Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information.
Filtering Next-Generation Sequencing of the Ig Gene Repertoire Data Using Antibody Structural Information.
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使用抗体结构信息过滤Ig基因库数据的下一代测序。
DOI：
10.4049/jimmunol.1800669
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发表时间：
2018-12-15
期刊：
影响因子：
--
通讯作者：
Deane CM
中科院分区：
文献类型：
--
作者：
Kovaltsuk A;Krawczyk K;Kelm S;Snowden J;Deane CM
免疫球蛋白基因库的下一代测序（Ig-seq）在核苷酸序列水平上产生大量信息。这些数据提高了我们对许多物种免疫系统的理解，并已成功应用于疫苗开发和药物发现。然而，Ig-seq的高通量性质意味着它受到高错误率的困扰。这导致了错误纠正方法的发展。计算误差校正方法仅使用序列信息，主要是将序列指定为可能是正确的，如果它们被频繁观察的话。在这项工作中，我们描述了一种用于过滤Ig-seq数据的正交方法，该方法考虑了每个序列的结构可行性。典型的天然抗体结构需要在其每个可变链内存在二硫桥以维持折叠。ABOSS，我们的AntiBOdy序列分析仪使用该桥的存在/不存在作为鉴定结构上可行的序列和估计测序错误率的方法。在模拟的Ig-seq数据集上，ABOSS能够识别超过99%的结构可行序列。将我们的方法应用于六个独立的Ig-seq数据集（1只小鼠和5个人），我们表明我们的误差计算与以前的实验和计算误差估计一致。我们还展示了ABOSS是如何能够识别结构上不可能的序列错过了其他纠错方法。
Next-generation sequencing of the immunoglobulin gene repertoire (Ig-seq) produces large volumes of information at the nucleotide sequence level. Such data have improved our understanding of immune systems across numerous species and have already been successfully applied in vaccine development and drug discovery. However, the high-throughput nature of Ig-seq means that it is afflicted by high error rates. This has led to the development of error correction approaches. Computational error correction methods use sequence information alone, primarily designating sequences as likely to be correct if they are observed frequently. In this work, we describe an orthogonal method for filtering Ig-seq data, which considers the structural viability of each sequence. A typical natural antibody structure requires the presence of a disulfide bridge within each of its variable chains to maintain the fold. ABOSS, our AntiBOdy Sequence Selector uses the presence/absence of this bridge as a way of both identifying structurally viable sequences and estimating the sequencing error rate. On simulated Ig-seq datasets, ABOSS is able to identify more than 99% of structurally viable sequences. Applying our method to six independent Ig-seq datasets (1 mouse and 5 human), we show that our error calculations are in line with previous experimental and computational error estimates. We also show how ABOSS is able to identify structurally impossible sequences missed by other error correction methods.
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影响因子：
12.3
作者：
Galson JD;Trück J;Clutterbuck EA;Fowler A;Cerundolo V;Pollard AJ;Lunter G;Kelly DF
通讯作者：
Kelly DF
影响因子：
7.3
作者：
Krawczyk K;Kelm S;Kovaltsuk A;Galson JD;Kelly D;Trück J;Regep C;Leem J;Wong WK;Nowak J;Snowden J;Wright M;Starkie L;Scott-Tucker A;Shi J;Deane CM
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通讯作者：
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作者：
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通讯作者：
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影响因子：
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作者：
Lefranc, MP;Pommié, C;Lefranc, G
通讯作者：
Lefranc, G