scholarly journals Metabolite and Transcriptome Profiling Analysis Revealed That Melatonin Positively Regulates Floral Scent Production in Hedychium coronarium

2021 ◽  
Vol 12 ◽  
Author(s):  
Farhat Abbas ◽  
Yiwei Zhou ◽  
Jingjuan He ◽  
Yanguo Ke ◽  
Wang Qin ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Floral Scent ◽  
Differentially Expressed ◽  
Floral Volatiles ◽  
Full Bloom ◽  
Melatonin Treatment ◽  
Flower Visitor ◽  
Hedychium Coronarium ◽  
Volatile Organic

Melatonin is a pleiotropic molecule that regulates a variety of developmental processes. Floral volatiles are important features of flowers that facilitate flower–visitor interactions by attracting pollinators, structure flower–visitor communities, and play defensive roles against plant and flower antagonists. Aside from their role in plants, floral volatiles are an essential ingredient in cosmetics, perfumes, pharmaceuticals, and flavorings. Herein, integrated metabolomic and transcriptomic approaches were carried out to analyze the changes triggered by melatonin exposure during the Hedychium coronarium flower development stages. Quantitative analysis of the volatiles of H. coronarium flowers revealed that volatile organic compound emission was significantly enhanced after melatonin exposure during the half bloom (HS), full bloom (FB) and fade stage (FS). Under the melatonin treatment, the emission of volatile contents was highest during the full bloom stage of the flower. Variable importance in projection (VIP) analysis and partial least-squares discriminant analysis (PLS-DA) identified 15 volatile compounds with VIP > 1 that were prominently altered by the melatonin treatments. According to the transcriptome sequencing data of the HS, FB, and FS of the flowers, 1,372, 1,510, and 1,488 differentially expressed genes were identified between CK-HS and 100MT-HS, CK-FB and 100MT-FB, and CK-FS and 100MT-FS, respectively. Among the significant differentially expressed genes (DEGs), 76 were significantly upregulated and directly involved in the floral scent biosynthesis process. In addition, certain volatile organic compounds were substantially linked with various DEGs after combining the metabolome and transcriptome datasets. Moreover, some transcription factors, such as MYB and bHLH, were also significantly upregulated in the comparison, which might be related to the floral aroma mechanism. Our results suggested that melatonin increased floral aroma production in H. coronarium flowers by modifying the expression level of genes involved in the floral scent biosynthesis pathway. These findings serve as a foundation for future research into the molecular mechanisms underlying the dynamic changes in volatile contents induced by melatonin treatment in H. coronarium.

Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma

2020 ◽  
Vol 23 (6) ◽  
pp. 546-553
Author(s):  
Hongyuan Cui ◽  
Mingwei Zhu ◽  
Junhua Zhang ◽  
Wenqin Li ◽  
Lihui Zou ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Cellular Proliferation ◽  
Mrna Level ◽  
Thyroid Tissue ◽  
Differentially Expressed ◽  
Thyroid Tumors ◽  
Papillary Thyroid

Objective: Next-generation sequencing (NGS) was performed to identify genes that were differentially expressed between normal thyroid tissue and papillary thyroid carcinoma (PTC). Materials & Methods: Six candidate genes were selected and further confirmed with quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry in samples from 24 fresh thyroid tumors and adjacent normal tissues. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to investigate signal transduction pathways of the differentially expressed genes. Results: In total, 1690 genes were differentially expressed between samples from patients with PTC and the adjacent normal tissue. Among these, SFRP4, ZNF90, and DCN were the top three upregulated genes, whereas KIRREL3, TRIM36, and GABBR2 were downregulated with the smallest p values. Several pathways were associated with the differentially expressed genes and involved in cellular proliferation, cell migration, and endocrine system tumor progression, which may contribute to the pathogenesis of PTC. Upregulation of SFRP4, ZNF90, and DCN at the mRNA level was further validated with RT-PCR, and DCN expression was further confirmed with immunostaining of PTC samples. Conclusion: These results provide new insights into the molecular mechanisms of PTC. Identification of differentially expressed genes should not only improve the tumor signature for thyroid tumors as a diagnostic biomarker but also reveal potential targets for thyroid tumor treatment.

scholarly journals Identification of Differentially Expressed Genes in Porcine Ovaries at Proestrus and Estrus Stages Using RNA-Seq Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Songbai Yang ◽  
Xiaolong Zhou ◽  
Yue Pei ◽  
Han Wang ◽  
Ke He ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Hormone Secretion ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
The Novel ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Single Organism

Estrus is an important factor for the fecundity of sows, and it is involved in ovulation and hormone secretion in ovaries. To better understand the molecular mechanisms of porcine estrus, the expression patterns of ovarian mRNA at proestrus and estrus stages were analyzed using RNA sequencing technology. A total of 2,167 differentially expressed genes (DEGs) were identified (P≤0.05, log2  Ratio≥1), of which 784 were upregulated and 1,383 were downregulated in the estrus compared with the proestrus group. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in the cellular process, single-organism process, cell and cell part, and binding and metabolic process. In addition, a pathway analysis showed that these DEGs were significantly enriched in 33 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cell adhesion molecules, ECM-receptor interaction, and cytokine-cytokine receptor interaction. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) confirmed the differential expression of 10 selected DEGs. Many of the novel candidate genes identified in this study will be valuable for understanding the molecular mechanisms of the sow estrous cycle.

scholarly journals Comparative Transcriptomic Analysis of Embryo Implantation in Mice and Rats

2018 ◽  
Vol 50 (2) ◽  
pp. 668-678 ◽  
Author(s):  
Wen-Qian Zhang ◽  
Miao Zhao ◽  
Ming-Yu Huang ◽  
Ji-Long Liu
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Embryo Implantation ◽  
Differentially Expressed ◽  
Rat Uterus ◽  
Mouse Uterus ◽  
Pathway Network ◽  
Implantation Sites ◽  
High Selection ◽  
Transcriptomic Changes

Background/Aims: Embryo implantation is an essential process for eutherian pregnancy, but this process varies across eutherians. The genomic mechanisms that led to the emergence and diversification of embryo implantation are largely unknown. Methods: In this study, we analyzed transcriptomic changes during embryo implantation in mice and rats by using RNA-seq. Bioinformatics and evolutionary analyses were performed to characterize implantation-associated genes in these two species. Results: We identified a total of 518 differentially expressed genes in mouse uterus during implantation, of which 253 genes were up-regulated and 265 genes were down-regulated at the implantation sites compared with the inter-implantation sites. In rat uterus, there were 374 differentially expressed genes, of which 284 genes were up-regulated and 90 genes were down-regulated. A cross-species comparison revealed that 92 up-regulated genes and 20 down-regulated genes were shared. The differences and similarities between mice and rats were investigated further at the gene ontology, pathway, network, and causal transcription factor levels. Additionally, we found that embryo implantation might have evolved through the recruitment of ancient genes into uterine expression. The evolutionary rates of the differentially expressed genes in mouse and rat uterus were significantly lower than those of the non-changed genes, indicating that implantation-related genes are evolutionary conserved due to high selection pressure. Conclusion: Our study provides insights into the molecular mechanisms involved in the evolution of embryo implantation.

scholarly journals Bioinformatics analysis of differentially expressed genes and identification of an miRNA–mRNA network associated with entorhinal cortex and hippocampus in Alzheimer’s disease

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Haoming Li ◽  
Linqing Zou ◽  
Jinhong Shi ◽  
Xiao Han
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Differentially Expressed Genes ◽  
Entorhinal Cortex ◽  
Molecular Mechanisms ◽  
Kegg Pathway ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Alzheimer’s disease (AD) is a fatal neurodegenerative disorder, and the lesions originate in the entorhinal cortex (EC) and hippocampus (HIP) at the early stage of AD progression. Gaining insight into the molecular mechanisms underlying AD is critical for the diagnosis and treatment of this disorder. Recent discoveries have uncovered the essential roles of microRNAs (miRNAs) in aging and have identified the potential of miRNAs serving as biomarkers in AD diagnosis. Methods We sought to apply bioinformatics tools to investigate microarray profiles and characterize differentially expressed genes (DEGs) in both EC and HIP and identify specific candidate genes and pathways that might be implicated in AD for further analysis. Furthermore, we considered that DEGs might be dysregulated by miRNAs. Therefore, we investigated patients with AD and healthy controls by studying the gene profiling of their brain and blood samples to identify AD-related DEGs, differentially expressed miRNAs (DEmiRNAs), along with gene ontology (GO) analysis, KEGG pathway analysis, and construction of an AD-specific miRNA–mRNA interaction network. Results Our analysis identified 10 key hub genes in the EC and HIP of patients with AD, and these hub genes were focused on energy metabolism, suggesting that metabolic dyshomeostasis contributed to the progression of the early AD pathology. Moreover, after the construction of an miRNA–mRNA network, we identified 9 blood-related DEmiRNAs, which regulated 10 target genes in the KEGG pathway. Conclusions Our findings indicated these DEmiRNAs having the potential to act as diagnostic biomarkers at an early stage of AD.

scholarly journals Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8096 ◽  
Author(s):  
Haiping Zhang ◽  
Jian Zou ◽  
Ying Yin ◽  
Bo Zhang ◽  
Yaling Hu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Clinical Stage ◽  
Stage I ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

scholarly journals Prognostic Value and Regulatory Network of Immune-Related Genes in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Xiang Zhou ◽  
Keying Zhang ◽  
Fa Yang ◽  
Chao Xu ◽  
Jianhua Jiao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Risk Model ◽  
Cox Regression ◽  
Wilcoxon Test ◽  
Differentially Expressed ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background: Hepatocellular carcinoma (HCC) is a disease with higher morbidity, mortality, and poor prognosis in the whole world. Understanding the crosslink between HCC and the immune system is essential for people to uncover a few potential and valuable therapeutic strategies. This study aimed to reveal the correlation between HCC and immune-related genes and establish a clinical evaluation model. Methods: We had analyzed the clinical information consisted of 373 HCC and 49 normal samples from the cancer genome atlas (TCGA). The differentially expressed genes (DEGs) were selected by the Wilcoxon test and the immune-related differentially expressed genes (IRDEGs) in DEGs were identified by matching DEGs with immune-related genes downloaded from the ImmPort database. Furthermore, the univariate Cox regression analysis and multivariate Cox regression analysis were performed to construct a prognostic risk model. Then, twenty-two types of tumor immune-infiltrating cells (TIICs) were downloaded from Tumor Immune Estimation Resource (TIMER) and were used to construct the correlational graphs between the TIICs and risk score by the CIBERSORT. Subsequently, the transcription factors (TFs) were gained in the Cistrome website and the differentially expressed TFs (DETFs) were achieved. Finally, the KEGG pathway analysis and GO analysis were performed to further understand the molecular mechanisms between DETFs and PDIRGs.Results: In our study, 5839 DEGs, 326 IRDEGs, and 31 prognosis-related IRDEGs (PIRDEGs) were identified. And 8 optimal PIRDEGs were employed to construct a prognostic risk model by multivariate Cox regression analysis. The correlation between risk genes and clinical characterizations and TIICs has verified that the prognostic model was effective in predicting the prognosis of HCC patients. Finally, several important immune-related pathways and molecular functions of the eight PIRDEGs were significantly enriched and there was a distinct association between the risk IRDEGs and TFs. Conclusion: The prognostic risk model showed a more valuable predicting role for HCC patients, and produced many novel therapeutic targets and strategies for HCC.

A Comprehensive Data Analysis of Differentially Regulated Genes in Melanoma

2020 ◽  
Author(s):  
Yanjie Han ◽  
Xinxin Li ◽  
Jiliang Yan ◽  
Chunyan Ma ◽  
Xin Wang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Growth Factor Receptor ◽  
Principal Component ◽  
Distant Metastases ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background: Melanoma is the most deadly tumor in skin tumors and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma.Methods: We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553 and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples.Results: Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL) and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL and EGFR were identified in the TCGA database and melanoma tissues.Conclusions: The results suggested that FLG, DSG1, DSG3, IVL and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma.

scholarly journals Transcriptome profiling of peanut (Arachis hypogaea) gynophores in gravitropic response

2013 ◽  
Vol 40 (12) ◽  
pp. 1249 ◽  
Author(s):  
Hai-fen Li ◽  
Xiao-Ping Chen ◽  
Fang-he Zhu ◽  
Hai-Yan Liu ◽  
Yan-Bin Hong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Arachis Hypogaea ◽  
Molecular Mechanisms ◽  
Carbon Fixation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pentose Phosphate ◽  
Differentially Expressed ◽  
Pcr Analysis

Peanut (Arachis hypogaea L.) produces flowers aerially, but the fruit develops underground. This process is mediated by the gynophore, which always grows vertically downwards. The genetic basis underlying gravitropic bending of gynophores is not well understood. To identify genes related to gynophore gravitropism, gene expression profiles of gynophores cultured in vitro with tip pointing upward (gravitropic stimulation sample) and downward (control) at both 6 and 12 h were compared through a high-density peanut microarray. After gravitropic stimulation, there were 174 differentially expressed genes, including 91 upregulated and 83 downregulated genes at 6 h, and 491 differentially expressed genes including 129 upregulated and 362 downregulated genes at 12 h. The differentially expressed genes identified were assigned to 24 functional categories. Twenty pathways including carbon fixation, aminoacyl-tRNA biosynthesis, pentose phosphate pathway, starch and sucrose metabolism were identified. The quantitative real-time PCR analysis was performed for validation of microarray results. Our study paves the way to better understand the molecular mechanisms underlying the peanut gynophore gravitropism.

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