Jaiswal Alok, Peddinti Gopal, Akimov Yevhen, Wennerberg Krister, Kuznetsov Sergey, Tang Jing, Aittokallio Tero
Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Department of Mathematics and Statistics, University of Turku, Turku, Finland.
Genome Med. 2017 Jun 1;9(1):51. doi: 10.1186/s13073-017-0440-2.
Genome-wide loss-of-function profiling is widely used for systematic identification of genetic dependencies in cancer cells; however, the poor reproducibility of RNA interference (RNAi) screens has been a major concern due to frequent off-target effects. Currently, a detailed understanding of the key factors contributing to the sub-optimal consistency is still a lacking, especially on how to improve the reliability of future RNAi screens by controlling for factors that determine their off-target propensity.
We performed a systematic, quantitative analysis of the consistency between two genome-wide shRNA screens conducted on a compendium of cancer cell lines, and also compared several gene summarization methods for inferring gene essentiality from shRNA level data. We then devised novel concepts of seed essentiality and shRNA family, based on seed region sequences of shRNAs, to study in-depth the contribution of seed-mediated off-target effects to the consistency of the two screens. We further investigated two seed-sequence properties, seed pairing stability, and target abundance in terms of their capability to minimize the off-target effects in post-screening data analysis. Finally, we applied this novel methodology to identify genetic interactions and synthetic lethal partners of cancer drivers, and confirmed differential essentiality phenotypes by detailed CRISPR/Cas9 experiments.
Using the novel concepts of seed essentiality and shRNA family, we demonstrate how genome-wide loss-of-function profiling of a common set of cancer cell lines can be actually made fairly reproducible when considering seed-mediated off-target effects. Importantly, by excluding shRNAs having higher propensity for off-target effects, based on their seed-sequence properties, one can remove noise from the genome-wide shRNA datasets. As a translational application case, we demonstrate enhanced reproducibility of genetic interaction partners of common cancer drivers, as well as identify novel synthetic lethal partners of a major oncogenic driver, PIK3CA, supported by a complementary CRISPR/Cas9 experiment.
We provide practical guidelines for improved design and analysis of genome-wide loss-of-function profiling and demonstrate how this novel strategy can be applied towards improved mapping of genetic dependencies of cancer cells to aid development of targeted anticancer treatments.
全基因组功能丧失分析广泛用于系统鉴定癌细胞中的遗传依赖性；然而，由于频繁的脱靶效应，RNA干扰（RNAi）筛选的可重复性较差一直是主要问题。目前，对于导致次优一致性的关键因素仍缺乏详细了解，尤其是如何通过控制决定其脱靶倾向的因素来提高未来RNAi筛选的可靠性。
我们对在一组癌细胞系上进行的两次全基因组shRNA筛选之间的一致性进行了系统的定量分析，并比较了几种从shRNA水平数据推断基因必需性的基因汇总方法。然后，我们基于shRNA的种子区域序列设计了种子必需性和shRNA家族的新概念，以深入研究种子介导的脱靶效应对两次筛选一致性的影响。我们进一步研究了两个种子序列特性，即种子配对稳定性和靶标丰度，以了解它们在筛选后数据分析中最小化脱靶效应的能力。最后，我们应用这种新方法来鉴定癌症驱动因子的遗传相互作用和合成致死伙伴，并通过详细的CRISPR/Cas9实验确认差异必需性表型。
使用种子必需性和shRNA家族的新概念，我们证明了在考虑种子介导的脱靶效应时，一组常见癌细胞系的全基因组功能丧失分析实际上可以具有相当高的可重复性。重要的是，通过根据种子序列特性排除具有较高脱靶倾向的shRNA，可以从全基因组shRNA数据集中去除噪声。作为一个转化应用案例，我们展示了常见癌症驱动因子的遗传相互作用伙伴的可重复性增强，并通过互补的CRISPR/Cas9实验鉴定了主要致癌驱动因子PIK3CA的新型合成致死伙伴。
我们为改进全基因组功能丧失分析的设计和分析提供了实用指南，并展示了这种新策略如何应用于改进癌细胞遗传依赖性的图谱绘制，以帮助开发靶向抗癌治疗。
