Genomics

Dataset Information

0

Arraystar m6A-mRNA&lncRNA Epitranscriptomic Microarray Service for 6 Mouse samples


ABSTRACT: Total RNA from each sample was quantified using the NanoDrop ND-1000 and RNA integrity was assessed by Bioanalyzer 2100 or Mops electrophoresis. The sample preparation and microarray hybridization were performed based on the Arraystar’s standard protocols. Briefly, the total RNAs were immunoprecipitated with anti-N6-methyladenosine (m6A) antibody. The modified RNAs were eluted from the immunoprecipitated magnetic beads as the “IP”. The unmodified RNAs were recovered from the supernatant as “Sup”. The “IP” and “Sup” RNAs were labeled with Cy5 and Cy3 respectively as cRNAs in separate reactions using Arraystar RNA Labeling protocol. The cRNAs were combined together and hybridized onto Arraystar Mouse mRNA&lncRNA Epitranscriptomic Microarray (8x60K, Arraystar). After washing the slides, the arrays were scanned in two-color channels by an Agilent Scanner G2505C.Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Raw intensities of IP (immunoprecipitated, Cy5-labelled) and Sup (supernatant, Cy3-labelled) were normalized with average of log2-scaled Spike-in RNA intensities. After Spike-in normalization, the probe signals having Present (P) or Marginal (M) QC flags in a certain proportion were retained for further “m6A quantity” analyses. “m6A quantity” was calculated for the m6A methylation amount based on the IP (Cy5-labelled) normalized intensities. Differentially m6A-methylated RNAs between two comparison groups were identified by filtering with the fold change and statistical significance (p-value) thresholds. Hierarchical Clustering was performed to show the distinguishable m6A-methylation pattern among samples.

ORGANISM(S): Mus musculus

PROVIDER: GSE218412 | GEO | 2022/11/24

REPOSITORIES: GEO

Similar Datasets

2009-07-09 | E-GEOD-16226 | biostudies-arrayexpress
2023-05-08 | GSE150251 | GEO
2024-04-20 | GSE228477 | GEO
2019-12-27 | GSE138274 | GEO
2015-04-20 | GSE68028 | GEO
2013-04-01 | GSE27582 | GEO
2020-12-18 | GSE150892 | GEO
2016-01-05 | E-GEOD-74255 | biostudies-arrayexpress
2023-12-15 | GSE190945 | GEO
2020-02-05 | GSE138589 | GEO