scholarly journals Identify CRNDE and LINC00152 as the key lncRNAs in age-related degeneration of articular cartilage through comprehensive and integrative analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7024 ◽  
Author(s):  
Pengfei Hu ◽  
Fangfang Sun ◽  
Jisheng Ran ◽  
Lidong Wu
Keyword(s):  
Gene Expression ◽  
Articular Cartilage ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Receptor Interaction ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Age Related ◽  
Pathway Analyses

Background Osteoarthritis (OA) is one of the most important age-related degenerative diseases, and the leading cause of disability and chronic pain in the aging population. Recent studies have identified several lncRNA-associated functions involved in the development of OA. Because age is a key risk factor for OA, we investigated the differential expression of age-related lncRNAs in each stage of OA. Methods Two gene expression profiles were downloaded from the GEO database and differentially expressed genes (DEGs) were identified across each of the different developmental stages of OA. Next, gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to annotate the function of the DEGs. Finally, a lncRNA-targeted DEG network was used to identify hub-lncRNAs. Results A total of 174 age-related DEGs were identified. GO analyses confirmed that age-related degradation was strongly associated with cell adhesion, endodermal cell differentiation and collagen fibril organization. Significantly enriched KEGG pathways associated with these DEGs included the PI3K–Akt signaling pathway, focal adhesion, and ECM–receptor interaction. Further analyses via a protein–protein interaction (PPI) network identified two hub lncRNAs, CRNDE and LINC00152, involved in the process of age-related degeneration of articular cartilage. Our findings suggest that lncRNAs may play active roles in the development of OA. Investigation of the gene expression profiles in different development stages may supply a new target for OA treatment.

scholarly journals Transcriptome profiling of digital flexor tendons after injury in a chicken model

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Wei Feng Mao ◽  
Yin Xian Yu ◽  
Chen Chen ◽  
Ya Fang Wu
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Expression Profiles ◽  
Tendon Repair ◽  
Tendon Healing ◽  
Gene Expression Profiles ◽  
Repair Process ◽  
Receptor Interaction ◽  
Protein Protein Interaction ◽  
Chicken Model

Abstract Background: Modulation of tendon healing remains a challenge because of our limited understanding of the tendon repair process. Therefore, we performed the present study to provide a global perspective of the gene expression profiles of tendons after injury and identify the molecular signals driving the tendon repair process. Results: The gene expression profiles of flexor digitorum profundus tendons in a chicken model were assayed on day 3, weeks 1, 2, 4, and 6 after injury using the Affymetrix microarray system. Principal component analysis (PCA) and hierarchical cluster analysis of the differentially expressed genes showed three distinct clusters corresponding to different phases of the tendon healing period. Gene ontology (GO) analysis identified regulation of cell proliferation and cell adhesion as the most enriched biological processes. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that the cytokine–cytokine receptor interaction and extracellular matrix (ECM)–receptor interaction pathways were the most impacted. Weighted gene co-expression network analysis (WGCNA) demonstrated four distinct patterns of gene expressions during tendon healing. Cell adhesion and ECM activities were mainly associated with genes with drastic increase in expression 6 weeks after injury. The protein–protein interaction (PPI) networks were constructed to identify the key signaling pathways and hub genes involved. Conclusions: The comprehensive analysis of the biological functions and interactions of the genes differentially expressed during tendon healing provides a valuable resource to understand the molecular mechanisms underlying tendon healing and to predict regulatory targets for the genetic engineering of tendon repair. Tendon healing, Adhesion, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Weighted Gene Co-expression Network Analysis, Protein–protein Interaction

scholarly journals Identification of Key Genes and Pathways for Enchondromas by Bioinformatics Analysis

Dose-Response ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 155932582090753
Author(s):  
Tianlong Wu ◽  
Honghai Cao ◽  
Lei Liu ◽  
Kan Peng
Keyword(s):  
Gene Expression ◽  
Endoplasmic Reticulum ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Protein Processing ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Exact Etiology

Background: The risk of malignant transformation of enchondromas (EC) toward central chondrosarcoma is increased up to 35%, while the exact etiology of EC is unknown. The purpose of this research was to authenticate gene signatures during EC and reveal their potential mechanisms in occurrence and development of EC. Methods: The gene expression profiles was acquired from Gene Expression Omnibus database (no. GSE22855). The gene ontology (GO), protein–protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were utilized to identify differentially expressed genes (DEGs). Results: Finally, 242 DEGs were appraisal, containing 200 overregulated genes and 42 downregulated genes. The outcomes of GO analysis indicated that upregulated DEGs were mainly enriched in several biological processes containing response to hypoxia, calcium ion, and negative regulation extrinsic apoptotic signaling pathway. Furthermore, the upregulated DEGs were enriched in extracellular matrix (ECM)–receptor interaction, protein processing in endoplasmic reticulum and ribosome, which was analyzed by KEGG pathway. From the PPI network, the top 10 hub genes were identified, which were related to significant pathways containing ribosome, protein processing in endoplasmic reticulum, and ECM-receptor interaction. Conclusion: In conclusion, the present study may be helpful for understanding the diagnostic biomarkers of EC.

scholarly journals Age-related differences in monocyte DNA methylation and immune function in healthy Kenyan adults and children

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Katherine R. Dobbs ◽  
Paula Embury ◽  
Emmily Koech ◽  
Sidney Ogolla ◽  
Stephen Munga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Young Adults ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Innate Immune ◽  
Inflammatory Gene Expression ◽  
Cpg Sites ◽  
Age Related ◽  
Adults And Children

Abstract Background Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profiles in monocytes from young adults and children from western Kenya. Results We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles. Conclusions These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.

scholarly journals Genome-Wide Identification of Soybean ABC Transporters Relate to Aluminum Toxicity

2021 ◽  
Vol 22 (12) ◽  
pp. 6556
Author(s):  
Junjun Huang ◽  
Xiaoyu Li ◽  
Xin Chen ◽  
Yaru Guo ◽  
Weihong Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Abc Transporters ◽  
Developmental Stages ◽  
Aluminum Toxicity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Purifying Selection ◽  
Biotic Stresses ◽  
Genome Wide ◽  
New Germplasm

ATP-binding cassette (ABC) transporter proteins are a gene super-family in plants and play vital roles in growth, development, and response to abiotic and biotic stresses. The ABC transporters have been identified in crop plants such as rice and buckwheat, but little is known about them in soybean. Soybean is an important oil crop and is one of the five major crops in the world. In this study, 255 ABC genes that putatively encode ABC transporters were identified from soybean through bioinformatics and then categorized into eight subfamilies, including 7 ABCAs, 52 ABCBs, 48 ABCCs, 5 ABCDs, 1 ABCEs, 10 ABCFs, 111 ABCGs, and 21 ABCIs. Their phylogenetic relationships, gene structure, and gene expression profiles were characterized. Segmental duplication was the main reason for the expansion of the GmABC genes. Ka/Ks analysis suggested that intense purifying selection was accompanied by the evolution of GmABC genes. The genome-wide collinearity of soybean with other species showed that GmABCs were relatively conserved and that collinear ABCs between species may have originated from the same ancestor. Gene expression analysis of GmABCs revealed the distinct expression pattern in different tissues and diverse developmental stages. The candidate genes GmABCB23, GmABCB25, GmABCB48, GmABCB52, GmABCI1, GmABCI5, and GmABCI13 were responsive to Al toxicity. This work on the GmABC gene family provides useful information for future studies on ABC transporters in soybean and potential targets for the cultivation of new germplasm resources of aluminum-tolerant soybean.

scholarly journals Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Baojie Wu ◽  
Shuyi Xi
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Kegg Pathways

Abstract Background This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Methods Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets. Results A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained. Conclusions These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis

Gene ◽  
2016 ◽  
Vol 591 (1) ◽  
pp. 43-47 ◽  
Author(s):  
Wenyu Wang ◽  
Yang Liu ◽  
Jingcan Hao ◽  
Shuyu Zheng ◽  
Yan Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Comparative Analysis ◽  
Articular Cartilage ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Bi-Qing Li ◽  
Jin You ◽  
Lei Chen ◽  
Jian Zhang ◽  
Ning Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Shortest Path ◽  
Protein Interaction ◽  
Expression Profiles ◽  
Shortest Paths ◽  
Gene Expression Profiles ◽  
Cancer Genes ◽  
Ppi Network ◽  
Protein Protein Interaction

Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI) network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutationPvalue less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

Age-related changes in the transcriptional profile of mouse RPE/choroid

2003 ◽  
Vol 15 (3) ◽  
pp. 258-262 ◽  
Author(s):  
Hisashi Ida ◽  
Sharon A. Boylan ◽  
Andrea L. Weigel ◽  
Leonard M. Hjelmeland
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Cdna Probe ◽  
Gene Expression Profiles ◽  
Age Related Macular Degeneration ◽  
Pcr Analysis ◽  
Rt Pcr ◽  
Mouse Cdna ◽  
Age Related ◽  
Age Related Changes

To evaluate the age-related changes in gene expression occurring in the complex of retinal pigmented epithelium, Bruch’s membrane, and choroid (RPE/choroid), we examined the gene expression profiles of young adult (2 mo) and old (24 mo) male C57BL/6 mice. cDNA probe sets from individual animals were synthesized using total RNA isolated from the RPE/choroid of each animal. Probes were amplified using the Clontech SMART system, radioactively labeled, and hybridized to two different Clontech Atlas mouse cDNA arrays. From each age group, three independent triplicates were hybridized to the arrays. Statistical analyses were performed using the Significance Analysis of Microarrays program (SAM version 1.13; Stanford University). Selected array results were confirmed by semi-quantitative RT-PCR analysis. Of 2,340 genes represented on the arrays, ∼60% were expressed in young and/or old mouse RPE/choroid. A moderate fraction (12%) of all expressed genes exhibited a statistically significant change in expression with age. Of these 150 genes, all but two, HMG14 and carboxypeptidase E, were upregulated with age. Many of these upregulated genes can be grouped into several broad functional categories: immune response, proteases and protease inhibitors, stress response, and neovascularization. RT-PCR results from six of six genes examined confirmed the differential change in expression with age of these genes. Our study provides likely candidate genes to further study their role in the development of age-related macular degeneration and other aging diseases affecting the RPE/choroid.

GENE FUNCTION PREDICTION BY A COMBINED ANALYSIS OF GENE EXPRESSION DATA AND PROTEIN-PROTEIN INTERACTION DATA

2005 ◽  
Vol 03 (06) ◽  
pp. 1371-1389 ◽  
Author(s):  
GUANGHUA XIAO ◽  
WEI PAN
Keyword(s):  
Gene Expression ◽  
Protein Interaction ◽  
Gene Function ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Function Prediction ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Gene Function Prediction ◽  
Protein Protein Interaction

Prediction of biological functions of genes is an important issue in basic biology research and has applications in drug discoveries and gene therapies. Previous studies have shown either gene expression data or protein-protein interaction data alone can be used for predicting gene functions. In particular, clustering gene expression profiles has been widely used for gene function prediction. In this paper, we first propose a new method for gene function prediction using protein-protein interaction data, which will facilitate combining prediction results based on clustering gene expression profiles. We then propose a new method to combine the prediction results based on either source of data by weighting on the evidence provided by each. Using protein-protein interaction data downloaded from the GRID database, published gene expression profiles from 300 microarray experiments for the yeast S. cerevisiae, we show that this new combined analysis provides improved predictive performance over that of using either data source alone in a cross-validated analysis of the MIPS gene annotations. Finally, we propose a logistic regression method that is flexible enough to combine information from any number of data sources while maintaining computational feasibility.

scholarly journals De novo characterization of the Lycium ruthenicum transcriptome and analysis of its digital gene expression profiles during fruit development and ripening

2017 ◽  
Vol 69 (1) ◽  
pp. 181-190 ◽  
Author(s):  
Yong Peng ◽  
Huiqin Ma ◽  
Shangwu Chen
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
De Novo ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Digital Gene Expression ◽  
Orthologous Group ◽  
Functional Studies ◽  
Lycium Ruthenicum

Lycium ruthenicum Murr., which belongs to the family Solanaceae, is a resource plant for Chinese traditional medicine and nutraceutical foods. In this study, RNA sequencing was applied to obtain raw reads of L. ruthenicum fruit at different stages of ripening, and a de novo assembly of its sequence was performed. Approximately 52.45 million 100-bp paired-end raw reads were generated from the samples by deep RNA-seq analysis. These short reads were assembled to obtain 164814 contigs, and the contigs were assembled into 84968 non-redundant unigenes using the Trinity method. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group and KEGG (Kyoto Encyclopedia of Genes and Genomes)pathway terms. Digital gene expression analysis was applied to compare gene-expression patterns at different fruit developmental stages. These results contribute to existing sequence resources for Lycium spp. during the fruit-ripening stages, which is valuable for further functional studies of genes involved in L. ruthenicum fruit nutraceutical quality.

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