Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
PLoS Comput Biol. 2019 Jul 22;15(7):e1007133. doi: 10.1371/journal.pcbi.1007133. eCollection 2019 Jul.
The collection of immunoglobulin genes in an individual's germline, which gives rise to B cell receptors via recombination, is known to vary significantly across individuals. In humans, for example, each individual has only a fraction of the several hundred known V alleles. Furthermore, the currently-accepted set of known V alleles is both incomplete (particularly for non-European samples), and contains a significant number of spurious alleles. The resulting uncertainty as to which immunoglobulin alleles are present in any given sample results in inaccurate B cell receptor sequence annotations, and in particular inaccurate inferred naive ancestors. In this paper we first show that the currently widespread practice of aligning each sequence to its closest match in the full set of IMGT alleles results in a very large number of spurious alleles that are not in the sample's true set of germline V alleles. We then describe a new method for inferring each individual's germline gene set from deep sequencing data, and show that it improves upon existing methods by making a detailed comparison on a variety of simulated and real data samples. This new method has been integrated into the partis annotation and clonal family inference package, available at https://github.com/psathyrella/partis, and is run by default without affecting overall run time.
个体的免疫球蛋白基因在个体的胚系中收集，通过重组产生 B 细胞受体，已知在个体之间存在显著差异。例如，在人类中，每个个体只有几百个已知 V 等位基因中的一部分。此外，目前公认的已知 V 等位基因集既不完整（特别是对于非欧洲样本），也包含大量虚假等位基因。由于对任何给定样本中存在哪些免疫球蛋白等位基因存在不确定性，导致 B 细胞受体序列注释不准确，特别是推断的幼稚祖先不准确。在本文中，我们首先表明，目前广泛采用的将每个序列与完整的 IMGT 等位基因集中的最接近匹配进行对齐的做法，会导致大量虚假等位基因，这些基因不在样本的真实胚系 V 等位基因集中。然后，我们描述了一种从深度测序数据推断每个个体的胚系基因集的新方法，并表明它通过在各种模拟和真实数据样本上进行详细比较，改进了现有方法。该新方法已集成到 partis 注释和克隆家族推断包中，可在 https://github.com/psathyrella/partis 上获得，并默认运行，不会影响整体运行时间。
