoe, Bcl3, Acap3, Alox5ap, Atxn2l and B2m, and regulation of apoptosis by parathyroid hormone-related proteins significantly associated with ferroptosis and immune cells in PTC, and we construct the risk score model which can be used as an independent prognostic index to predict the prognosis of patients with PTC.

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