通过短读数高通量测序研究 RSV 的宿主内遗传变异。

IF 0.3 Q4 SOCIAL ISSUES
David Henke, Felipe-Andrés Piedra, Vasanthi Avadhanula, Harsha Doddapaneni, Donna M Muzny, Vipin K Menon, Kristi L Hoffman, Matthew C Ross, Sara J Javornik Cregeen, Ginger Metcalf, Richard A Gibbs, Joseph F Petrosino, Pedro A Piedra
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引用次数: 0

摘要

每一次病毒感染都会导致病毒基因组群体的演变。高通量测序技术可用于描述此类群体的特征,但迄今为止,此类工作的发表实例还很少。此外,混合测序数据有时被用来推断感染基因组的特性,而没有区分基因组衍生读数和来自更丰富的转录本(在典型的活跃病毒感染中)的读数。在这里,我们将基于捕获探针的短读数高通量测序技术应用于鼻腔清洗样本,该样本取自之前描述过的一组自然感染了呼吸道合胞病毒(RSV)的成年造血细胞移植(HCT)受者。我们通过计算每个位置的香农熵,分别分析了基因组和转录本的读数,以了解遗传变异的水平和分布。我们的分析表明,在本文分析的 RSV 感染中,遗传变异水平较低,但基因组和转录本之间在以下方面存在有趣的差异:1)每个样本的平均香农熵;2)变异 "热点 "的基因组分布;3)编码替代氨基酸的热点的基因组分布。总之,我们的研究结果表明,在解读高通量测序数据以深入了解宿主内病毒基因组的复制、表达和进化时,分别分析基因组和转录本的读数非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining intra-host genetic variation of RSV by short read high-throughput sequencing.

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation 'hotspots'; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

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