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利用蛋白质复合物预测基因突变的表型效应。

Using protein complexes to predict phenotypic effects of gene mutation.

作者信息

Fraser Hunter B, Plotkin Joshua B

机构信息

Broad Institute of Harvard and MIT, 320 Charles St, Cambridge, Massachhusetts 02142, USA.

出版信息

Genome Biol. 2007;8(11):R252. doi: 10.1186/gb-2007-8-11-r252.

Abstract

BACKGROUND

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.

RESULTS

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.

CONCLUSION

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.

摘要

背景

预测突变的表型效应是遗传学研究的核心目标;它在阐明基因型如何决定表型以及鉴定人类疾病基因方面具有重要应用。

结果

利用来自酿酒酵母的广泛功能基因组数据,我们表明蛋白质敲除表型的最佳预测指标是与其存在于蛋白质复合物中的其他蛋白质的敲除表型。即使添加多个数据集也无法改进基于蛋白质复合物成员关系所做的预测。同样,我们发现蛋白质复合物的替代指标是人类疾病表型的有力预测指标。

结论

我们提出,识别包含已知疾病基因的人类蛋白质复合物将是大规模疾病基因发现的有效方法,并且酵母可能被证明是用于研究甚至预测孟德尔和复杂疾病表型遗传基础的信息丰富的模型系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b35/2258176/4b56d444e93a/gb-2007-8-11-r252-1.jpg

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