Department of Genetics, Stanford University, California, USA.
Nat Methods. 2012 Jun;9(6):579-81. doi: 10.1038/nmeth.1982. Epub 2012 Apr 4.
We developed a computational framework to robustly identify RNA editing sites using transcriptome and genome deep-sequencing data from the same individual. As compared with previous methods, our approach identified a large number of Alu and non-Alu RNA editing sites with high specificity. We also found that editing of non-Alu sites appears to be dependent on nearby edited Alu sites, possibly through the locally formed double-stranded RNA structure.
我们开发了一种计算框架，使用来自同一个体的转录组和基因组深度测序数据，稳健地识别 RNA 编辑位点。与以前的方法相比，我们的方法以高特异性识别出大量的 Alu 和非 Alu RNA 编辑位点。我们还发现，非 Alu 位点的编辑似乎依赖于附近编辑的 Alu 位点，可能是通过局部形成的双链 RNA 结构。
