Computational protocol: Heterogeneity of p53 dependent genomic responses following ethanol exposure in a developmental mouse model of fetal alcohol spectrum disorder

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Protocol publication

[…] We first used stranded RNA-Sequencing (RNA-Seq) to examine global gene expression changes in the four treatment groups (n = 6/group). Brains used for these studies were extracted and rapidly frozen at -80°C at 8 hrs after the second ethanol injection. Brains were shipped to SUNY Upstate Medical University for processing. Initially, we dissected the primary somatosensory cortex after crysectioning brains in the sagittal plane at 20 μM thickness and rapidly mounting them on PENfoil slides (Leica, Wetzlar, Germany) before performing a cytoarchitectural stain using the HistoGene (ThermoFisher Scientific, Waltham, MA) stain and procedure (Arcturus). Stained sections were compared with the Allen Developing Mouse Brain Atlas cytoarchitectural images and the somatosensory cortex dissected using the AS LMD laser dissection microscope (Leica) into PCR tubes containing Qiazol solution (Qiagen, Valencia, CA). These tubes were stored frozen at -20°C until purification according to manufacturer protocol using a two step procedure that combined the Trizol method for DNA, RNA, and protein purification followed by the RNeasy method for clean-up of the RNA. After performing the laser microdissection on half of the samples, the subsequent collections of somatosensory cortex were obtained using a hole-punch method on the same cortical areas in frozen brain specimens. These were also collected into Qiazol and the RNA purified in the same manner as before. All purified RNA samples were subsequently assessed to determine the yield, purity, and quality of the RNA using a Nanodrop (ThermoFisher) and the Agilent Technologies (Santa Clara, CA) RNA 6000 Pico Kit.For whole-transcriptome analysis, three of the RNA samples that passed quality control standards (RNA Integrity Number ≥ 7) in each treatment group (n = 12 total) were submitted to the SUNY Molecular Analysis Core for Stranded Total RNA-Seq. Libraries were prepared using standard Illumina methods and sequenced with an Illumina (San Diego, CA) NextSeq 500 instrument using 1 x 75 bp single end reads at a targeted depth ≥ 15 million (M) reads per sample. Raw FASTQ files from the sequencing were generated in Illumina BaseSpace for initial quality control (filtering out reads with a q score < 30) and alignment was performed to version mm10 of the mouse genome and annotated to RefSeq (5-2-16) using the Bowtie2 algorithm within the TopHat application.The aligned BAM files were downloaded into Partek Flow and Genomics Suite (St Louis, MO) for downstream analysis. The data summarization, quantification, and normalization of RNA counts into total reads per kilobase of gene model per million reads (RPKM) and initial single statistical analysis were performed in Partek Flow. Raw FASTQ files and normalized RPKM data are freely available in the NCBI Gene Expression Omnibus (Accession GSE100217). To identify single genes and transcripts with changes in expression, we used a two-way ANOVA to test for significant main effects of the two factors ethanol Treatment and p53 Genotype, as well as the interaction of these two factors. Whenever possible, false discovery rate (FDR) adjustment for multiple testing was performed on the main and interaction effects, with a cutoff of 0.3 or less initially used for single gene discovery in the comparisons of ethanol effects in WT mice, as well as the genotype effects and the ethanol x genotype interaction effects. Notably, no FDR cutoff was used for the ethanol contrasts in the KO mice due to less robust effects. For these comparisons, the top 25 genes were shown based on uncorrected nominal significance. False discovery rate (FDR) adjustment for multiple testing was performed on the main and interaction effects, with a cutoff of 0.3 or less used for single gene findings. Post-hoc contrasts were obtained using a Fisher's Protected Least Significant Difference, without correction for multiple testing. Functional enrichment analysis of the 50 most-robustly affected genes for each contrast of interest was performed based on the Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) annotation using Partek Pathway. We also transferred the normalized data from Partek Flow into Partek Genomics Suite to perform Pathway ANOVA using the KEGG annotation database. This procedure tests for shifts in the expression of all of the transcripts represented in a particular gene set, rather than annotating the most robustly-changed in a particular contrast. [...] Laser dissected RNA samples of discrete lamina in the somatosensory cortex (layers 2–3 combined, layer 4, layer 5, layer 6) and discrete regions of the hippocampus (CA1 and dentate gyrus) were obtained using the previously described staining methods, with the exception that the dissected cells were collected into RLT Lysis Buffer from the RNeasy Kit (Qiagen, Valencia, CA). These RNA samples (6 per group for each region of interest, n = 144 samples total) were then subjected to Targeted RNA-Seq Expression (TREx) analysis according to the manufacturer’s protocol.The content of the TREx panel included 280 genes involved in neuronal activity, apoptosis, DNA damage and repair, cell cycle regulation, and cell fate, plus housekeeping genes (). These libraries were sequenced using the Illumina MiSeq instrument, with reads mapped to the mouse genome, normalized to the mean counts of peptidylprolyl isomerase A (PPIA) and hypoxanthine phosphoribosyltransferase (HPRT), and subsequently analyzed using a two-way ANOVA and t-test procedures for each brain region of interest in Metaboanalyst software. The 25 most robustly affected genes in each brain region comparison were subjected to hierarchical clustering for display purposes. […]

Pipeline specifications

Software tools BaseSpace, Bowtie2, TopHat, Partek Flow, Partek Pathway, Partek Genomics Suite, MetaboAnalyst
Databases GEO KEGG KEGG Annotation
Application RNA-seq analysis
Organisms Mus musculus
Diseases Mitochondrial Diseases, Fetal Alcohol Spectrum Disorders
Chemicals Ethanol