A Broad Survey and Functional Analysis of Immunoglobulin Loci Variation in Rhesus Macaques.

Ayelet Peres, Amit A Upadhyay, Vered Hana Klein, Swati Saha, Oscar L Rodriguez, Zachary M Vanwinkle, Kirti Karunakaran, Amanda Metz, William Lauer, Mark C Lin, Timothy Melton, Lukas Granholm, Pazit Polak, Samuel M Peterson, Eric J Peterson, Nagarajan Raju, Kaitlyn Shields, Steven Schultze, Thang Ton, Adam Ericsen, Stacey A Lapp, Francois J Villinger, Mats Ohlin, Christopher Cottrell, Rama Rao Amara, Cynthia A Derdeyn, Shane Crotty, William Schief, Gunilla B Karlsson Hedestam, Melissa Smith, William Lees, Corey T Watson, Gur Yaari, Steven E Bosinger
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Abstract

Rhesus macaques (RMs) are a vital model for studying human disease and invaluable to pre-clinical vaccine research, particularly for the study of broadly neutralizing antibody responses. Such studies require robust genetic resources for antibody-encoding genes within the immunoglobulin (IG) loci. The complexity of the IG loci has historically made them challenging to characterize accurately. To address this, we developed novel experimental and computational methodologies to generate the largest collection to date of integrated antibody repertoire and long-read genomic sequencing data in 106 Indian origin RMs. We created a comprehensive resource of IG heavy and light chain variable (V), diversity (D), and joining (J) alleles, as well as leader, intronic, and recombination signal sequences (RSSs), including the curation of 1474 novel alleles, unveiling tremendous diversity, and expanding existing IG allele sets by 60%. This publicly available, continually updated resource (https://vdjbase.org/reference_book/Rhesus_Macaque) provides the foundation for advancing RM immunogenomics, vaccine discovery, and translational research.

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恒河猴免疫球蛋白基因座变异的广泛调查与功能分析。
恒河猴(RMs)是研究人类疾病的重要模型,对疫苗发现和测试的临床前管道非常宝贵。特别是在这方面,它们通常用于研究感染和疫苗相关的广泛中和抗体反应。这导致对免疫球蛋白(IG)基因座的遗传资源的需求不断增加,免疫球蛋白(IG)基因座含有抗体编码基因。然而,这些基因座的高度多态性和结构可变性使它们在基因组和表达库水平上的测序和表征具有历史挑战性。为了应对这些挑战,我们开发了一种新的集成分析工作流程,用于将B细胞受体库测序数据与匹配的全基因组和靶向长读基因组测序数据进行组合处理。使用这种新颖的方法,我们收集了迄今为止报道的最大的IG种系等位基因集合,这些等位基因来自106个印度血统的rm。使用保守的注释方法,需要从基因组和表达数据集进行样本水平的内部验证,我们创建了一个全面的资源,可以捕获IG重链和轻链变量(V),多样性(D)和连接(J)等位基因,以及先导子,内含子和重组信号序列(rss)的广泛多样性。这个公开的、不断更新的数据库将推进传染病疫苗研究,并为免疫基因组学和未来的转化研究提供坚实的基础。
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