Prioritizing genes for X-linked diseases using population exome data.

ABSTRACT: Many new disease genes can be identified through high-throughput sequencing. Yet, variant interpretation for the large amounts of genomic data remains a challenge given variation of uncertain significance and genes that lack disease annotation. As clinically significant disease genes may be subject to negative selection, we developed a prediction method that measures paucity of non-synonymous variation in the human population to infer gene-based pathogenicity. Integrating human exome data of over 6000 individuals from the NHLBI Exome Sequencing Project, we tested the utility of the prediction method based on the ratio of non-synonymous to synonymous substitution rates (dN/dS) on X-chromosome genes. A low dN/dS ratio characterized genes associated with childhood disease and outcome. Further

SUBMITTER: Ge X 

PROVIDER: S-EPMC4291241 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature