Mirna qc tool software

Manufactured by Thermo Fisher Scientific

Sourced in United States

The MiRNA QC Tool software is a bioinformatics tool designed to evaluate the quality of miRNA sequencing data. It provides users with metrics and visualizations to assess the integrity and consistency of miRNA samples.

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18 protocols using mirna qc tool software

Microarray Data QC and Analysis

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The statistical analysis was performed by Transcriptome Analysis Console (TAC) software (Thermo Fisher Scientific).
To survey outliers that could disturb the dataset, a Principal Component Analysis (implemented by means of R statistical software) was performed and its visualization, which led to the knowledge of which subjects needed to be excluded from the dataset. MicroRNA probe outliers were defined from the manufacturer's instructions (Affymetrix, USA), and further analysis included data summarization, normalization, and quality control using the web-based miRNA QC Tool software (Affymetrix).
The microarray data has been submitted and assigned a GEO omnibus accession number GSE85105.

Giglio S., Annibali V., Cirombella R., Faruq O., Volinia S., De Vitis C., Pesce M., Caserta D., Pettinato A., Fraggetta F, & Vecchione A. (2019). miRNAs as Candidate Biomarker for the Accurate Detection of Atypical Endometrial Hyperplasia/Endometrial Intraepithelial Neoplasia. Frontiers in Oncology, 9, 526.

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miRNA Profiling in T98G Cells

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miRNA expression profiles were conducted in T98G cell line DPG exposure (24 mM; 48 h of DPG treatment) (14 (link)) and control cells. Analyses were performed using Affymetrix^® GeneChip miRNA 2.0 array (Affymetrix, Santa Clara, CA, USA), which detects 2,578 known human miRNAs (miRBase v.15; Affymetrix). Total RNA was labeled with FlashTag Biotin HSR, hybridized with the arrays, then washed with PBS, stained, and scanned according to Affymetrix GeneChip Command Console software. The miRNA QC Tool software (Affymetrix) was used for data summarization, normalization, and quality control.

Bonafé G.A., dos Santos J.S., Fernandes A.M., Ziegler J.V., Marson F.A., Rocha T., Carvalho P.D, & Ortega M.M. (2022). Anti-Migratory Effect of Dipotassium Glycyrrhizinate on Glioblastoma Cell Lines: Microarray Data for the Identification of Key MicroRNA Signatures. Frontiers in Oncology, 12, 819599.

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Transcriptional Profiling of DIS3-Depleted Myeloma Cells

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Total RNA from RPMI-8226 and KMS12-BM cell lines knocked-down with a scrambled shRNA (control sh) or DIS3 shRNA (DIS3 sh) was collected 72 h after infection and extracted with TRIzol^® RNA Isolation Reagent. Quality assessment was performed using a Bioanalyzer Agilent 2100 (Agilent, Santa Clara, CA, USA). Total RNA samples were processed using the FlashTag labeling kit and then hybridized to the GeneChip^® miRNA arrays v1.0 (Affymetrix Inc., Santa Clara, CA, USA), according to the Affymetrix recommended protocol. Expression values for 847 human miRNAs were extracted from CEL ﬁles using Affymetrix miRNA QC tool software (RMA normalized and log₂-transformed (31 (link))). Data were analyzed using the software dCHIP (http://biosun1.harvard.edu/complab/dchip). The microarray data have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE55246 (available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=orydwgscvrmpbaz&acc=GSE55246). Gene set enrichment analysis (GSEA) was performed as previously described (GSEA v2.0 at http://www.broad.mit.edu/gsea, (32 (link))) using gene set as permutation type and 1000 permutations and signal to noise as metric for ranking genes. miRNA families were derived from miRBase (http://www.mirbase.org). In line with GSEA default settings, only miRNA families including at least five members were included in the analysis.

Segalla S., Pivetti S., Todoerti K., Chudzik M.A., Giuliani E.C., Lazzaro F., Volta V., Lazarevic D., Musco G., Muzi-Falconi M., Neri A., Biffo S, & Tonon G. (2015). The ribonuclease DIS3 promotes let-7 miRNA maturation by degrading the pluripotency factor LIN28B mRNA. Nucleic Acids Research, 43(10), 5182-5193.

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miRNA Microarray Profiling Workflow

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The miRNA microarray profiling was performed using Affymetrix GeneChip miRNA arrays (Affymetrix, Inc., Santa Clara, CA, USA) according to the manufacturer's instructions. Briefly, 1 µg of total RNA was labeled by polyA polymerase addition using the Genisphere FlashTag HSR kit according to the manufacturer's instructions (Genisphere, Hatfield, PA, USA). The labeled RNA was hybridized as a probe to the Affymetrix miRNA array, according to the manufacturer's details. Standard Affymetrix array cassette staining, washing and scanning was performed using the post-hybridization kit (cat. no. 900720; Affymetrix) and GeneChip Scanner 3000 (Affymetrix, Inc.). Feature extraction was performed using Affymetrix Command Console software (v.1.2). The raw data were treated by the following workflow: Background detection, RMA global background correlation, quartile normalization, median polish and log2-transformation with miRNA QC tool software (Affymetrix).

TAO L., ZENG Y., WANG J., LIU Z., SHEN B., GE J., LIU Y., GUO Y, & QIU J. (2015). Differential microRNA expression in aristolochic acid-induced upper urothelial tract cancers ex vivo. Molecular Medicine Reports, 12(5), 6533-6546.

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Microarray Analysis of miRNA Expression

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Total RNA from frozen tissue of different groups was extracted using a mirVANA miRNA Isolation Kit (Ambion, Austin, TX, USA). The quality and integrity of total RNA was determined by capillary electrophoresis using the Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). Only RNA extracts with RNA integrity number values ≥ 6 underwent a further analysis. RNA was used in a GeneChip miRNA Array containing 46,228 probe sets representing 6703 miRNA sequences from the Sanger miRNA database (V.11) and an additional 922 sequences of Human snoRNA and scaRNA from the Ensembl database and snoRNABase (Affimetrix, Santa Clara, CA, USA) was used for microarray analysis according to manufacturer’s instructions.
Data files (.CEL) were analyzed with Partek Genomic Suite 6.6 software (Partex Inc., St. Louis, MO, USA). Input files were normalized with a robust multichip average (RMA) algorithm for gene array and analyzed with the web-based miRNA QC Tool software (www.affymetrix.com).

Muñoz-Hidalgo L., San-Miguel T., Megías J., Serna E., Calabuig-Fariñas S., Monleón D., Gil-Benso R., Cerdá-Nicolás M, & López-Ginés C. (2020). The Status of EGFR Modulates the Effect of miRNA-200c on ZEB1 Expression and Cell Migration in Glioblastoma Cells. International Journal of Molecular Sciences, 22(1), 368.

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Profiling miRNA expression in Kras-driven cancer

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GeneChip^® miRNA Array (Cat. No: 901325) was used to study the global expression profile of miRNAs at 25-week of Kras^G12D;Pdx-1-Cre mice and LSLKras^G12D mice. Two micrograms of total RNA from two floxed Kras^G12D (Kras^G12D;Pdx1-Cre) and two unfloxed LSL-Kras^G12D (LSL Kras^G12D) animals were labeled with the FlashTag Biotin RNA Labeling Kit for Affymetrix GeneChip^® miRNA arrays (Genisphere, Hatfield, PA, USA) and hybridized on Affymetrix GeneChip^® miRNA arrays (Affymetrix, Santa Clara, CA, USA). Hybridization, washing, and scanning of the slides were done according to Affymetrix's recommendations (Fluidics Protocol FS450_0003). Data was extracted from the images, quintile normalized, summarized (median polish) and log2-transformed with the miRNA QC tool software from Affymetrix.

Rachagani S., Macha M.A., Menning M.S., Dey P., Pai P., Smith L.M., Mo Y.Y, & Batra S.K. (2015). Changes in microRNA (miRNA) expression during pancreatic cancer development and progression in a genetically engineered KrasG12D;Pdx1-Cre mouse (KC) model. Oncotarget, 6(37), 40295-40309.

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Microarray Analysis of RNA Quality

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RNA quality was evaluated using Agilent 2100 bioanalyser (Agilent Technologies) prior to microarray experiment. All the samples had rRNA Ratio (28s/18s) over 1.8 and RNA Integrity Number (RIN) over 8.0 (Figure 8). The experiments were performed in the Centre for Genomic Sciences, The University of Hong Kong. Data were analyzed by miRNA QC Tool software (Affymetrix). MicroRNA with P < 0.05 and 1.5-fold difference were considered as deregulated microRNA in LSCC.

Li J.Z., Gao W., Lei W.B., Zhao J., Chan J.Y., Wei W.I., Ho W.K, & Wong T.S. (2016). MicroRNA 744-3p promotes MMP-9-mediated metastasis by simultaneously suppressing PDCD4 and PTEN in laryngeal squamous cell carcinoma. Oncotarget, 7(36), 58218-58233.

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MiRNA Differential Expression Analysis

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MiRNA probe outliers were defined as per the manufacturer’s instructions (Affymetrix) and further analyzed for data summarization, normalization and quality control by using the miRNA QC Tool software (www.affymetrix.com). To select the differentially expressed miRNAs, we used threshold values of ≥1.5 and ≤−1.5-fold change and a FDR significance level of <5 %. The data was Log2 transformed and median centered by miRNAs using the Adjust Data function of CLUSTER 3.0 software (Michiel de Hoon, Human Genome Center, University of Tokyo, Tokyo, Japan), then further analyzed with hierarchical clustering with average linkage. Finally, we performed tree visualization by using Java Treeview (Stanford University School of Medicine, Stanford, CA, USA).

Yu S., Geng Q., Pan Q., Liu Z., Ding S., Xiang Q., Sun F., Wang C., Huang Y, & Hong A. (2016). MiR-690, a Runx2-targeted miRNA, regulates osteogenic differentiation of C2C12 myogenic progenitor cells by targeting NF-kappaB p65. Cell & Bioscience, 6, 10.

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Profiling miRNA Expression in PTSD Patients

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Total RNA, including miRNA and other small RNA molecules, were isolated from randomized PBMC samples of PTSD patients and normal controls, using miRNeasy Mini kit and following the protocol of the company (Qiagen, Valencia, CA). The RNA integrity was verified using Agilent 2100 BioAnalyzer (Agilent Tech, Palo Alto, CA). Next, total RNA samples were subjected to miRNA array hybridization assay using Affymetrix miRNA-v1 gene chip according to the manufacturer's instructions. The miRNA array data were analyzed with Affymetrix miRNA QC tool software. The analysis pipeline detected the probe signals, estimated background and correction, normalized the signals and summarized the signal using median polish. The array performance was assessed using the quality control probes on the array and Pearson correlation of the control probes across the arrays. Fold changes in miRNA up-regulation or down-regulation were calculated using the formula: [Fold change = IF(X2> = 0, 2∧X2, −1/(2∧X2)), X = A-B, A = raw signal of specific miRNA from a PTSD patient, and B = raw signal of specific miRNA from a control], to compare the differences in1163 miRNAs expressed between PTSD patients and normal controls.

Zhou J., Nagarkatti P., Zhong Y., Ginsberg J.P., Singh N.P., Zhang J, & Nagarkatti M. (2014). Dysregulation in microRNA Expression Is Associated with Alterations in Immune Functions in Combat Veterans with Post-Traumatic Stress Disorder. PLoS ONE, 9(4), e94075.

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Exosomal miRNA Profiling and Analysis

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RNA was isolated from different exosomes and cell preparations using total exosomal RNA, and a miRNA isolation kits in accordance with the manufacturer's instructions (Fig. 12). The RNA was quantified spectrophotometrically and its quality was analyzed using an Agilent 2100 Bioanalyzer. To characterize the miRNA expression profiles of exosomes and exosome-treated cells and to detect differences in the expression profiles of the cells, a miRNA microarray was performed. In this sense, miRNAs from K562S, K562R, Sexo, Rexo, and K562S + Rexo were labeled using an exosomal RNA Flash Tag RNA labeling kit in accordance with the recommendations of the Affymetrix manufacturer. Next, cells were washed under standard conditions using an Affymetrix Fluidics Station 450 and a hybridization oven 640. Affymetrix Gene Array 3000 scanner was used to process the images, and Affymetrix miRNA QC Tool software was used to analyze the raw data files of the samples. The Affymetrix Gene Chip miRNA 3.0 Array included 19,724 probes and 1733 human adult miRNAs (Fig. 12). Pairwise comparisons of groups were made to exclude miRNAs with less than two fold changes.

Karabay A.Z., Ozkan T., Karadag Gurel A., Koc A., Hekmatshoar Y., Sunguroglu A., Aktan F, & Buyukbingöl Z. (2024). Identification of exosomal microRNAs and related hub genes associated with imatinib resistance in chronic myeloid leukemia. Naunyn-Schmiedeberg's archives of pharmacology.

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