Comprehensive characterization of amino acid positions in protein structures reveals molecular effect of missense variants.
Comprehensive characterization of amino acid positions in protein structures reveals molecular effect of missense variants.
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DOI：
10.1073/pnas.2002660117
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发表时间：
2020-11-10
影响因子：
11.1
通讯作者：
Lal D
中科院分区：
文献类型：
--
作者：
Iqbal S;Pérez-Palma E;Jespersen JB;May P;Hoksza D;Heyne HO;Ahmed SS;Rifat ZT;Rahman MS;Lage K;Palotie A;Cottrell JR;Wagner FF;Daly MJ;Campbell AJ;Lal D
最近的大规模测序工作已经能够检测到数百万个错义变异。阐明它们的功能作用至关重要，但也具有挑战性。我们通过使用14,000个蛋白质结构对1330个疾病相关基因的错义变异进行广泛的表征来解决这个问题。我们确定了与致病和良性变异相关的3D特征，这些变异在分子水平上揭示了突变的影响。我们进一步扩展了我们的分析，以解释执行不同功能的蛋白质中不同的基本结构区域。通过分析编码不同蛋白质功能家族的24组基因的变体，我们捕获了错义变体的特定功能特征，这些特征与实验读数相匹配。我们表明，我们使用结构数据得出的结果将有效地为变体解释提供信息。从测序应用中识别的大量遗传变异的解释是临床遗传学的主要瓶颈之一，其中氨基酸替代错义变异对蛋白质结构和功能的影响的推断尤其具有挑战性。在这里，我们使用超过14,000个实验解决的人类蛋白质结构来表征1330个疾病相关基因的致病和群体变异中受影响的三维(3D)氨基酸位置。通过测量所有基因在40个3D蛋白质特征上的变异(即点突变)的统计负担，考虑到变异位置的结构、化学和功能背景，我们识别出通常与致病和群体错义变异相关的特征。然后，我们对24个蛋白质功能类别分别进行了相同的氨基酸水平分析，揭示了改变的氨基酸位置的独特特征：我们观察到类别特定特征与所有基因分析获得的一般特征的差异高达46%，这与不同蛋白质类别必需区域的结构多样性一致。我们证明，这些变体的功能特异性3D特征与BRCA1和PTEN的突变实验读数相匹配，并与一组独立的临床解释的致病和良性错义变体呈正相关。最后，我们通过Web服务器提供我们的结果，以促进可访问性和下游研究。我们的发现代表着向翻译遗传学迈出的关键一步，从强调突变对蛋白质结构的影响，到根据扰动的分子机制来合理化变异的致病性。
Recent large-scale sequencing efforts have enabled the detection of millions of missense variants. Elucidating their functional effect is of crucial importance but challenging. We approach this problem by performing a wide-scale characterization of missense variants from 1,330 disease-associated genes using >14,000 protein structures. We identify 3D features associated with pathogenic and benign variants that unveiled the mutations’ effect at the molecular level. We further extend our analysis to account for the different essential structural regions in proteins performing different functions. By analyzing variants from 24 gene groups encoding for different protein functional families, we capture function-specific characteristics of missense variants, which match the experimental readouts. We show that our results derived using structural data will effectively inform variant interpretation. Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variations on protein structure and function being especially challenging. Here we characterize the three-dimensional (3D) amino acid positions affected in pathogenic and population variants from 1,330 disease-associated genes using over 14,000 experimentally solved human protein structures. By measuring the statistical burden of variations (i.e., point mutations) from all genes on 40 3D protein features, accounting for the structural, chemical, and functional context of the variations’ positions, we identify features that are generally associated with pathogenic and population missense variants. We then perform the same amino acid-level analysis individually for 24 protein functional classes, which reveals unique characteristics of the positions of the altered amino acids: We observe up to 46% divergence of the class-specific features from the general characteristics obtained by the analysis on all genes, which is consistent with the structural diversity of essential regions across different protein classes. We demonstrate that the function-specific 3D features of the variants match the readouts of mutagenesis experiments for BRCA1 and PTEN, and positively correlate with an independent set of clinically interpreted pathogenic and benign missense variants. Finally, we make our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step toward translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the variants’ pathogenicity in terms of the perturbed molecular mechanisms.
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影响因子：
4.8
作者：
Aukrust, Ingvild;Bjorkhaug, Lise;Njolstad, Pal R.
通讯作者：
Njolstad, Pal R.
影响因子：
12.3
作者：
Glusman G
通讯作者：
Glusman G
影响因子：
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作者：
Findlay GM;Daza RM;Martin B;Zhang MD;Leith AP;Gasperini M;Janizek JD;Huang X;Starita LM;Shendure J
通讯作者：
Shendure J
影响因子：
30.8
作者：
Kircher, Martin;Witten, Daniela M.;Jain, Preti;O'Roak, Brian J.;Cooper, Gregory M.;Shendure, Jay
通讯作者：
Shendure, Jay
影响因子：
64.8
作者：
Karczewski, Konrad J;Francioli, Laurent C;MacArthur, Daniel G
通讯作者：
MacArthur, Daniel G