Like most RNA viruses, influenza viruses generate defective viral genomes (DVGs) with large internal deletions during replication. There is accumulating evidence supporting a biological relevance of such DVGs. However, further understanding of the molecular mechanisms that underlie the production and biological activity of DVGs is conditioned upon the sensitivity and accuracy of detection methods, i.e. next-generation sequencing (NGS) technologies and related bioinformatics algorithms. Although many algorithms were developed, their sensitivity and reproducibility were mostly assessed on simulated data. Here, we introduce DG-seq, a time-efficient pipeline for DVG detection and quantification, and a set of biological controls to assess the performance of not only our bioinformatics algorithm but also the upstream NGS steps. Using these tools, we provide the first rigorous comparison of the two commonly used sample processing methods for RNA-seq, with or without a PCR pre-amplification step. Our data show that pre-amplification confers a limited advantage in terms of sensitivity and introduces size- but also sequence-dependent biases in DVG quantification, thereby providing a strong rationale to favor pre-amplification-free methods. We further examine the features of DVGs produced by wild-type and transcription-defective (PA-K635A or PA-R638A) influenza viruses, and show an increased diversity and frequency of DVGs produced by the PA mutants compared to the wild-type virus. Finally, we show a significant enrichment in DVGs showing direct, A/T-rich sequence repeats at the deletion breakpoint sites. Our findings give novel insights into the mechanisms of influenza virus DVG production.

中文翻译：

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用于流感缺陷病毒基因组定位和定量的 RNA-seq 准确性和可重复性

与大多数 RNA 病毒一样，流感病毒会在复制过程中产生具有大量内部缺失的缺陷病毒基因组 (DVG)。有越来越多的证据支持此类 DVG 的生物学相关性。然而，对 DVG 产生和生物活性背后的分子机制的进一步理解取决于检测方法的灵敏度和准确性，即下一代测序 (NGS) 技术和相关的生物信息学算法。尽管开发了许多算法，但它们的灵敏度和再现性主要是根据模拟数据评估的。在这里，我们介绍了 DG-seq，一种用于 DVG 检测和量化的省时管道，以及一组生物控制，不仅可以评估我们的生物信息学算法的性能，还可以评估上游 NGS 步骤的性能。使用这些工具，我们首次对 RNA-seq 的两种常用样品处理方法进行了严格比较，无论是否进行 PCR 预扩增步骤。我们的数据表明，预放大在灵敏度方面具有有限的优势，并在 DVG 量化中引入了大小和序列相关的偏差，从而为支持无预放大方法提供了强有力的理由。我们进一步检查了由野生型和转录缺陷型（PA-K635A 或 PA-R638A）流感病毒产生的 DVG 的特征，并显示与野生型病毒相比，PA 突变体产生的 DVG 的多样性和频率增加。最后，我们在 DVG 中显示了显着的富集，显示在删除断点位点处直接的、富含 A/T 的序列重复。我们的发现为流感病毒 DVG 产生的机制提供了新的见解。