Gene expression analysis

RNA-seq data analysis was performed by the University of Chicago CRI Bioinformatic Core as follows. The quality of raw sequencing data was assessed using FastQC v0.11.5 [39] and Illumina adapter/primer sequences were detected from sequencing reads. All RNA reads were first mapped to the mouse (mm10) reference genome using STAR v2.5.2b release with default parameters [40]. Picard v2.18.11 (http://broadinstitute.github.io/picard/) was used to collect mapping metrics. The resulting files from the previous alignment step in the RNA-seq analysis were taken individually as input to evaluate transcriptional expression using Rsubread::featureCounts v1.28.1 [41]. Data were inspected using normal distribution of GC content, principal component analysis, and normalized expression distribution. Afterwards, several methods of differential expression analysis (DEA); including edgeR v3.23.5 [42], DESeq2 v1.21.22 [43], and limma v3.45.5 [44] were employed to discover differentially expressed (DE) mRNAs between pair-wise groups based on expression estimation of individual mRNA genes (fold-change ≥ 1.5 and false discovery rate (FDR) < 0.1). Genes detected by all three DEA methods were collected to create a list of high-confidence DE genes (DEGs). To obtain the groups with similar expression trends based on identified DE genes, several in-house scripts were implemented using R (https://www.r-project.org/) and Perl (https://www.perl.org/) languages [45–47]. The identified DEGs were further used as input to functional analysis modules to identify enrichment of functional categories and regulatory networks using Gene Ontology (GO) terms and KEGG-enrichment analyses, as well as QIAGEN’s Ingenuity Pathway Analysis (IPA®) (www.qiagen.com/ingenuity). Pathways significantly enriched in the genes of interest were identified using clusterProfiler [48] (v3.6.0) at FDR-adjusted p-value < 0.10 (hypergeometric test). Gene Set Enrichment Analysis was performed using clusterProfiler [48] (v3.6.0), as well. It should be noted that due to the high level of stringency in the statistical analysis of RNA-seq for 2-, 3-, and 4- month-old tissue, the differences reported by this analysis may underestimate the total numbers of differentially expressed transcripts.

The cell-type (neuron, astrocyte, microglia, oligodendrocyte) specificities of the DEGs were determined based on transcriptome data from Zhang et. al. [49] as previously described [28]. DEGs considered to be enriched in the choroid plexus (ChPx) were assigned on the basis of published ChPx transcriptome analysis [50–53] and confirmed using the Allen Mouse Brain Atlas (https://mouse.brain-map.org/).