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RNA sequencing of Sleeping Beauty transposon-induced tumors detects transposon-RNA fusions in forward genetic cancer screens

机译:睡美人转座子诱发的肿瘤的RNA测序可在正向遗传癌症筛查中检测到转座子-RNA融合

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摘要

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.
机译:使用“睡美人”(SB)动员的T2 / Onc转座子进行正向遗传筛选已用于鉴定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)进行鉴定。在这里,我们使用RNA测序(RNA-seq)数据直接识别T2 / Onc介导的转录事件。出乎意料的是,大多数(〜80%)LM-PCR鉴定的连接片段未导致RNA转录物的可观察到的变化。然而,在CIS区域,观察到转座子插入的直接转录作用。我们开发了一种自动化的方法来系统地识别RNA序列数据中的T2 / Onc基因组RNA融合序列。鉴定出基于RNA融合的CIS与基于DNA的CIS(Cdkn2a,Mycl1,Nf2,Pten,Sema6d和Rere)以及与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)。除了计算复发性CIS外,我们还提出了补充方法,可通过确定强支持的融合蛋白和在没有多肿瘤复发的情况下具有较大转录水平变化的融合蛋白来确定潜在的驱动程序事件。这些方法独立地识别CIS区域,也指向与癌症相关的基因,如Braf。我们预期从正向遗传筛选中对肿瘤进行RNA序列分析将成为识别因果事件的有效工具。

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