13 research outputs found
AIRR Community Standardized Representations for Annotated Immune Repertoires
Increased interest in the immune system's involvement in pathophysiological phenomena coupled with decreased DNA sequencing costs have led to an explosion of antibody and T cell receptor sequencing data collectively termed “adaptive immune receptor repertoire sequencing” (AIRR-seq or Rep-Seq). The AIRR Community has been actively working to standardize protocols, metadata, formats, APIs, and other guidelines to promote open and reproducible studies of the immune repertoire. In this paper, we describe the work of the AIRR Community's Data Representation Working Group to develop standardized data representations for storing and sharing annotated antibody and T cell receptor data. Our file format emphasizes ease-of-use, accessibility, scalability to large data sets, and a commitment to open and transparent science. It is composed of a tab-delimited format with a specific schema. Several popular repertoire analysis tools and data repositories already utilize this AIRR-seq data format. We hope that others will follow suit in the interest of promoting interoperable standards
Inferred Allelic Variants of Immunoglobulin Receptor Genes: a system for their evaluation, documentation, and naming
Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC—focusing, to begin with, on human IGHV genes—with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species
Identification of the Biologically Relevant HLA DR-DQ Amino Acids in Type 1 Diabetes (T1D)
Sequence feature variant type (SFVT) analysis of HLA DR-DQ amino acids in type 1 diabetes (T1D)
Organism identification using a genome sequence-independent universal microarray probe set
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VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements
BackgroundThe genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D)J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D)J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D)J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D)J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses.ResultsTo help address this problem, we propose a standardized file format for representing V(D)J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D)J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format.ConclusionsThe VDJML suite will allow users to streamline their V(D)J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https://vdjserver.org/vdjml/ . We welcome participation from the community in developing the file format standard, as well as code contributions
VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements
Background: The genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D) J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D) J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D) J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D) J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses. Results: To help address this problem, we propose a standardized file format for representing V(D) J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D) J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format. Conclusions: The VDJML suite will allow users to streamline their V(D) J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https:// vdjserver. org/ vdjml/. We welcome participation from the community in developing the file format standard, as well as code contributions.Burroughs Welcome Fund Career Award; NIAID [AI097403]; Bioinformatics Support Contract (BISC) [HHSN272201200028C]; National Institute of Allergy and Infectious Diseases grant [U19 AI090019, R01 AI104739]; PhRMA foundation pre-doctoral informatics fellowship; National Library of Medicine of the National Institutes of Health [T15 LM07056]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Novel sequence feature variant type analysis of the HLA genetic association in systemic sclerosis
We describe a novel approach to genetic association analyses with proteins sub-divided into biologically relevant smaller sequence features (SFs), and their variant types (VTs). SFVT analyses are particularly informative for study of highly polymorphic proteins such as the human leukocyte antigen (HLA), given the nature of its genetic variation: the high level of polymorphism, the pattern of amino acid variability, and that most HLA variation occurs at functionally important sites, as well as its known role in organ transplant rejection, autoimmune disease development and response to infection. Further, combinations of variable amino acid sites shared by several HLA alleles (shared epitopes) are most likely better descriptors of the actual causative genetic variants. In a cohort of systemic sclerosis patients/controls, SFVT analysis shows that a combination of SFs implicating specific amino acid residues in peptide binding pockets 4 and 7 of HLA-DRB1 explains much of the molecular determinant of risk