Genome-wide colocalization of RNA–DNA interactions and fusion RNA pairs
Genome-wide colocalization of RNA–DNA interactions and fusion RNA pairs
复制标题
DOI：
10.1073/pnas.1819788116
复制
发表时间：
2018-11
影响因子：
11.1
通讯作者：
Zhangming Yan;Norman Huang;Weixin Wu;Weizhong Chen;Yiqun Jiang;Jingyao Chen;Xuerui Huang;Xingzhao Wen;Jie Xu;Q. Jin;Kang Zhang;Z. Chen;S. Chien;Sheng Zhong
中科院分区：
文献类型：
--
作者：
Zhangming Yan;Norman Huang;Weixin Wu;Weizhong Chen;Yiqun Jiang;Jingyao Chen;Xuerui Huang;Xingzhao Wen;Jie Xu;Q. Jin;Kang Zhang;Z. Chen;S. Chien;Sheng Zhong
预测哪些未报道的RNA对可以形成新的融合转录本仍然是困难的。通过系统绘制染色质相关RNA及其各自的基因组相互作用位点，我们获得了两种非癌细胞类型的全基因组RNA-DNA相互作用图谱。在这些正常细胞中参与RNA-DNA相互作用的基因对与癌症衍生的融合转录物表现出强烈的重叠。这些数据表明了一个RNA平衡模型，其中一个基因的转录本和另一个基因的基因组序列的空间接近性平衡了融合转录本的产生。我们用96个额外的肺癌样本验证了这个模型。这些额外的样品之一显示融合转录物而没有相应的融合基因，表明基因组重组不是RNA-泊斯模型所需的步骤。融合转录物在伴随诊断中用作生物标志物。虽然已经从不同的癌症类型中鉴定出超过15，000种融合RNA，但很少有共同特征被报道。在这里，我们比较了在癌症中检测到的16，410个融合转录物（来自33种癌症类型的9，966个肿瘤样本的已发表队列）与在两种正常非癌细胞类型中绘制的全基因组RNA-DNA相互作用[使用iMARGI，RNA-基因组相互作用（MARGI）测定的增强版]。在正常细胞中前10个最重要的RNA-DNA相互作用中，有5个与癌症中形成融合RNA的基因对共定位。此外，在整个基因组中，基因对表现出RNA-DNA相互作用的频率与该基因对在癌症中呈现记录的融合转录物的概率正相关。为了测试正常细胞中的RNA-DNA相互作用是否预测融合RNA，我们使用RNA测序（RNA-seq）在96个肺癌样本的验证队列中分析了这些。在验证组群中的42个融合转录物中，发现有37个在正常细胞中表现出RNA-DNA相互作用。最后，通过结合RNA-seq、单分子RNA FISH和DNA FISH，我们检测了具有EML 4-ALK融合RNA而不形成EML 4-ALK融合基因的癌症样本。总的来说，这些数据表明了一个RNA平衡模型，其中RNA和DNA的空间接近性可以平衡融合转录物的产生。
Significance It remains formidable to predict what unreported RNA pairs can form new fusion transcripts. By systematic mapping of chromatin-associated RNAs and their respective genomic interaction loci, we obtained genome-wide RNA–DNA interaction maps from two noncancerous cell types. The gene pairs involved in RNA–DNA interactions in these normal cells exhibited strong overlap with those with cancer-derived fusion transcripts. These data suggest an RNA-poise model, where the spatial proximity of one gene’s transcripts and the other gene’s genomic sequence poises for the creation of fusion transcripts. We validated this model with 96 additional lung cancer samples. One of these additional samples exhibited fusion transcripts without a corresponding fusion gene, suggesting that genome recombination is not a required step of the RNA-poise model. Fusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA–DNA interactions mapped in two normal, noncancerous cell types [using iMARGI, an enhanced version of the mapping of RNA–genome interactions (MARGI) assay]. Among the top 10 most significant RNA–DNA interactions in normal cells, 5 colocalized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA–DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA–DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA sequencing (RNA-seq). Thirty-seven of 42 fusion transcripts in the validation cohort were found to exhibit RNA–DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest an RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.