title: GSM5639706: Control + SARS-CoV-2 rep2; Mus musculus; RNA-Seq
library_construction_protocol: RNA-sequencing  Mice lungs were stored at -70oC in RNALater (Sigma Aldrich) then total RNA was isolated using RNeasy preparation kit (Qiagen) according to the manufacturer protocol. RNA was stored frozen (-70oC) until used.   RNA quality was evaluated in TapeStation, using RNA ScreenTape kit (Agilent Technologies), and quantified in Qubit apparatus (Qubit® DNA HS Assay kit, Invitrogen). Libraries for RNA-sequencing were prepared using the ribosomal depletion method, due to low RNA integrated number (RIN) that was between 6 and 7. Libraries were prepared from 10 ng RNA using SMARTer Stranded Total RNA-Seq Kit v2-Pico Input Mammalian according to manufacturer's recommendations. The libraries were barcoded and pooled for multiplex sequencing (1.5 pM total including 1.5% PhiX control library). The pooled DNA was loaded on NextSeq 500 High Output v2 kit (75 cycles) cartridge (Illumina) and sequenced on Illumina NextSeq 500 System, using sequencing conditions of 75 cycles, single-read and sequencing at least 35 million reads per sample.   Reads were aligned to the mouse genome, GRCm38, supplemented with the human ACE2 sequence (NM_021804.3), the mKate2 sequence (from Addgene), and the SARS-CoV-2 sequence (EPI_ISL_406862).   Differential expression analysis was performed using the DESeq2 package. Normalized counts were used for several quality control assays, such as counts distributions and principal component analysis, which were calculated and visualized in R. Those assays showed sample Lenti-hACE2_1 to be an outlier and it was thus removed from the analysis.   Pair-wise comparisons were tested with default parameters, but not using the independent filtering algorithm, with two different models: (1) The exposure model (divided into two groups), and (2) The infection model (divided into 3 groups), as described in the tables below:   The exposure model  Sample Group Lentiviral Transgene SARS-  CoV-2 Productive  SARS-CoV-2  Replication Manuscript  Annotation  Lenti-control_1 1 mKate2  (RFP) - - Lenti-control  Lenti-control _2 1 mKate2  (RFP) - - Lenti-control  Lenti-hACE2_2 1 hACE2 - - Lenti-hACE2  Lenti-control/SARS-CoV-2(dpi 2) 2 mKate2  (RFP) + - Lenti-control/SARS-CoV-2  Lenti-control/SARS-CoV-2(dpi 4) 2 mKate2  (RFP) + - Lenti-control/SARS-CoV-2  Lenti-hACE2/SARS-CoV-2(dpi 2) 2 hACE2 + + Lenti-hACE2/SARS-CoV-2  Lenti-hACE2/SARS-CoV-2(dpi 4) 2 hACE2 + + Lenti-hACE2/SARS-CoV-2    The infection model  Sample Group Lentiviral Transgene SARS-CoV-2 SARS-CoV-2  Replication Manuscript  Annotation  Lenti-control_1 1 mKate2  (RFP) - - Lenti-control  Lenti-control_2  1 mKate2  (RFP) - - Lenti-control  Lenti-hACE2_2 1 hACE2 - - Lenti-hACE2  Lenti-control/SARS-CoV-2(dpi 2) 2 mKate2  (RFP) + - Lenti-control/SARS-CoV-2  Lenti-control/SARS-CoV-2(dpi 4) 2 mKate2  (RFP) + - Lenti-control/SARS-CoV-2  Lenti-hACE2/SARS-CoV-2(dpi 2) 3 hACE2 + + Lenti-hACE2/SARS-CoV-2   Lenti- hACE2/SARS-CoV-2(dpi 4) 3 hACE2 + + Lenti-hACE2/SARS-CoV-2    For each pair-wise comparison, genes were defined as significant if their adjusted p-value (padj) was less than 0.1 (DESeq2's default), their mean expression was above 5, and their absolute fold-change was large enough, in a mean expression-dependent manner (|log2FoldChange| > 5/sqrt(baseMean) + 0.3). The latter condition gave weight to the expression levels of the genes, so that highly expressed genes required a fold-change of at least 1.2, while genes with a very low expression level would need a 5.8-fold change to pass the filtering.  All the differential expression data were subjected to gene set enrichment analysis using GSEA (https://pubmed.ncbi.nlm.nih.gov/16199517/). GSEA uses all differential expression data (cutoff independent) to determine whether a priori defined sets of genes show statistically significant, concordant differences between two biological states. We used the following gene sets collections: Hallmark, Gene Ontology (GO), and REACTOME, all taken from the molecular signatures database MSigDB (v7.2 September 2020). In addition, we used a collection of cell type markers, extracted from the following databases: PanglaoDB (https://panglaodb.se/index.html); CIBERSORT (https://cibersort.stanford.edu/); and ImmGen (https://www.immgen.org/). Ribosomal RNA depletion, followed by SMARTer Stranded Total RNA-Seq Kit v2-Pico Input Mammalian according to manufacturer's recommendations.