Association analysis of a novel SNV (chr2:212426588).

<p>Association analysis of a novel SNV (chr2:212426588).</p

Description of novel variants identified by sequencing in <i>ERBB4</i>.

<p>Description of novel variants identified by sequencing in <i>ERBB4</i>.</p

Variants identified by sequencing in <i>ERBB4</i>.

<p>Variants identified by sequencing in <i>ERBB4</i>.</p

<i>ERBB4</i> gene structure with a focus on a novel variant within a “bleeding” exon 20.

<p><i>ERBB4</i> gene structure with a focus on a novel variant within a “bleeding” exon 20.</p

Chronic social stress induces DNA methylation changes at an evolutionary conserved intergenic region in chromosome X

<p>Chronic stress resulting from prolonged exposure to negative life events increases the risk of mood and anxiety disorders. Although chronic stress can change gene expression relevant for behavior, molecular regulators of this change have not been fully determined. One process that could play a role is DNA methylation, an epigenetic process whereby a methyl group is added onto nucleotides, predominantly cytosine in the CpG context, and which can be induced by chronic stress. It is unknown to what extent chronic social defeat, a model of human social stress, influences DNA methylation patterns across the genome. Our study addressed this question by using a targeted-capture approach called Methyl-Seq to investigate DNA methylation patterns of the dentate gyrus at putative regulatory regions across the mouse genome from mice exposed to 14 days of social defeat. Findings were replicated in independent cohorts by bisulfite-pyrosequencing. Two differentially methylated regions (DMRs) were identified. One DMR was located at intron 9 of <i>Drosha</i>, and it showed reduced methylation in stressed mice. This observation replicated in one of two independent cohorts. A second DMR was identified at an intergenic region of chromosome X, and methylation in this region was increased in stressed mice. This methylation difference replicated in two independent cohorts and in Major Depressive Disorder (MDD) postmortem brains. These results highlight a region not previously known to be differentially methylated by chronic social defeat stress and which may be involved in MDD.</p

Power estimates for multiple genes case-control studies with causal variants from disease etiologies randomly sampled from nine multinomial distributions (Figure S3).

<p>Power estimates for BOMP, VT, SKAT, KBAC (KBAC1P = minor allele frequency defined as , KBAC5P = minor allele frequency defined as ). Each vertical line represents power estimates for each method, based on 250 simulated case-control studies. The genomic individuals each had nine genes, of which three contained causal variants and six did not. The disease etiologies for the three genes with causal variants were randomly sampled from nine multinomial distributions (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003224#pgen.1003224.s003" target="_blank">Figure S3</a>). AA = African-American simple bottleneck demographic model. EA = European-American exponential growth demographic model.</p

Analytical comparison of SKAT, BOMP, and VT on a toy example.

<p>Genotypes of 8 cases and 8 controls at 10 positions. Matrix column colors: controls = light blue, cases = light red. Position distribution bar colors: controls = blue, cases = red. Detailed description is in the section “Toy example with analytical calculations” (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003224#pgen.1003224.s013" target="_blank">Text S1</a>).</p

Power estimates for multiple gene case-control studies with causal variants equally likely to be from any disease etiology dominated by rare variants.

<p>A,B. X-axis shows number of candidate genes in 250 simulated case-control studies (approximately one-third each from disease etiologies Rare, LowFreq and KeyRegion). All genes contain causal variants. For each method, average power is shown. Power increases for all methods as the number of candidate genes with causal variants increases. C,D. X-axis shows the number of candidate genes and the ratio of genes containing causal variants to those that do not contain causal variants. As the ratio decreases, the power of the tested methods also decreases. (Tested methods are BOMP, VT, SKAT and KBAC1P = minor allele frequency defined as , KBAC5P = minor allele frequency defined as ). AA = the case-control studies were drawn from gene populations generated with an African-American simple bottleneck demographic model. EA = the case-control studies were drawn from gene populations generated with a European-American exponential growth demographic model.)</p

Single gene methods power comparison.

<p>Power estimates for BOMP, VT, SKAT, KBAC (KBAC1P = minor allele frequency defined as , KBAC5P = minor allele frequency defined as ). Each vertical line represents power estimates for each method, based on 250 simulated case-control studies. AA = the case-control studies were drawn from gene populations generated with an African-American simple bottleneck demographic model. EA = the case-control studies were drawn from gene populations generated with a European-American exponential growth demographic model. The eight variant causality (disease etiology) models are defined in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003224#pgen-1003224-t001" target="_blank">Table 1</a>. Since the European-American demographic model does not account for common or protective variants, etiologies involving common or protective variants were only considered for the African-American demographic model.</p

Eight disease etiologies used in simulation experiments.

<p><i>Rare variant</i> = disease caused by multiple rare deleterious variants. <i>Low frequency variant</i> = disease caused by multiple low frequency deleterious variants. <i>Key Region variant</i> = rare deleterious variants are localized to key regions. <i>Common variant</i> = disease caused by a single deleterious common variant. The etiologies <i>Rare+Protect</i>, <i>LowFreq+Protect</i>, <i>KeyRegion+Protect</i> and <i>Common+Protect</i> were identical to the first four except that they include protective variants.</p>1<p>Minor allele frequency of deleterious causal variants,</p>2<p>Selection coefficients of deleterious causal variants,</p>3<p>Effect size of deleterious causal variants,</p>4<p>Selection coefficient of protective causal variants,</p>5<p>Effect size of protective modifier variants,</p>6<p>Required functional role of causal and protective variants, NS = coding non-synonymous, AA = African-American simple bottleneck demographic model <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003224#pgen.1003224-Boyko1" target="_blank">[44]</a>, EA = European-American exponential growth demographic model <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003224#pgen.1003224-Kryukov1" target="_blank">[19]</a>).</p>*<p> for protective modifier variants with AF5%, for protective modifier variants with AF5%.</p