Swiss Federal Institute of Technology Zurich, Department of Biology, Institute of Molecular Health Sciences, Chair of RNAi and Genome Integrity, Zurich, Switzerland.
Life Science Zurich Graduate School, Molecular and Translational Biomedicine program, University of Zurich, Zurich, Switzerland.
Sci Rep. 2017 Mar 17;7:44736. doi: 10.1038/srep44736.
Forward genetic screens using retroviral (or transposon) gene-trap vectors in a haploid genome revolutionized the investigation of molecular networks in mammals. However, the sequencing data generated by Phenotypic interrogation followed by Tag sequencing (PhiT-seq) were not well characterized. The analysis of human and mouse haploid screens allowed us to describe PhiT-seq data and to define quality control steps. Moreover, we identified several blind spots in both haploid genomes where gene-trap vectors can hardly integrate. Integration of transcriptomic data improved the performance of candidate gene identification. Furthermore, we experimented with various statistical tests to account for biological replicates in PhiT-seq and investigated the effect of normalization methods and other parameters on the performance. Finally, we developed: VISITs, a dedicated pipeline for analyzing PhiT-seq data (https://sourceforge.net/projects/visits/).
利用逆转录病毒（或转座子）基因捕获载体在单倍体基因组中进行正向遗传筛选，彻底改变了哺乳动物中分子网络的研究。然而，表型询问后通过标签测序（PhiT-seq）产生的测序数据尚未得到很好的描述。对人类和小鼠单倍体筛选的分析使我们能够描述 PhiT-seq 数据并定义质量控制步骤。此外，我们还发现了单倍体基因组中几个基因捕获载体很难整合的盲点。转录组数据的整合提高了候选基因鉴定的性能。此外，我们尝试了各种统计检验来解释 PhiT-seq 中的生物学重复，并研究了归一化方法和其他参数对性能的影响。最后，我们开发了：VISITs，一个专门用于分析 PhiT-seq 数据的管道（https://sourceforge.net/projects/visits/）。
