Exome sequencing and the genetic basis of complex traits.

Discovery of novel variants for increasing numbers of samples. For each functional class, the fold-increase over the number of variants in one sample for that class is plotted as a function of the number of samples in a sequencing experiment. For example, the number of nonsense variants discovered in 300 samples is 40 times greater than the average number discovered in a single sample while the number of synonymous variants is only 10 times greater (although the absolute number of nonsense variants is a relatively minor proportion of the total variation discovered); this effect is due to purifying selection. All classes of variants are discovered at rates exceeding what would be predicted under a neutral model of evolution in a population of constant size, an effect of population growth. The crossing between curves for synonymous variants and the theoretical prediction most likely is a signature of the out-of-Africa bottleneck. See Methods for additional details.

Association analysis. (a) Q-Q plot of association p-values under the null hypothesis. (b) Distributions of lowest p-values under whole-exome permutations. The histograms show the distributions of the lowest p-values across permutations for the T5 test. The red vertical line indicates the 0.05 exome-wide significance level for the most significant gene (i.e., the most significant gene is exome-wide significant if its p-value is lower that the level indicated by the red line).

Extrapolation of gene burden results. Horizontal solid red line shows Bonferroni genome-wide significance threshold of P = 2.5 × 10−6. Horizontal dashed line shows the threshold derived from whole-exome permutations (Figure 2b). For larger sample sizes, the permutation threshold would be closer to the Bonferroni threshold, asymptotically approaching it as the sample sizes increase.