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      High-throughput analysis of the human thymic Vδ1 + T cell receptor repertoire

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          Abstract

          γδ T cells are a relatively rare subset of lymphocytes in the human peripheral blood, but they play important roles at the interface between the innate and the adaptive immune systems. The γδ T cell lineage is characterized by a signature γδ T cell receptor (γδTCR) that displays extensive sequence variability originated by DNA rearrangement of the corresponding V(D)J loci. Human γδ T cells comprise Vγ9Vδ2 T cells, the major subset in the peripheral blood; and Vδ1 + T cells, the predominant subpopulation in the post-natal thymus and in peripheral tissues. While less studied, Vδ1 + T cells recently gathered significant attention due to their anti-cancer and anti-viral activities. In this study we applied next-generation sequencing (NGS) to analyse the γδTCR repertoire of highly (FACS-)purified Vδ1 + T cells from human thymic biopsies. Our analysis reveals unsuspected aspects of thymically rearranged and expressed (at the mRNA level) TRG and TRD genes, thus constituting a data resource that qualifies previous conclusions on the TCR repertoire of γδ T cells developing in the human thymus.

          Abstract

          Design Type(s) transcription profiling design • cellular data analysis objective
          Measurement Type(s) gamma delta T-lymphocyte
          Technology Type(s) RNA sequencing
          Factor Type(s) sex • gene
          Sample Characteristic(s) Homo sapiens • thymus

          Machine-accessible metadata file describing the reported data (ISA-Tab format)

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          Most cited references16

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          γδ T cells in cancer.

          With the promise of T cell-based therapy for cancer finally becoming reality, this Review focuses on the less-studied γδ T cell lineage and its diverse responses to tumours. γδ T cells have well-established protective roles in cancer, largely on the basis of their potent cytotoxicity and interferon-γ production. Besides this, recent studies have revealed a series of tumour-promoting functions that are linked to interleukin-17-producing γδ T cells. Here, we integrate the current knowledge from both human and mouse studies to highlight the potential of γδ T cell modulation to improve cancer immunotherapy.
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            IMGT(®) tools for the nucleotide analysis of immunoglobulin (IG) and T cell receptor (TR) V-(D)-J repertoires, polymorphisms, and IG mutations: IMGT/V-QUEST and IMGT/HighV-QUEST for NGS.

            IMGT/V-QUEST is the highly customized and integrated online IMGT(®) tool for the standardized analysis of the immunoglobulin (IG) or antibody and T cell receptor (TR) rearranged nucleotide sequences. The analysis of these antigen receptors represents a crucial challenge for the study of the adaptive immune response in normal and disease-related situations. The expressed IG and TR repertoires represent a potential of 10(12) IG and 10(12) TR per individual. This huge diversity results from mechanisms that occur at the DNA level during the IG and TR molecular synthesis. These mechanisms include the combinatorial rearrangements of the variable (V), diversity (D) and joining (J) genes, the N-diversity (deletion and addition at random of nucleotides during the V-(D)-J rearrangement) and, for IG, somatic hypermutations. IMGT/V-QUEST identifies the V, D, J genes and alleles by alignment with the germline IG and TR gene and allele sequences of the IMGT reference directory. The tool describes the V-REGION mutations and identifies the hot spot positions in the closest germline V gene. IMGT/V-QUEST integrates IMGT/JunctionAnalysis for a detailed analysis of the V-J and V-D-J junctions and IMGT/Automat for a complete annotation of the sequences and also provides IMGT Collier de Perles. IMGT/HighV-QUEST, the high-throughput version of IMGT/V-QUEST, implemented to answer the needs of deep sequencing data analysis from Next Generation Sequencing (NGS), allows the analysis of thousands of IG and TR sequences in a single run. IMGT/V-QUEST and IMGT/HighV-QUEST are available at the IMGT(®) Home page, http://www.imgt.org.
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              tcR: an R package for T cell receptor repertoire advanced data analysis

              Background The Immunoglobulins (IG) and the T cell receptors (TR) play the key role in antigen recognition during the adaptive immune response. Recent progress in next-generation sequencing technologies has provided an opportunity for the deep T cell receptor repertoire profiling. However, a specialised software is required for the rational analysis of massive data generated by next-generation sequencing. Results Here we introduce tcR, a new R package, representing a platform for the advanced analysis of T cell receptor repertoires, which includes diversity measures, shared T cell receptor sequences identification, gene usage statistics computation and other widely used methods. The tool has proven its utility in recent research studies. Conclusions tcR is an R package for the advanced analysis of T cell receptor repertoires after primary TR sequences extraction from raw sequencing reads. The stable version can be directly installed from The Comprehensive R Archive Network (http://cran.r-project.org/mirrors.html). The source code and development version are available at tcR GitHub (http://imminfo.github.io/tcr/) along with the full documentation and typical usage examples.
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                Author and article information

                Contributors
                Ravens.Sarina@mh-hannover.de
                bssantos@medicina.ulisboa.pt
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                4 July 2019
                4 July 2019
                2019
                : 6
                : 115
                Affiliations
                [1 ]ISNI 0000 0001 2181 4263, GRID grid.9983.b, Instituto de Medicina Molecular, Faculdade de Medicina, , Universidade de Lisboa, ; Lisbon, Portugal
                [2 ]ISNI 0000 0001 2181 4263, GRID grid.9983.b, Instituto Superior Técnico, , Universidade de Lisboa, ; Lisbon, Portugal
                [3 ]ISNI 0000 0000 9529 9877, GRID grid.10423.34, Institute of Immunology, , Hannover Medical School, ; Hannover, Germany
                Author information
                http://orcid.org/0000-0003-4141-9302
                Article
                118
                10.1038/s41597-019-0118-2
                6609709
                31273218
                ca3ee372-bcaa-4539-be9a-5a4b7e1c7ce4
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

                History
                : 15 November 2018
                : 29 May 2019
                Funding
                Funded by: Fundação para a Ciência e a Tecnologia (PD/BD/105880/2014); FEDER, through POR Lisboa 2020 - Programa Operacional Regional de Lisboa, PORTUGAL 2020, and Fundação para a Ciência e a Tecnologia
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: SFB900/B11
                Award Recipient :
                Funded by: Hannover Medical School Young Investigator Fund (MHH HiLF)
                Funded by: Fundação para a Ciência e a Tecnologia (PTDC/DTP-PIC/4931/2014); FEDER, through POR Lisboa 2020 - Programa Operacional Regional de Lisboa, PORTUGAL 2020, and Fundação para a Ciência e a Tecnologia
                Categories
                Data Descriptor
                Custom metadata
                © The Author(s) 2019

                immunogenetics,next-generation sequencing,gammadelta t cells

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