使用ALoFT来确定蛋白质编码基因中假定的功能丧失变异的影响。

Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes.

作者信息

Balasubramanian Suganthi, Fu Yao, Pawashe Mayur, McGillivray Patrick, Jin Mike, Liu Jeremy, Karczewski Konrad J, MacArthur Daniel G, Gerstein Mark

机构信息

Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.

Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT, 06520, USA.

出版信息

Nat Commun. 2017 Aug 29;8(1):382. doi: 10.1038/s41467-017-00443-5.

Abstract

Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes.Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.

摘要

预测会导致人类基因功能丧失的变异因其临床影响以及在健康个体中出人意料的高发生率而备受关注。在此,我们介绍了ALoFT(功能丧失转录本注释),这是一种注释和预测功能丧失变异致病潜力的方法。利用孟德尔疾病基因发现项目的数据,我们表明ALoFT能够区分作为杂合子有害的功能丧失变异和仅在纯合状态下致病的变异。对在健康人群中发现的变异进行的研究表明,每个个体至少携带两个杂合的过早终止等位基因,如果它们以纯合子形式存在,可能会导致疾病。当应用于自闭症患者家庭中的新生推定功能丧失变异时,ALoFT能够区分患者中的有害变异和未受影响的兄弟姐妹中的良性变异。最后,对6500多个癌症外显子组中的体细胞变异进行分析表明,ALoFT预测为有害的推定功能丧失变异在已知的驱动基因中富集。导致人类基因功能丧失(LoF)的变异具有临床意义。在此,作者介绍了一种预测LoF变异致病潜力的方法——ALoFT(功能丧失转录本注释),并展示了其在不同背景下解释LoF变异的应用。

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