A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus.
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus.
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DOI：
10.3389/fimmu.2020.02136
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发表时间：
2020
影响因子：
7.3
通讯作者：
Watson CT
中科院分区：
文献类型：
--
作者：
Rodriguez OL;Gibson WS;Parks T;Emery M;Powell J;Strahl M;Deikus G;Auckland K;Eichler EE;Marasco WA;Sebra R;Sharp AJ;Smith ML;Bashir A;Watson CT
高度多态性的免疫球蛋白重链位点（IGH）遗传变异的不完全确定阻碍了我们确定影响抗体介导过程的遗传因素的能力。由于基因座的复杂性，标准的高通量方法无法准确、全面地捕获IGH多态性。因此，该基因座仅被完整地描述了两次，严重限制了我们对人类IGH多样性的认识。在这里，我们将靶向长读测序与一种新的生物信息学工具IGenotyper结合起来，以单倍型特异性的方式全面表征IGH变异。我们将这种方法应用于8个人类样本，包括一个单倍体细胞系和两个母亲-父亲-孩子三胞胎，并证明了产生高质量组装（>98%完整，>99%准确），基因型和基因注释的能力，鉴定了2个新的结构变体和15个新的IGH等位基因。我们表明，多路复用允许在不影响数据质量的情况下扩展方法，并且我们的基因型调用集比短读（>真阳性增加35%，>假阳性减少97%）和基于阵列/假设的数据集更准确。该框架为利用IG基因组数据研究抗体介导免疫的人群水平变化奠定了迫切需要的基础，这对我们更好地了解疾病风险以及对疫苗和治疗的反应至关重要。
An incomplete ascertainment of genetic variation within the highly polymorphic immunoglobulin heavy chain locus (IGH) has hindered our ability to define genetic factors that influence antibody-mediated processes. Due to locus complexity, standard high-throughput approaches have failed to accurately and comprehensively capture IGH polymorphism. As a result, the locus has only been fully characterized two times, severely limiting our knowledge of human IGH diversity. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize IGH variation in a haplotype-specific manner. We apply this approach to eight human samples, including a haploid cell line and two mother-father-child trios, and demonstrate the ability to generate high-quality assemblies (>98% complete and >99% accurate), genotypes, and gene annotations, identifying 2 novel structural variants and 15 novel IGH alleles. We show multiplexing allows for scaling of the approach without impacting data quality, and that our genotype call sets are more accurate than short-read (>35% increase in true positives and >97% decrease in false-positives) and array/imputation-based datasets. This framework establishes a desperately needed foundation for leveraging IG genomic data to study population-level variation in antibody-mediated immunity, critical for bettering our understanding of disease risk, and responses to vaccines and therapeutics.
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DOI：
10.1073/pnas.1417683112
发表时间：
2015-02-24
影响因子：
11.1
作者：
Gadala-Maria, Daniel;Yaari, Gur;Kleinstein, Steven H.
通讯作者：
Kleinstein, Steven H.
影响因子：
7.3
作者：
Calonga-Solis, Veronica;Malheiros, Danielle;Augusto, Danillo G.
通讯作者：
Augusto, Danillo G.
影响因子：
48
作者：
Chin, Chen-Shan;Peluso, Paul;Schatz, Michael C.
通讯作者：
Schatz, Michael C.
影响因子：
7.7
作者：
Hoff, Siv Nam Khang;Baalsrud, Helle T.;Jentoft, Sissel
通讯作者：
Jentoft, Sissel
影响因子：
4.6
作者：
Dhande, Isha S.;Kneedler, Sterling C.;Doris, Peter A.
通讯作者：
Doris, Peter A.