Literature DB >> 35674381

WAT3R: Recovery of T Cell Receptor Variable Regions From 3' Single-Cell RNA-Sequencing.

Marina Ainciburu1,2,3, Duncan M Morgan4,5, Erica A K DePasquale2,3, J Christopher Love3,4,5, Felipe Prósper1, Peter van Galen2,3.   

Abstract

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'-based 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 low in non-T cell populations, demonstrating specificity. Finally, we show that TCR clones are larger in CD8 Memory T cells than in 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 GSE195956). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2022). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2022        PMID: 35674381      PMCID: PMC9272805          DOI: 10.1093/bioinformatics/btac382

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.931


  22 in total

1.  Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data.

Authors:  Namita T Gupta; Jason A Vander Heiden; Mohamed Uduman; Daniel Gadala-Maria; Gur Yaari; Steven H Kleinstein
Journal:  Bioinformatics       Date:  2015-06-10       Impact factor: 6.937

2.  pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires.

Authors:  Jason A Vander Heiden; Gur Yaari; Mohamed Uduman; Joel N H Stern; Kevin C O'Connor; David A Hafler; Francois Vigneault; Steven H Kleinstein
Journal:  Bioinformatics       Date:  2014-03-10       Impact factor: 6.937

3.  Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers.

Authors:  Frank J Lowery; Sri Krishna; Rami Yossef; Neilesh B Parikh; Praveen D Chatani; Nikolaos Zacharakis; Maria R Parkhurst; Noam Levin; Sivasish Sindiri; Abraham Sachs; Kyle J Hitscherich; Zhiya Yu; Nolan R Vale; Yong-Chen Lu; Zhili Zheng; Li Jia; Jared J Gartner; Victoria K Hill; Amy R Copeland; Shirley K Nah; Robert V Masi; Billel Gasmi; Scott Kivitz; Biman C Paria; Maria Florentin; Sanghyun P Kim; Ken-Ichi Hanada; Yong F Li; Lien T Ngo; Satyajit Ray; Mackenzie L Shindorf; Shoshana T Levi; Ryan Shepherd; Chris Toy; Anup Y Parikh; Todd D Prickett; Michael C Kelly; Rachel Beyer; Stephanie L Goff; James C Yang; Paul F Robbins; Steven A Rosenberg
Journal:  Science       Date:  2022-02-03       Impact factor: 47.728

4.  High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes.

Authors:  Mandeep Singh; Ghamdan Al-Eryani; Shaun Carswell; James M Ferguson; James Blackburn; Kirston Barton; Daniel Roden; Fabio Luciani; Tri Giang Phan; Simon Junankar; Katherine Jackson; Christopher C Goodnow; Martin A Smith; Alexander Swarbrick
Journal:  Nat Commun       Date:  2019-07-16       Impact factor: 14.919

5.  Coevolving JAK2V617F+relapsed AML and donor T cells with PD-1 blockade after stem cell transplantation: an index case.

Authors:  Livius Penter; Satyen H Gohil; Teddy Huang; Emily M Thrash; Dominik Schmidt; Shuqiang Li; Mariano Severgnini; Donna Neuberg; F Stephen Hodi; Kenneth J Livak; Robert Zeiser; Pavan Bachireddy; Catherine J Wu
Journal:  Blood Adv       Date:  2021-11-23

6.  Single-Cell Multiomics Reveals Clonal T-Cell Expansions and Exhaustion in Blastic Plasmacytoid Dendritic Cell Neoplasm.

Authors:  Erica A K DePasquale; Daniel Ssozi; Marina Ainciburu; Jonathan Good; Jenny Noel; Martin A Villanueva; Charles P Couturier; Alex K Shalek; Sary F Aranki; Hari R Mallidi; Gabriel K Griffin; Andrew A Lane; Peter van Galen
Journal:  Front Immunol       Date:  2022-03-10       Impact factor: 7.561

7.  Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma.

Authors:  Moshe Sade-Feldman; Keren Yizhak; Stacey L Bjorgaard; John P Ray; Carl G de Boer; Russell W Jenkins; David J Lieb; Jonathan H Chen; Dennie T Frederick; Michal Barzily-Rokni; Samuel S Freeman; Alexandre Reuben; Paul J Hoover; Alexandra-Chloé Villani; Elena Ivanova; Andrew Portell; Patrick H Lizotte; Amir R Aref; Jean-Pierre Eliane; Marc R Hammond; Hans Vitzthum; Shauna M Blackmon; Bo Li; Vancheswaran Gopalakrishnan; Sangeetha M Reddy; Zachary A Cooper; Cloud P Paweletz; David A Barbie; Anat Stemmer-Rachamimov; Keith T Flaherty; Jennifer A Wargo; Genevieve M Boland; Ryan J Sullivan; Gad Getz; Nir Hacohen
Journal:  Cell       Date:  2018-11-01       Impact factor: 41.582

8.  IgBLAST: an immunoglobulin variable domain sequence analysis tool.

Authors:  Jian Ye; Ning Ma; Thomas L Madden; James M Ostell
Journal:  Nucleic Acids Res       Date:  2013-05-13       Impact factor: 16.971

9.  T cell fate and clonality inference from single-cell transcriptomes.

Authors:  Michael J T Stubbington; Tapio Lönnberg; Valentina Proserpio; Simon Clare; Anneliese O Speak; Gordon Dougan; Sarah A Teichmann
Journal:  Nat Methods       Date:  2016-03-07       Impact factor: 28.547

10.  Detection and removal of barcode swapping in single-cell RNA-seq data.

Authors:  Jonathan A Griffiths; Arianne C Richard; Karsten Bach; Aaron T L Lun; John C Marioni
Journal:  Nat Commun       Date:  2018-07-10       Impact factor: 14.919

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