Fig. 4: Contribution of genes and 50kb regions to height (HT), body-mass-index (BMI), cardiovascular disease (CAD) and type-2-diabetes (T2D). | Nature Communications

Fig. 4: Contribution of genes and 50kb regions to height (HT), body-mass-index (BMI), cardiovascular disease (CAD) and type-2-diabetes (T2D).

From: Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

Fig. 4

a We grouped SNPs in 50 kb-regions genome-wide and estimated the sum of the squared regression coefficient estimates for each 50 kb-region. We then select the number of 50 kb regions that explain at least 0.001% of the variance attributed to all SNP markers in 80, 90 and 95% of the iterations. This gives a measure called the posterior probability that the window variance (PPWV)20 exceeds 1/10,000 of the phenotypic variation attributed to SNP markers. b We mapped SNPs to the closest gene +/−50 kb from the SNP position and labelled them as located in a coding region, an intron, 1 kb upstream of a gene using our functional annotations (Fig. 3a). Remaining snps are labelled as located in a cis-region (up to +/−50 kb from a gene). We then select the number of regions where PPWV is higher than 95% and explains at least 0.001 % of the phenotypic variance attributed to all SNP markers. We then calculate the number of significant coding regions, introns, 1 kb regions and cis regions as a proportion of the total number of genes for each chromosome. Genic associations that explain at least 0.001% of the phenotypic variance attributed to all SNP markers are again spread across chromosomes according to the chromosome length. c Shows the mean of the phenotypic variance attributed to intron and cis regions (y-axis) and coding regions (x-axis) that explain at least 0.001% of the phenotypic variance attributable to SNP markers in ≥95% of the iterations (PPWV > 0.95). These results provide joint estimates of the proportions of variance contributed by different gene bodies and automatic fine-mapping of gene bodies and their cis-regulatory regions. For example, introns and cis-regulatory regions of FTO respectively contribute 0.48% (95% CI 0.29, 1.12) and 0.01% (95% CI 0, 0.01) to the phenotypic variance of BMI. d We calculated the phenotypic variance contributed by exonic, intronic, promoter region and SNPs +/−50 kb outside of the exon and promotor regions (cis) for each gene. Bar plots show the correlation among the variance explained by the groups across genes. Error bars show the SD.

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