Unknown,Transcriptomics,Genomics,Proteomics

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MiRNA microarray analysis to explore the expression profiles of miRNAs using the same liver tissues of NFD-fed mice and HFD-fed mice

ABSTRACT: The miRNA microarray analysis was performed to explore the expression profiles of miRNAs using the same liver tissues of NFD-fed mice and HFD-fed mice  Summary: An abstract of the experiment and the data analysis.  Project Description: Sample and experiment information.  Array Information: miRCURY™ LNA expression array information.  Data Analysis for miRNAs: 1. Low intensity filtering and data normalization: After low intensity miRNAs filtering, raw signal intensities are normalized in Median method. (miRNAs that intensities>=30 in all samples are chosen for calculating normalization factor) 2. Quality assessment of miRNA data after filtering: Contains box plot, Correlation Matrix and scatter plot for miRNAs after normalization. 3. Differentially expressed miRNAs screening: Contains significant differentially expressed miRNAs that pass Volcano Plot filtering. (Fold Change>=1.5, P-value<=0.05) 4. Heat map and hierarchical clustering: Hierarchical clustering on the significant differentially expressed miRNAs that passed Volcano Plots filtering.  Sample RNA Quality Control: Sample quality control data file from Nanodrop 1000 spectrophotometer and standard denaturing agarose gel electrophoresis.  Methods: A brief introduction for microarray, experiment, and data analysis.  FAQ: Frequently asked question Additional miRNA Array Analysis (charge an extra fee):  Prediction Analysis for Microarrays (PAM analysis)  miRNA Target Gene Prediction and Functional Analysis Additional files provided:  Graphs (*.jpg)  Raw Intensity File(*.xls, raw miRNAs signal intensity)  Layout File (*.gal, the files contain information on the positioning of the capture probes on the array and microRNA annotations for your species of interest)  Raw data files produced by GenePix Pro 6.0

ORGANISM(S): Mus musculus

SUBMITTER: Fei Xu

PROVIDER: E-MTAB-8731 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and the second most common form of leukemia in children. Multiple lncRNAs participate in normal and may be implicated in malignant hematopoiesis associated with blood cell cancers, such as leukemia. Currently, the expression profile of lncRNAs in pediatric AML is unclear. In this study, we evaluated the lncRNA expression profile in the tissue of three pediatric AML patients with lncRNA microarray techniques. In order to gain insight into the function of targets of lncRNAs, GO term and KEGG pathway annotation were applied to the target gene pool. qPCR was performed to evaluate the expression patterns of dys-regulated lncRNAs. Bone marrow specimens were obtained at the time of diagnosis during routine clinical assessment of 3 pediatric patients with AML, who presented at the Department of Hematology and Oncology, Children's Hospital of Soochow University between 2000 and 2011. Additionally, bone marrow samples from 3 healthy donors were analyzed as controls. Human LncRNA Array analysis was performed by KangChen Bio-tech, Shanghai P.R. China. Total RNA from each sample was quantified by the NanoDrop ND-1000 and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. For microarray analysis, Agilent Array platform was employed. The sample preparation and microarray hybridization were performed based on the manufacturerâs standard protocols with minor modifications. Briefly, mRNA was purified from total RNA after removal of rRNA (mRNA-ONLYâ¢ Eukaryotic mRNA Isolation Kit, Epicentre). Then, each sample was amplified and transcribed into fluorescent cRNA along the entire length of the transcripts without 3â bias utilizing a random priming method. The labeled cRNAs were hybridized onto the Human LncRNA Array v2.0 (8 x 60K, Arraystar). After having washed the slides, the arrays were scanned by the Agilent Scanner G2505C. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed using the GeneSpring GX v12.0 software package (Agilent Technologies). After quantile normalization of the raw data, LncRNAs and mRNAs that at least 4 out of 6 samples have flags in Present or Marginal (âAll Targets Valueâ) were chosen for further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance between the two groups were identified through Volcano Plot filtering. Pathway analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show the distinguishable LncRNAs and mRNAs expression pattern among samples.

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