Abstract
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 and Clontech), 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 1 K 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 1 K cell input and above in all protocols, with AmpliSeq showing better detection at 100 cells.
Highlights
Understanding the transcriptome profiles of human T cells is important in deciphering their biology, and recent advances in RNA sequencing technology have been significant towards this goal
Well established T cell activation signature was detected at 1 K cell input and above with both protocols; with AmpliSeq detecting significantly higher number of these genes at 100 cell input
Number of detected genes decreased with reduced input in SMART technology, while it remained constant for AmpliSeq technology
Summary
Understanding the transcriptome profiles of human T cells is important in deciphering their biology, and recent advances in RNA sequencing technology have been significant towards this goal. Studies have been published evaluating the performance of these protocols such as Ovation (Nugen), SMARTer (Clonetech), DP-seq and CEL-seq which provided valuable insights on advantages and disadvantages of each protocol and practical considerations when performing ultra-low input RNA sequencing[6,7,8,9,10,11] These protocols are based on unbiased sequencing of the whole cDNA pools that sequence and map all cDNA fragments to the reference transcriptome, and expression is measured by counting the total number of fragments mapping to each transcript. AmpliSeq utilizes PCR assays specific for each gene being targeted, and a short amplicon is amplified and quantified to measure gene expression This platform has shown satisfactory performance in standard RNA sequencing experiments[12]. Well established T cell activation signature was detected at 1 K cell input and above with both protocols; with AmpliSeq detecting significantly higher number of these genes at 100 cell input
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