Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage.
Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage.
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DOI：
10.1186/s13015-016-0064-x
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发表时间：
2016
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影响因子：
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通讯作者：
Antoneli F
中科院分区：
文献类型：
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作者：
Zukurov JP;do Nascimento-Brito S;Volpini AC;Oliveira GC;Janini LM;Antoneli F
在本文中，我们提出了一种方法，并讨论了其计算实现作为一个综合工具，分析病毒的遗传多样性的数据产生的高通量测序。这项工作的主要动机是更好地了解具有高核苷酸取代率的病毒的遗传多样性，如HIV-1和流感。迄今为止提出的用于病毒多样性估计的大多数方法旨在利用由一些下一代测序平台产生的较长读段，以便估计代表原始群体多样性的单倍型群体。这里提出的方法是定制的，以利用非常低的错误率和每个站点的极深覆盖率，这是一些被忽视的技术的主要特征，这些技术由于其读段长度短而没有受到太多关注，这排除了单倍型估计。这种方法使我们能够避免一些与单倍型重建相关的困难问题（需要长读段，初步错误过滤和组装）。我们建议通过由病毒基因组的位点索引的多项概率分布的家族来测量病毒群体的遗传多样性，每一个代表每个位点的核酸碱基的分布。此外，该方法的实施集中在两个主要的优化策略：一个读映射/对齐程序，旨在恢复最大可能数量的短读段;在贝叶斯框架中的多项式参数的推断与平滑Dirichlet估计。贝叶斯方法为多项式参数提供了条件概率分布，允许人们考虑控制实验的先验信息，并提供了一种自然的方法来分离信号和噪声，因为它自动消除了贝叶斯置信区间，从而避免了初步误差过滤的缺点。本文中描述的方法已作为一种称为Tanden（病毒种群多样性分析工具）的集成工具实施，并在许多不同病毒繁殖条件下对从原代人细胞培养物上的HIV-1毒株NL 4 -3（M组，B亚型）培养物获得的样本进行了成功检测。Tanden是用C#（Microsoft）编写的，在Windows操作系统上运行，可以从http://tanden.url.ph/下载。
In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. The main motivation for this work is to better understand the genetic diversity of viruses with high rates of nucleotide substitution, as HIV-1 and Influenza. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some next-generation sequencing platforms in order to estimate a population of haplotypes which represent the diversity of the original population. The method proposed here is custom-made to take advantage of the very low error rate and extremely deep coverage per site, which are the main features of some neglected technologies that have not received much attention due to the short length of its reads, which precludes haplotype estimation. This approach allowed us to avoid some hard problems related to haplotype reconstruction (need of long reads, preliminary error filtering and assembly). We propose to measure genetic diversity of a viral population through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the distribution of nucleic bases per site. Moreover, the implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the inference of the multinomial parameters in a Bayesian framework with smoothed Dirichlet estimation. The Bayesian approach provides conditional probability distributions for the multinomial parameters allowing one to take into account the prior information of the control experiment and providing a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals and thus avoids the drawbacks of preliminary error filtering. The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations) and successfully tested on samples obtained from HIV-1 strain NL4-3 (group M, subtype B) cultivations on primary human cell cultures in many distinct viral propagation conditions. Tanden is written in C# (Microsoft), runs on the Windows operating system, and can be downloaded from: http://tanden.url.ph/.