Center for Human Disease Modeling, Department of Pediatrics, Duke University Medical Center, Durham, NC 27710, USA.
Curr Opin Genet Dev. 2012 Jun;22(3):290-303. doi: 10.1016/j.gde.2012.04.006. Epub 2012 May 23.
The last decade has witnessed an explosion in the identification of genes, mutations in which appear sufficient to cause clinical phenotypes in humans. This is especially true for disorders of ciliary dysfunction in which an excess of 50 causal loci are now known; this discovery was driven partly by an improved understanding of the protein composition of the cilium and the co-occurrence of clinical phenotypes associated with ciliary dysfunction. Despite this progress, the fundamental challenge of predicting phenotype and or clinical progression based on single locus information remains unsolved. Here, we explore how the combinatorial knowledge of allele quality and quantity, an improved understanding of the biological composition of the primary cilium, and the expanded appreciation of the subcellular roles of this organelle can be synthesized to generate improved models that can explain both causality but also variable penetrance and expressivity.
过去十年见证了基因的大量发现,这些基因突变足以在人类中引起临床表型。对于纤毛功能障碍疾病尤其如此,现在已知有超过 50 个致病基因座;这一发现部分是由于对纤毛的蛋白质组成和与纤毛功能障碍相关的临床表型的共同发生有了更好的理解。尽管取得了这一进展,但根据单一基因座信息预测表型或临床进展的基本挑战仍然没有解决。在这里,我们探讨如何综合等位基因质量和数量的组合知识、对初级纤毛生物学组成的更深入理解以及对该细胞器亚细胞作用的扩展认识,以生成可以解释因果关系以及可变外显率和表现度的改进模型。