The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time--an ultra-deep approach.
The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time--an ultra-deep approach.
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DOI：
10.1371/journal.pcbi.1001022
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发表时间：
2010-12-16
影响因子：
4.3
通讯作者：
Robertson DL
中科院分区：
文献类型：
--
作者：
Archer J;Rambaut A;Taillon BE;Harrigan PR;Lewis M;Robertson DL
大规模平行焦磷酸测序产生前所未有的序列数据量。然而，当从病毒种群生成时，当前的制图软件不足以处理存在的高水平变异，从而导致有偏差的数据丢失的可能性。为了将454生命科学公司的焦磷酸测序系统应用于病毒种群的研究，我们开发了用于处理高度可变序列数据的软件。在这里，我们通过分析来自马拉维洛克临床研究的两个临时采样的HIV-1患者内部数据集来演示我们的软件。这种药物结合CCR5辅助受体，从而防止HIV-1感染细胞。目的是确定病毒的趋向性（CCR5与CXCR4的使用），并跟踪少数使用CXCR4的变异的演变，这些变异可能限制对含有马拉韦洛克的治疗方案的反应。每个患者可获得5个时间点（治疗前2个）。我们首先量化了差异对初始读k-mer映射的影响，并证明了在分析下一代序列数据时利用群体特异性模板序列的重要性。然后，结合推断HIV趋向性的共受体预测算法，我们的软件被用于量化治疗前后的病毒种群结构。在这两种情况下，治疗前检测到使用cxcr4的低频变异（2.5-15%）。根据系统发育的推断，这些变异被观察到作为不同的谱系存在，并随着时间的推移而保持。因此，我们的分析证实了先前存在的使用cxcr4的病毒在马拉韦洛克不敏感的HIV出现中的作用。该软件将用于研究宿主内病毒多样性和其他快速进化病毒的进化，并可从http://www.bioinf.manchester.ac.uk/segminator/获得。由于数据量大、错误率高、序列长度短，新的测序技术对计算生物学提出了新的挑战。此外，高深度（或超深度）数据集，例如来自病原体的数据集，在短基因组或基因组区域中包含异常大量的变异。在这里，我们提出的软件处理和下游分析这种短读病毒序列数据。我们将该软件应用于两名HIV-1感染者的分析，他们对药物马拉韦洛克没有最佳反应。对于每位患者，可获得5个时间点的焦序数据。在这两种情况下，我们检测到不同的低频药物不敏感变异簇，这些变异在马拉韦洛克治疗之前就存在，并通过去除药物敏感的HIV有效地揭示出来。
Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5–15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from http://www.bioinf.manchester.ac.uk/segminator/. Due to high data volumes, error rates, and short sequence lengths, new sequencing technologies present a new challenge for computational biology. In addition, high-depth (or ultra-deep) datasets, for example from pathogens, contain exceptionally large amounts of variation over short genomes or genomic regions. Here we present software for the processing and downstream analysis of such short-read viral sequence data. We apply the software to the analysis of two HIV-1 infected individuals who did not respond optimally to the drug maraviroc. For each patient, pyrosequence data was available for five time points. In both cases we detect distinct clusters of low-frequency drug-insensitive variants that were present prior to maraviroc treatment and effectively unmasked by the removal of the drug-sensitive HIV.
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影响因子：
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