Dudley Aimée Marie, Janse Daniel Maarten, Tanay Amos, Shamir Ron, Church George McDonald
Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
Mol Syst Biol. 2005;1:2005.0001. doi: 10.1038/msb4100004. Epub 2005 Mar 29.
Pleiotropy, the ability of a single mutant gene to cause multiple mutant phenotypes, is a relatively common but poorly understood phenomenon in biology. Perhaps the greatest challenge in the analysis of pleiotropic genes is determining whether phenotypes associated with a mutation result from the loss of a single function or of multiple functions encoded by the same gene. Here we estimate the degree of pleiotropy in yeast by measuring the phenotypes of 4710 mutants under 21 environmental conditions, finding that it is significantly higher than predicted by chance. We use a biclustering algorithm to group pleiotropic genes by common phenotype profiles. Comparisons of these clusters to biological process classifications, synthetic lethal interactions, and protein complex data support the hypothesis that this method can be used to genetically define cellular functions. Applying these functional classifications to pleiotropic genes, we are able to dissect phenotypes into groups associated with specific gene functions.
多效性是指单个突变基因导致多种突变表型的能力,这在生物学中是一种相对常见但却了解甚少的现象。在对多效性基因的分析中,或许最大的挑战在于确定与某一突变相关的表型是源于单一功能的丧失,还是同一基因所编码的多种功能的丧失。在此,我们通过测量4710个突变体在21种环境条件下的表型来估算酵母中的多效性程度,发现其显著高于随机预测值。我们使用一种双聚类算法,依据共同的表型谱对多效性基因进行分组。将这些聚类与生物学过程分类、合成致死相互作用以及蛋白质复合物数据进行比较,支持了这样一种假说,即该方法可用于从遗传学角度定义细胞功能。将这些功能分类应用于多效性基因,我们能够将表型分解为与特定基因功能相关的组。