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      VDJServer: A Cloud-Based Analysis Portal and Data Commons for Immune Repertoire Sequences and Rearrangements

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          Abstract

          Background

          Recent technological advances in immune repertoire sequencing have created tremendous potential for advancing our understanding of adaptive immune response dynamics in various states of health and disease. Immune repertoire sequencing produces large, highly complex data sets, however, which require specialized methods and software tools for their effective analysis and interpretation.

          Results

          VDJServer is a cloud-based analysis portal for immune repertoire sequence data that provide access to a suite of tools for a complete analysis workflow, including modules for preprocessing and quality control of sequence reads, V(D)J gene segment assignment, repertoire characterization, and repertoire comparison. VDJServer also provides sophisticated visualizations for exploratory analysis. It is accessible through a standard web browser via a graphical user interface designed for use by immunologists, clinicians, and bioinformatics researchers. VDJServer provides a data commons for public sharing of repertoire sequencing data, as well as private sharing of data between users. We describe the main functionality and architecture of VDJServer and demonstrate its capabilities with use cases from cancer immunology and autoimmunity.

          Conclusion

          VDJServer provides a complete analysis suite for human and mouse T-cell and B-cell receptor repertoire sequencing data. The combination of its user-friendly interface and high-performance computing allows large immune repertoire sequencing projects to be analyzed with no programming or software installation required. VDJServer is a web-accessible cloud platform that provides access through a graphical user interface to a data management infrastructure, a collection of analysis tools covering all steps in an analysis, and an infrastructure for sharing data along with workflows, results, and computational provenance. VDJServer is a free, publicly available, and open-source licensed resource.

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          Most cited references47

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          Somatic generation of antibody diversity.

          In the genome of a germ-line cell, the genetic information for an immunoglobulin polypeptide chain is contained in multiple gene segments scattered along a chromosome. During the development of bone marrow-derived lymphocytes, these gene segments are assembled by recombination which leads to the formation of a complete gene. In addition, mutations are somatically introduced at a high rate into the amino-terminal region. Both somatic recombination and mutation contribute greatly to an increase in the diversity of antibody synthesized by a single organism.
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            pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires.

            Driven by dramatic technological improvements, large-scale characterization of lymphocyte receptor repertoires via high-throughput sequencing is now feasible. Although promising, the high germline and somatic diversity, especially of B-cell immunoglobulin repertoires, presents challenges for analysis requiring the development of specialized computational pipelines. We developed the REpertoire Sequencing TOolkit (pRESTO) for processing reads from high-throughput lymphocyte receptor studies. pRESTO processes raw sequences to produce error-corrected, sorted and annotated sequence sets, along with a wealth of metrics at each step. The toolkit supports multiplexed primer pools, single- or paired-end reads and emerging technologies that use single-molecule identifiers. pRESTO has been tested on data generated from Roche and Illumina platforms. It has a built-in capacity to parallelize the work between available processors and is able to efficiently process millions of sequences generated by typical high-throughput projects.
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              Precise determination of the diversity of a combinatorial antibody library gives insight into the human immunoglobulin repertoire.

              Antibody repertoire diversity, potentially as high as 10(11) unique molecules in a single individual, confounds characterization by conventional sequence analyses. In this study, we present a general method for assessing human antibody sequence diversity displayed on phage using massively parallel pyrosequencing, a novel application of Kabat column-labeled profile Hidden Markov Models, and translated complementarity determining region (CDR) capture-recapture analysis. Pyrosequencing of domain amplicon and RCA PCR products generated 1.5 x 10(6) reads, including more than 1.9 x 10(5) high quality, full-length sequences of antibody variable fragment (Fv) variable domains. Novel methods for germline and CDR classification and fine characterization of sequence diversity in the 6 CDRs are presented. Diverse germline contributions to the repertoire with random heavy and light chain pairing are observed. All germline families were found to be represented in 1.7 x 10(4) sequences obtained from repeated panning of the library. While the most variable CDR (CDR-H3) presents significant length and sequence variability, we find a substantial contribution to total diversity from somatically mutated germline encoded CDRs 1 and 2. Using a capture-recapture method, the total diversity of the antibody library obtained from a human donor Immunoglobulin M (IgM) pool was determined to be at least 3.5 x 10(10). The results provide insights into the role of IgM diversification, display library construction, and productive germline usages in antibody libraries and the humoral repertoire.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                08 May 2018
                2018
                : 9
                : 976
                Affiliations
                [1] 1Department of Clinical Sciences, University of Texas Southwestern Medical Center , Dallas, TX, United States
                [2] 2Texas Advanced Computing Center, University of Texas at Austin , Austin, TX, United States
                [3] 3Bank of America Corporate Center , Charlotte, NC, United States
                [4] 4Bio5 Institute, University of Arizona , Tucson, AZ, United States
                [5] 5Department of Microbiology and Immunology, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine , Stanford, CA, United States
                [6] 6H. Lee Moffitt Cancer Center and Research Institute , Tampa, FL, United States
                [7] 7Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center , Dallas, TX, United States
                [8] 8Department of Immunology, University of Texas Southwestern Medical Center , Dallas, TX, United States
                [9] 9J. Craig Venter Institute , La Jolla, CA, United States
                [10] 10Department of Pathology, University of California, San Diego , San Diego, CA, United States
                [11] 11La Jolla Institute for Allergy & Immunology , La Jolla, CA, United States
                Author notes

                Edited by: Deborah K. Dunn-Walters, University of Surrey, United Kingdom

                Reviewed by: Johannes Trück, University Children’s Hospital Zurich, Switzerland; Michael Zemlin, Universitätsklinikum des Saarlandes, Germany; Nina Luning Prak, University of Pennsylvania, United States

                *Correspondence: Lindsay G. Cowell, lindsay.cowell@ 123456utsouthwestern.edu

                Specialty section: This article was submitted to B Cell Biology, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2018.00976
                5953328
                29867956
                4c66ce99-dbb6-4eb6-a77a-5f1580b13a63
                Copyright © 2018 Christley, Scarborough, Salinas, Rounds, Toby, Fonner, Levin, Kim, Mock, Jordan, Ostmeyer, Buntzman, Rubelt, Davila, Monson, Scheuermann and Cowell.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 January 2018
                : 19 April 2018
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 67, Pages: 12, Words: 9274
                Funding
                Funded by: National Institute of Allergy and Infectious Diseases 10.13039/100000060
                Award ID: AI097403, AI057229
                Funded by: H. Lee Moffitt Cancer Center and Research Institute 10.13039/100005567
                Funded by: National Multiple Sclerosis Society 10.13039/100000890
                Categories
                Immunology
                Technology Report

                Immunology
                bioinformatics,cloud computing,rep-seq,immune repertoire,b-cell receptor,t cell receptor
                Immunology
                bioinformatics, cloud computing, rep-seq, immune repertoire, b-cell receptor, t cell receptor

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