Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Japan.
PLoS One. 2013;8(1):e54210. doi: 10.1371/journal.pone.0054210. Epub 2013 Jan 22.
Human gene catalogs are fundamental to the study of human biology and medicine. But they are all based on open reading frames (ORFs) in a reference genome sequence (with allowance for introns). Individual genomes, however, are polymorphic: their sequences are not identical. There has been much research on how polymorphism affects previously-identified genes, but no research has been done on how it affects gene identification itself. We computationally predict protein-coding genes in a straightforward manner, by finding long ORFs in mRNA sequences aligned to the reference genome. We systematically test the effect of known polymorphisms with this procedure. Polymorphisms can not only disrupt ORFs, they can also create long ORFs that do not exist in the reference sequence. We found 5,737 putative protein-coding genes that do not exist in the reference, whose protein-coding status is supported by homology to known proteins. On average 10% of these genes are located in the genomic regions devoid of annotated genes in 12 other catalogs. Our statistical analysis showed that these ORFs are unlikely to occur by chance.
人类基因目录是人类生物学和医学研究的基础。但是,它们都是基于参考基因组序列中的开放阅读框(ORFs)(允许有内含子)。然而,个体基因组是多态的:它们的序列并不完全相同。已经有很多关于多态性如何影响先前确定的基因的研究,但没有关于它如何影响基因识别本身的研究。我们通过在与参考基因组对齐的 mRNA 序列中找到长 ORF,以简单直接的方式计算预测蛋白质编码基因。我们通过此程序系统地测试已知多态性的影响。多态性不仅可以破坏 ORF,还可以创建在参考序列中不存在的长 ORF。我们发现了 5737 个不存在于参考序列中的假定蛋白质编码基因,这些基因的蛋白质编码状态通过与已知蛋白质的同源性得到支持。这些基因平均有 10%位于其他 12 个目录中没有注释基因的基因组区域。我们的统计分析表明,这些 ORF 不太可能是偶然出现的。