GSE130882
Evaluation of ultra-low input RNA sequencing for the study of human T cell transcriptome
Deeper understanding of T cell biology is crucial for the development of new therapeutics.  Human naïve T cells have low RNA content and their numbers can be limiting; therefore we set out to determine the parameters for robust ultra-low input RNA sequencing.  We performed transcriptome profiling at different cell inputs and compared three protocols: Switching Mechanism at 5' End of RNA Template technology (SMART)  with two different library preparation methods (Nextera (SMART_Nxt) and Clontech (SMART_CC)), and AmpliSeq technology.  As the cell input decreased the number of detected coding genes decreased with SMART, while stayed constant with AmpliSeq. However, SMART enables detection of non-coding genes, which is not feasible for AmpliSeq. The detection is dependent on gene abundance, but not transcript length. The consistency between technical replicates and cell inputs was comparable across methods above 1K but highly variable at 100 cell input. Sensitivity of detection for differentially expressed genes decreased dramatically with decreased cell inputs in all protocols, support that additional approaches, such as pathway enrichment, are important for data interpretation at ultra-low input.  Finally, T cell activation signature was detected at 1K cell input and above in all protocols, with AmpliSeq showing better detection at 100 cells. Overall design: Primary human naïve CD4 T cells were treated with a-CD3 only or a-CD3 and B7-1 Fc, which stimulate T cell activation, for 2 hours.  Next, the cells were collected and serially diluted to achieve 100K, 5K, 1K and 100 cells. Finally, RNA was extracted and transcriptome library was generated with two different protocols: SMART-Seq and AmpliSeq.  For SMART-Seq technology, two different library preparation kits were utilized: Nextera Library Preparation Kit (SMART_Nxt) and Clontech Library Preparation kit (SMART_CC)