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Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing

机译:运用桑格和高通量测序方法分析Avain白血病病毒J亚群的准种

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Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data.
机译:背景禽白血病J亚组(ALV-J)以不同但紧密相关的名为准种的基因组的复杂混合物形式存在,该种根据达尔文进化原理不断变化。方法本研究旨在比较传统的Sanger测序和使用MiSeq平台进行的深度测序,以研究ALV-J的准种动态。结果通过重复进行每个实验,MiSeq测序的准确性和可重复性比Sanger测序更好。根据单位突变率和两种测序方法区分优势种的能力,传统的Sanger测序技术由于样品数量少而显示出高度的随机性,而深测序可以更准确地反映出种的组成。同时,通过重采样策略对Sanger测序的准种研究进行了模拟和分析,从高通量测序数据中替换了1000次重复序列,这表明抗体效价越高,序列熵越高,传统的Sanger测序方法较难分析,导致显性变体的比率降低。结论总之,深度测序更适合全面检测稀有变异。我们在此提出的Sanger测序模拟也将有助于标准化基于下一代测序数据在不同选择压力下的准种研究。

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