Demultiplexing, QC, Alignment, and Analysis 

Raw reads generated from the Illumina basecalls were demultiplexed using bcl2fastq version 2.20.0. Quality filtering and adapter removal are performed using FastP version 0.23.1 with the following parameters:  "--length_required 35 --cut_front_window_size 1 --cut_front_mean_quality 13 --cut_front --cut_tail_window_size 1 --cut_tail_mean_quality 13 --cut_tail -y –r".1 Processed/cleaned reads were then mapped to the GRCm39/gencode M31 or GRCh38/genecode38 (Mouse OR Human) reference using STAR_2.7.9a with the following parameters: "—twopass Mode Basic --runMode alignReads --outSAMtype BAM Unsorted – outSAMstrandField intronMotif --outFilterIntronMotifs RemoveNoncanonical –outReadsUnmapped Fastx".2,3 Genelevel read quantification was derived using the subread-2.0.1 package (featureCounts) with a GTF annotation file (GRCm39/gencode M31 or GRCh38/gencode42) and the following parameters for stranded RNA libraries  "-s 2 -t exon -g gene_name" OR  "-s 0 -t exon -g gene_name" for un stranded libraries.4 Differential expression analysis was performed using DESeq2-1.34.0 with a P-value threshold of 0.05 within R version 3.5.1 (https://www.R-project.org/).5 A PCAplot was created within R using the pcaExplorer to measure sample expression variance.6
Heatmaps were generated using the pheatmap package were given the rLog transformed expression values.7 Gene ontology analyses were performed using the EnrichR package.8,9,10 Volcano plots and dot plots were created using ggplot2.11


References 
1.	Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu; fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, 1 September 2018, Pages i884–i890, https://doi.org/10.1093/bioinformatics/bty560
2.	Frankish A, Diekhans M, Jungreis I, et al. GENCODE 2021. Nucleic Acids Res. 2021;49(D1):D916-D923. doi:10.1093/nar/gkaa1087
3.	Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15-21. doi:10.1093/bioinformatics/bts635
4.	Liao Y, Smyth GK, Shi W (2019). “The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads.” Nucleic Acids Research, 47, e47. doi: 10.1093/nar/gkz114.
5.	Love MI, Huber W, Anders S (2014). “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.” Genome Biology, 15, 550. doi: 10.1186/s13059-014-0550-8.
6.	Marini F, Binder H (2019). “pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components.” BMC Bioinformatics, 20(1), 331. doi: 10.1186/s12859-019-2879-1, https://bioconductor.org/packages/pcaExplorer/.
7.	Kolde, Raivo. Package ‘pheatmap’. Version 1.0.12. https://cran.r-project.org/web/packages/pheatmap/pheatmap.pdf
8.	Chen EY, Tan CM, Kou Y, et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013;14:128. Published 2013 Apr 15. doi:10.1186/1471-2105-14-128
9.	Kuleshov MV, Jones MR, Rouillard AD, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44(W1):W90-W97. doi:10.1093/nar/gkw377
10.	Xie Z, Bailey A, Kuleshov MV, et al. Gene Set Knowledge Discovery with Enrichr. Curr Protoc. 2021;1(3):e90. doi:10.1002/cpz1.90
11.	Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.