Summary of RNA-seq data with statistics.

Description

The spreadsheets include pairwise comparisons of gene expression levels under specified conditions. Abbreviations used are as follows: PV for Parvalbumin; Sst for Somatostatin; CFC for Contextual Fear Conditioning; PTZ for Pentylenetetrazol; WT for wild type; cKO for conditional Nr4a1 knockouts; and HC for home cage.

Steps to reproduce

Cortices of p60 PvalbCre/RiboTag and SstCre/RiboTag mice were dissected in ice-cold PBS and homogenized in the buffer containing 100 mM KCl, 50 mM Tris-HCl pH 7.4, 12 mM MgCl2, 100 g/ml cycloheximide (Sigma), 1 mg/ml heparin (Sigma), 1x complete mini, EDTA-free protease inhibitor cocktail (Roche), 200 units/ml RNasin© plus inhibitor (Promega) and 1 mM DTT (Sigma) (500 µl ~3% w/v). The lysate was centrifuged at 2,000g for 10 minutes at 4°C. Igepal-CA380 was then added to the supernatant at the final concentration of 1%. The lysate was briefly incubated on ice and then centrifuged at 12,000g for 10 minutes at 4°C. 25 µl of the supernatant was collected as input sample. 30 µl/ml of anti-HA coupled magnetic beads (Pierce) were then added to the remaining supernatant. Incubation was performed on a rotator for 3 hours at 4°C. The beads were washed four times in the high salt buffer containing 350 mM KCl, 1% Igepal-CA380, 50 mM Tris-HCl, pH7.4, 12 mM MgCl2, 100 µg/ml Cycloheximide (Sigma) and 1 mM DTT (Sigma). Ribosomes were eluted in 350 µl of RLT plus buffer (Qiagen). RNA purification was performed using RNeasy Plus Mini kit (Qiagen) following the manufacturers’ instructions. RNA-seq was performed at the TSRI Next Generation Sequencing Core on the Illumina HiSeq platform. The libraries were generated, barcoded, and sequenced according to the manufacturers’ recommendations. The reads were trimmed from adapter sequences using cutadapt 1.18 with Python 3.6.3. The trimmed reads were mapped to the reference genome using the STAR aligner 2.5.2a and gene abundance was estimated with python 2.7.11, and HTSeq 0.11.0. Differential expression analysis was performed in the R package DESeq2. DESeq2 first adjusts read counts based on a normalization factor that accounts for sample size. This was followed by dispersion estimates based on a negative binomial model which accounts for genes with very few counts. Finally, the Wald test was performed to test for statistical significance. Genes with adjusted p-values (padj) of <0.05 were identified as differentially expressed. To remove genes with high fold changes due to low expression, a minimum normalized expression level (basemean) filter of 50 was added. The filtered data were used to generate volcano plots and heatmaps.

Institutions

Categories

Funding

Licence