Identify alternative splicing events based on position-specific evolutionary conservation.
Identify alternative splicing events based on position-specific evolutionary conservation.
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DOI：
10.1371/journal.pone.0002806
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发表时间：
2008-07-30
期刊：
影响因子：
3.7
通讯作者：
Zheng S
中科院分区：
文献类型：
--
作者：
Chen L;Zheng S
真核生物的进化伴随着选择性剪接的复杂性增加，这极大地扩展了基因组信息。后基因组时代最大的挑战之一是考虑选择性剪接的人类转录组的完整揭示。在这里，我们介绍了一个比较基因组学的方法，系统地确定选择性剪接事件的基础上，外显子和内含子之间的差异进化保守性和高质量的注释的ENCODE区域。具体来说，我们关注的是那些包含在某些转录本中，但在其他转录本中被完全剪接掉的外显子，我们称之为条件外显子。首先，我们描述了条件外显子，组成型外显子和内含子之间的区别特征。最重要的特征之一是位置特异性保护分数。条件性外显子和组成性外显子之间的保守性得分存在显著差异。更重要的是，这些差异是特定于位置的。对于侧翼内含子区域，条件性外显子和组成性外显子之间的差异也是位置特异性的。使用随机森林算法，我们可以对具有高特异性（97%用于从内含子区域识别条件外显子，95%用于已知外显子的分类）和公平敏感性（分别为64%和32%）的条件外显子进行分类。我们将该方法应用于人类基因组，并确定了39，640个实际包含条件外显子的内含子，并从当前RefSeq外显子列表中分类了8，813个条件外显子。其中，包含条件外显子的31，673个内含子和从已知外显子分类的5，294个条件外显子不能从RefSeq、UCSC或Ensembl注释推断。这些从头预测的一些实验验证。
The evolution of eukaryotes is accompanied by the increased complexity of alternative splicing which greatly expands genome information. One of the greatest challenges in the post-genome era is a complete revelation of human transcriptome with consideration of alternative splicing. Here, we introduce a comparative genomics approach to systemically identify alternative splicing events based on the differential evolutionary conservation between exons and introns and the high-quality annotation of the ENCODE regions. Specifically, we focus on exons that are included in some transcripts but are completely spliced out for others and we call them conditional exons. First, we characterize distinguishing features among conditional exons, constitutive exons and introns. One of the most important features is the position-specific conservation score. There are dramatic differences in conservation scores between conditional exons and constitutive exons. More importantly, the differences are position-specific. For flanking intronic regions, the differences between conditional exons and constitutive exons are also position-specific. Using the Random Forests algorithm, we can classify conditional exons with high specificities (97% for the identification of conditional exons from intron regions and 95% for the classification of known exons) and fair sensitivities (64% and 32% respectively). We applied the method to the human genome and identified 39,640 introns that actually contain conditional exons and classified 8,813 conditional exons from the current RefSeq exon list. Among those, 31,673 introns containing conditional exons and 5,294 conditional exons classified from known exons cannot be inferred from RefSeq, UCSC or Ensembl annotations. Some of these de novo predictions were experimentally verified.
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