TY - JOUR T1 - WAT3R: Recovery of T-Cell Receptor Variable Regions From 3’ Single-Cell RNA-Sequencing JF - bioRxiv DO - 10.1101/2022.01.26.477886 SP - 2022.01.26.477886 AU - Marina Ainciburu AU - Duncan M. Morgan AU - Erica A. K. DePasquale AU - J. Christopher Love AU - Felipe Prósper AU - Peter van Galen Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/01/28/2022.01.26.477886.abstract N2 - Summary Diversity of the T-cell receptor (TCR) repertoire is central to adaptive immunity. The TCR is composed of α and β chains, encoded by the TRA and TRB genes, of which the variable regions determine antigen specificity. To generate novel biological insights into the complex functioning of immune cells, combined capture of variable regions and single-cell transcriptomes provides a compelling approach. Recent developments enable the enrichment of TRA and TRB variable regions from widely used technologies for 3’-biased single-cell RNA-sequencing (scRNA-seq). However, a comprehensive computational pipeline to process TCR-enriched data from 3’ scRNA-seq is not available. Here we present an analysis pipeline to process TCR variable regions enriched from 3’ scRNA-seq cDNA. The tool reports TRA and TRB nucleotide and amino acid sequences linked to cell barcodes, enabling the reconstruction of T-cell clonotypes with associated transcriptomes. We demonstrate the software using peripheral blood mononuclear cells (PBMCs) from a healthy donor and detect TCR sequences in a high proportion of single T-cells. Detection of TCR sequences is negligible in non-T-cell populations, demonstrating specificity. Finally, we show that TCR clones are larger in CD8 Memory T-cells than other T-cell types, indicating an association between T-cell clonotypes and differentiation states.Availability and implementation The Workflow for Association of T-cell receptors from 3’ single-cell RNA-seq (WAT3R), including test data, is available on GitHub (https://github.com/mainciburu/WAT3R), Docker Hub (https://hub.docker.com/r/mainciburu/wat3r), and a workflow on the Terra platform (https://app.terra.bio). The test dataset is available on GEO (accession number pending).Competing Interest StatementThe authors have declared no competing interest. ER -