Sex differences in body composition, fat storage, and gene expression profile inCaenorhabditis elegansin response to dietary restriction

The metabolic and health-promoting effects of dietary restriction (DR) have been extensively studied in several species. The response to DR with respect to sex is essentially unknown. To address this question, we used the model organism Caenorhabditis elegans to analyze body composition and gene expression in males and hermaphrodites in response to DR. Unexpectedly, DR increased the fat-to-fat-free mass ratio and enlarged lipid droplets in both sexes to a similar extent. These effects were linked to a downregulation of the lipase-like 5 ( lipl-5) gene in both sexes at two developmental stages. By contrast, the reductions in body size, protein content, and total RNA content in response to DR were more pronounced in hermaphrodites than in males. Functional enrichment analysis of gene expression data showed a DR-induced downregulation of several embryogenesis-associated genes concomitant with an ongoing expression of sperm-associated genes in hermaphrodites. In conclusion, DR increases fat stores in both sexes of C. elegans in the form of large and possibly lipolysis-resistant lipid droplets and markedly alters the reproductive program in hermaphrodites but not in males.

Download Full-text

Demethylation alters transcriptome profiling of buds and leaves in ‘Kyoho’ grape

BMC Plant Biology ◽

10.1186/s12870-020-02754-0 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Haoran Jia ◽

Zibo Zhang ◽

Ehsan Sadeghnezhad ◽

Qianqian Pang ◽

Shangyun Li ◽

...

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Epigenetic Modification ◽

Deep Understanding ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Glutathione Metabolism ◽

Endogenous Factors

Abstract Background Grape buds and leaves are directly associated with the physiology and metabolic activities of the plant, which is monitored by epigenetic modifications induced by environment and endogenous factors. Methylation is one of the epigenetic regulators that could be involved in DNA levels and affect gene expression in response to stimuli. Therefore, changes of gene expression profile in leaves and bud through inhibitors of DNA methylation provide a deep understanding of epigenetic effects in regulatory networks. Results In this study, we carried out a transcriptome analysis of ‘Kyoho’ buds and leaves under 5-azacytidine (5-azaC) exposure and screened a large number of differentially expressed genes (DEGs). GO and KEGG annotations showed that they are mainly involved in photosynthesis, flavonoid synthesis, glutathione metabolism, and other metabolic processes. Functional enrichment analysis also provided a holistic perspective on the transcriptome profile when 5-azaC bound to methyltransferase and induced demethylation. Enrichment analysis of transcription factors (TFs) also showed that the MYB, C2H2, and bHLH families are involved in the regulation of responsive genes under epigenetic changes. Furthermore, hormone-related genes have also undergone significant changes, especially gibberellin (GA) and abscisic acid (ABA)-related genes that responded to bud germination. We also used protein-protein interaction network to determine hub proteins in response to demethylation. Conclusions These findings provide new insights into the establishment of molecular regulatory networks according to how methylation as an epigenetic modification alters transcriptome patterns in bud and leaves of grape.

Download Full-text

Identification and Validation of a Potential Prognostic 7-lncRNA Signature for Predicting Survival in Patients with Multiple Myeloma

BioMed Research International ◽

10.1155/2020/3813546 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16 ◽

Cited By ~ 1

Author(s):

Yun Zhong ◽

Zhe Liu ◽

Dangchi Li ◽

Qinyuan Liao ◽

Jingao Li

Keyword(s):

Gene Expression ◽

Risk Score ◽

Cox Regression ◽

External Validation ◽

Survival Rates ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Test Set ◽

Cox Regression Analysis

Background. An increasing number of studies have indicated that the abnormal expression of certain long noncoding RNAs (lncRNAs) is linked to the overall survival (OS) of patients with myeloma. Methods. Gene expression data of myeloma patients were downloaded from the Gene Expression Omnibus (GEO) database (GSE4581 and GSE57317). Cox regression analysis, Kaplan-Meier, and receiver operating characteristic (ROC) analysis were performed to construct and validate the prediction model. Single sample gene set enrichment (ssGSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to predict the function of a specified lncRNA. Results. In this study, a seven-lncRNA signature was identified and used to construct a risk score system for myeloma prognosis. This system was used to stratify patients with different survival rates in the training set into high-risk and low-risk groups. Test set, the entire test set, the external validation set, and the myeloma subtype achieved the authentication of the results. In addition, functional enrichment analysis indicated that 7 prognostic lncRNAs may be involved in the tumorigenesis of myeloma through cancer-related pathways and biological processes. The results of the immune score showed that IF_I was negatively correlated with the risk score. Compared with the published gene signature, the 7-lncRNA model has a higher C-index (above 0.8). Conclusion. In summary, our data provide evidence that seven lncRNAs could be used as independent biomarkers to predict the prognosis of myeloma, which also indicated that these 7 lncRNAs may be involved in the progression of myeloma.

Download Full-text

Identification of novel potential biomarkers in hepatocarcinoma cancer; a transcriptome analysis

10.21203/rs.3.rs-154350/v3 ◽

2021 ◽

Author(s):

Mohib kakar ◽

Muhammad Mehboob ◽

Muhammad Akram ◽

Imran Iqbal ◽

Hafza Ijaz ◽

...

Keyword(s):

Gene Expression ◽

Cancer Progression ◽

Predictive Biomarkers ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Molecular Therapy ◽

Hub Genes ◽

Healthy Control

Abstract Objective The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods GEO contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting genes interacting. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. Results We identified the top 10 hub genes through Cytohubba plugin. These genes include Cell Cycle Regulatory Cyclins and Cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. Conclusion In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

Download Full-text

Identification of Novel Potential Biomarkers in Hepatocarcinoma Cancer; A Transcriptome Analysis

10.21203/rs.3.rs-154350/v1 ◽

2021 ◽

Author(s):

Mohib kakar ◽

Muhammad Mehboob ◽

Muhammad Akram ◽

Imran Iqbal ◽

Hafza Ijaz ◽

...

Keyword(s):

Gene Expression ◽

Cancer Progression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Predictive Biomarker ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Molecular Therapy ◽

Hub Genes ◽

Healthy Control

Abstract The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Gene Expression Omnibus (GEO) contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server GEO. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and functional enrichment analysis was performed to extract rational information from a set of DEGs. The protein-protein relationship networking search method was used for extracting interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. We identified the top 10 hub genes through Cytohubba plugin. These genes include cell cycle regulatory cyclins and cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarker studies that could promote selective molecular therapy for HCC.

Download Full-text

reString: an open-source Python software to perform automatic functional enrichment retrieval, results aggregation and data visualization

Scientific Reports ◽

10.1038/s41598-021-02528-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Stefano Manzini ◽

Marco Busnelli ◽

Alice Colombo ◽

Elsa Franchi ◽

Pasquale Grossano ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Statistical Tests ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Knowledge Bases ◽

Functional Enrichment ◽

Reference Database ◽

Multiple User ◽

Daunting Task

AbstractFunctional enrichment analysis is an analytical method to extract biological insights from gene expression data, popularized by the ever-growing application of high-throughput techniques. Typically, expression profiles are generated for hundreds to thousands of genes/proteins from samples belonging to two experimental groups, and after ad-hoc statistical tests, researchers are left with lists of statistically significant entities, possibly lacking any unifying biological theme. Functional enrichment tackles the problem of putting overall gene expression changes into a broader biological context, based on pre-existing knowledge bases of reference: database collections of known expression regulation, relationships and molecular interactions. STRING is among the most popular tools, providing both protein–protein interaction networks and functional enrichment analysis for any given set of identifiers. For complex experimental designs, manually retrieving, interpreting, analyzing and abridging functional enrichment results is a daunting task, usually performed by hand by the average wet-biology researcher. We have developed reString, a cross-platform software that seamlessly retrieves from STRING functional enrichments from multiple user-supplied gene sets, with just a few clicks, without any need for specific bioinformatics skills. Further, it aggregates all findings into human-readable table summaries, with built-in features to easily produce user-customizable publication-grade clustermaps and bubble plots. Herein, we outline a complete reString protocol, showcasing its features on a real use-case.

Download Full-text

Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.631650 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ningyuan Chen ◽

Liu Miao ◽

Wei Lin ◽

Donghua Zou ◽

Ling Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Regulatory Networks ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Functional Enrichment Analysis ◽

Normal Subjects ◽

Functional Enrichment ◽

Differentially Methylated Genes

Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects. (2) Functional enrichment analysis and construction of differential methylation gene regulatory networks were performed. (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray dataset. (4) Correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNAs matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes—s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interesting different expression positions [differentially methylated positions (DMPs)] and their corresponding gene expression, we found that methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expressions in obese subjects were validated in a separate microarray dataset.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

Download Full-text

Cistrome-GO: a web server for functional enrichment analysis of transcription factor ChIP-seq peaks

Nucleic Acids Research ◽

10.1093/nar/gkz332 ◽

2019 ◽

Vol 47 (W1) ◽

pp. W206-W211 ◽

Cited By ~ 15

Author(s):

Shaojuan Li ◽

Changxin Wan ◽

Rongbin Zheng ◽

Jingyu Fan ◽

Xin Dong ◽

...

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Transcription Factor ◽

Target Genes ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Differential Gene ◽

Direct Target ◽

Human And Mouse

AbstractCharacterizing the ontologies of genes directly regulated by a transcription factor (TF), can help to elucidate the TF’s biological role. Previously, we developed a widely used method, BETA, to integrate TF ChIP-seq peaks with differential gene expression (DGE) data to infer direct target genes. Here, we provide Cistrome-GO, a website implementation of this method with enhanced features to conduct ontology analyses of gene regulation by TFs in human and mouse. Cistrome-GO has two working modes: solo mode for ChIP-seq peak analysis; and ensemble mode, which integrates ChIP-seq peaks with DGE data. Cistrome-GO is freely available at http://go.cistrome.org/.

Download Full-text

Role of COL3A1 and POSTN on Pathologic Stages of Esophageal Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820977489 ◽

2020 ◽

Vol 19 ◽

pp. 153303382097748

Author(s):

Shao-wei Zhang ◽

Nan Zhang ◽

Na Wang

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

And Control ◽

The Impact

Background: Esophageal cancer (EC) is a primary malignant tumor originating from the esophageal of the epithelium. Surgical resection is a potential treatment for EC, but this is only appropriate for patients who have locally resectable lesions suitable for surgery. However, most patients with EC are at a late stage when diagnosed. Therefore, there is an urgent need to further explore the pathogenesis of EC to enable early diagnosis and treatment. Methods: Our study downloaded 2 expression spectrum datasets (GSE92396 and GSE100942) in the Gene Expression Omnibus (GEO) database. GEO2 R was used to identify the Differentially expressed genes (DEGs) between the samples of EC and control. Using the DAVID tool to make the Functional enrichment analysis. Constructing A protein–protein interaction (PPI) network. Identifying the Hub genes. The impact of hub gene expression on overall survival and their expression based on immunohistochemistry were analyzed. Associated microRNAs were also predicted. Results: There were 36 common DEGs identified. The analysis of GO and KEGG results shown that the variations were predominantly concentrated in the extracellular matrix (ECM), ECM organization, DNA binding, platelet activation, and ECM-receptor interactions. COL3A1 and POSTN had high expression in EC tissues which was compared with their expression in healthy tissues. Analysis of pathologic stages showed that when COL3A1 and POSTN were highly expressed, the stage of the pathologic of EC patients was relatively high (P < 0.005). Conclusions: COL3A1 and POSTN may play an important role in the advancement and occurrence of EC. These genes could provide some novel ideas and basis for the diagnosis and targeted treatment of EC.

Download Full-text

Behavioral Sensitization Induced by Methamphetamine Causes Differential Alterations in Gene Expression and Histone Acetylationin of Prefrontal Cortex in the Rat

10.21203/rs.2.20165/v1 ◽

2020 ◽

Author(s):

Hui Li ◽

Jing-An Chen ◽

Qian-Zhi Ding ◽

Guan-Yi Lu ◽

Ning Wu ◽

...

Keyword(s):

Gene Expression ◽

Prefrontal Cortex ◽

Histone Acetylation ◽

Behavioral Sensitization ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Adult Rats ◽

Behavioural Sensitization ◽

Genes Expression

Abstract BACKGROUND: Methamphetamine (METH) is one of the most widely abused illicit substances around the world, unfortunately its addiction mechanism remains unclear. Increasing evidences indicate that the change of gene expression and the involvement of chromatin modifications might be related with the lasting effects of METH on the brain. In the study, we took advantage of METH-induced behavioral sensitization as the animal model that reflects some aspects of drug addiction, and examined the transcription and histone acetylation changes in gene expression in prefrontal cortex (PFC) of adult rats. METHODS: We conducted the mRNA microarray and chromatin immunoprecipitation (ChIP) coupled to DNA microarrays (ChIP-chip) analysis to test and screen the transcriptional changes and histone acetylation modifications. The functional-enrichment analysis including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to analyze the diﬀerential expression genes. We then further identified the alterations of ANP32A (Acidic leucine-rich nuclear phosphoprotein-32A) and POU3F2 (The POU domain, class 3, transcription factor 2) by real-time PCR and ChIP-PCR assay. RESULTS: In the rat model of METH-induced behavioral sensitization, challenge of METH caused 275 differentially expressed genes and a number of hyperacetylations (821 genes in H3 acetylation and 10 genes in H4 acetylation). We further tested the alteration of ANP32A and POU3F2 in transcription and histone acetylation at the different periods of this model, and revealed that histone acetylation modifications contributed to mRNA change of the genes expression caused by METH induced-behavioural sensitization while not by METH acute treatment. CONCLUSIONS: the present results revealed an amount of alteration in transcription and histone acetylation in rat PFC by the exposure of METH, and provided the evidence that the modifications of histone acetylation is contributed to the alteration of the genes expression caused by METH-induced behavioural sensitization.

Download Full-text

Analysis of Serum miRNAs in Alzheimer’s Disease

American Journal of Alzheimer s Disease & Other Dementias® ◽

10.1177/15333175211021712 ◽

2021 ◽

Vol 36 ◽

pp. 153331752110217

Author(s):

Liu Lu ◽

Wen-Zhuo Dai ◽

Xi-Chen Zhu ◽

Tao Ma

Keyword(s):

Gene Expression ◽

Target Genes ◽

Enrichment Analysis ◽

Gene Interaction ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed ◽

Mitogen Activated Protein Kinase ◽

Regulatory Relationship

This paper was aimed to analyze the microRNA (miRNA) signatures in Alzheimer disease (AD) and find the significant expressions of miRNAs, their target genes, the functional enrichment analysis of the confirmed genes, and potential drug treatment. The miRNA expression information of the gene expression profile data was downloaded from the Gene Expression Omnibus database. The total data sample size is 1309, including 1021 AD samples and 288 normal samples. A total of 21 differentially expressed miRNAs were obtained, of which 16 (hsa-miR-6761-3p, hsa-miR-6747-3p, hsa-miR-6875-3p, hsa-miR-6754-3p, hsa-miR-6736-3p, hsa-miR-6762-3p, hsa-miR-6787-3p, hsa-miR-208a-5p, hsa-miR-6740-3p, hsa-miR-6778-3p, hsa-miR-595, hsa-miR-6753-3p, hsa-miR-4747-3p, hsa-miR-3646, hsa-miR-6716-3p and hsa-miR-4435) were up-regulated and 5 (hsa-miR-125a-3p, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-6131 and hsa-miR-125b-1-3p) were down-regulated in AD. A total of 6 miRNAs (hsa-miR-595, hsa-miR-3646, hsa-miR-4435 hsa-miR-125a-3p, hsa-miR-22-3p and hsa-miR-24-3p) and 78 miRNA-disease-related gene sub-networks were predicted, and 116 ceRNA regulatory relationship pairs, and the ceRNA regulatory network were obtained. The results of enrichment analysis suggested that the main target pathways of several miRNAs differentially expressed in AD were mitogen-activated protein kinase signal pathway. According to the prediction results of Drug-Gene Interaction database 2.0, we obtained 53 pairs of drug-gene interaction, including 7 genes (PTGS2, EGFR, CALM1, PDE4D, FGFR2, HMGCR, cdk6) and 53 drugs. We hope our results are helpful to find a viable way to prevent, delay the onset, diagnose, and treat AD.

Download Full-text