RNA Sequencing of WT, RAG2-KO, and RAG2-KO TCRbeta-Transduced CD4+CD8+ T-Cells Derived From Human Embryonic Stem Cells

T-cell development is predicated on the successful rearrangement of the T-cell receptor (TCR) gene loci, which encode for antigen-specific receptors that enable an immune response. Recombination Activating Gene (RAG) 2 is required for TCR gene rearrangements, which occur during specific stages of T-cell development. Here, we differentiated human pluripotent stem cells with a CRISPR/Cas9-directed deletion of the RAG2 gene (RAG2-KO) to elucidate the requirement for the TCRb chain in mediating b-selection during human T-cell development in vitro. In stark contrast to what is seen in mice, human RAG2-KO T-lineage progenitors progressed to the CD4+CD8+ double-positive (DP) stage in the absence of TCRb rearrangements. Nevertheless, RAG2-KO DPs retrovirally-transduced to ectopically express a rearranged TCRb chain showed increased survival and proliferation as compared to control-transduced RAG2-KO DPs. Furthermore, transcriptomic analysis showed that TCRb-transduced and control-transduced RAG2-KO DPs differed in gene pathways related to survival and proliferation. Our results provide new insights as to the distinct requirement for the TCRb chain during human T-cell development. Overall design: Cells were collected at OP9-DL4-7FS co-culture day 24-28 and stained with fluorochrome-labelled monoclonal antibodies to CD45, CD7 (eBioscience), CD5, CD4, CD8 (BD Biosciences), DAPI, and sorted into CD4+CD8+ DP populations using FACSVantage Diva or FACSAria cell sorters (BD Biosciences). Total RNA was extracted from the sorted cell populations using TRIzol. Purified RNA were subjected to RNA sequencing using Illumina Novaseq 6000. Library preparation was done using Illumina TruSeq Strandard Total RNA Sample Preparation kit. Sequencing was done using 100-cycle paired read protocol and multiplexing to obtain ~40 million reads/sample. Samples were aligned to GRCh38 using HISAT2. Read counts were calculated using HTSeq. Differential gene expression analysis was done using edgeR package and R program.