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

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.

SUBMITTER: Myers RA

PROVIDER: S-EPMC3044677 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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

Myers Rachel A RA Casals Ferran F Gauthier Julie J Hamdan Fadi F FF Keebler Jon J Boyko Adam R AR Bustamante Carlos D CD Piton Amelie M AM Spiegelman Dan D Henrion Edouard E Zilversmit Martine M Hussin Julie J Quinlan Jacklyn J Yang Yan Y Lafrenière Ronald G RG Griffing Alexander R AR Stone Eric A EA Rouleau Guy A GA Awadalla Philip P

PLoS genetics 20110224 2

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 e ...[more]

PMID: 21383861

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Project description:Rare genetic variants, identified by in-detail resequencing of loci, may contribute to complex traits. We used the apolipoprotein A-I gene (APOA1), a major high-density lipoprotein (HDL) gene, and population-based resequencing to determine the spectrum of genetic variants, the phenotypic characteristics of these variants, and how these results compared with results based on resequencing only the extremes of the apolipoprotein A-I (apoA-I) distribution. First, we resequenced APOA1 in 10,330 population-based participants in the Copenhagen City Heart Study. The spectrum and distribution of genetic variants was determined as a function of the number of individuals resequenced. Second, apoA-I and HDL cholesterol phenotypes were determined for nonsynonymous (NS) and synonymous (S) variants and were validated in the Copenhagen General Population Study (n = 45,239). Third, observed phenotypes were compared with those predicted using an extreme phenotype approach based on the apoA-I distribution. Our results are as follows: First, population-based resequencing of APOA1 identified 40 variants of which only 7 (18%) had minor allele frequencies >1%, and most were exceedingly rare. Second, 0.27% of individuals in the general population were heterozygous for NS variants which were associated with substantial reductions in apoA-I (up to 39 mg/dL) and/or HDL cholesterol (up to 0.9 mmol/L) and, surprisingly, 0.41% were heterozygous for variants predisposing to amyloidosis. NS variants associated with a hazard ratio of 1.72 (1.09-2.70) for myocardial infarction (MI), largely driven by A164S, a variant not associated with apoA-I or HDL cholesterol levels. Third, using the extreme apoA-I phenotype approach, NS variants correctly predicted the apoA-I phenotype observed in the population-based resequencing. However, using the extreme approach, between 79% (screening 0-1(st) percentile) and 21% (screening 0-20(th) percentile) of all variants were not identified; among these were variants previously associated with amyloidosis. Population-based resequencing of APOA1 identified a majority of rare NS variants associated with reduced apoA-1 and HDL cholesterol levels and/or predisposing to amyloidosis. In addition, NS variants associated with increased risk of MI.

Project description:BackgroundTransposable element (TE) polymorphisms are important components of population genetic variation. The functional impacts of TEs in gene regulation and generating genetic diversity have been observed in multiple species, but the frequency and magnitude of TE variation is under appreciated. Inexpensive and deep sequencing technology has made it affordable to apply population genetic methods to whole genomes with methods that identify single nucleotide and insertion/deletion polymorphisms. However, identifying TE polymorphisms, particularly transposition events or non-reference insertion sites can be challenging due to the repetitive nature of these sequences, which hamper both the sensitivity and specificity of analysis tools.MethodsWe have developed the tool RelocaTE2 for identification of TE insertion sites at high sensitivity and specificity. RelocaTE2 searches for known TE sequences in whole genome sequencing reads from second generation sequencing platforms such as Illumina. These sequence reads are used as seeds to pinpoint chromosome locations where TEs have transposed. RelocaTE2 detects target site duplication (TSD) of TE insertions allowing it to report TE polymorphism loci with single base pair precision.Results and discussionThe performance of RelocaTE2 is evaluated using both simulated and real sequence data. RelocaTE2 demonstrate high level of sensitivity and specificity, particularly when the sequence coverage is not shallow. In comparison to other tools tested, RelocaTE2 achieves the best balance between sensitivity and specificity. In particular, RelocaTE2 performs best in prediction of TSDs for TE insertions. Even in highly repetitive regions, such as those tested on rice chromosome 4, RelocaTE2 is able to report up to 95% of simulated TE insertions with less than 0.1% false positive rate using 10-fold genome coverage resequencing data. RelocaTE2 provides a robust solution to identify TE insertion sites and can be incorporated into analysis workflows in support of describing the complete genotype from light coverage genome sequencing.

Dataset Information

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

Publications

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

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