With large-scale population sequencing projects gathering pace, there is a need for strategies that advance disease gene prioritization1,2. Metrics that provide information about a gene and its ability to tolerate protein-altering variation can aid in clinical interpretation of human genomes and can advance disease gene discovery1-4. Previous reported methods analyzed the total variant load in a gene1-4, but did not analyze the distribution pattern of variants within a gene. Using data from 138,632 exome and genome sequences2, we developed gene variation intolerance rank (GeVIR), a continuous gene-level metric for 19,361 genes that is able to prioritize both dominant and recessive Mendelian disease genes5, that outperforms missense constraint metrics3 and that is comparable-but complementary-to loss-of-function (LOF) constraint metrics2. GeVIR is also able to prioritize short genes, for which LOF constraint cannot be estimated with confidence2. The majority of the most intolerant genes identified here have no defined phenotype and are candidates for severe dominant disorders.

中文翻译：

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GeVIR是一种连续的基因水平指标，使用变体分布模式来确定疾病候选基因的优先级。

随着大规模人群测序项目的发展，需要一种策略来促进疾病基因的优先排序1,2。提供有关基因及其耐受蛋白质改变变异能力的信息的度量标准可以帮助对人类基因组进行临床解释，并可以促进疾病基因的发现1-4。先前报道的方法分析了基因1-4中的总变异体负荷，但是没有分析基因内变异体的分布模式。利用来自138,632个外显子组和基因组序列2的数据，我们开发了基因变异不耐受等级（GeVIR），这是一种连续的基因水平指标，适用于19,361个基因，能够优先检测孟德尔的显性和隐性疾病基因5，优于错义约束指标-但对功能丧失（LOF）约束条件的度量标准是互补的2。GeVIR还能够对短基因进行优先排序，对于这些短基因，LOF约束无法可靠地估计。这里鉴定的大多数最不耐受的基因没有明确的表型，是严重的显性疾病的候选者。