Afik Shaked, Yates Kathleen B, Bi Kevin, Darko Samuel, Godec Jernej, Gerdemann Ulrike, Swadling Leo, Douek Daniel C, Klenerman Paul, Barnes Eleanor J, Sharpe Arlene H, Haining W Nicholas, Yosef Nir
Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Nucleic Acids Res. 2017 Sep 19;45(16):e148. doi: 10.1093/nar/gkx615.
The T cell compartment must contain diversity in both T cell receptor (TCR) repertoire and cell state to provide effective immunity against pathogens. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current methods for TCR inference from scRNA-seq are limited in their sensitivity and require long sequencing reads, thus increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present TRAPeS, a publicly available tool that can efficiently extract TCR sequence information from short-read scRNA-seq libraries. We apply it to investigate heterogeneity in the CD8+ T cell response in humans and mice, and show that it is accurate and more sensitive than existing approaches. Coupling TRAPeS with transcriptome analysis of CD8+ T cells specific for a single epitope from Yellow Fever Virus (YFV), we show that the recently described 'naive-like' memory population have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype cells. This suggests that TCR usage is associated with the differentiation state of the CD8+ T cell response to YFV.
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