Carter David, Durbin Richard
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
Genome Biol. 2006;7 Suppl 1(Suppl 1):S6.1-12. doi: 10.1186/gb-2006-7-s1-s6. Epub 2006 Aug 7.
One way in which the accuracy of gene structure prediction in vertebrate DNA sequences can be improved is by analyzing alignments with multiple related species, since functional regions of genes tend to be more conserved.
We describe DOGFISH, a vertebrate gene finder consisting of a cleanly separated site classifier and structure predictor. The classifier scores potential splice sites and other features, using sequence alignments between multiple vertebrate species, while the structure predictor hypothesizes coding transcripts by combining these scores using a simple model of gene structure. This also identifies and assigns confidence scores to possible additional exons. Performance is assessed on the ENCODE regions. We predict transcripts and exons across the whole human genome, and identify over 10,000 high confidence new coding exons not in the Ensembl gene set.
We present a practical multiple species gene prediction method. Accuracy improves as additional species, up to at least eight, are introduced. The novel predictions of the whole-genome scan should support efficient experimental verification.
提高脊椎动物DNA序列中基因结构预测准确性的一种方法是分析与多个相关物种的比对，因为基因的功能区域往往更保守。
我们描述了DOGFISH，一种脊椎动物基因发现工具，它由一个完全分离的位点分类器和结构预测器组成。分类器利用多个脊椎动物物种之间的序列比对，对潜在的剪接位点和其他特征进行评分，而结构预测器则通过使用一个简单的基因结构模型组合这些评分来推测编码转录本。这也能识别可能的额外外显子并为其赋予置信度分数。在ENCODE区域评估了性能。我们预测了整个人类基因组的转录本和外显子，并识别出超过10000个不在Ensembl基因集中的高置信度新编码外显子。
我们提出了一种实用的多物种基因预测方法。随着引入至少八个额外物种，准确性会提高。全基因组扫描的新预测应该支持高效的实验验证。
