scholarly journals Transcriptome Profiling of Mouse Corpus Callosum After Cerebral Hypoperfusion

2021 ◽  
Vol 9 ◽  
Author(s):  
Hajime Takase ◽  
Gen Hamanaka ◽  
Ryo Ohtomo ◽  
Hidehiro Ishikawa ◽  
Kelly K. Chung ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Vascular Cognitive Impairment ◽  
Gene Set Enrichment Analysis ◽  
Cerebral Hypoperfusion ◽  
White Matter Damage ◽  
Gene Set Enrichment ◽  
Object Recognition Test ◽  
Bilateral Carotid

White matter damage caused by cerebral hypoperfusion is a major hallmark of subcortical ischemic vascular dementia (SIVD), which is the most common subtype of vascular cognitive impairment and dementia (VCID) syndrome. In an aging society, the number of SIVD patients is expected to increase; however, effective therapies have yet to be developed. To understand the pathological mechanisms, we analyzed the profiles of the cells of the corpus callosum after cerebral hypoperfusion in a preclinical SIVD model. We prepared cerebral hypoperfused mice by subjecting 2-month old male C57BL/6J mice to bilateral carotid artery stenosis (BCAS) operation. BCAS-hypoperfusion mice exhibited cognitive deficits at 4 weeks after cerebral hypoperfusion, assessed by novel object recognition test. RNA samples from the corpus callosum region of sham- or BCAS-operated mice were then processed using RNA sequencing. A gene set enrichment analysis using differentially expressed genes between sham and BCAS-operated mice showed activation of oligodendrogenesis pathways along with angiogenic responses. This database of transcriptomic profiles of BCAS-hypoperfusion mice will be useful for future studies to find a therapeutic target for SIVD.

scholarly journals Transcriptome Profiling and Metagenomic Analysis Help to Elucidate Interactions in an Inflammation-Associated Cancer Mouse Model

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3683
Author(s):  
Kazuko Sakai ◽  
Marco A. De Velasco ◽  
Yurie Kura ◽  
Kazuto Nishio
Keyword(s):  
Protein A ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Gene Set Enrichment Analysis ◽  
Biosynthetic Pathways ◽  
Microbial Composition ◽  
Gene Set Enrichment ◽  
Downstream Target ◽  
Whole Transcriptome ◽  
16S Rdna Gene Sequencing

Colitis is a risk factor for colorectal cancer (CRC) and can change the dynamics of gut microbiota, leading to dysbiosis and contributing to carcinogenesis. The functional interactions between colitis-associated CRC and microbiota remain unknown. In this study, colitis and CRC were induced in BALB/c mice by the administration of dextran sodium sulfate (DSS) and/or azoxymethane (AOM). Whole transcriptome profiling of normal colon was then performed, and gene set enrichment analysis (GSEA) revealed enriched fatty acid metabolism, oxidative phosphorylation, and PI3K-Akt-mTOR signaling in the tissues from DSS/AOM mice. Additionally, immunohistochemical staining showed increased expression levels of phosphorylated S6 ribosomal protein, a downstream target of the PI3K-Akt-mTOR pathway in the inflamed mucosa of DSS/AOM mice. Fecal microbes were characterized using 16S rDNA gene sequencing. Redundancy analysis demonstrated a significant dissimilarity between the DSS/AOM group and the others. Functional analysis inferred from microbial composition showed enrichments of the sphingolipid signal and lipoarabinomannan biosynthetic pathways. This study provides additional insights into alterations associated with DSS/AOM-induced colitis and associates PI3K-Akt-mTOR, sphingolipid-signaling and lipoarabinomannan biosynthetic pathways in mouse DSS/AOM-induced colitis.

scholarly journals Transcriptome profiling identifies multistep regulation through E93, Forkhead and Ecdysone Oxidase in survival of Malpighian tubules during metamorphosis in Drosophila

2020 ◽  
Vol 64 (4-5-6) ◽  
pp. 331-341
Author(s):  
Shainy Ojha ◽  
Madhu G. Tapadia
Keyword(s):  
Cell Death ◽  
Ectopic Expression ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Malpighian Tubules ◽  
Gene Set Enrichment Analysis ◽  
Concerted Action ◽  
Gene Set Enrichment ◽  
Over Expression ◽  
Hormone Titer

Drosophila metamorphosis is associated with substantial metabolic activity involving cell death and cell proliferation leading to differentiation of adult tissues and structures. Unlike other larval tissues, Malpighian tubules (MTs) exhibit apoptotic immunity and do not undergo cell death but are carried over to the adult with some cell reorganisation. They persist despite the fact that they express apoptotic proteins and caspases. In the present study, we analysed the global transcription changes in MTs and compared with salivary glands, to decipher the biology of MTs. Gene set enrichment analysis indicated reduced expression of many ecdysone induced genes, including the critical regulator of cell death, E93 in MTs. We hypothesize that reduction of E93 could be because of over expression of ecdysone oxidase, which is high in MTs and is responsible for regulation of hormone titer by degradation of ecdysone. Ectopic expression of E93 in MTs results in cell death through autophagy. Fork head, which is crucial for survival, is enriched in the MT transcriptome, and its down regulation in MTs could be consequent to over expression of E93. Together our data suggests that the cascade of events initiated by ecdysone mediates survival of MTs through concerted action of multiple factors.

scholarly journals iRAP - an integrated RNA-seq Analysis Pipeline

2014 ◽  
Author(s):  
Nuno A. Fonseca ◽  
Robert Petryszak ◽  
John Marioni ◽  
Alvis Brazma
Keyword(s):  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Transcript Level ◽  
Gene Set Enrichment Analysis ◽  
Rna Seq ◽  
Gene Set Enrichment ◽  
Analysis Pipeline ◽  
Advantages And Disadvantages ◽  
Computational Resources ◽  
Whole Transcriptome

RNA-sequencing (RNA-Seq) has become the technology of choice for whole-transcriptome profiling. However, processing the millions of sequence reads generated requires considerable bioinformatics skills and computational resources. At each step of the processing pipeline many tools are available, each with specific advantages and disadvantages. While using a specific combination of tools might be desirable, integrating the different tools can be time consuming, often due to specificities in the formats of input/output files required by the different programs. Here we present iRAP, an integrated RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression, testing for differential expression. iRAP also includes multiple tools for gene set enrichment analysis and generates web browsable reports of the results obtained in the different stages of the pipeline. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level. iRAP is aimed at a broad group of users with basic bioinformatics training and requires little experience with the command line. Despite this, it also provides more advanced users with the ability to customise the options used by their chosen tools.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

scholarly journals Placental Transcriptome Adaptations to Maternal Nutrient Restriction in Sheep

2021 ◽  
Vol 22 (14) ◽  
pp. 7654
Author(s):  
Chelsie B. Steinhauser ◽  
Colleen A. Lambo ◽  
Katharine Askelson ◽  
Gregory W. Burns ◽  
Susanta K. Behura ◽  
...  
Keyword(s):  
Mhc Class Ii ◽  
Killer Cell ◽  
National Research Council ◽  
Enrichment Analysis ◽  
Nutrient Utilization ◽  
Gene Set Enrichment Analysis ◽  
Nutrient Restriction ◽  
Placental Development ◽  
Gene Set Enrichment ◽  
Pregnant Sheep

Placental development is modified in response to maternal nutrient restriction (NR), resulting in a spectrum of fetal growth rates. Pregnant sheep carrying singleton fetuses and fed either 100% (n = 8) or 50% (NR; n = 28) of their National Research Council (NRC) recommended intake from days 35–135 of pregnancy were used to elucidate placentome transcriptome alterations at both day 70 and day 135. NR fetuses were further designated into upper (NR NonSGA; n = 7) and lower quartiles (NR SGA; n = 7) based on day 135 fetal weight. At day 70 of pregnancy, there were 22 genes dysregulated between NR SGA and 100% NRC placentomes, 27 genes between NR NonSGA and 100% NRC placentomes, and 22 genes between NR SGA and NR NonSGA placentomes. These genes mediated molecular functions such as MHC class II protein binding, signaling receptor binding, and cytokine activity. Gene set enrichment analysis (GSEA) revealed significant overrepresentation of genes for natural-killer-cell-mediated cytotoxicity in NR SGA compared to 100% NRC placentomes, and alterations in nutrient utilization pathways between NR SGA and NR NonSGA placentomes at day 70. Results identify novel factors associated with impaired function in SGA placentomes and potential for placentomes from NR NonSGA pregnancies to adapt to nutritional hardship.

scholarly journals Higher Acid-Base Imbalance Associated with Respiratory Failure Could Decrease the Survival of Patients with Scrub Typhus during Intensive Care Unit Stay: A Gene Set Enrichment Analysis

2019 ◽  
Vol 8 (10) ◽  
pp. 1580 ◽  
Author(s):  
Kyoung Min Moon ◽  
Kyueng-Whan Min ◽  
Mi-Hye Kim ◽  
Dong-Hoon Kim ◽  
Byoung Kwan Son ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Respiratory Failure ◽  
Scrub Typhus ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Acid Base ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets

Ninety percent of patients with scrub typhus (SC) with vasculitis-like syndrome recover after mild symptoms; however, 10% can suffer serious complications, such as acute respiratory failure (ARF) and admission to the intensive care unit (ICU). Predictors for the progression of SC have not yet been established, and conventional scoring systems for ICU patients are insufficient to predict severity. We aimed to identify simple and robust indicators to predict aggressive behaviors of SC. We evaluated 91 patients with SC and 81 non-SC patients who were admitted to the ICU, and 32 cases from the public functional genomics data repository for gene expression analysis. We analyzed the relationships between several predictors and clinicopathological characteristics in patients with SC. We performed gene set enrichment analysis (GSEA) to identify SC-specific gene sets. The acid-base imbalance (ABI), measured 24 h before serious complications, was higher in patients with SC than in non-SC patients. A high ABI was associated with an increased incidence of ARF, leading to mechanical ventilation and worse survival. GSEA revealed that SC correlated to gene sets reflecting inflammation/apoptotic response and airway inflammation. ABI can be used to indicate ARF in patients with SC and assist with early detection.

scholarly journals Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mike Fang ◽  
Brian Richardson ◽  
Cheryl M. Cameron ◽  
Jean-Eudes Dazard ◽  
Mark J. Cameron
Keyword(s):  
Drug Targets ◽  
T Regulatory Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Regulatory Cells ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets ◽  
Gastroenteropancreatic Neuroendocrine Tumor ◽  
Public Datasets

Abstract Background In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Results We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting. Conclusions dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules.

A Six-Gene Prognostic Risk Prediction Model In Hepatitis B Virus-Associated Hepatocellular Carcinoma

2021 ◽  
Vol 44 (3) ◽  
pp. E32-44
Author(s):  
Jia Shen ◽  
Ming Shu ◽  
Shujie Xie ◽  
Jia Yan ◽  
Kaile Pan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Model ◽  
Prognostic Score ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Gene Set Enrichment ◽  
B Virus ◽  
Score Model ◽  
Normal Controls

Purpose: This study aimed to screen hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC)-related feature ribonucleic acids (RNAs) and to establish a prognostic model. Methods: The transcriptome expression data of HBV-associated HCC were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus database. Differential RNAs between HBV-associated HCC and normal controls were identified by a meta-analysis of TCGA, GSE55092 and GSE121248. Weighted gene co-expression network analysis was performed to identify key RNAs and modules. A prognostic score model was established using TCGA as a training set by Cox regression analysis and was validated in E-TABM-36 dataset. Additionally, independent prognostic clinical factors were screened, and the function of lncRNAs waspredicted through Gene Set Enrichment Analysis. Results: A total of 710 consistent differential RNAs between HBV-associated HCC and normal controls were obtained, including five lncRNAs and 705 mRNAs. An optimized combination of six differential RNAs (DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4) was selected and a prognostic score model was constructed. Kaplan-Meier analysis demonstrated that the prognosis of the high-risk and low-risk groups separated by this model was significantly different in the training set and the validation set. Gene Set Enrichment Analysis showed that the co-expression genes of DSCR4 were significantly correlated with neuroactive ligand receptor interactionpathway. Conclusion: A prognostic model based on DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4 was developed that can accurately predict the prognosis of patients with HBV-associated HCC. These genes, as well as histologic grade, may serve as independent prognostic factors in HBV-associated HCC.

A Hypoxia-related LncRNA Signature Predicts Survival of Primary Lower-grade glioma

2021 ◽  
Author(s):  
Yanjia Hu ◽  
Jing Zhang ◽  
Jing Chen
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Gene Set Enrichment

Abstract Background Hypoxia-related long non-coding RNAs (lncRNAs) have been proven to play a role in multiple cancers and can serve as prognostic markers. Lower-grade gliomas (LGGs) are characterized by large heterogeneity. Methods This study aimed to construct a hypoxia-related lncRNA signature for predicting the prognosis of LGG patients. Transcriptome and clinical data of LGG patients were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LGG cohort in TCGA was chosen as training set and LGG cohorts in CGGA served as validation sets. A prognostic signature consisting of fourteen hypoxia-related lncRNAs was constructed using univariate and LASSO Cox regression. A risk score formula involving the fourteen lncRNAs was developed to calculate the risk score and patients were classified into high- and low-risk groups based on cutoff. Kaplan-Meier survival analysis was used to compare the survival between two groups. Cox regression analysis was used to determine whether risk score was an independent prognostic factor. A nomogram was then constructed based on independent prognostic factors and assessed by C-index and calibration plot. Gene set enrichment analysis and immune cell infiltration analysis were performed to uncover further mechanisms of this lncRNA signature. Results LGG patients with high risk had poorer prognosis than those with low risk in both training and validation sets. Recipient operating characteristic curves showed good performance of the prognostic signature. Univariate and multivariate Cox regression confirmed that the established lncRNA signature was an independent prognostic factor. C-index and calibration plots showed good predictive performance of nomogram. Gene set enrichment analysis showed that genes in the high-risk group were enriched in apoptosis, cell adhesion, pathways in cancer, hypoxia etc. Immune cells were higher in high-risk group. Conclusion The present study showed the value of the 14-lncRNA signature in predicting survival of LGGs and these 14 lncRNAs could be further investigated to reveal more mechanisms involved in gliomas.

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