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Exome-based linkage disequilibrium maps of individual genes: functional clustering and relationship to disease

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Abstract

Exome sequencing identifies thousands of DNA variants and a proportion of these are involved in disease. Genotypes derived from exome sequences provide particularly high-resolution coverage enabling study of the linkage disequilibrium structure of individual genes. The extent and strength of linkage disequilibrium reflects the combined influences of mutation, recombination, selection and population history. By constructing linkage disequilibrium maps of individual genes, we show that genes containing OMIM-listed disease variants are significantly under-represented amongst genes with complete or very strong linkage disequilibrium (P = 0.0004). In contrast, genes with disease variants are significantly over-represented amongst genes with levels of linkage disequilibrium close to the average for genes not known to contain disease variants (P = 0.0038). Functional clustering reveals, amongst genes with particularly strong linkage disequilibrium, significant enrichment of essential biological functions (e.g. phosphorylation, cell division, cellular transport and metabolic processes). Strong linkage disequilibrium, corresponding to reduced haplotype diversity, may reflect selection in utero against deleterious mutations which have profound impact on the function of essential genes. Genes with very weak linkage disequilibrium show enrichment of functions requiring greater allelic diversity (e.g. sensory perception and immune response). This category is not enriched for genes containing disease variation. In contrast, there is significant enrichment of genes containing disease variants amongst genes with more average levels of linkage disequilibrium. Mutations in these genes may less likely lead to in utero lethality and be subject to less intense selection.

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Correspondence to Andrew Collins.

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Gibson, J., Tapper, W., Ennis, S. et al. Exome-based linkage disequilibrium maps of individual genes: functional clustering and relationship to disease. Hum Genet 132, 233–243 (2013). https://doi.org/10.1007/s00439-012-1243-6

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  • DOI: https://doi.org/10.1007/s00439-012-1243-6

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