Journal: BioMed Research International

Article Title: Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

doi: 10.1155/2017/5936171

Figure Lengend Snippet: circRNA profiles differentiate the normal group from model group. (a) Principal component analysis (PCA) shows the difference between normal and model groups. (b) Scatter plots assess the variation of circRNA expression between two groups. The values plotted on x and y axes are the normalized signal values of each group (log2 scaled). Dots above the top green line and below the bottom green line represent differentially expressed circRNAs. (c, d) Unsupervised hierarchical clustering (c) and volcano plot (d) demonstrate the differential expression of circRNAs during hepatic steatosis. Both downregulated (green) and upregulated (red) circRNAs were visualized in the cluster. In similar, the red points in volcano plot represent the differentially expressed circRNAs with statistical significance. (e, f) Validation of the upregulated (e) and downregulated circRNAs (f) using QPCR. (g) The results of QPCR exhibit well consistence with those of microarray. Pairwise scatter plots reflect the fold changes (log2 transformed) of both microarray (horizontal axis) and the QPCR (vertical axis). The R stands for linear correlation coefficient. The presented results are expressed as means ± SD. ∗∗ P < 0.01.

Article Snippet: To remove linear RNAs and enrich circRNA, total RNA from each sample was treated with Rnase R. circRNA was then transcribed into fluorescent cRNA by random primer according to the Arraystar Super RNA Labeling protocol (Arraystar, Inc., USA) and hybridized onto the Arraystar Human circRNA Arrays V2.0 (Arraystar, Inc., USA) at 65°C for 17 hours.

Techniques: Expressing, Quantitative Proteomics, Biomarker Discovery, Microarray, Transformation Assay

Journal: BioMed Research International

Article Title: Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

doi: 10.1155/2017/5936171

Figure Lengend Snippet: Predicted targets of top-20 differentially expressed circRNAs.

Article Snippet: To remove linear RNAs and enrich circRNA, total RNA from each sample was treated with Rnase R. circRNA was then transcribed into fluorescent cRNA by random primer according to the Arraystar Super RNA Labeling protocol (Arraystar, Inc., USA) and hybridized onto the Arraystar Human circRNA Arrays V2.0 (Arraystar, Inc., USA) at 65°C for 17 hours.

Techniques:

Journal: BioMed Research International

Article Title: Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

doi: 10.1155/2017/5936171

Figure Lengend Snippet: Enumeration data of differentially expressed circRNAs and target miRNAs/mRNAs.

Article Snippet: To remove linear RNAs and enrich circRNA, total RNA from each sample was treated with Rnase R. circRNA was then transcribed into fluorescent cRNA by random primer according to the Arraystar Super RNA Labeling protocol (Arraystar, Inc., USA) and hybridized onto the Arraystar Human circRNA Arrays V2.0 (Arraystar, Inc., USA) at 65°C for 17 hours.

Techniques:

Journal: BioMed Research International

Article Title: Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

doi: 10.1155/2017/5936171

Figure Lengend Snippet: circRNA-miRNA-mRNA regulatory network uncovers the circRNA_021412-miR-1972-LPIN1 signaling underlying circRNAs' effects. (a) The circRNA-miRNA-mRNA network related to transcriptional regulation. Red cycles, violet squares, and blue cycles represent circRNAs, miRNAs, and mRNAs, respectively. The size of each symbol reflects its degree, which is scored by the number of downstream targets. (b) circRNA_021412-miR-1972-LPIN1 signaling within the circRNA-miRNA-mRNA network is recognized to underlie the actions of circRNAs. (c) The circRNA_021412-miR-1972-LPIN1 signaling controls the pathway of lipid degradation via PPAR α -induced ACSLs expression.

Article Snippet: To remove linear RNAs and enrich circRNA, total RNA from each sample was treated with Rnase R. circRNA was then transcribed into fluorescent cRNA by random primer according to the Arraystar Super RNA Labeling protocol (Arraystar, Inc., USA) and hybridized onto the Arraystar Human circRNA Arrays V2.0 (Arraystar, Inc., USA) at 65°C for 17 hours.

Techniques: Expressing

Journal: BioMed Research International

Article Title: Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

doi: 10.1155/2017/5936171

Figure Lengend Snippet: Diagram of circRNA_021412-based regulation of hepatic steatosis. Arrow, blunt-headed line, and red cross represent effects of activation, inhibition, and blocking, respectively.

Article Snippet: To remove linear RNAs and enrich circRNA, total RNA from each sample was treated with Rnase R. circRNA was then transcribed into fluorescent cRNA by random primer according to the Arraystar Super RNA Labeling protocol (Arraystar, Inc., USA) and hybridized onto the Arraystar Human circRNA Arrays V2.0 (Arraystar, Inc., USA) at 65°C for 17 hours.

Techniques: Activation Assay, Inhibition, Blocking Assay

Journal: Frontiers in Oncology

Article Title: CircHADHA-augmented autophagy suppresses tumor growth of colon cancer by regulating autophagy-related gene via miR-361

doi: 10.3389/fonc.2022.937209

Figure Lengend Snippet: Plasma circRNA expression pattern in healthy individuals and colon polyp and colon cancer patients. (A) The endoscopic diagnosis of healthy individuals (left panel) and colon polyp (central panel) and colon cancer (right panel) patients. (B) The schematic diagram of Arraystar assay performance in plasma circRNAs. (C) The differential expression of plasma circRNAs in polyp patients ( N = 5) and healthy individuals ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between polyp patients and healthy individuals (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between polyp patients and healthy individuals (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (D) The differential expression of plasma circRNAs in colon cancer ( N = 5) and colon polyp patients ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between colon cancer and colon polyp patients (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between colon cancer and colon polyp patients (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (E) The differential expression of plasma circRNAs in colon cancer patients ( N = 5) and healthy individuals ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between colon cancer patients and healthy individuals (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between cancer patients and healthy individuals (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (F–H) The composition of types in detectable circRNAs. (F) The composition of circRNA types in polyp and colon cancer patients. (I) The Venn analysis between upregulated circRNAs from colon cancer patients compared with colon polyp patients and downregulated circRNAs from colon polyp patients compared with healthy individuals. (J) The Venn analysis between downregulated circRNAs from colon cancer patients compared with colon polyp patients and upregulated circRNAs from colon polyp patients compared with healthy individuals. (K) The potential circRNA candidates were validated by performing real-time PCR in plasma from healthy individuals ( N = 15) and colon polyp ( N = 15) and colon cancer ( N = 15) patients. (L) The schematic diagram of circHADHA dynamic alteration in healthy individuals and colon polyp and colon cancer patients. **** P < 0.0001; ns, no significant difference.

Article Snippet: We collected plasma from healthy individuals and colon polyp and colon cancer patients confirmed by endoscopic diagnosis ( ) and analyzed 2,162 human circRNAs by Arraystar ( ).

Techniques: Clinical Proteomics, Expressing, Biomarker Discovery, Quantitative Proteomics, Real-time Polymerase Chain Reaction

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The experimental scheme of the study. The discovery cohort was composed of two TB patients and two age- and gender-matched healthy controls: one young male case-control pair and one senior female case-control pair. PBMC circRNA expression in the discovery cohort was profiled by both rRNA-depleted RNA-seq and a circRNA expression microarray. We aggregated circRNAs into pathway-level mechanisms using KEGG pathway definitions. Pathways with significant circRNA dysregulation were prioritized by performing a paired Wilcoxon signed-rank test between paired control and TB samples. A molecular signature was developed based on the dysregulated circRNAs within the prioritized pathways. This circRNA signature was further validated by qRT-PCR in a validation cohort with 11 healthy controls and 10 TB patients.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Control, Expressing, RNA Sequencing, Microarray, Quantitative RT-PCR, Biomarker Discovery

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: Landscape of PBMC circRNA expression. (a) A Venn diagram of the parental genes with circRNA transcripts among PBMCs, platelets, RBCs, and whole blood. (b) Distribution of log 2 -transformed TPM values of circular transcripts in PBMCs, platelets, RBCs, and whole blood. (c) The fraction of RNA-seq reads from coding linear, non-coding linear, and circular transcripts. (d) The cumulative distribution of TPM values of circular transcripts. A significantly increased circRNA TPM was observed in the TB patients compared with the healthy controls. The P -values were computed by the Kolmogorov-Smirnov test.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Expressing, Transformation Assay, RNA Sequencing

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The KEGG pathways enriched by upregulated circRNAs. A paired Wilcoxon test was applied to identify the KEGG pathways enriched by dysregulated circRNAs in young and senior TB patients. (a) The correlation in Z -scores (computed by a paired Wilcoxon test) between young and senior case-control pairs. Each dot represents one KEGG pathway. The red points stand for the pathways with circular transcripts commonly upregulated in both young and senior TB patients. (b) Paired comparison of circRNA expression in the five prioritized KEGG pathways. (c) Comparison of the fraction of circRNA reads in the five pathways between healthy controls and TB patients.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Control, Comparison, Expressing

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: Technical validation of the five prioritized KEGG pathways using a circRNA expression microarray. Total RNA was treated with RNase R to remove linear transcripts and then subject to microarray hybridization.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Biomarker Discovery, Expressing, Microarray, Hybridization

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The 7-circRNA signature.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques:

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The 7-circRNA signature. (a) Expression heatmap of the circRNAs within the 7-circRNA signature in the discovery cohort. The expression measured by both RNA-seq and circRNA microarray is displayed. (b) Comparison of the expression levels of the 7-circRNA signature between the healthy controls and TB patients in the validation cohort. The error bars represent the standard error of the mean. (c) Principal component analysis of the 7-circRNA signature. PC1: the first principal component; PC2: the second principal component. (d) Comparison of the circRNA-based TB index between the healthy controls and TB patients in the validation cohort. (e) The ROC curve of the TB index in distinguishing TB patients from healthy controls. The light blue area indicates the confidence interval of the ROC curve.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Expressing, RNA Sequencing, Microarray, Comparison, Biomarker Discovery

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: The expression of circRNA SCARB1, mature miR-497 and miR-497 precursor was altered in HCC. HCC and paired non-tumor tissues were collected from the 64 HCC patients included in this study, and the expression of circRNA SCARB1 ( A ), mature miR-497 ( B ) and miR-497 precursor ( C ) in these tissue samples was determined by RT-qPCR. Average values of three technical replicates were used to express gene expression data in paired HCC and non-tumor tissues, ** p < 0.01.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Expressing, Quantitative RT-PCR, Gene Expression

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: The Correlations Between Clinicopathological Variables and the Expression of circRNA SCARB1 in HCC

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Expressing, Infection

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: CircRNA SCARB1 and mature miR-497 were inversely correlated across HCC samples. Pearson’s correlation coefficient analysis was used to analyze the correlations between circRNA SCARB1 and mature miR-497 ( A ) or miR-497 precursor ( B ) across HCC tissue samples.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques:

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 downregulated mature miR-497 in HCC cells. To explore the effects of overexpression of circRNA SCARB1 on the maturation of miR-497, SNU-423 and SNU-387 cells were transfected with either circRNA SCARB1 expression vector or miR-497 mimic, followed by the confirmation of transfections at 48 h post-transfection by RT-qPCR ( A ). The effects of overexpression of circRNA SCARB1 of the expression of mature miR-497 ( B ) and miR-497 precursor ( C ), as well as the effects of the transfection of miR-497 mimic on circRNA SCARB1 expression ( D ) were also analyzed by RT-qPCR. Mean ± SD values were used to express data of 3 biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, Transfection, Expressing, Plasmid Preparation, Quantitative RT-PCR, In Vitro

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 increased HCC cell proliferation through miR-497. CCK-8 assay was performed to analyze the effects of overexpression of circRNA SCARB1 and miR-497 on the proliferation of SNU-423 ( A ) and SNU-387 cells ( B ). Mean ± SD values were used to express data of three biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, CCK-8 Assay, In Vitro

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 increased HCC cell migration through miR-497. Transwell assay was conducted to analyze the effects of overexpression of circRNA SCARB1 and miR-497 on the migration of SNU-423 ( A and C ) and SNU-387 cells ( B and D ). Mean ± SD values were used to express data of three biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, Migration, Transwell Assay, In Vitro