Global analysis of gene expression was performed using Illumina Sequencing platform in Georgia Cancer Center Core Facility, Augusta University. Naive CD4+CD44CD62L+Foxp3GFP− cells were flow-sorted from lymph nodes and spleens of unmanipulated wild-type mice. Lymph node and spleen cells isolated from wild-type or BMPR1αT− mice were activated with Con A (2 μg/ml; Sigma) and LPS (10 ng/ml; Sigma) for 4 days, and activated CD4+CD44+CD62LFoxp3GFP- cells were flow cytometry–sorted. At least three different samples were processed for each cell type. Total RNA was prepared using a commercial kit (Qiagen). DNA for sequencing was produced with Illumina kit. RNA-seq data analysis was performed using Tuxedo protocol as described in (92). Briefly, sequencing reads were aligned to reference genome using Tophat2, followed by estimation of RNA using Cufflinks 2.11. Differential gene expression analysis was performed using Cuffdiff application of Cufflinks. Genes were considered differentially expressed if fold expression was 1.5 or more, and the difference was statistically significant. To visualize differences between gene expression profiles of activated wild-type and BMPR1α-deficient CD4+ T cells, we performed PCA. The gene lists subject to PCA analysis included all genes with expression levels above the threshold allowing for differential expression analysis in Cufflinks suite. Expression profiles of genes differentially expressed between activated BMPR1α-sufficient and BMPR1α-deficient CD4+ T cells were visualized as a heat map. Expression profiles of genes differentially expressed between naive wild-type and activated BMPR1α-sufficient and BMPR1α-deficient CD4+ T cells were visualized as volcano plots. All analyses were done in R (version 3.4.3). Bioinformatics transcriptome analysis was performed in College of Public Health of Ohio State University. GO and gene enrichment analyses were performed using Metascape (http://metascape.org), and network graphs were edited using Cytoscape (93, 94).

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