scholarly journals Identification of Differentially Expressed Genes and Lipid Metabolism Signaling Pathways between Muscle and Fat Tissues in Broiler Chickens

2020 ◽  
Author(s):  
Min Zhang ◽  
Dan Zheng ◽  
Zhimei Peng ◽  
Yuting Zhu ◽  
Rongrong Li ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Broiler Chickens ◽  
Differentially Expressed

scholarly journals Transcriptomic analysis of PPARα-dependent alterations during cardiac hypertrophy

2008 ◽  
Vol 36 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Pascal J. H. Smeets ◽  
Heleen M. de Vogel-van den Bosch ◽  
Peter H. M. Willemsen ◽  
Alphons P. Stassen ◽  
Torik Ayoubi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Lipid Metabolism ◽  
Cardiac Hypertrophy ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Left Ventricular ◽  
Transcriptomic Analysis ◽  
Differentially Expressed ◽  
Wild Type

Peroxisome proliferator-activated receptor (PPAR)α regulates lipid metabolism at the transcriptional level and modulates the expression of genes involved in inflammation, cell proliferation, and differentiation. Although PPARα has been shown to mitigate cardiac hypertrophy, knowledge about underlying mechanisms and the nature of signaling pathways involved is fragmentary and incomplete. The aim of this study was to identify the processes and signaling pathways regulated by PPARα in hearts challenged by a chronic pressure overload by means of whole genome transcriptomic analysis. PPARα−/− and wild-type mice were subjected to transverse aortic constriction (TAC) for 28 days, and left ventricular gene expression profile was determined with Affymetrix GeneChip Mouse Genome 430 2.0 arrays containing >45,000 probe sets. In unchallenged hearts, the mere lack of PPARα resulted in 821 differentially expressed genes, many of which are related to lipid metabolism and immune response. TAC resulted in a more pronounced cardiac hypertrophy and more extensive changes in gene expression (1,910 and 312 differentially expressed genes, respectively) in PPARα−/− mice than in wild-type mice. Many of the hypertrophy-related genes were related to development, signal transduction, actin filament organization, and collagen synthesis. Compared with wild-type hypertrophied hearts, PPARα−/− hypertrophied hearts revealed enrichment of gene clusters related to extracellular matrix remodeling, immune response, oxidative stress, and inflammatory signaling pathways. The present study therefore demonstrates that, in addition to lipid metabolism, PPARα is an important modulator of immune and inflammatory response in cardiac muscle.

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 Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Biomolecules ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 850 ◽  
Author(s):  
Mehran Piran ◽  
Reza Karbalaei ◽  
Mehrdad Piran ◽  
Jehad Aldahdooh ◽  
Mehdi Mirzaie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Signaling Network ◽  
Differentially Expressed ◽  
Network Activity ◽  
Gene Products ◽  
Expression Data ◽  
Gene Pairs

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

scholarly journals Comparative transcriptional analysis provides insights of possible molecular mechanisms of wing polyphenism induced by postnatal crowding in Aphis gossypii

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Jichao JI ◽  
Shuai ZHANG ◽  
Junyu LUO ◽  
Li WANG ◽  
Xiangzhen ZHU ◽  
...  
Keyword(s):  
Population Density ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Aphis Gossypii ◽  
Plant Viruses ◽  
Differentially Expressed ◽  
Transcriptional Analysis ◽  
Cotton Aphid ◽  
Pathways Analysis

Abstract Background Aphis gossypii is a worldwide sap-sucking pest with a variety of hosts and a vector of more than 50 plant viruses. The strategy of wing polyphenism, mostly resulting from population density increasing, contributes to the evolutionary success of this pest. However, the related molecular basis remains unclear. Here, we identified the effects of postnatal crowding on wing morph determination in cotton aphid, and examined the transcriptomic differences between wingless and wing morphs. Results Effect of postnatal crowding on wing determination in A. gossypii was evaluated firstly. Under the density of 5 nymphs·cm− 2, no wing aphids appeared. Proportion of wing morphs rised with the increase of density in a certain extent, and peaked to 56.1% at the density of 20 nymphs·cm− 2, and reduced afterwards. Then, transcriptomes of wingless and wing morphs were assembled and annotated separately to identify potentially exclusively or differentially expressed transcripts between these two morphs, in which 3 126 and 3 392 unigenes annotated in Nr (Non-redundant protein sequence) database were found in wingless or wing morphs exclusively. Moreover, 3 187 up- and 1 880 down-regulated genes were identified in wing versus wingless aphid. Pathways analysis suggested the involvement of differentially expressed genes in multiple cellular signaling pathways involved in wing morphs determination, including lipid catabolic and metabolism, insulin, ecdysone and juvenile hormone biosynthesis. The expression levels of related genes were validated by the reverse transcription quantitative real time polymerase chain reaction (RT-qPCR) soon afterwards. Conclusions The present study identified the effects of postnatal crowding on wing morphs induction and demonstrated that the critical population density for wing morphs formation in A. gossypii was 20 nymphs·cm− 2. Comparative transcriptome analysis provides transcripts potentially expressed exclusively in wingless or wing morph, respectively. Differentially expressed genes between wingless and wing morphs were identified and several signaling pathways potentially involved in cotton aphid wing differentiation were obtained.

scholarly journals Combined Analysis of Expression Profiles in a Mouse Model and Patients Identified BHMT2 as a New Regulator of Lipid Metabolism in Metabolic-Associated Fatty Liver Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Yongqiang Ma ◽  
Zhi Tan ◽  
Qiang Li ◽  
Wenling Fan ◽  
Guangshun Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lipid Metabolism ◽  
Liver Disease ◽  
Fatty Liver ◽  
Differentially Expressed Genes ◽  
Fatty Liver Disease ◽  
Target Genes ◽  
Differentially Expressed ◽  
Overlapping Genes ◽  
Geo Database

Metabolic associated fatty liver disease (MAFLD) is associated with obesity, type 2 diabetes mellitus, and other metabolic syndromes. Farnesoid X receptor (FXR, NR1H4) plays a prominent role in hepatic lipid metabolism. This study combined the expression of liver genes in FXR knockout (KO) mice and MAFLD patients to identify new pathogenic pathways for MAFLD based on genome-wide transcriptional profiling. In addition, the roles of new target genes in the MAFLD pathogenic pathway were also explored. Two groups of differentially expressed genes were obtained from FXR-KO mice and MAFLD patients by transcriptional analysis of liver tissue samples. The similarities and differences between the two groups of differentially expressed genes were analyzed to identify novel pathogenic pathways and target genes. After the integration analysis of differentially expressed genes, we identified 134 overlapping genes, many of which have been reported to play an important role in lipid metabolism. Our unique analysis method of comparing differential gene expression between FXR-KO mice and patients with MAFLD is useful to identify target genes and pathways that may be strongly implicated in the pathogenesis of MAFLD. The overlapping genes with high specificity were screened using the Gene Expression Omnibus (GEO) database. Through comparison and analysis with the GEO database, we determined that BHMT2 and PKLR could be highly correlated with MAFLD. Clinical data analysis and RNA interference testing in vitro confirmed that BHMT2 may a new regulator of lipid metabolism in MAFLD pathogenesis. These results may provide new ideas for understanding the pathogenesis of MAFLD and thus provide new targets for the treatment of MAFLD.

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