Evaluating linkage disequilibrium and recombination provides a haplotype-tagging SNP panel of the major histocompatibility complex in African Americans

The effect of genomic inversions on estimation of population genetic parameters from SNP data

In recent years it has emerged that structural variants have a substantial impact on genomic variation. Inversion polymorphisms represent a significant class of structural variant, and despite the challenges in their detection, data on inversions in the human genome are increasing rapidly. Statistical methods for inferring parameters such as the recombination rate and the selection coefficient have generally been developed without accounting for the presence of inversions. Here we exploit new software for simulating inversions in population genetic data, invertFREGENE, to assess the potential impact of inversions on such methods. Using data simulated by invertFREGENE, as well as real data from several sources, we test whether large inversions have a disruptive effect on widely applied population genetics methods for inferring recombination rates, for detecting selection, and for controlling for population structure in genome-wide association studies (GWAS). We find that recombination rates estimated by LDhat are biased downward at inversion loci relative to the true contemporary recombination rates at the loci but that recombination hotspots are not falsely inferred at inversion breakpoints as may have been expected. We find that the integrated haplotype score (iHS) method for detecting selection appears robust to the presence of inversions. Finally, we observe a strong bias in the genome-wide results of principal components analysis (PCA), used to control for population structure in GWAS, in the presence of even a single large inversion, confirming the necessity to thin SNPs by linkage disequilibrium at large physical distances to obtain unbiased results.

Genetic association of htSNPs across the major histocompatibility complex with rheumatoid arthritis in an African-American population

Notwithstanding the well-established association of HLA-DRB1 shared epitope alleles, interest remains in identifying additional major histocompatibility complex (MHC) region variants associated with rheumatoid arthritis (RA). We used a panel of 1201 haplotype-tagging single nucleotide polymorphisms (SNPs) designed for African Americans to find genetic variants associated with RA in a 3.8-Mb region encompassing the MHC. Conditioning on seven covariates, including HLA-DRB1 risk alleles and population structure, we identified an SNP in HLA-DOA (rs9276977) significantly associated with RA; minor allele frequency (MAF) 0.27 in cases versus 0.21 in controls, odds ratio (+/-95% confidence interval)=2.86 (1.61, 5.31). Genotyping of rs9276977 in an independent sample of African-American RA patients and controls did not replicate the association (MAF 0.28 in cases versus 0.27 in controls). This study points to the potential association of a SNP in the HLA-DOA gene with RA in African Americans, but also underscores the importance of replication of findings in larger patient cohorts.