Whole genome sequences are required to fully resolve the linkage disequilibrium structure of human populations

Abstract

BACKGROUND: An understanding of linkage disequilibrium (LD) structures in the human genome underpins much of medical genetics and provides a basis for disease gene mapping and investigating biological mechanisms such as recombination and selection. Whole genome sequencing (WGS) provides the opportunity to determine LD structures at maximal resolution.

RESULTS: We compare LD maps constructed from WGS data with LD maps produced from the array-based HapMap dataset, for representative European and African populations. WGS provides up to 5.7-fold greater SNP density than array-based data and achieves much greater resolution of LD structure, allowing for identification of up to 2.8-fold more regions of intense recombination. The absence of ascertainment bias in variant genotyping improves the population representativeness of the WGS maps, and highlights the extent of uncaptured variation using array genotyping methodologies. The complete capture of LD patterns using WGS allows for higher genome-wide association study (GWAS) power compared to array-based GWAS, with WGS also allowing for the analysis of rare variation. The impact of marker ascertainment issues in arrays has been greatest for Sub-Saharan African populations where larger sample sizes and substantially higher marker densities are required to fully resolve the LD structure.

CONCLUSIONS: WGS provides the best possible resource for LD mapping due to the maximal marker density and lack of ascertainment bias. WGS LD maps provide a rich resource for medical and population genetics studies. The increasing availability of WGS data for large populations will allow for improved research utilising LD, such as GWAS and recombination biology studies.

More information

Identifiers

ORCID for Reuben Pengelly: orcid.org/0000-0001-7022-645X

ORCID for William Tapper: orcid.org/0000-0002-5896-1889

ORCID for Jane Gibson: orcid.org/0000-0002-0973-8285

ORCID for Andrew Collins: orcid.org/0000-0001-7108-0771

ORCID for Sarah Ennis: orcid.org/0000-0003-2648-0869

Catalogue record

Export record

Altmetrics