Visualizing Chromosome Mosaicism and Detecting Ethnic Outliers by the Method of “Rare” Heterozygotes and Homozygotes (RHH)

We describe a novel approach for evaluating SNP genotypes of a genome-wide association scan to identify “ethnic outlier” subjects whose ethnicity is different or admixed compared to most other subjects in the genotyped sample set. Each ethnic outlier is detected by counting a genomic excess of “rare” heterozygotes and/or homozygotes whose frequencies are low (<1%) within genotypes of the sample set being evaluated. This method also enables simple and striking visualization of non-Caucasian chromosomal DNA segments interspersed within the chromosomes of ethnically admixed individuals. We show that this visualization of the mosaic structure of admixed human chromosomes gives results similar to another visualization method (SABER) but with much less computational time and burden. We also show that other methods for detecting ethnic outliers are enhanced by evaluating only genomic regions of visualized admixture rather than diluting outlier ancestry by evaluating the entire genome considered in aggregate. We have validated our method in the Wellcome Trust Case Control Consortium (WTCCC) study of 17,000 subjects as well as in HapMap subjects and simulated outliers of known ethnicity and admixture. The method's ability to precisely delineate chromosomal segments of non-Caucasian ethnicity has enabled us to demonstrate previously unreported non-Caucasian admixture in two HapMap Caucasian parents and in a number of WTCCC subjects. Its sensitive detection of ethnic outliers and simple visual discrimination of discrete chromosomal segments of different ethnicity implies that this method of rare heterozygotes and homozygotes (RHH) is likely to have diverse and important applications in humans and other species

Linkage Disequilibrium Mapping via Cladistic Analysis of Single-Nucleotide Polymorphism Haplotypes

We present a novel approach to disease-gene mapping via cladistic analysis of single-nucleotide polymorphism (SNP) haplotypes obtained from large-scale, population-based association studies, applicable to whole-genome screens, candidate-gene studies, or fine-scale mapping. Clades of haplotypes are tested for association with disease, exploiting the expected similarity of chromosomes with recent shared ancestry in the region flanking the disease gene. The method is developed in a logistic-regression framework and can easily incorporate covariates such as environmental risk factors or additional unlinked loci to allow for population structure. To evaluate the power of this approach to detect disease-marker association, we have developed a simulation algorithm to generate high-density SNP data with short-range linkage disequilibrium based on empirical patterns of haplotype diversity. The results of the simulation study highlight substantial gains in power over single-locus tests for a wide range of disease models, despite overcorrection for multiple testing

A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. Availability: http://www.sanger.ac.uk/resources/software/genevar Contact: [email protected]

Allelic expression mapping across cellular lineages to establish impact of non-coding SNPs

This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited

Genetically modulated educational attainment and coronary disease risk.

AIMS: Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment-an important denominator of lifestyle-and coronary artery disease (CAD) risk. METHODS AND RESULTS: Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a 'genetic education score' in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10-8; odds ratio (OR) 0.79, 95% confidence interval (CI) 0.73-0.85 for the higher compared with the lowest score quintile]. We replicated in 146 514 individuals from UK Biobank (P = 1.85 × 10-6) and also found strong associations between the 'genetic education score' with 'modifiable' risk factors including smoking (P = 5.36 × 10-23), body mass index (BMI) (P = 1.66 × 10-30), and hypertension (P = 3.86 × 10-8). Interestingly, these associations were only modestly attenuated by adjustment for years spent in school. In contrast, a model adjusting for BMI and smoking abolished the association signal between the 'genetic education score' and CAD risk suggesting an intermediary role of these two risk factors. Mendelian randomization analyses performed with summary statistics from large genome-wide meta-analyses and sensitivity analysis using 1271 variants affecting educational attainment (OR 0.68 for the higher compared with the lowest score quintile; 95% CI 0.63-0.74; P = 3.99 × 10-21) further strengthened these findings. CONCLUSION: Genetic variants known to affect educational attainment may have implications for a health-conscious lifestyle later in life and subsequently affect the risk of CAD.This work was supported by grants from the Fondation Leducq (CADgenomics: Understanding CAD Genes, 12CVD02), the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (e:AtheroSysMed, grant 01ZX1313A-2014), and the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no HEALTH-F2-2013-601456 (CVgenes-at-target). Further grants were received from the DFG as part of the Sonderforschungsbereich CRC 1123 (B2). T.K. was supported by a DZHK Rotation Grant

A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip (R) for Methylome Profiling

Peer reviewe

The Influence of Recombination on Human Genetic Diversity

In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale. Despite considerable debate, it is not clear whether these factors are causally linked or, if they are, whether this is driven by the repeated action of adaptive evolution or molecular processes such as double-strand break formation and mismatch repair. We introduce three innovations to the analysis of recombination and diversity: fine-scale genetic maps estimated from genotype experiments that identify recombination hotspots at the kilobase scale, analysis of an entire human chromosome, and the use of wavelet techniques to identify correlations acting at different scales. We show that recombination influences genetic diversity only at the level of recombination hotspots. Hotspots are also associated with local increases in GC content and the relative frequency of GC-increasing mutations but have no effect on substitution rates. Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition. To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations. However, that hotspots have no influence on substitution rates suggests that they are too ephemeral on an evolutionary time scale to have a strong influence on broader scale patterns of base composition and long-term molecular evolution

High-throughput analysis of candidate imprinted genes and allele-specific gene expression in the human term placenta.

BACKGROUND: Imprinted genes show expression from one parental allele only and are important for development and behaviour. This extreme mode of allelic imbalance has been described for approximately 56 human genes. Imprinting status is often disrupted in cancer and dysmorphic syndromes. More subtle variation of gene expression, that is not parent-of-origin specific, termed 'allele-specific gene expression' (ASE) is more common and may give rise to milder phenotypic differences. Using two allele-specific high-throughput technologies alongside bioinformatics predictions, normal term human placenta was screened to find new imprinted genes and to ascertain the extent of ASE in this tissue. RESULTS: Twenty-three family trios of placental cDNA, placental genomic DNA (gDNA) and gDNA from both parents were tested for 130 candidate genes with the Sequenom MassArray system. Six genes were found differentially expressed but none imprinted. The Illumina ASE BeadArray platform was then used to test 1536 SNPs in 932 genes. The array was enriched for the human orthologues of 124 mouse candidate genes from bioinformatics predictions and 10 human candidate imprinted genes from EST database mining. After quality control pruning, a total of 261 informative SNPs (214 genes) remained for analysis. Imprinting with maternal expression was demonstrated for the lymphocyte imprinted gene ZNF331 in human placenta. Two potential differentially methylated regions (DMRs) were found in the vicinity of ZNF331. None of the bioinformatically predicted candidates tested showed imprinting except for a skewed allelic expression in a parent-specific manner observed for PHACTR2, a neighbour of the imprinted PLAGL1 gene. ASE was detected for two or more individuals in 39 candidate genes (18%). CONCLUSIONS: Both Sequenom and Illumina assays were sensitive enough to study imprinting and strong allelic bias. Previous bioinformatics approaches were not predictive of new imprinted genes in the human term placenta. ZNF331 is imprinted in human term placenta and might be a new ubiquitously imprinted gene, part of a primate-specific locus. Demonstration of partial imprinting of PHACTR2 calls for re-evaluation of the allelic pattern of expression for the PHACTR2-PLAGL1 locus. ASE was common in human term placenta.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Genetic Risk Score for Coronary Disease Identifies Predispositions to Cardiovascular and Noncardiovascular Diseases.

BACKGROUND: The taxonomy of cardiovascular (CV) diseases is divided into a broad spectrum of clinical entities. Many such diseases coincide in specific patient groups and suggest shared predisposition. OBJECTIVES: This study focused on coronary artery disease (CAD) and investigated the genetic relationship to CV and non-CV diseases with reported CAD comorbidity. METHODS: This study examined 425,196 UK Biobank participants to determine a genetic risk score (GRS) based on 300 CAD associated variants (CAD-GRS). This score was associated with 22 traits, including risk factors, diseases secondary to CAD, as well as comorbid and non-CV conditions. Sensitivity analyses were performed in individuals free from CAD or stable angina diagnosis. RESULTS: Hypercholesterolemia (odds ratio [OR]: 1.27; 95% CI: 1.26 to 1.29) and hypertension (OR: 1.11; 95% CI: 1.10 to 1.12) were strongly associated with the CAD-GRS, which indicated that the score contained variants predisposing to these conditions. However, the CAD-GRS was also significant in patients with CAD who were free of CAD risk factors (OR: 1.37; 95% CI: 1.30 to 1.44). The study observed significant associations between the CAD-GRS and peripheral arterial disease (OR: 1.28; 95% CI: 1.23 to 1.32), abdominal aortic aneurysms (OR: 1.28; 95% CI: 1.20 to 1.37), and stroke (OR: 1.08; 95% CI: 1.05 to 1.10), which remained significant in sensitivity analyses that suggested shared genetic predisposition. The score was also associated with heart failure (OR: 1.25; 95% CI: 1.22 to 1.29), atrial fibrillation (OR: 1.08; 95% CI: 1.05 to 1.10), and premature death (OR: 1.04; 95% CI: 1.02 to 1.06). These associations were abolished in sensitivity analyses that indicated that they were secondary to prevalent CAD. Finally, an inverse association was observed between the score and migraine headaches (OR: 0.94; 95% CI: 0.93 to 0.96). CONCLUSIONS: A wide spectrum of CV conditions, including premature death, might develop consecutively or in parallel with CAD for the same genetic roots. In conditions like heart failure, the study found evidence that the CAD-GRS could be used to stratify patients with no or limited genetic overlap with CAD risk. Increased genetic predisposition to CAD was inversely associated with migraine headaches.National Institute of Health Research (NIHR) Barts Biomedical Research Centre - NIHR (IS-BRC-1215-20022)Fondation Leducq (CADgenomics, 12CVD02)Sonderforschungsbereich CRC 1123 (B2)German Federal Ministry of Education and Research (BMBF) (ERA-CVD: grant JTC2017_21-040