Florea Liliana, Song Li, Salzberg Steven L
Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA ; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA ; Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21205, USA.
F1000Res. 2013 Sep 16;2:188. doi: 10.12688/f1000research.2-188.v2. eCollection 2013.
Alternative splicing is widely recognized for its roles in regulating genes and creating gene diversity. However, despite many efforts, the repertoire of gene splicing variation is still incompletely characterized, even in humans. Here we describe a new computational system, ASprofile, and its application to RNA-seq data from Illumina's Human Body Map project (>2.5 billion reads). Using the system, we identified putative alternative splicing events in 16 different human tissues, which provide a dynamic picture of splicing variation across the tissues. We detected 26,989 potential exon skipping events representing differences in splicing patterns among the tissues. A large proportion of the events (>60%) were novel, involving new exons (3000), new introns (16000), or both. When tracing these events across the sixteen tissues, only a small number (4-7%) appeared to be differentially expressed ('switched') between two tissues, while 30-45% showed little variation, and the remaining 50-65% were not present in one or both tissues compared. Novel exon skipping events appeared to be slightly less variable than known events, but were more tissue-specific. Our study represents the first effort to build a comprehensive catalog of alternative splicing in normal human tissues from RNA-seq data, while providing insights into the role of alternative splicing in shaping tissue transcriptome differences. The catalog of events and the ASprofile software are freely available from the Zenodo repository ( http://zenodo.org/record/7068; doi: 10.5281/zenodo.7068) and from our web site http://ccb.jhu.edu/software/ASprofile.
可变剪接因其在调节基因和创造基因多样性方面的作用而被广泛认可。然而，尽管付出了诸多努力，但基因剪接变异的全部情况仍未得到完全表征，即便在人类中也是如此。在此，我们描述了一种新的计算系统ASprofile及其在来自Illumina人体图谱项目的RNA测序数据（超过25亿条读数）中的应用。利用该系统，我们在16种不同的人体组织中鉴定出了推定的可变剪接事件，这些事件提供了各组织间剪接变异的动态图景。我们检测到26,989个潜在的外显子跳跃事件，这些事件代表了各组织间剪接模式的差异。其中很大一部分事件（>60%）是新发现的，涉及新的外显子（约3000个）、新的内含子（约16000个）或两者皆有。当追踪这些事件在16种组织中的情况时，只有少数（4 - 7%）似乎在两种组织之间存在差异表达（“切换”），而30 - 45%的变化很小，其余50 - 65%在比较的一种或两种组织中不存在。新的外显子跳跃事件似乎比已知事件的变异性略小，但更具组织特异性。我们的研究首次尝试从RNA测序数据构建正常人体组织中可变剪接的综合目录，同时深入了解可变剪接在塑造组织转录组差异中的作用。事件目录和ASprofile软件可从Zenodo库（http://zenodo.org/record/7068；doi: 10.5281/zenodo.7068）以及我们的网站http://ccb.jhu.edu/software/ASprofile免费获取。
