Institute of Microbiology, University Hospital Center and University of Lausanne, Bugnon 48, CH-1011 Lausanne, Switzerland.
J Virol. 2011 Jul;85(13):6205-11. doi: 10.1128/JVI.00252-11. Epub 2011 Apr 20.
Next-generation sequencing offers an unprecedented opportunity to jointly analyze cellular and viral transcriptional activity without prerequisite knowledge of the nature of the transcripts. SupT1 cells were infected with a vesicular stomatitis virus G envelope protein (VSV-G)-pseudotyped HIV vector. At 24 h postinfection, both cellular and viral transcriptomes were analyzed by serial analysis of gene expression followed by high-throughput sequencing (SAGE-Seq). Read mapping resulted in 33 to 44 million tags aligning with the human transcriptome and 0.23 to 0.25 million tags aligning with the genome of the HIV-1 vector. Thus, at peak infection, 1 transcript in 143 is of viral origin (0.7%), including a small component of antisense viral transcription. Of the detected cellular transcripts, 826 (2.3%) were differentially expressed between mock- and HIV-infected samples. The approach also assessed whether HIV-1 infection modulates the expression of repetitive elements or endogenous retroviruses. We observed very active transcription of these elements, with 1 transcript in 237 being of such origin, corresponding on average to 123,123 reads in mock-infected samples (0.40%) and 129,149 reads in HIV-1-infected samples (0.45%) mapping to the genomic Repbase repository. This analysis highlights key details in the generation and interpretation of high-throughput data in the setting of HIV-1 cellular infection.
下一代测序技术提供了一个前所未有的机会,可以在无需预先了解转录本性质的情况下,联合分析细胞和病毒的转录活性。SupT1 细胞被水疱性口炎病毒 G 包膜蛋白(VSV-G)假型 HIV 载体感染。感染后 24 小时,通过基因表达序列分析(SAGE) followed by 高通量测序(SAGE-Seq)联合分析细胞和病毒转录组。读取映射结果表明,有 3300 万至 4400 万个标签与人类转录组匹配,有 23 万至 25 万个标签与 HIV-1 载体基因组匹配。因此,在感染高峰期,有 1/143 的转录本来源于病毒(0.7%),其中包括一小部分反义病毒转录本。在所检测到的细胞转录本中,有 826 个(2.3%)在 mock 和 HIV 感染样本之间差异表达。该方法还评估了 HIV-1 感染是否调节重复元件或内源性逆转录病毒的表达。我们观察到这些元件的转录非常活跃,有 1/237 的转录本来自这些元件,平均在 mock 感染样本中对应 123123 个读数(0.40%),在 HIV-1 感染样本中对应 129149 个读数(0.45%),这些读数映射到基因组 Repbase 存储库。该分析突出了在 HIV-1 细胞感染背景下生成和解释高通量数据的关键细节。