Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression

Zheng Song; Lara Henze; Christian Casar; Dorothee Schwinge; Christoph Schramm; Johannes Fuss; Likai Tan; Immo Prinz

doi:10.1093/jleuko/qiad069

Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression

Standard

Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression. / Song, Zheng ; Henze, Lara ; Casar, Christian ; Schwinge, Dorothee ; Schramm, Christoph; Fuss, Johannes; Tan, Likai; Prinz, Immo.

in: J LEUKOCYTE BIOL, Jahrgang 114, Nr. 6, 24.11.2023, S. 630-638.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Song, Z , Henze, L , Casar, C , Schwinge, D , Schramm, C, Fuss, J, Tan, L & Prinz, I 2023, 'Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression', J LEUKOCYTE BIOL, Jg. 114, Nr. 6, S. 630-638. https://doi.org/10.1093/jleuko/qiad069

APA

Song, Z., Henze, L., Casar, C., Schwinge, D., Schramm, C., Fuss, J., Tan, L., & Prinz, I. (2023). Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression. J LEUKOCYTE BIOL, 114(6), 630-638. https://doi.org/10.1093/jleuko/qiad069

Vancouver

Song Z , Henze L , Casar C , Schwinge D , Schramm C, Fuss J et al. Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression. J LEUKOCYTE BIOL. 2023 Nov 24;114(6):630-638. https://doi.org/10.1093/jleuko/qiad069

Bibtex

@article{532d36ffefdc49cf8530d8f7849a611b,

title = "Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression",

abstract = "Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.",

author = "Zheng Song and Lara Henze and Christian Casar and Dorothee Schwinge and Christoph Schramm and Johannes Fuss and Likai Tan and Immo Prinz",

note = "{\textcopyright} The Author(s) 2023. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.",

year = "2023",

month = nov,

day = "24",

doi = "10.1093/jleuko/qiad069",

language = "English",

volume = "114",

pages = "630--638",

journal = "J LEUKOCYTE BIOL",

issn = "0741-5400",

publisher = "FASEB",

number = "6",

}

RIS

TY - JOUR

T1 - Human γδ T cell Identification from Single-cell RNA Sequencing Datasets by Modular TCR Expression

AU - Song, Zheng

AU - Henze, Lara

AU - Casar, Christian

AU - Schwinge, Dorothee

AU - Schramm, Christoph

AU - Fuss, Johannes

AU - Tan, Likai

AU - Prinz, Immo

PY - 2023/11/24

Y1 - 2023/11/24

N2 - Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.

AB - Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.

U2 - 10.1093/jleuko/qiad069

DO - 10.1093/jleuko/qiad069

M3 - SCORING: Journal article

C2 - 37437101

VL - 114

SP - 630

EP - 638

JO - J LEUKOCYTE BIOL

JF - J LEUKOCYTE BIOL

SN - 0741-5400

IS - 6

ER -