Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state

Abstract

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.

Reconstructing B cell receptor sequences from short-read single cell RNA-sequencir with BRAPeS

“…BRAPes is an extension of the TCR reconstruction software TRAPeS (Afik et al, 2017), with significant modifications added to address the processes of class switching and somatic hypermutations which are specific to B cells (Figure 1, see Materials and Methods for full description of BRAPeS). Briefly, BRAPeS takes as input the alignment of the reads to the genome.…”

“…Single cell RNAsequencing (scRNA-seq) has emerged as one of the leading technologies to characterize and study heterogeneity in the immune system across cell types, development and dynamic processes (Papalexi & Satija, 2018;Villani et al, 2018). Combining transcriptome analysis with BCR reconstruction in single cells can provide valuable insights to the relation between BCR and cell state, as was demonstrated by similar studies in T cells (Afik et al, 2017;Eltahla et al, 2016).…”

Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database

“…For example alternative splicing (BRIE 40 , Outrigger 41 , SingleSplice 42 ), single nucleotide variants (SSrGE 43 ) and allele-specific expression (SCALE 44 ). Reconstruction of immune cell receptors is another area that has received considerable attention from tools such as BASIC 45 , TraCeR 46 and TRAPeS 47 . While tools that complete these tasks are unlikely to ever dominate scRNA-seq analysis it is likely that we will see an increase in methods for tackling specialised analyses as researchers continue to push the boundaries of what can be observed using scRNA-seq data.…”

Single-cell technologies for profiling T cells to enable monitoring of immunotherapies

“…Computation approaches, such as TraCeR [65], scTCRseq [66], VDJPuzzle [67], work quite well with transcriptomic profiling results obtained from full-length mRNA transcripts. More recently, the TRAPeS pipeline was reported to enable TCR information extraction from short-read (25–30 bp) sequencing data [68]. Combining transcriptomic profiling and TCR profiling at single-cell resolution, the clonal expansion of exhausted or dysfunctional T cells was found in tumor sites, indicating the reinvigoration of T cell function may recover its anti-cancer functionality [31,61].…”