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Transcriptomic profiling of circadian genes in WT mouse tissues (miRNA-Seq)

ABSTRACT: A goal of a collaboration between the CHDI Foundation and Prof. Jenny Morton at Cambridge University was to identify genes in mice with diurnal/circadian expression patterns. Tissues from wild type mice were harvested every 3 hrs over a 36 hour time period, for a total of 13 time points. Striatal, cortical, hypothalamic and liver samples were harvested, flash frozen, and transferred to Expression Analysis for RNA extraction and miRNA-seq sequencing. Samples passing QC were analyzed to produce high quality, 50-base paired-end RNA-seq results.

ORGANISM(S): Mus musculus

PROVIDER: GSE151566 | GEO | 2020/07/14

REPOSITORIES: GEO

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Project description:Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n=223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals (42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD) were processed and hybridized to Affymetrix HG-U133 2.0 Plus microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥7.0 using Agilent 2100 Bioanalyzer software; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤3.0; and (3) the multi-chip normalization scaling factor ≤10.0 Of the 223 samples, 213 (95.5%) passed the QC criteria. In a data set of 34 arrays (10 samples failing QC criteria, 24 randomly chosen samples passing QC criteria), correlation coefficients for pairwise comparisons of expression levels for 100 housekeeping genes in which at least one array failed the QC criteria were significantly lower (average Pearson r = 0.90 ± 0.04) and more broadly dispersed than correlation coefficients for pairwise comparisons between any two arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). By using the QC cutoff criteria, the inter-array variability, as assessed by the coefficient of variation in the expression levels for 100 housekeeping genes, was reduced from 35.7% to 21.7%. Based on the aberrant housekeeping gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.

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Transcriptomic profiling of circadian genes in WT mouse tissues (miRNA-Seq)

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