Gussow Ayal B, Copeland Brett R, Dhindsa Ryan S, Wang Quanli, Petrovski Slavé, Majoros William H, Allen Andrew S, Goldstein David B
Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, United States of America.
Institute for Genomic Medicine, Columbia University, New York, NY, United States of America.
PLoS One. 2017 Aug 10;12(8):e0181604. doi: 10.1371/journal.pone.0181604. eCollection 2017.
There is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion, an approach that detects regions of the non-coding genome that are depleted of variation, suggesting that the regions are intolerant of mutations and subject to purifying selection in the human lineage. We show that Orion is highly correlated with known intolerant regions as well as regions that harbor putatively pathogenic variation. This approach provides a mechanism to identify pathogenic variation in the human non-coding genome and will have immediate utility in the diagnostic interpretation of patient genomes and in large case control studies using whole-genome sequences.
人们普遍认为，发生在蛋白质编码区域之外的基因突变在人类疾病中起着关键作用。尽管已达成这一共识，但我们仍无法辨别非编码序列的哪些部分在人类疾病背景下是重要的。在此，我们介绍Orion，这是一种检测非编码基因组中变异缺失区域的方法，这表明这些区域对突变不耐受，并在人类谱系中受到纯化选择。我们表明，Orion与已知的不耐受区域以及含有推定致病变异的区域高度相关。这种方法提供了一种识别人类非编码基因组中致病变异的机制，并且在患者基因组的诊断解释以及使用全基因组序列的大型病例对照研究中具有直接用途。
