A population genetic approach to mapping neurological disorder genes using deep resequencing

Rachel A. Myers, Ferran Casals, Julie Gauthier, Fadi F. Hamdan, Jon Keebler, Adam R. Boyko, Carlos D. Bustamante, Amelie M. Piton, Dan Spiegelman, Edouard Henrion, Martine Zilversmit, Julie Hussin, Jacklyn Quinlan, Yan Yang, Ronald G. Lafrenière, Alexander R. Griffing, Eric A. Stone, Guy A. Rouleau, Philip Awadalla*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

78 Citations (Scopus)

Abstract

Deep resequencing of functional regions in human genomes is key to identifying potentially causal rare variants for complex disorders. Here, we present the results from a large-sample resequencing (n = 285 patients) study of candidate genes coupled with population genetics and statistical methods to identify rare variants associated with Autism Spectrum Disorder and Schizophrenia. Three genes, MAP1A, GRIN2B, and CACNA1F, were consistently identified by different methods as having significant excess of rare missense mutations in either one or both disease cohorts. In a broader context, we also found that the overall site frequency spectrum of variation in these cases is best explained by population models of both selection and complex demography rather than neutral models or models accounting for complex demography alone. Mutations in the three disease-associated genes explained much of the difference in the overall site frequency spectrum among the cases versus controls. This study demonstrates that genes associated with complex disorders can be mapped using resequencing and analytical methods with sample sizes far smaller than those required by genome-wide association studies. Additionally, our findings support the hypothesis that rare mutations account for a proportion of the phenotypic variance of these complex disorders.

Original languageEnglish
Article numbere1001318
JournalPLoS Genetics
Volume7
Issue number2
DOIs
Publication statusPublished - Feb 2011
Externally publishedYes

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