Temiz Nuri A, Moriarity Branden S, Wolf Natalie K, Riordan Jesse D, Dupuy Adam J, Largaespada David A, Sarver Aaron L
Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota 55455, USA;
Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota 55455, USA; Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota 55455, USA; Brain Tumor Program, University of Minnesota, Minneapolis, Minnesota 55455, USA; Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55455, USA;
Genome Res. 2016 Jan;26(1):119-29. doi: 10.1101/gr.188649.114. Epub 2015 Nov 9.
Forward genetic screens using Sleeping Beauty (SB)-mobilized T2/Onc transposons have been used to identify common insertion sites (CISs) associated with tumor formation. Recurrent sites of transposon insertion are commonly identified using ligation-mediated PCR (LM-PCR). Here, we use RNA sequencing (RNA-seq) data to directly identify transcriptional events mediated by T2/Onc. Surprisingly, the majority (∼80%) of LM-PCR identified junction fragments do not lead to observable changes in RNA transcripts. However, in CIS regions, direct transcriptional effects of transposon insertions are observed. We developed an automated method to systematically identify T2/Onc-genome RNA fusion sequences in RNA-seq data. RNA fusion-based CISs were identified corresponding to both DNA-based CISs (Cdkn2a, Mycl1, Nf2, Pten, Sema6d, and Rere) and additional regions strongly associated with cancer that were not observed by LM-PCR (Myc, Akt1, Pth, Csf1r, Fgfr2, Wisp1, Map3k5, and Map4k3). In addition to calculating recurrent CISs, we also present complementary methods to identify potential driver events via determination of strongly supported fusions and fusions with large transcript level changes in the absence of multitumor recurrence. These methods independently identify CIS regions and also point to cancer-associated genes like Braf. We anticipate RNA-seq analyses of tumors from forward genetic screens will become an efficient tool to identify causal events.
利用睡美人（SB）转座的T2/Onc转座子进行的正向遗传筛选已被用于识别与肿瘤形成相关的常见插入位点（CIS）。转座子插入的复发位点通常使用连接介导的PCR（LM-PCR）来识别。在这里，我们使用RNA测序（RNA-seq）数据直接识别由T2/Onc介导的转录事件。令人惊讶的是，大多数（约80%）通过LM-PCR鉴定的连接片段不会导致RNA转录本出现可观察到的变化。然而，在CIS区域，观察到了转座子插入的直接转录效应。我们开发了一种自动化方法，用于系统地识别RNA-seq数据中的T2/Onc-基因组RNA融合序列。鉴定出了基于RNA融合的CIS，它们对应于基于DNA的CIS（Cdkn2a、Mycl1、Nf2、Pten、Sema6d和Rere）以及LM-PCR未观察到的与癌症密切相关的其他区域（Myc、Akt1、Pth、Csf1r、Fgfr2、Wisp1、Map3k5和Map4k3）。除了计算复发的CIS外，我们还提出了补充方法，通过确定在没有多肿瘤复发情况下得到有力支持的融合以及具有大转录水平变化的融合来识别潜在的驱动事件。这些方法独立地识别CIS区域，还指向像Braf这样的癌症相关基因。我们预计，对正向遗传筛选中肿瘤的RNA-seq分析将成为识别因果事件的有效工具。
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