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 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 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.

Re-sequencing and transcriptomic analysis reveals rich DNA sequence variation and differential gene expression between varieties of Ziziphus jujuba

2021 ◽  
Author(s):  
Na Li ◽  
Yuqin Song ◽  
Jie Li ◽  
Ruijie Hao ◽  
Xinxin Feng ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Genetic Relationship ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Protein Translation ◽  
Differentially Expressed ◽  
Sequencing Analysis ◽  
Gene Structures ◽  
Relationship Of ◽  
Base Insertion

Abstract Background: Jujube is one of the characteristic fruit tree species in China. ‘Linhuang No. 1’, a cracking-resistant cultivar, and ‘Muzao’, a cracking-susceptible cultivar, were selected as materials by previous study. Whole-genome re-sequencing and transcriptome of ‘Linhuang No. 1’ and ‘Muzao’ allow the screening out of differently expressed genes with different gene structures between them. It could be helpful in explaining divergence/similarity of cracking resistance between the two cultivars. Results: There are 664,129 mutation sites between ‘Linhuang No. 1’ and ‘Muzao’ by re-sequencing. To determine the genetic relationship of ‘Linhuang 1’, ‘Muzao’ and reference genome ‘Dongzao’, the characteristic mutation sites were analyzed by principal component analysis. The genetic relationship between ‘Linhuang No. 1’ and ‘Muzao’ was closer than that with ‘Dongzao’. A total of 431 differentially expressed genes was screened by transcriptomics, and 19 differentially expressed genes were screened by combining the transcriptomics with re-sequencing analysis. LOC107427052 (encoding nitrite reductase) was determined by KEGG enrichment analysis for further study. Conclusions: The large base insertion was not in the domain region of the LOC107427052 gene CDS region. As verified by the finding that the base insertion did not affect protein translation. Our study has laid a foundation for the analysis of genetic information and the comparative nitrite metabolism of ‘Linhuang No. 1’ and ‘Muzao’.

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.

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.

HUBUNGAN KEPADATAN BIVALVIA DENGAN PARAMETER LINGKUNGAN DI PESISIR TANJUNG PURA KABUPATEN BANGKA TENGAH

2020 ◽  
Vol 13 (2) ◽  
pp. 112-121
Author(s):  
Sudiyar . ◽  
Okto Supratman ◽  
Indra Ambalika Syari
Keyword(s):  
Negative Impact ◽  
Principal Component ◽  
Environmental Parameters ◽  
Data Retrieval ◽  
Distribution Patterns ◽  
Random System ◽  
System Method ◽  
Relationship Of ◽  
The Relationship ◽  
Anadara Granosa

The destructive fishing feared will give a negative impact on the survival of this organism. This study aims to analyze the density of bivalves, distribution patterns, and to analyze the relationship of bivalves with environmental parameters in Tanjung Pura village. This research was conducted in March 2019. The systematic random system method was used for collecting data of bivalves. The collecting Data retrieval divided into five research stasions. The results obtained 6 types of bivalves from 3 families and the total is 115 individuals. The highest bivalve density is 4.56 ind / m², and the lowest bivalves are located at station 2,1.56 ind / m²,  The pattern of bivalve distribution in the Coastal of Tanjung Pura Village is grouping. The results of principal component analysis (PCA) showed that Anadara granosa species was positively correlated with TSS r = 0.890, Dosinia contusa, Anomalocardia squamosa, Mererix meretrix, Placamen isabellina, and Tellinella spengleri were positively correlated with currents r = 0.933.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Phytophthora infestans Sporangia Produced in Culture and on Tomato Leaflet Lesions Show Marked Differences in Indirect Germination Rates, Aggressiveness, and Global Transcription Profiles

2019 ◽  
Vol 32 (5) ◽  
pp. 515-526 ◽  
Author(s):  
William E. Fry ◽  
Sean P. Patev ◽  
Kevin L. Myers ◽  
Kan Bao ◽  
Zhangjun Fei
Keyword(s):  
Phytophthora Infestans ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Moist Chamber ◽  
Field Isolates ◽  
Rxlr Effectors ◽  
Transcription Profiles ◽  
Independent Field ◽  
Pure Cultures

Sporangia of Phytophthora infestans from pure cultures on agar plates are typically used in lab studies, whereas sporangia from leaflet lesions drive natural infections and epidemics. Multiple assays were performed to determine if sporangia from these two sources are equivalent. Sporangia from plate cultures showed much lower rates of indirect germination and produced much less disease in field and moist-chamber tests. This difference in aggressiveness was observed whether the sporangia had been previously incubated at 4°C (to induce indirect germination) or at 21°C (to prevent indirect germination). Furthermore, lesions caused by sporangia from plates produced much less sporulation. RNA-Seq analysis revealed that thousands of the >17,000 P. infestans genes with a RPKM (reads per kilobase of exon model per million mapped reads) >1 were differentially expressed in sporangia obtained from plate cultures of two independent field isolates compared with sporangia of those isolates from leaflet lesions. Among the significant differentially expressed genes (DEGs), putative RxLR effectors were overrepresented, with almost half of the 355 effectors with RPKM >1 being up- or downregulated. DEGs of both isolates include nine flagellar-associated genes, and all were down-regulated in plate sporangia. Ten elicitin genes were also detected as DEGs in both isolates, and nine (including INF1) were up-regulated in plate sporangia. These results corroborate previous observations that sporangia produced from plates and leaflets sometimes yield different experimental results and suggest hypotheses for potential mechanisms. We caution that use of plate sporangia in assays may not always produce results reflective of natural infections and epidemics.

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