T7 DNA polymerase treatment improves quantitative sequencing of both double-stranded and single-stranded DNA viruses
biorxiv(2024)
摘要
Background Bulk microbiome, as well as virome-enriched shotgun sequencing only reveals the double-stranded DNA (dsDNA) content of a given sample, unless specific treatments are applied. However, genomes of viruses often consist of a circular single-stranded DNA (ssDNA) molecule. Pre- treatment and amplification of DNA using the multiple displacement amplification (MDA) method enables conversion of ssDNA to dsDNA, but this process can lead to over-representation of these circular ssDNA genomes. A more recent alternative permits to bypass the amplification step, as library adapters are ligated to sheared and denatured DNA, after an end-modification step (xGen kit). However, the sonication step might shear ssDNA more efficiently than dsDNA, therefore introducing another bias in virome sequencing. These limitations prompted us to explore an alternative method of DNA preparation for sequencing mixed ssDNA and dsDNA viromes.
Methods We present here a new method for sequencing both ssDNA and dsDNA, using the T7 DNA polymerase (T7pol) to convert ssDNA into dsDNA. We compared this method to two others: short MDA, where the amplification step is limited by a 30-minute instead of 90-minute incubation time, and no pre-treatment before the xGen kit for library preparation. These various methods were first applied on synthetic a mixtures, then the most effective one was applied on virome samples.
Results Our findings indicate that the T7pol method better represents the original synthetic mixtures compared to the other methods. Furthermore, when applied to two complex virome samples, the T7pol treatment improved both the richness and abundance in the Microviridae fraction.
Conclusion We conclude that T7pol pretreatment is preferable to MDA for the shotgun sequencing of viromes, which is easy to implement and inexpensive.
### Competing Interest Statement
The authors have declared no competing interest.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要