scholarly journals Identification of Differentially Expressed Genes in Pituitary Adenomas by Integrating Analysis of Microarray Data

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Peng Zhao ◽  
Wei Hu ◽  
Hongyun Wang ◽  
Shengyuan Yu ◽  
Chuzhong Li ◽  
...  
Keyword(s):  
Pituitary Adenoma ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Gene Function ◽  
Pituitary Adenomas ◽  
Function Analysis ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Ppi Networks ◽  
Gene Function Analysis

Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs) and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC) tissues. Gene function analysis including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated) in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.

scholarly journals A cassava common mosaic virus vector for virus-induced gene silencing in cassava

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Decai Tuo ◽  
Peng Zhou ◽  
Pu Yan ◽  
Hongguang Cui ◽  
Yang Liu ◽  
...  
Keyword(s):  
Gene Silencing ◽  
Mosaic Virus ◽  
Gene Function ◽  
Viral Vector ◽  
Function Analysis ◽  
Systemic Infection ◽  
Cdna Clones ◽  
Virus Induced Gene Silencing ◽  
Efficient Gene ◽  
Gene Function Analysis

Abstract Background Cassava is an important crop for food security and industry in the least-developed and developing countries. The completion of the cassava genome sequence and identification of large numbers of candidate genes by next-generation sequencing provide extensive resources for cassava molecular breeding and increase the need for rapid and efficient gene function analysis systems in cassava. Several plant virus-induced gene silencing (VIGS) systems have been developed as reverse genetic tools for rapid gene function analysis in cassava. However, these VIGS vectors could cause severe viral symptoms or inefficient gene silencing. Results In this study, we constructed agroinfection-compatible infectious cDNA clones of cassava common mosaic virus isolate CM (CsCMV-CM, genus Potexvirus, family Alphaflexiviridae) that causes systemic infection with mild symptoms in cassava. CsCMV-CM was then modified to a viral vector carrying the Nimble cloning frame, which facilitates the rapid and high-throughput cloning of silencing fragments into the viral genome. The CsCMV-based vector successfully silenced phytoene desaturase (PDS) and magnesium chelatase subunit I (ChlI) in different cassava varieties and Nicotiana benthamiana. The silencing of the ChlI gene could persist for more than two months. Conclusions This CsCMV-based VIGS system provides a new tool for rapid and efficient gene function studies in cassava.

scholarly journals The role of ferroptosis in breast cancer patients: a comprehensive analysis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Hong Yu ◽  
Hua-Dong Li
Keyword(s):  
Breast Cancer ◽  
T Cell ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Function Analysis ◽  
Cancer Prognosis ◽  
Differentially Expressed ◽  
Immune Checkpoints ◽  
Cell Functions

AbstractBreast cancer (BC) affects the breast tissue and is the second most common cause of mortalities among women. Ferroptosis is an iron-dependent cell death mode that is characterized by intracellular accumulation of reactive oxygen species (ROS). We constructed a prognostic multigene signature based on ferroptosis-associated differentially expressed genes (DEGs). Moreover, we comprehensively analyzed the role of ferroptosis-associated miRNAs, lncRNAs, and immune responses. A total of 259 ferroptosis-related genes were extracted. KEGG function analysis of these genes revealed that they were mainly enriched in the HIF-1 signaling pathway, NOD-like receptor signaling pathway, central carbon metabolism in cancer, and PPAR signaling pathway. Fifteen differentially expressed genes (ALOX15, ALOX15B, ANO6, BRD4, CISD1, DRD5, FLT3, G6PD, IFNG, NGB, NOS2, PROM2, SLC1A4, SLC38A1, and TP63) were selected as independent prognostic factors for BC patients. Moreover, T cell functions, including the CCR score, immune checkpoint, cytolytic activity, HLA, inflammation promotion, para-inflammation, T cell co-stimulation, T cell co-inhibition, and type II INF responses were significantly different between the low-risk and high-risk groups of the TCGA cohort. Immune checkpoints between the two groups revealed that the expressions of PDCD-1 (PD-1), CTLA4, LAG3, TNFSF4/14, TNFRSF4/8/9/14/18/25, and IDO1/2 among others were significantly different. A total of 1185 ferroptosis-related lncRNAs and 219 ferroptosis-related miRNAs were also included in this study. From the online database, we identified novel ferroptosis-related biomarkers for breast cancer prognosis. The findings of this study provide new insights into the development of new reliable and accurate cancer treatment options.

scholarly journals Screening the Hub Genes and Analyzing the Mechanisms in Discharged COVID-19 Patients Retesting Positive through Bioinformatics Analysis

2021 ◽  
Author(s):  
Ke-Ying Fang ◽  
Gui-Ning Liang ◽  
Zhuo-Qing Zhuang ◽  
Yong-Xin Fang ◽  
Yu-Qian Dong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Social Order ◽  
Expression System ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Virus Reactivation ◽  
Hub Genes ◽  
Messenger Ribonucleic Acid ◽  
Ppi Networks ◽  
Significant Enrichment

Abstract Background: With the worldwide spread of COVID-19, people’s health and social order have been exposed to enormous risks. After encountering patients who test positive again after discharge, our study analyzed the pathogenesis to further assess the risk and possibility of virus reactivation.Methods: A separate microarray was acquired from the Integrated Gene Expression System (GEO), and its samples were divided into two groups: a “convalescent-RTP” group consisting of recovery and “retesting-positive” (RTP) patients (group CR) and a “health-RTP” group consisting of healthy control and RTP patients (group HR). The enrichment analysis was performed with R software, obtaining the gene ontology (GO) and Kyoto pluripotent stem cells (KEGG) of the genes and genomes. Subsequently, the protein–protein interaction (PPI) networks of each group were established and the hub genes were discovered using the cytoHubba plug-in.Results: In this study, 20 differentially expressed genes were identified, and 6622 genes were identified in the group CR, consisting of 5003 up-regulated and 1619 down-regulated genes. Meanwhile, 7335 genes were screened in the group HR, including 4323 up-regulated and 3012 down-regulated ones. The GO and KEGG analysis of the two groups revealed significant enrichment of these differentially expressed genes in pathways associated with immune response and apoptosis. In the PPI network constructed, 10 hub genes in group CR were identified, including TP53BP1, SNRPD1, SNRPD2, SF3B1, SNRNP200, MRPS16, MRPS9, CALM1, PPP2R1A, YWHAZ. Similarly, TP53BP1, RPS15, EFTUD2, MRPL16, MRPL17, MRPS14, RPL35A, MRPL32, MRPS6, POLR2G were selected as hub genes.Conclusions: Using the messenger ribonucleic acid (mRNA) expression data from GSE166253, we explore the pathogenesis of retesting positive in COVID-19 from the immune mechanism and molecular level. We found TP53BP1, SNRPD1 and SNRPD2 as hub genes in RTP patients. Hence, their regulatory pathway is vital to the management and prognostic prediction of RTP patients, rendering the further study of these hub genes necessary.

scholarly journals Comparative functional genomic analysis of Alzheimer’s affected and naturally aging brains

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8682
Author(s):  
Yi-Shian Peng ◽  
Chia-Wei Tang ◽  
Yi-Yun Peng ◽  
Hung Chang ◽  
Chien-Lung Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Gene List ◽  
Amyloid Β ◽  
Differentially Expressed ◽  
Gene Expression Microarray ◽  
Expression Microarray ◽  
Functional Genomic Analysis ◽  
Gene Expression Microarray Data

Background Alzheimer’s disease (AD) is a prevalent progressive neurodegenerative human disease whose cause remains unclear. Numerous initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests. Natural aging (AG) is a high-risk factor for AD. Here, we aim to gain insights in AD that may lead to its novel therapeutic treatment through conducting meta-analyses of gene expression microarray data from AG and AD-affected brain. Methods Five sets of gene expression microarray data from different regions of AD (hereafter, ALZ when referring to data)-affected brain, and one set from AG, were analyzed by means of the application of the methods of differentially expressed genes and differentially co-expressed gene pairs for the identification of putatively disrupted biological pathways and associated abnormal molecular contents. Results Brain-region specificity among ALZ cases and AG-ALZ differences in gene expression and in KEGG pathway disruption were identified. Strong heterogeneity in AD signatures among the five brain regions was observed: HC/PC/SFG showed clear and pronounced AD signatures, MTG moderately so, and EC showed essentially none. There were stark differences between ALZ and AG. OXPHOS and Proteasome were the most disrupted pathways in HC/PC/SFG, while AG showed no OXPHOS disruption and relatively weak Proteasome disruption in AG. Metabolic related pathways including TCA cycle and Pyruvate metabolism were disrupted in ALZ but not in AG. Three pathogenic infection related pathways were disrupted in ALZ. Many cancer and signaling related pathways were shown to be disrupted AG but far less so in ALZ, and not at all in HC. We identified 54 “ALZ-only” differentially expressed genes, all down-regulated and which, when used to augment the gene list of the KEGG AD pathway, made it significantly more AD-specific.

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