RNA-Seq profiling of microdissected glomeruli identifies potential biomarkers for human IgA nephropathy

2020 ◽  
Vol 319 (5) ◽  
pp. F809-F821
Author(s):  
Sehoon Park ◽  
Seung Hee Yang ◽  
Chang Wook Jeong ◽  
Kyung Chul Moon ◽  
Dong Ki Kim ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Iga Nephropathy ◽  
Differentially Expressed Genes ◽  
Mesangial Cells ◽  
Principal Component ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Ontology Term ◽  
Transcriptomic Profiling

Few studies have examined gene expression changes occurring in the glomeruli of IgA nephropathy (IgAN) using a sensitive transcriptomic profiling method such as RNA sequencing (RNA-Seq). We collected glomeruli from biopsy specimens from patients with IgAN with relatively preserved kidney function (estimated glomerular filtration rate ≥ 60 mL·min−1·1.73 m−2 and urine protein-to-creatinine ratio < 3 g/g) and from normal kidney cortexes by hand microdissection and performed RNA-Seq. Differentially expressed genes were identified, and gene ontology term annotation and pathway analysis were performed. Immunohistochemical labeling and primary mesangial cell cultures were performed to confirm the findings of RNA-Seq analysis. Fourteen patients with IgAN and ten controls were included in this study. Glomerulus-specific genes were highly abundant. Principal component analysis showed clear separation between the IgAN and control groups. There were 2,497 differentially expressed genes, of which 1,380 were upregulated and 1,117 were downregulated (false discovery rate < 0.01). The enriched gene ontology terms included motility/migration, protein/vesicle transport, and immune system, and kinase binding was the molecular function overrepresented in IgAN. B cell signaling, chemokine signal transduction, and Fcγ receptor-mediated phagocytosis were the canonical pathways overrepresented. In vitro experiments confirmed that spleen tyrosine kinase (SYK), reported as upregulated in the IgAN transcriptome, was also upregulated in glomeruli from an independent set of patients with IgAN and that treatment with patient-derived IgA1 increased the expression of SYK in mesangial cells. In conclusion, transcriptomic profiling of the IgAN glomerulus provides insights in the intraglomerular pathophysiology of IgAN before it reaches profound kidney dysfunction. SYK may have a pathogenetic role in IgAN.

scholarly journals Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

2021 ◽  
Author(s):  
Chengang Guo ◽  
Zhimin wei ◽  
Wei Lyu ◽  
Yanlou Geng
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Hierarchical Cluster ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

scholarly journals A Differential Host Response to Viral Infection Defines a Subset of Earlier-Onset Diverticulitis Patients

2018 ◽  
Vol 27 (3) ◽  
pp. 249-255 ◽  
Author(s):  
Kathleen M Schieffer ◽  
Bryan P Kline ◽  
Leonard R Harris ◽  
Sue Deiling ◽  
Walter A Koltun ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Viral Pathogen ◽  
Viral Response ◽  
Elevated Expression ◽  
Bioinformatic Approaches ◽  
Relationship Of ◽  
The Relationship

Background & Aims: Diverticulitis is the chronic inflammation of diverticula. Whether the pathophysiology of earlier-onset patients differs from later-onset patients is unknown. We profiled the colonic transcriptomes of these two patient populations to gain insight into the molecular underpinnings of diverticulitis. Methods: We conducted deep RNA sequencing (RNA-seq) on colonic segments surgically resected from earlier-onset (<42 years old, n=13) and later-onset (>65 years old, n=13) diverticulitis patients. We used bioinformatic approaches to cluster the patients based on the relationship of differentially expressed genes and to inform on the molecular pathways that segregated the clusters. Results: Principal component analysis identified three patient clusters; diverticulitis later-onset (DVT-LO), diverticulitis mixed-onset (DVT-MO), and diverticulitis earlier-onset (DVT-EO). The patients comprising DVT-EO, which was the majority of earlier-onset patients, displayed increased expression of anti-viral response genes. This finding was confirmed using an independent weighted co-expression network analysis (WGCNA) of differentially expressed genes. Conclusions: We found that the majority of patients with earlier-onset disease contained elevated expression of host genes involved in the anti-viral response. Thus, susceptibility to a viral pathogen may offer one explanation why some individuals develop diverticulitis at an earlier age.

scholarly journals Bayesian analysis of fMRI data and RNA-Seq time course experiment data

2015 ◽  
Author(s):  
◽  
Yuan Cheng
Keyword(s):  
Model Selection ◽  
Bayesian Analysis ◽  
Differentially Expressed Genes ◽  
Time Course ◽  
Selection Procedure ◽  
Principal Component ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Hemodynamic Response Function ◽  
Model Selection Procedure

The present dissertation contains two parts. In the first part, we develop a new Bayesian analysis of functional MRI data. We propose a novel triple gamma Hemodynamic Response Function (HRF) including the component to describe the initial dip. We use HRF to inform voxel-wise neuronal activities. Then we devise a new model selection procedure with a nonlocal pMOM prior for joint detection of neuronal activation and estimation of HRF, in order to time the activation time difference between visual and motor areas in the brain. In the second part, we develop a new Bayesian analysis of RNA-Seq Time Course experiments data. We propose to use Bayesian Principal Component regression model and based on that, devise a model selection procedure by using nonlocal piMOM prior in order to identify differentially expressed genes. Most current existing methods for RNA-Seq Time Course experiments data are from static view of point and cannot predict temporal patterns. Our method estimate the posterior differentially expressed probability for each gene by borrowing information across all subjects. Use of nonlocal prior in the model selection procedure reduces false discovered differentially expressed genes.

Bayesian analysis for detecting differentially expressed genes from RNA-seq data

2014 ◽  
Author(s):  
◽  
Shiqi Cui
Keyword(s):  
Differentially Expressed Genes ◽  
Time Course ◽  
Markov Models ◽  
Single Gene ◽  
Principal Component ◽  
Integrated Approach ◽  
Differentially Expressed ◽  
Monte Carlo Algorithm ◽  
Rna Seq ◽  
Paired Data

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces hmmSeq, a model-based hierarchical Bayesian technique for detecting differentially expressed genes from RNA-seq data. Our novel hmmSeq methodology uses hidden Markov models to account for potential co-expression of neighboring genes. In addition, hmmSeq employs an integrated approach to studies with technical or biological replicates, automatically adjusting for any extra-Poisson variability. Moreover, for cases when paired data are available, hmmSeq includes a paired structure between treatments that incorporates subject-specific effects. To perform parameter estimation for the hmmSeq model, we develop an efficient Markov chain Monte Carlo algorithm. Further, we develop a procedure for detection of differentially expressed genes that automatically controls false discovery rate. A simulation study shows that the hmmSeq methodology performs better than competitors in terms of receiver operating characteristic curves. Finally, the analyses of three publicly available RNA-Seq datasets demonstrate the power and flexibility of the hmmSeq methodology. This dissertation also introduces an empirical Bayesian approach to detect differentially expressed genes in time course RNA-seq experiments. The proposed Bayesian method identifies major variation in gene expression profile by Bayesian principal component regression. The expression data are normalized for each gene, and the high dimentionality of time course data is first reduced by principal component analysis. The proposed model assumes a mixture distribution of expression parameters for differentially and nondifferentially expressed genes, borrows strength by sharing same variance across multiple subjects for each single gene, as well as shares information across genes by assuming gene-wise probabilities of being differentially expressed from the common beta prior distribution.

scholarly journals A Sense of Place: Transcriptomics Identifies Environmental Signatures in Cabernet Sauvignon Berry Skins in the Late Stages of Ripening

2019 ◽  
Author(s):  
Grant R. Cramer ◽  
Noé Cochetel ◽  
Ryan Ghan ◽  
Agnès Destrac-Irvine ◽  
Serge Delrot
Keyword(s):  
Gene Ontology ◽  
Differentially Expressed Genes ◽  
Transcript Abundance ◽  
Differentially Expressed ◽  
Cabernet Sauvignon ◽  
Rna Seq ◽  
Cold Response ◽  
Berry Ripening ◽  
Berry Skins ◽  
Late Stages

AbstractBackgroundGrape berry ripening is influenced by climate, the main component of the “terroir” of a place. Light and temperature are major factors in the vineyard that affect berry development and fruit metabolite composition.ResultsTo better understand the effect of “place” on transcript abundance during the late stages of berry ripening, Cabernet Sauvignon berries grown in Bordeaux and Reno were compared at similar sugar levels (19 to 26 °Brix (total soluble solids)). Day temperatures were warmer and night temperatures were cooler in Reno. °Brix was lower in Bordeaux berries compared to Reno at maturity levels considered optimum for harvest. RNA-Seq analysis identified 5528 differentially expressed genes between Bordeaux and Reno grape skins at 22°Brix. Weighted Gene Coexpression Network Analysis for all expressed transcripts for all four °Brix levels measured indicated that the majority (75%) of transcript expression differed significantly between the two locations. Top gene ontology categories for the common transcript sets were translation, photosynthesis, DNA metabolism and catabolism. Top gene ontology categories for the differentially expressed genes at 22°Brix involved response to stimulus, biosynthesis and response to stress. Some differentially expressed genes encoded terpene synthases, cell wall enzymes, kinases, transporters, transcription factors and photoreceptors. Most circadian clock genes had higher transcript abundance in Bordeaux. Bordeaux berries had higher transcript abundance with differentially expressed genes associated with seed dormancy, light, auxin, ethylene signaling, powdery mildew infection, phenylpropanoid, carotenoid and terpenoid metabolism, whereas Reno berries were enriched with differentially expressed genes involved in water deprivation, cold response, ABA signaling and iron homeostasis.ConclusionsTranscript abundance profiles in the berry skins at maturity were highly dynamic. RNA-Seq analysis identified a smaller (25% of total) common core set of ripening genes that appear not to depend on rootstock, vineyard management, plant age, soil and climatic conditions. Much of the gene expression differed between the two locations and could be associated with multiple differences in environmental conditions that may have affected the berries in the two locations; some of these genes may be potentially controlled in different ways by the vinegrower to adjust final berry composition and reach a desired result.

scholarly journals Complement C3a Not C4a Activates Osteoclasts By Regulating the PI3K/PDK1/SGK3 Pathway in Patients with Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4416-4416
Author(s):  
Rong Fu ◽  
Fengjuan Jiang ◽  
Hui Liu ◽  
Zhaoyun Liu ◽  
Siyang Yan ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Bone Disease ◽  
Cathepsin K ◽  
Differentially Expressed ◽  
Control Group ◽  
Rna Seq ◽  
Relative Expression ◽  
Absorption Area ◽  
Osteoclast Resorption

Objective: Myeloma bone disease (MBD) is the most common complication of multiple myeloma (MM). We found that the serum levels of C3/C4 in MM patients were significantly positive correlated with the severity of bone disease in our previously study. Thus, we conduct detailed studies to explore the effect and potential mechanism of C3a/C4a on osteoclasts in patients with MM. Methods: By adding C3a/C4a to culture system of osteoclasts induced from mononuclear cells in vitro, and the expression of related gene, number and function of osteoclasts were detected. RNA-Seq analysis was used to detect the differentially expressed genes on osteoclasts between the complement group and control group, and the possible signal pathways were analyzed. Quantitative real-time PCR (qRT-PCR), Western blot and pathway inhibitors were used for further validation. R esults: In vitro, the osteoclasts area per view induced by C3a 1μg/ml (52.794±13.027 %) and 10μg/ml (51.797±12.464 %) was significantly increased than control group (0μg/ml) (33.668±8.427 %) (P<0.001; P<0.001), the mRNA relative expression of osteoclasts related genes OSCAR/TRAP/RANKL/Cathepsin K induced by C3a 1μg/ml (median 5.041; 3.726; 1.638; 4.752) and 10μg/ml (median 5.140; 3.702; 2.250; 5.172) was significantly increased than control group (0μg/ml) (median 3.137; 2.004; 0.573; 2.257) (1μg/ml P=0.001; P=0.003; P<0.001; P=0.008; 1μg/ml P<0.001; P=0.019; P<0.001; P=0.002), and the absorption area of osteoclast resorption pit per view induced by C3a 1μg/ml (51.464±11.983 %) and 10μg/ml (50.219±12.067 %) was also significantly increased than control group (0μg/ml) (33.845±8.331 %) (P<0.001; P<0.001) in NDMM patients. There was no difference among the osteoclasts area, relative expression of osteoclasts related genes and absorption area of osteoclast resorption pit between C4a (1μg/ml and 10μg/ml) group and control group (0μg/ml). RNA-Seq was performed on total RNA of osteoclasts induced by C3a in 1μg/ml group and 0μg/ml group of 4 patients with NDMM. There were 184 differentially expressed genes that were detected by RNA-Seq analysis. KEGG Pathway enrichment bubble chart shows C3a may through Phosphoinositide 3-kinase (PI3K) signaling pathways (including PI3K-Akt pathway and AKT-independent signaling pathway) promotes the proliferation of osteoclast. Upregulated differentially expressed genes in this pathway among at least 3 patients with sequencing were validated by qRT-PCR and Western Blot. It was found that the relative expression level of Phosphoinositide dependent kinase-1 (PDK1) / Serum and glucocorticoid inducible protein kinases (SGK3) genes (median 2.078; 4.428) in C3a group (1μg/ml) was significantly higher than control group (0μg/ml) (median 1.336; 1.714) (P<0.001; P=0.001). The relative grayscale levels of PDK1/ P-SGK3 protein (1.785±0.323; 2.190±0.274) in C3a group (1μg/ml) was significantly stronger than control group (0μg/ml) (0.8653±0.588; 0.176±0.152) (P=0.034; P<0.001). Under the action of C3a in patients with NDMM, osteoclasts area per view in SGK inhibitor (EMD638683) 1μM group (39.244±9.089 %) and 10μM group (39.299±9.587 %) significantly reduced than control group (0μM) (54.884±12.837 %) (P<0.001; P<0.001), the relative expression of osteoclast related genes OSCAR/RANKL/TRAP/Cathepsin K in EMD638683 1μM group (median 0.869; 1.097; 0.902; 1.328) and 10μM group (median 0.703; 1.391; 0.843; 1.418) significantly decreased than control group (0μM) (median 2.270; 3.024; 2.208; 3.237) (1μM P=0.015; P=0.002; P=0.003; P=0.015; 10μM P=0.012; P=0.006; P<0.001; P=0.017), and the absorption area per view of osteoclast resorption pit in EMD638683 1μM (35.383±7.794 %) group and 10μM group (32.886±8.993 %) significantly reduced than control group (0μM) (49.358±11.856 %) (P < 0.001; P < 0.001). Conclusions:ComplementC3a activates osteoclasts by regulating the PI3K/PDK1/SGK3 pathway in patients with MM, thus leading to the occurrence of bone diseases. SGK inhibitor has a significant inhibitory effect on osteoclasts in patients with MM. This study provide important evidences for the search for new therapeutic targets and strategies for myeloma bone disease patients. Disclosures No relevant conflicts of interest to declare.

scholarly journals Transcriptome Analysis Reveals Dynamic Cultivar-Dependent Patterns of Gene Expression in Potato Spindle Tuber Viroid-Infected Pepper

Plants ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 2687
Author(s):  
Nikol Hadjieva ◽  
Elena Apostolova ◽  
Vesselin Baev ◽  
Galina Yahubyan ◽  
Mariyana Gozmanova
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Differentially Expressed Genes ◽  
Transcriptome Analysis ◽  
Quantitative Polymerase Chain Reaction ◽  
Potato Spindle Tuber Viroid ◽  
Fine Tuning ◽  
Differentially Expressed ◽  
Gene Ontology Term ◽  
Ontology Term

Potato spindle tuber viroid (PSTVd) infects various plants. PSTVd pathogenesis is associated with interference with the cellular metabolism and defense signaling pathways via direct interaction with host factors or via the transcriptional or post-transcriptional modulation of gene expression. To better understand host defense mechanisms to PSTVd infection, we analyzed the gene expression in two pepper cultivars, Capsicum annuum Kurtovska kapia (KK) and Djulunska shipka (DS), which exhibit mild symptoms of PSTVd infection. Deep sequencing-based transcriptome analysis revealed differential gene expression upon infection, with some genes displaying contrasting expression patterns in KK and DS plants. More genes were downregulated in DS plants upon infection than in KK plants, which could underlie the more severe symptoms seen in DS plants. Gene ontology enrichment analysis revealed that most of the downregulated differentially expressed genes in both cultivars were enriched in the gene ontology term photosynthesis. The genes upregulated in DS plants fell in the biological process of gene ontology term defense response. We validated the expression of six overlapping differentially expressed genes that are involved in photosynthesis, plant hormone signaling, and defense pathways by quantitative polymerase chain reaction. The observed differences in the responses of the two cultivars to PSTVd infection expand the understanding of the fine-tuning of plant gene expression that is needed to overcome the infection.

scholarly journals In Silico Analysis and Characterization of Differentially Expressed Genes to Distinguish Glioma Stem Cells from Normal Neural Stem Cells

2021 ◽  
Author(s):  
Urja Parekh ◽  
Mohit Mazumder ◽  
Harpreet Kaur ◽  
Elia Brodsky
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Neural Stem Cells ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Principal Component ◽  
Differentially Expressed ◽  
Glioma Stem Cells ◽  
Rna Seq ◽  
Bioinformatics Analyses

AbstractGlioblastoma multiforme (GBM) is a heterogeneous, invasive primary brain tumor that develops chemoresistance post therapy. Theories regarding the aetiology of GBM focus on transformation of normal neural stem cells (NSCs) to a cancerous phenotype or tumorigenesis driven via glioma stem cells (GSCs). Comparative RNA-Seq analysis of GSCs and NSCs can provide a better understanding of the origin of GBM. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of a total 40 RNA-seq samples including 20 NSC and 20 GSC, that were obtained from the NCBI-SRA (SRP200400). First, differential gene expression (DGE) analysis using DESeq2 revealed 358 significantly differentially expressed genes between GSCs and NSCs (padj. value <0.05, log2fold change ±3) with 192 upregulated and 156 downregulated genes in GSCs in comparison to NSCs. Subsequently, exploratory data analysis using the principal component analysis (PCA) based on key significant genes depicted the clear separation between both the groups. Further, the Hierarchical clustering confirmed the distinct clusters of GSC and NSC samples. Eventually, the biological enrichment analysis of the significant genes showed their enrichment in tumorigenesis pathways such as Wnt-signalling, VEGF- signalling and TGF-β-signalling pathways. Conclusively, our study depicted significant differences in the gene expression patterns between NSCs and GSCs. Besides, we also identified novel genes and genes previously unassociated with gliomagenesis that may prove to be valuable in establishing diagnostic, prognostic biomarkers and therapeutic targets for GBM.

scholarly journals Comparative Analysis of Mouse Decidualization Models at the Molecular Level

Genes ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 935 ◽  
Author(s):  
Chong Wang ◽  
Miao Zhao ◽  
Wen-Qian Zhang ◽  
Ming-Yu Huang ◽  
Can Zhu ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Mouse Models ◽  
Differentially Expressed Genes ◽  
Molecular Level ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Golden Standard ◽  
Transcriptomic Level ◽  
Similarity And Difference

The mouse is widely used to study decidualization and there are three well-established mouse models of decidualization, namely natural pregnancy decidualization (NPD), artificial decidualization (AD), and in vitro decidualization (IVD). However, the extent of similarity and difference between these models at the molecular level remains largely unknown. Here, we performed a comparative analysis using the RNA-seq approach. In the NPD model, which is thought to be the golden standard of mouse decidualization, we found a total of 5277 differentially expressed genes, with 3158 genes being up-regulated and 2119 genes being down-regulated. A total of 4294 differentially expressed genes were identified in the AD model: 1127 up-regulated genes and 3167 down-regulated genes. In comparison to NPD, 1977 genes were consistently expressed, whereas only 217 genes were inconsistently expressed, indicating that AD is a reliable model for mouse decidualization. In the IVD model, RNA-seq analysis revealed that 513 genes were up-regulated and 988 genes were down-regulated. Compared to NPD, 310 genes were consistently expressed, whereas 456 genes were inconsistently expressed. Moreover, although the decidualization marker Prl8a2 (prolactin family 8 subfamily a member 2) was up-regulated, the widely-used marker Alpl (alkaline phosphatase liver/bone/kidney) was down-regulated in the IVD model. Therefore, we suggest that the IVD model should be optimized to mimic NPD at the transcriptomic level. Our study contributes to an increase in the knowledge about mouse models of decidualization.

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