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Identification of s-RNYs targets in bone marrow-derived macrophages

ABSTRACT: Bone marrow-derived macrophages (BMDMs) were collected from 4 C57BL/6J males and transfected with siRNAs against the terminal loop of mouse RNYs and control. 48 hr after transfection, the total RNA was isolated by using RNAeasy kit (Qiagen) and mRNA profiling was performed on Agilent Sureprint whole genomemicroarrays. The normalized data were analyzed with Biometric Research Branch (BRB) array tools 3.8.0. Log2-transformed signal intensities were used to identify probes with at least 1.2 fold change of expression difference between BMDMs overexpressing s-RNYs and control, and with a statistically significant p-value (p<0.05).

ORGANISM(S): Mus musculus

PROVIDER: GSE47518 | GEO | 2015/09/16

SECONDARY ACCESSION(S): PRJNA205944

REPOSITORIES: GEO

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Project description:Transcriptional profiling of mouse cerebellar extract comparing SCA7 KI mice with wild type mice. Female mice were killed by decapitation on post natal days 10 and 22 and 11 weeks. Goal was to determine gene expression profiles differing between SCA7 KI mice and wild-type mice during post-natal developement of the cerebellum. Gene expression profiling was performed using RNA extracted from the cerebellum of KI and WT mice at P10 (5 WT and 5 KI), P22 (5 WT and 4 KI) and 11 wks (5WT and 6 KI). After labeling, RNAs were hybridized on dual-label G4122F AgilentM-BM-. chips; a mix of all P10 samples was used as common reference (green channel). Quality control included visual control of the reconstructed image of the chip, M/A plot, corner intensities, outliers, positive and negative intensities, normalization factors. Normalization and statistical analyses were carried out by using BRB-array Tools developed by Dr. Richard Simon and the BRB-ArrayTools development team (Biometrics Research Branch, http://linus.nci.nih.gov/BRB-ArrayTools.html). Genes with less than 50% present calls or with low variability along the arrays (less than 20% of values with at least 2-fold change in either direction from the geneM-bM-^@M-^Ys median value) were excluded from further analysis. For the 1905 remaining probes an interaction between time and genotype was analyzed by regression analysis of the time course of expression. In brief, probes for which variation over time differed for the genotype class were fitted to the following model: log expression ~ time + time**2 + genotype + genotype*time + genotype*time**2. A univiariate p-value < 0.001 (random variance model) was set for significant probes (genotype*time + genotype*time**2) and a False Discovery Rate (FDR) was calculated for each probe (Benjamini & Hochberg, 1995). Differences in profiles were identified with a Self Organisation Tree Algorithm (MultiplExperiment Viewer (MeV), (Saeed et al, 2006). Expression values were averaged by group and then clustered according to their profile as a function of time.

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Identification of s-RNYs targets in bone marrow-derived macrophages

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