scholarly journals Identification and comparison of circular RNAs in preeclampsia

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11299
Author(s):  
Zepeng Ping ◽  
Ling Ai ◽  
Huaxiang Shen ◽  
Xing Zhang ◽  
Huling Jiang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Gestational Hypertension ◽  
Interaction Analysis ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Mortality And Morbidity ◽  
Specific Syndrome

Background Preeclampsia (PE) is a pregnancy-specific syndrome, belongs to the gestational hypertension diseases category and is considered among the causes of maternal and perinatal mortality and morbidity. However, the pathogenesis of PE is still vague. Methods In the present study, the circular RNA (circRNA) expression patterns of normal pregnant women and PE patients were investigated using whole RNA sequencing. Results A total of 151 differential expressed circRNAs were identified including 121 upregulated and 30 downregulated ones. Functional and pathway enrichment analysis was conducted on the differentially expressed circRNAs using Gene Ontology and KEGG databases. The results of this analysis indicated that several crucial biological processes and pathways were enriched in PE patients. circRNA–microRNA (miRNA) interaction analysis indicated that the reported differentially expresse circRNAs may be associated with some regulatory functions through miRNAs in PE patients. Two ceRNAs networks were constructed according to the targeting relationship between circRNAs/miRNAs and miRNAs/mRNAs. One sub-network contained one upregulated circRNA, four downregulated miRNAs and five upregulated mRNAs, and another sub-network contained 10 downregulated circRNAs, 21 upregulated miRNAs and 15 downregulated mRNAs. Conclusion CircRNA expression patterns have been investigated and this analysis revealed their potential regulatory mechanisms in PE patients. We constructed the ceRNAs (competing endogenous RNA) to reveal the potential molecular roles of dysregulated circRNAs in the PE patients using RNA sequencing data. circRNA_13301 was the only one upregulated circRNA in ceRNA being targeted by four miRNAs.

scholarly journals SMARTer single cell total RNA sequencing

2018 ◽  
Author(s):  
Verboom Karen ◽  
Everaert Celine ◽  
Bolduc Nathalie ◽  
Livak J. Kenneth ◽  
Yigit Nurten ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Transcript Level ◽  
Cellular Heterogeneity ◽  
Circular Rnas ◽  
Rna Seq ◽  
Sequencing Data ◽  
Total Rna ◽  
Sequencing Experiment

AbstractSingle cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3’ end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.

scholarly journals RNA-sequencing data-driven dissection of human plasma cell differentiation reveals new potential transcription regulators

Leukemia ◽  
2021 ◽  
Author(s):  
Alboukadel Kassambara ◽  
Laurie Herviou ◽  
Sara Ovejero ◽  
Michel Jourdan ◽  
Coraline Thibaut ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Continuous Production ◽  
Expression Patterns ◽  
Gene Clusters ◽  
Transcriptional Networks ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Sequencing Data

AbstractPlasma cells (PCs) play an important role in the adaptive immune system through a continuous production of antibodies. We have demonstrated that PC differentiation can be modeled in vitro using complex multistep culture systems reproducing sequential differentiation process occurring in vivo. Here we present a comprehensive, temporal program of gene expression data encompassing human PC differentiation (PCD) using RNA sequencing (RNA-seq). Our results reveal 6374 differentially expressed genes classified into four temporal gene expression patterns. A stringent pathway enrichment analysis of these gene clusters highlights known pathways but also pathways largely unknown in PCD, including the heme biosynthesis and the glutathione conjugation pathways. Additionally, our analysis revealed numerous novel transcriptional networks with significant stage-specific overexpression and potential importance in PCD, including BATF2, BHLHA15/MIST1, EZH2, WHSC1/MMSET, and BLM. We have experimentally validated a potent role for BLM in regulating cell survival and proliferation during human PCD. Taken together, this RNA-seq analysis of PCD temporal stages helped identify coexpressed gene modules with associated up/downregulated transcription regulator genes that could represent major regulatory nodes for human PC maturation. These data constitute a unique resource of human PCD gene expression programs in support of future studies for understanding the underlying mechanisms that control PCD.

scholarly journals Bioinformatics Analysis of circRNA Expression and Construction of “circRNA-miRNA-mRNA” Competing Endogenous RNAs Networks in Bipolar Disorder Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Yonghui Fu ◽  
Wenfeng He ◽  
Chaoxiong Zhou ◽  
Xia Fu ◽  
Qigen Wan ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Rna Sequencing ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Control Group ◽  
Sequencing Data ◽  
Competitive Endogenous Rnas ◽  
Competing Endogenous Rnas ◽  
Polymerase Chain

Bipolar disorder (BD) is a severe mood disorder disease in China, and its underlying pathogenesis remains unknown. Circular RNAs (circRNAs) have been reported to play a key role in mental disorders and can be used as competitive endogenous RNAs (ceRNAs). However, little is known about the correlation of circRNAs with BD. In this study, Deep RNA sequencing was used to identify differentially expressed circRNAs (DE-circRNAs) and differentially expressed mRNAs (DE-mRNAs) between BD patients and a control group. Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to validate the differentially expressed RNAs (DE-RNAs). In all 9,593 circRNAs and 20,030 mRNAs were found in the two groups of specimens, among which 50 DE-circRNAs and 244 DE-mRNAs were significantly upregulated, and 44 DE-circRNAs and 294 DE-mRNAs were significantly downregulated. Based on the regulatory mechanism of ceRNAs, circRNAs can directly bind microRNAs (miRNAs) to affect mRNA expression, and the expression trends of circRNAs and mRNAs are consistent. According to this mechanism, we constructed two ceRNA networks by using the RNA sequencing data. The function of these DE-circRNAs was further elucidated by enrichment analysis. In summary, the present study showed that the circRNA expression profile of BD patients is altered, and a ceRNA regulatory network was constructed, which provided a hypothesis about the pathogenesis of BD.

scholarly journals RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage

2018 ◽  
Vol 78 (2) ◽  
pp. 270-277 ◽  
Author(s):  
Rodrigo Coutinho de Almeida ◽  
Yolande F M Ramos ◽  
Ahmed Mahfouz ◽  
Wouter den Hollander ◽  
Nico Lakenberg ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Messenger Rna ◽  
Enrichment Analysis ◽  
Integrated Approach ◽  
Nervous System Development ◽  
Regulatory Mechanisms ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Pathway Enrichment ◽  
Mrna Targets

ObjectiveTo uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.MethodsWe performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.ResultsWe found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10−5). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.ConclusionsBy an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

scholarly journals Single-cell Transcriptome Analysis Uncovers Heterogeneity and Key Regulators in Ibrutinib-resistant Chronic Lymphocytic Leukemia

2021 ◽  
Author(s):  
Hui Jin ◽  
Bin Huang ◽  
Zijuan Wu ◽  
Huayuan Zhu ◽  
Hanning Tang ◽  
...  
Keyword(s):  
Chronic Lymphocytic Leukemia ◽  
Single Cell ◽  
Rna Sequencing ◽  
Kinase Inhibitor ◽  
Enrichment Analysis ◽  
Lymphocytic Leukemia ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Ibrutinib Resistance

Abstract BackgroundIbrutinib as a widely used Bruton’s tyrosine kinase inhibitor has shown outstanding value in clinical therapy for chronic lymphocytic leukemia (CLL). However, the bottleneck of ibrutinib resistance has caused widespread concerns, necessitating the exploration of novel targets. MethodsSingle-cell RNA sequencing (scRNA-seq) was used to characterize the heterogeneity of ibrutinib-sensitive (IBS) and -resistant (IBR) CLL patients and single-cell stemness estimation and metabolic pathway enrichment analysis were performed. Lectin galactoside-binding soluble 1 (LGALS1) and lymphocyte-activating gene 3 (LAG3) were screened as key factors by analyzing the RNA-sequencing data at bulk and single cell levels. Subsequently, pseudo-time trajectory analysis and gene set enrichment analysis were conducted. In addition, an IBR CLL cell line (MEC1-IR) was generated and RT-qPCR, western blotting, and immunofluorescence were performed to detect the expression of LGALS1 and LAG3. OTX008, a selective inhibitor of galectin-1 (Gal-1, encoded by LGALS1) was assessed in CLL cells and CCK8 and apoptotic assays were conducted for functional analysis.ResultsIBR CLL showed significantly different characteristics from IBS in terms of transcriptome expression and energy metabolism. LGALS1 and LAG3 were gradually upregulated in B cells along the evolution trajectory from IBS to IBR. Their expression was verified to be closely related to the prognosis of CLL, as well as sensitivity to ibrutinib. OTX008 could effectively suppress the proliferation and induce apoptosis of CLL cells, especially for those with ibrutinib resistance.ConclusionsAn LGALS1 and LAG3 gene panel is a promising indicator of ibrutinib resistance and a prognostic marker for CLL. OTX008 displays pronounced performance against CLL cells, especially with IBR, and might represent a novel therapeutic strategy for CLL.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

scholarly journals Identification of candidate genes controlling chilling tolerance of rice in the cold region at the booting stage by BSA-Seq and RNA-Seq

2020 ◽  
Vol 7 (11) ◽  
pp. 201081
Author(s):  
Zhenhua Guo ◽  
Lijun Cai ◽  
Zhiqiang Chen ◽  
Ruiying Wang ◽  
Lanming Zhang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Bulked Segregant Analysis ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Chilling Tolerance ◽  
Pathway Enrichment Analysis ◽  
Potential Candidate ◽  
Rice Varieties ◽  
Booting Stage ◽  
F2 Population

Rice is sensitive to low temperatures, specifically at the booting stage. Chilling tolerance of rice is a quantitative trait loci that is governed by multiple genes, and thus, its precise identification through the conventional methods is an arduous task. In this study, we investigated the candidate genes related to chilling tolerance at the booting stage of rice. The F2 population was derived from Longjing25 (chilling-tolerant) and Longjing11 (chilling-sensitive) cross. Two bulked segregant analysis pools were constructed. A 0.82 Mb region containing 98 annotated genes on chromosomes 6 and 9 was recognized as the candidate region associated with chilling tolerance of rice at the booting stage. Transcriptomic analysis of Longjing25 and Longjing11 revealed 50 differentially expressed genes (DEGs) on the candidate intervals. KEGG pathway enrichment analysis of DEGs was performed. Nine pathways were found to be enriched, which contained 10 DEGs. A total of four genes had different expression patterns or levels between Longjing25 and Longjing11. Four out of the 10 DEGs were considered as potential candidate genes for chilling tolerance. This study will assist in the cloning of the candidate genes responsible for chilling tolerance and molecular breeding of rice for the development of chilling-tolerant rice varieties.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

Quantitative proteomics analysis of FFPE tumor samples reveals the influences of novel targeting nanobubbles conjugated with NET-1 siRNA on tetraspanin protein involved in HCC

2020 ◽  
Author(s):  
Bolin Wu ◽  
Haitao Shang ◽  
Xitian Liang ◽  
Huajing Yang Huajing Yang ◽  
Hui Jing ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Differentially Expressed Proteins ◽  
Label Free ◽  
Protein Protein Interaction ◽  
Study Results ◽  
Ffpe Tumor

Abstract Background: Hepatocellular carcinoma (HCC) poses a severe threat to human health. The NET-1 protein has been proved to be strongly associated with HCC proliferation and metastasis in our previous study. Methods: Here, we developed a label-free proteome mass spectrometry workflow to analyze formalin-fixed and paraffin-embedded HCC xenograft samples collected in our previous study. Results: The result showed that 78 proteins were differentially expressed after NET-1 protein inhibited. Among them, the expression of 61 proteins up-regulated and the expression of 17 proteins were significantly down-regulated. Of the differentially expressed proteins, the vast majority of Gene Ontology enrichment terms belong to the biological process. The KEGG pathway enrichment analysis showed that the 78 differentially expressed proteins significantly enriched in 45 pathways. We concluded that the function of the NET-1 gene is not only to regulate HCC but also to participate in a variety of biochemical metabolic pathways in the human body. Furthermore, the protein-protein interaction analysis indicated that the interactions of differentially expressed proteins are incredibly sophisticated. All the protein-protein interactions happened after the NET-1 gene has been silenced. Conclusions: Finally, our study also provides a useful proposal for targeted therapy based on tetraspanin proteins to treat HCC, and further mechanism investigations are needed to reveal a more detailed mechanism of action for NET-1 protein regulation of HCC.

scholarly journals Single-Cell RNA Sequencing Unveils Unique Transcriptomic Signatures of Organ-Specific Endothelial Cells

Circulation ◽  
2020 ◽  
Vol 142 (19) ◽  
pp. 1848-1862 ◽  
Author(s):  
David T. Paik ◽  
Lei Tian ◽  
Ian M. Williams ◽  
Siyeon Rhee ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Receptor Expression ◽  
Transcriptional Networks ◽  
Sequencing Data ◽  
Tissue Specific ◽  
Functional Relationships ◽  
Single Cell Rna Sequencing

Background: Endothelial cells (ECs) display considerable functional heterogeneity depending on the vessel and tissue in which they are located. Whereas these functional differences are presumably imprinted in the transcriptome, the pathways and networks that sustain EC heterogeneity have not been fully delineated. Methods: To investigate the transcriptomic basis of EC specificity, we analyzed single-cell RNA sequencing data from tissue-specific mouse ECs generated by the Tabula Muris consortium. We used a number of bioinformatics tools to uncover markers and sources of EC heterogeneity from single-cell RNA sequencing data. Results: We found a strong correlation between tissue-specific EC transcriptomic measurements generated by either single-cell RNA sequencing or bulk RNA sequencing, thus validating the approach. Using a graph-based clustering algorithm, we found that certain tissue-specific ECs cluster strongly by tissue (eg, liver, brain), whereas others (ie, adipose, heart) have considerable transcriptomic overlap with ECs from other tissues. We identified novel markers of tissue-specific ECs and signaling pathways that may be involved in maintaining their identity. Sex was a considerable source of heterogeneity in the endothelial transcriptome and we discovered Lars2 to be a gene that is highly enriched in ECs from male mice. We found that markers of heart and lung ECs in mice were conserved in human fetal heart and lung ECs. We identified potential angiocrine interactions between tissue-specific ECs and other cell types by analyzing ligand and receptor expression patterns. Conclusions: We used single-cell RNA sequencing data generated by the Tabula Muris consortium to uncover transcriptional networks that maintain tissue-specific EC identity and to identify novel angiocrine and functional relationships between tissue-specific ECs.

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