Kirik Ufuk, Greiff Lennart, Levander Fredrik, Ohlin Mats
Dept. of Immunotechnology, Lund University, Lund, Sweden.
Dept. of Clinical Sciences, Division of Otorhinolaryngology, Head and Neck Cancer, Lund University, Sweden; Dept. of Otorhinolaryngology, Skåne University Hospital, Lund, Sweden.
Mol Immunol. 2017 Jul;87:12-22. doi: 10.1016/j.molimm.2017.03.012. Epub 2017 Apr 4.
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.
高通量测序及相关生物信息学流程支持对抗体库发育以及对自身免疫性疾病、过敏和疾病防护等重要的特异性抗体反应进行分析，这些流程描述了编码抗体可变区的多样性。将序列正确分配到种系基因对许多此类过程都很重要，例如在体细胞超突变分析中。通过使用诸如TIgGER或IgDiscover等工具从抗体编码转录组中推断种系基因，有可能提高此类分析的质量。这些工具还可用于识别以前未知的种系基因。在本研究中，我们利用此类软件进行种系基因推断，并确定影响基因推断结果的分析设置方面以及种系基因的现有知识。此外，我们证明了在受试者对此类基因杂合时，IGHJ和IGHD单倍型推断能够总体上支持IGHV基因推断，并有助于识别目前种系基因参考目录未识别的新等位基因。我们建议，在未来的最佳实践中，只要有可能，都应使用这种单倍型分析来支持种系基因推断的结果。IGHJ导向的单倍型推断还用于识别不表达某些IGHV种系基因的单倍型。特别是，我们鉴定出一种不表达几种主要种系基因的单倍型，如IGHV1-8、IGHV3-9、IGHV3-15、IGHV-18、IGHV3-21和IGHV3-23。我们设想，单倍型分析将提供一种有效的方法来识别受试者，以便进一步研究可用免疫球蛋白库与免疫反应结果之间的联系。
