Rare genetic variants underlie outlying levels of DNA methylation and gene-expression.

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

The Coronary Artery Disease-associated Coding Variant in Zinc Finger C3HC-type Containing 1 (ZC3HC1) Affects Cell Cycle Regulation.

Genome-wide association studies have to date identified multiple coronary artery disease (CAD)-associated loci; however, for most of these loci the mechanism by which they affect CAD risk is unclear. The CAD-associated locus 7q32.2 is unusual in that the lead variant, rs11556924, is not in strong linkage disequilibrium with any other variant and introduces a coding change in ZC3HC1, which encodes NIPA. In this study, we show that rs11556924 polymorphism is associated with lower regulatory phosphorylation of NIPA in the risk variant, resulting in NIPA with higher activity. Using a genome-editing approach we show that this causes an effective decrease in cyclin-B1 stability in the nucleus, thereby slowing its nuclear accumulation. By perturbing the rate of nuclear cyclin-B1 accumulation, rs11556924 alters the regulation of mitotic progression resulting in an extended mitosis. This study shows that the CAD-associated coding polymorphism in ZC3HC1 alters the dynamics of cell-cycle regulation by NIPA.

A molecular dynamics study of C1r and C1s dimers: implications for the structure of the C1 complex.

Complement is an important part of the immune system. It is initiated through three different pathways known as the classical, lectin, and alternative pathway. The multimolecular C1 complex of the classical pathway consists of a subcomponent, C1q, which binds to a tetramer comprising two C1r and two C1s proteases. A detailed description of the structure of the C1 complex is essential to fully understand how the complex acts on pathogens. A variety of different models have been proposed, which differ mainly in the way the proteases interact with C1q. In this study, we have used a combination of homology-based structure prediction and molecular dynamics to predict a partial structure of the C1s/C1r/C1r/C1s tetramer. For computational expediency the study was restricted to the CUB(1) -EGF-CUB(2) domains which are directly involved in the formation of the tetramer and its interaction with C1q; the catalytic fragments (CCP(1) -CCP(2) -SP), which mediate C1 activation and subsequent cleavage of substrates, were omitted. A systematic molecular dynamics (MD) study of several possible dimeric combinations suggest that the tetramer is formed when a pair of C1r/C1s dimers form a "doughnut" via a C1s/C1s head-to-tail interaction, which is stabilized by several putative salt bridges at the dimer interface. This result is consistent with biochemical data which have shown that self assembly requires the formation of C1r-C1s contacts and that electrostatic interactions play a key role. Furthermore, it identifies a number of putative binding residues that can be tested using site-directed mutagenesis.

Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait.

Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models to test fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (Bayesian imputation-based association mapping, Bayesian sparse linear mixed model, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals (n = 1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Project Phase 3 (1000G) reference panel (n = 2504 from 26 populations) giving a mean nonreference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n = 32,470 Europeans). These imputation errors had an impact on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼23% and ∼7% between the WGS and the 1000G and HRC imputed datasets, respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong linkage disequilibrium with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low-level biological trait with imputed genetic data has implications for the study of higher-order complex traits and disease.