publication . Article . Other literature type . 2016

T cell fate and clonality inference from single-cell transcriptomes

Valentina Proserpio; Sarah A. Teichmann; Sarah A. Teichmann; Gordon Dougan; Michael J. T. Stubbington; Tapio Lönnberg; Anneliese O. Speak; Simon Clare;
Open Access
  • Published: 07 Mar 2016 Journal: Nature Methods, volume 13, pages 329-332 (issn: 1548-7091, eissn: 1548-7105, Copyright policy)
  • Publisher: Springer Science and Business Media LLC
  • Country: United Kingdom
Abstract
The enormous sequence diversity within T cell receptor (TCR) repertoires allows specific TCR sequences to be used as lineage markers for T cells that derive from a common progenitor. We have developed a computational method, called TraCeR, to reconstruct full-length, paired TCR sequences from T lymphocyte single-cell RNA-seq by combining existing assembly and alignment programs with “combinatorial recombinome” sequences comprising all possible TCR combinations. We validate this method to quantify its accuracy and sensitivity. Inferred TCR sequences reveal clonal relationships between T cells whilst the cells’ complete transcriptional landscapes can be quantified...
Read more
doi: 10.1038/nmeth.3800 , 10.17863/cam.40037
pmc: PMC4835021
View all 4 identifiers
Subjects
free text keywords: Article, CD4-Positive T-Lymphocytes, Animals, Mice, Salmonella, Salmonella Infections, Animal, Receptors, Antigen, T-Cell, Lymphocyte Activation, Software, High-Throughput Nucleotide Sequencing, Transcriptome, Antigen, T cell, medicine.anatomical_structure, medicine, Biology, Cell, Genetics, Single-cell analysis, T lymphocyte, Acquired immune system, Cell biology, T-cell receptor
Related Organizations
View more
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
, EC| ThDEFINE
Project
ThDEFINE
Re(defining) CD4+ T Cell Identities One Cell at a Time
  • Funder: European Commission (EC)
  • Project Code: 646794
  • Funding stream: H2020 | ERC | ERC-COG
, EC| THSWITCH
Project
THSWITCH
Decoding genetic switches in T helper cell differentiation
  • Funder: European Commission (EC)
  • Project Code: 260507
  • Funding stream: FP7 | SP2 | ERC
Download fromView all 6 versions
Nature Methods
Article
Provider: UnpayWall
Europe PubMed Central
Article . 2016
Provider: PubMed Central
Nature Methods
Article
Provider: Sygma
http://dx.doi.org/10.17863/cam...
Other literature type . 2019
Provider: Datacite
View more
44 references, page 1 of 3

Rossjohn, J. T cell antigen receptor recognition of antigen-presenting molecules. Annu. Rev. Immunol. 2015; 33: 169-200 [PubMed]

Krangel, MS. Mechanics of T cell receptor gene rearrangement. Curr. Opin. Immunol. 2009; 21: 133-139 [OpenAIRE] [PubMed]

Lieber, MR. Site-specific recombination in the immune system. FASEB J. 1991; 5: 2934-2944 [PubMed]

Becattini, S. Functional heterogeneity of human memory CD4+ T cell clones primed by pathogens or vaccines. Science. 2015; 347: 400-406 [PubMed]

Mamedov, IZ. Quantitative tracking of T cell clones after haematopoietic stem cell transplantation. EMBO Mol. Med. 2011; 3: 201-207 [OpenAIRE] [PubMed]

Thomas, N. Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinformatics. 2014; 30: 3181-3188 [OpenAIRE] [PubMed]

Dash, P. Paired analysis of TCRα and TCRβ chains at the single-cell level in mice. J. Clin. Invest. 2011; 121: 288-295 [OpenAIRE] [PubMed]

Linnemann, C. High-throughput identification of antigen-specific TCRs by TCR gene capture. Nat. Med. 2013; 19: 1534-1541 [OpenAIRE] [PubMed]

Turchaninova, MA. Pairing of T-cell receptor chains via emulsion PCR. Eur. J. Immunol. 2013; 43: 2507-2515 [PubMed]

Kim, S-M. Analysis of the paired TCR α- and β-chains of single human T cells. PLoS One. 2012; 7: e37338 [OpenAIRE] [PubMed]

Howie, B. High-throughput pairing of T cell receptor α and β sequences. Sci. Transl. Med. 2015; 7: 301ra131

Han, A, Glanville, J, Hansmann, L, Davis, MM. Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat. Biotechnol. 2014; 32: 684-692 [OpenAIRE] [PubMed]

Buettner, F. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol. 2015; 33: 155-160 [PubMed]

Jaitin, DA. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science. 2014; 343: 776-779 [OpenAIRE] [PubMed]

Patel, AP. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 2014; 344: 1396-1401 [OpenAIRE] [PubMed]

44 references, page 1 of 3
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue