@article{Wu2020,
  doi = {10.1038/s41586-020-2056-8},
  url = {https://doi.org/10.1038/s41586-020-2056-8},
  year = {2020},
  month = feb,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {579},
  number = {7798},
  pages = {274--278},
  author = {Thomas D. Wu and Shravan Madireddi and Patricia E. de Almeida and Romain Banchereau and Ying-Jiun J. Chen and Avantika S. Chitre and Eugene Y. Chiang and Hina Iftikhar and William E. O'Gorman and Amelia Au-Yeung and Chikara Takahashi and Leonard D. Goldstein and Chungkee Poon and Shilpa Keerthivasan and Denise E. de Almeida Nagata and Xiangnan Du and Hyang-Mi Lee and Karl L. Banta and Sanjeev Mariathasan and Meghna Das Thakur and Mahrukh A. Huseni and Marcus Ballinger and Ivette Estay and Patrick Caplazi and Zora Modrusan and L{\'{e}}lia Delamarre and Ira Mellman and Richard Bourgon and Jane L. Grogan},
  title = {Peripheral T cell expansion predicts tumour infiltration and clinical response},
  journal = {Nature}
}

@article{Schuldt2019,
  doi = {10.4049/jimmunol.1800904},
  url = {https://doi.org/10.4049/jimmunol.1800904},
  year = {2019},
  month = jan,
  publisher = {The American Association of Immunologists},
  volume = {202},
  number = {3},
  pages = {637--644},
  author = {Nathaniel J. Schuldt and Bryce A. Binstadt},
  title = {Dual {TCR} T Cells: Identity Crisis or Multitaskers?},
  journal = {The Journal of Immunology}
}

@article{TCRdist,
  doi = {10.1038/nature22383},
  url = {https://doi.org/10.1038/nature22383},
  year = {2017},
  month = jun,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {547},
  number = {7661},
  pages = {89--93},
  author = {Pradyot Dash and Andrew J. Fiore-Gartland and Tomer Hertz and George C. Wang and Shalini Sharma and Aisha Souquette and Jeremy Chase Crawford and E. Bridie Clemens and Thi H. O. Nguyen and Katherine Kedzierska and Nicole L. La Gruta and Philip Bradley and Paul G. Thomas},
  title = {Quantifiable predictive features define epitope-specific T cell receptor repertoires},
  journal = {Nature}
}

@article{Brady2010-gh,
  title    = "Antigen receptor allelic exclusion: an update and reappraisal",
  author   = "Brady, Brenna L and Steinel, Natalie C and Bassing, Craig H",
  abstract = "Most lymphocytes express cell surface Ag receptor chains from
              single alleles of distinct Ig or TCR loci. Since the
              identification of Ag receptor allelic exclusion, the importance
              of this process and the precise molecular mechanisms by which it
              is achieved have remained enigmatic. This brief review summarizes
              current knowledge of the extent to which Ig and TCR loci are
              subject to allelic exclusion. Recent progress in studying and
              defining mechanistic steps and molecules that may control the
              monoallelic initiation and subsequent inhibition of V-to-(D)-J
              recombination is outlined using the mouse TCR$\beta$ locus as a
              model with frequent comparisons to the mouse IgH and Ig$\kappa$
              loci. Potential consequences of defects in mechanisms that
              control Ag receptor allelic exclusion and a reappraisal of the
              physiologic relevance of this immunologic process also are
              discussed.",
  journal  = "J. Immunol.",
  volume   =  185,
  number   =  7,
  pages    = "3801--3808",
  month    =  oct,
  year     =  2010,
  language = "en"
}

@article{Afik2017-sg,
  title    = "Targeted reconstruction of {T} cell receptor sequence from single
              cell {RNA-seq} links {CDR3} length to {T} cell differentiation
              state",
  author   = "Afik, Shaked and Yates, Kathleen B and Bi, Kevin and Darko,
              Samuel and Godec, Jernej and Gerdemann, Ulrike and Swadling, Leo
              and Douek, Daniel C and Klenerman, Paul and Barnes, Eleanor J and
              Sharpe, Arlene H and Haining, W Nicholas and Yosef, Nir",
  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.",
  journal  = "Nucleic Acids Res.",
  volume   =  45,
  number   =  16,
  pages    = "e148",
  month    =  sep,
  year     =  2017,
  language = "en"
}

@article{Fischer2019,
  doi = {10.1101/734053},
  url = {https://doi.org/10.1101/734053},
  year = {2019},
  month = aug,
  publisher = {Cold Spring Harbor Laboratory},
  author = {David S. Fischer and Yihan Wu and Benjamin Schubert and Fabian J. Theis},
  title = {Predicting antigen-specificity of single T-cells based on {TCR} {CDR}3 regions},
  journal = {BioRxiv}
}

@article{Zhang2018-ip,
  title    = "Lineage tracking reveals dynamic relationships of {T} cells in
              colorectal cancer",
  author   = "Zhang, Lei and Yu, Xin and Zheng, Liangtao and Zhang, Yuanyuan
              and Li, Yansen and Fang, Qiao and Gao, Ranran and Kang, Boxi and
              Zhang, Qiming and Huang, Julie Y and Konno, Hiroyasu and Guo,
              Xinyi and Ye, Yingjiang and Gao, Songyuan and Wang, Shan and Hu,
              Xueda and Ren, Xianwen and Shen, Zhanlong and Ouyang, Wenjun and
              Zhang, Zemin",
  abstract = "T cells are key elements of cancer immunotherapy1 but certain
              fundamental properties, such as the development and migration of
              T cells within tumours, remain unknown. The enormous T cell
              receptor (TCR) repertoire, which is required for the recognition
              of foreign and self-antigens2, could serve as lineage tags to
              track these T cells in tumours3. Here we obtained transcriptomes
              of 11,138 single T cells from 12 patients with colorectal cancer,
              and developed single T cell analysis by RNA sequencing and TCR
              tracking (STARTRAC) indices to quantitatively analyse the dynamic
              relationships among 20 identified T cell subsets with distinct
              functions and clonalities. Although both CD8+ effector and
              'exhausted' T cells exhibited high clonal expansion, they were
              independently connected with tumour-resident CD8+ effector memory
              cells, implicating a TCR-based fate decision. Of the CD4+ T
              cells, most tumour-infiltrating T regulatory (Treg) cells showed
              clonal exclusivity, whereas certain Treg cell clones were
              developmentally linked to several T helper (TH) cell clones.
              Notably, we identified two IFNG+ TH1-like cell clusters in
              tumours that were associated with distinct IFN$\gamma$-regulating
              transcription factors -the GZMK+ effector memory T cells, which
              were associated with EOMES and RUNX3, and CXCL13+BHLHE40+
              TH1-like cell clusters, which were associated with BHLHE40. Only
              CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in
              patients with microsatellite-instable tumours, and this might
              explain their favourable responses to immune-checkpoint blockade.
              Furthermore, IGFLR1 was highly expressed in both CXCL13+BHLHE40+
              TH1-like cells and CD8+ exhausted T cells and possessed
              co-stimulatory functions. Our integrated STARTRAC analyses
              provide a powerful approach to dissect the T cell properties in
              colorectal cancer comprehensively, and could provide insights
              into the dynamic relationships of T cells in other cancers.",
  journal  = "Nature",
  volume   =  564,
  number   =  7735,
  pages    = "268--272",
  month    =  dec,
  year     =  2018,
  language = "en"
}

@article{Ji2010-bn,
  title    = "Viral infection triggers central nervous system autoimmunity via
              activation of {CD8+} {T} cells expressing dual {TCRs}",
  author   = "Ji, Qingyong and Perchellet, Antoine and Goverman, Joan M",
  abstract = "Multiple sclerosis is an inflammatory, demyelinating, central
              nervous system disease mediated by myelin-specific T cells.
              Environmental triggers that cause the breakdown of
              myelin-specific T cell tolerance are unknown. Here we found that
              CD8(+) myelin basic protein (MBP)-specific T cell tolerance was
              broken and autoimmunity was induced by infection with a virus
              that did not express MBP cross-reactive epitopes and did not
              depend on bystander activation. Instead, the virus activated T
              cells expressing dual T cell antigen receptors (TCRs) that were
              able to recognize both MBP and viral antigens. Our results
              demonstrate the importance of dual TCR-expressing T cells in
              autoimmunity and suggest a mechanism by which a ubiquitous viral
              infection could trigger autoimmunity in a subset of infected
              people, as suggested by the etiology of multiple sclerosis.",
  journal  = "Nat. Immunol.",
  volume   =  11,
  number   =  7,
  pages    = "628--634",
  month    =  jul,
  year     =  2010,
  language = "en"
}

@article{Stubbington2016-kh,
  title    = "{T} cell fate and clonality inference from single-cell
              transcriptomes",
  author   = "Stubbington, Michael J T and L{\"o}nnberg, Tapio and Proserpio,
              Valentina and Clare, Simon and Speak, Anneliese O and Dougan,
              Gordon and Teichmann, Sarah A",
  abstract = "We developed TraCeR, a computational method to reconstruct
              full-length, paired T cell receptor (TCR) sequences from T
              lymphocyte single-cell RNA sequence data. TraCeR links T cell
              specificity with functional response by revealing clonal
              relationships between cells alongside their transcriptional
              profiles. We found that T cell clonotypes in a mouse Salmonella
              infection model span early activated CD4(+) T cells as well as
              mature effector and memory cells.",
  journal  = "Nat. Methods",
  volume   =  13,
  number   =  4,
  pages    = "329--332",
  month    =  apr,
  year     =  2016,
  language = "en"
}

@article{Glanville2017-ay,
  title    = "Identifying specificity groups in the {T} cell receptor
              repertoire",
  author   = "Glanville, Jacob and Huang, Huang and Nau, Allison and Hatton,
              Olivia and Wagar, Lisa E and Rubelt, Florian and Ji, Xuhuai and
              Han, Arnold and Krams, Sheri M and Pettus, Christina and Haas,
              Nikhil and Arlehamn, Cecilia S Lindestam and Sette, Alessandro
              and Boyd, Scott D and Scriba, Thomas J and Martinez, Olivia M and
              Davis, Mark M",
  abstract = "T cell receptor (TCR) sequences are very diverse, with many more
              possible sequence combinations than T cells in any one
              individual. Here we define the minimal requirements for TCR
              antigen specificity, through an analysis of TCR sequences using a
              panel of peptide and major histocompatibility complex
              (pMHC)-tetramer-sorted cells and structural data. From this
              analysis we developed an algorithm that we term GLIPH (grouping
              of lymphocyte interactions by paratope hotspots) to cluster TCRs
              with a high probability of sharing specificity owing to both
              conserved motifs and global similarity of
              complementarity-determining region 3 (CDR3) sequences. We show
              that GLIPH can reliably group TCRs of common specificity from
              different donors, and that conserved CDR3 motifs help to define
              the TCR clusters that are often contact points with the antigenic
              peptides. As an independent validation, we analysed 5,711
              TCR$\beta$ chain sequences from reactive CD4 T cells from 22
              individuals with latent Mycobacterium tuberculosis infection. We
              found 141 TCR specificity groups, including 16 distinct groups
              containing TCRs from multiple individuals. These TCR groups
              typically shared HLA alleles, allowing prediction of the likely
              HLA restriction, and a large number of M. tuberculosis T cell
              epitopes enabled us to identify pMHC ligands for all five of the
              groups tested. Mutagenesis and de novo TCR design confirmed that
              the GLIPH-identified motifs were critical and sufficient for
              shared-antigen recognition. Thus the GLIPH algorithm can analyse
              large numbers of TCR sequences and define TCR specificity groups
              shared by TCRs and individuals, which should greatly accelerate
              the analysis of T cell responses and expedite the identification
              of specific ligands.",
  journal  = "Nature",
  volume   =  547,
  number   =  7661,
  pages    = "94--98",
  month    =  jul,
  year     =  2017,
  language = "en"
}
