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- Kirik, Ufuk, et al.
(författare)
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Antibody heavy chain variable domains of different germline gene origins diversify through different paths
- 2017
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Ingår i: Frontiers in Immunology. - : Frontiers Media SA. - 1664-3224. ; 8:NOV
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Tidskriftsartikel (refereegranskat)abstract
- B cells produce antibodies, key effector molecules in health and disease. They mature their properties, including their affinity for antigen, through hypermutation events; processes that involve, e.g., base substitution, codon insertion and deletion, often in association with an isotype switch. Investigations of antibody evolution define modes whereby particular antibody responses are able to form, and such studies provide insight important for instance for development of efficient vaccines. Antibody evolution is also used in vitro for the design of antibodies with improved properties. To better understand the basic concepts of antibody evolution, we analyzed the mutational paths, both in terms of amino acid substitution and insertions and deletions, taken by antibodies of the IgG isotype. The analysis focused on the evolution of the heavy chain variable domain of sets of antibodies, each with an origin in 1 of 11 different germline genes representing six human heavy chain germline gene subgroups. Investigated genes were isolated from cells of human bone marrow, a major site of antibody production, and characterized by next-generation sequencing and an in-house bioinformatics pipeline. Apart from substitutions within the complementarity determining regions, multiple framework residues including those in protein cores were targets of extensive diversification. Diversity, both in terms of substitutions, and insertions and deletions, in antibodies is focused to different positions in the sequence in a germline gene-unique manner. Altogether, our findings create a framework for understanding patterns of evolution of antibodies from defined germline genes.
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| 2. |
- Kirik, Ufuk, et al.
(författare)
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Data on haplotype-supported immunoglobulin germline gene inference
- 2017
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Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409. ; 13, s. 620-640
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Tidskriftsartikel (refereegranskat)abstract
- Data that defines IGHV (immunoglobulin heavy chain variable) germline gene inference using sequences of IgM-encoding transcriptomes obtained by Illumina MiSeq sequencing technology are described. Such inference is used to establish personalized germline gene sets for in-depth antibody repertoire studies and to detect new antibody germline genes from widely available immunoglobulin-encoding transcriptome data sets. Specifically, the data has been used to validate (Parallel antibody germline gene and haplotype analyses support the validity of immunoglobulin germline gene inference and discovery (DOI: 10.1016/j.molimm.2017.03.012) (Kirik et al., 2017) [1]) the inference process. This was accomplished based on analysis of the inferred germline genes’ association to the donors’ different haplotypes as defined by their different, expressed IGHJ alleles and/or IGHD genes/alleles. The data is important for development of validated germline gene databases containing entries inferred from immunoglobulin-encoding transcriptome sequencing data sets, and for generation of valid, personalized antibody germline gene repertoires.
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| 3. |
- Kirik, Ufuk, et al.
(författare)
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Parallel antibody germline gene and haplotype analyses support the validity of immunoglobulin germline gene inference and discovery
- 2017
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Ingår i: Molecular Immunology. - : Elsevier BV. - 0161-5890. ; 87, s. 12-22
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of antibody repertoire development and specific antibody responses important for e.g. autoimmune conditions, allergy, and protection against disease is supported by high throughput sequencing and associated bioinformatics pipelines that describe the diversity of the encoded antibody variable domains. Proper assignment of sequences to germline genes are important for many such processes, for instance in the analysis of somatic hypermutation. Germline gene inference from antibody-encoding transcriptomes, by using tools such as TIgGER or IgDiscover, has a potential to enhance the quality of such analyses. These tools may also be used to identify germline genes not previously known. In this study, we exploited such software for germline gene inference and define aspects of analysis settings and pre-existing knowledge of germline genes that affect the outcome of gene inference. Furthermore, we demonstrate the capacity of IGHJ and IGHD haplotype inference, whenever subjects are heterozygous with respect to such genes, to lend support to IGHV gene inference in general, and to the identification of novel alleles presently not recognized by germline gene reference directories. We propose that such haplotype analysis shall, whenever possible, be used in future best practice to support the outcome of germline gene inference. IGHJ-directed haplotype inference was also used to identify haplotypes not expressing some IGHV germline genes. In particular, we identified a haplotype that did not express several major germline genes such as IGHV1-8, IGHV3-9, IGHV3-15, IGHV1-18, IGHV3-21, and IGHV3-23. We envisage that haplotype analysis will provide an efficient approach to identify subjects for further studies of the link between the available immunoglobulin repertoire and outcomes of immune responses.
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