背景:由专门的细胞酶催化的腺苷(A)向肌苷(I)的转化或编辑代表了与疾病有关的最常见的转录后RNA修饰之一。A到I的转换可以发生在特定位点,并导致蛋白质组多样性的增加和RNA稳定性的变化。拼接,和监管。这样的位点可以通过下一代RNA测序检测为腺嘌呤到鸟嘌呤的序列变化,这导致来自多个全基因组调查的数百万个报告位点。尽管如此,在这些努力中缺乏广泛的独立验证,考虑到下一代测序的错误率相对较高,这一点至关重要,导致关于编辑网站当前简编的有效性以及基于它们的结论的挥之不去的问题。
结果:引人注目的是,我们发现,目前的分析方法存在很高的假阳性率,公共数据库中很大一部分网站无法验证.在这项工作中,我们提出了这些问题的潜在解决方案,并提供了人类癌细胞系中A-to-I编辑位点的全面且广泛验证的列表。我们的发现表明,人类癌细胞系中大多数真正的A到I编辑位点都位于非编码转录本中,所谓的RNA“暗物质”。另一方面,许多ADAR编辑事件发生在人类蛋白质编码mRNA的外显子中,包括那些可以重新编码转录组的,代表假阳性,需要谨慎解释。尽管如此,尚未发现的增加人类蛋白质组多样性的真正的ADAR位点存在,需要进一步鉴定。
结论:准确识别人类ADAR位点仍然是一个具有挑战性的问题,特别是蛋白质编码mRNA的外显子中的位点。因此,对ADAR编辑组的全基因组调查仍必须伴随着广泛的Sanger验证工作。然而,鉴于大量未知的人类ADAR站点,需要进一步发展分析技术,可能是基于深度学习解决方案的,以便快速可靠地鉴定任何样品中的editome。
Conversion or editing of adenosine (A) into inosine (I) catalyzed by specialized cellular enzymes represents one of the most common post-transcriptional RNA modifications with emerging connection to disease. A-to-I conversions can happen at specific sites and lead to increase in proteome diversity and changes in RNA stability, splicing, and regulation. Such sites can be detected as adenine-to-guanine sequence changes by next-generation RNA sequencing which resulted in millions reported sites from multiple genome-wide surveys. Nonetheless, the lack of extensive independent validation in such endeavors, which is critical considering the relatively high error rate of next-generation sequencing, leads to lingering questions about the validity of the current compendiums of the editing sites and conclusions based on them.
Strikingly, we found that the current analytical methods suffer from very high false positive rates and that a significant fraction of sites in the public databases cannot be validated. In this work, we present potential solutions to these problems and provide a comprehensive and extensively validated list of A-to-I editing sites in a human cancer cell line. Our findings demonstrate that most of true A-to-I editing sites in a human cancer cell line are located in the non-coding transcripts, the so-called RNA \'dark matter\'. On the other hand, many
ADAR editing events occurring in exons of human protein-coding mRNAs, including those that can recode the transcriptome, represent false positives and need to be interpreted with caution. Nonetheless, yet undiscovered authentic
ADAR sites that increase the diversity of human proteome exist and warrant further identification.
Accurate identification of human
ADAR sites remains a challenging problem, particularly for the sites in exons of protein-coding mRNAs. As a result, genome-wide surveys of
ADAR editome must still be accompanied by extensive Sanger validation efforts. However, given the vast number of unknown human
ADAR sites, there is a need for further developments of the analytical techniques, potentially those that are based on deep learning solutions, in order to provide a quick and reliable identification of the editome in any sample.