Using protein complexes to predict phenotypic effects of gene mutation.
Using protein complexes to predict phenotypic effects of gene mutation.
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DOI：
10.1186/gb-2007-8-11-r252
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发表时间：
2007
期刊：
影响因子：
12.3
通讯作者：
Plotkin JB
中科院分区：
文献类型：
--
作者：
Fraser HB;Plotkin JB
一个蛋白质的敲除表型的最佳预测被证明是敲除表型的其他蛋白质，是目前在一个蛋白质复合物与it.Predicting突变的表型效应是遗传学研究的中心目标，它在阐明基因型如何决定表型和识别人类疾病基因有重要的应用。使用广泛的功能基因组数据从酵母酿酒酵母，我们表明，蛋白质的敲除表型的最佳预测是敲除表型的其他蛋白质，是存在于一个蛋白质复合物与它。即使添加多个数据集并没有改善后，从蛋白质复合物的成员资格的预测。同样，我们发现蛋白质复合物的替代物是人类疾病表型的有力预测因子。我们建议，识别人类蛋白质复合物含有已知的疾病基因将是一个有效的方法，大规模的疾病基因的发现，酵母可能被证明是一个信息模型系统，调查，甚至预测，孟德尔和复杂的疾病表型的遗传基础。
The best predictor of a protein's knockout phenotype is shown to be the knockout phenotype of other proteins that are present in a protein complex with it. Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes.
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