Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure, bioRxiv, 2019-07-11
AbstractHeart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2–4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.
biorxiv genetics 0-100-users 2019Assessing the analytical validity of SNP-chips for detecting very rare pathogenic variants implications for direct-to-consumer genetic testing, bioRxiv, 2019-07-10
ABSTRACTObjectivesTo determine the analytical validity of SNP-chips for genotyping very rare genetic variants.DesignRetrospective study using data from two publicly available resources, the UK Biobank and the Personal Genome Project.SettingResearch biobanks and direct-to-consumer genetic testing in the UK and USA.Participants49,908 individuals recruited to UK Biobank, and 21 individuals who purchased consumer genetic tests and shared their data online via the Personal Genomes Project.Main outcome measuresWe assessed the analytical validity of genotypes from SNP-chips (index test) with sequencing data (reference standard). We evaluated the genotyping accuracy of the SNP-chips and split the results by variant frequency. We went on to select rare pathogenic variants in the BRCA1 and BRCA2 genes as an exemplar for detailed analysis of clinically-actionable variants in UK Biobank, and assessed BRCA-related cancers (breast, ovarian, prostate and pancreatic) in participants using cancer registry data.ResultsSNP-chip genotype accuracy is high overall; sensitivity, specificity and precision are all >99% for 108,574 common variants directly genotyped by the UK Biobank SNP-chips. However, the likelihood of a true positive result reduces dramatically with decreasing variant frequency; for variants with a frequency <0.001% in UK Biobank the precision is very low and only 16% of 4,711 variants from the SNP-chips confirm with sequencing data. Results are similar for SNP-chip data from the Personal Genomes Project, and 2021 individuals have at least one rare pathogenic variant that has been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, the overall performance metrics of the SNP-chips in UK Biobank are sensitivity 34.6%, specificity 98.3% and precision 4.2%. Rates of BRCA-related cancers in individuals in UK Biobank with a positive SNP-chip result are similar to age-matched controls (OR 1.28, P=0.07, 95% CI 0.98 to 1.67), while sequence-positive individuals have a significantly increased risk (OR 3.73, P=3.5×10−12, 95% CI 2.57 to 5.40).ConclusionSNP-chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.SUMMARY BOXSection 1 What is already known on this topicSNP-chips are an accurate and affordable method for genotyping common genetic variants across the genome. They are often used by direct-to-consumer (DTC) genetic testing companies and research studies, but there several case reports suggesting they perform poorly for genotyping rare genetic variants when compared with sequencing.Section 2 What this study addsOur study confirms that SNP-chips are highly inaccurate for genotyping rare, clinically-actionable variants. Using large-scale SNP-chip and sequencing data from UK Biobank, we show that SNP-chips have a very low precision of <16% for detecting very rare variants (i.e. the majority of variants with population frequency of <0.001% are false positives). We observed a similar performance in a small sample of raw SNP-chip data from DTC genetic tests. Very rare variants assayed using SNP-chips should not be used to guide health decisions without validation.
biorxiv genetics 200-500-users 2019Emergence of the Ug99 lineage of the wheat stem rust pathogen through somatic hybridisation, bioRxiv, 2019-07-04
AbstractParasexuality contributes to diversity and adaptive evolution of haploid (monokaryotic) fungi. However non-sexual genetic exchange mechanisms are not defined in dikaryotic fungi (containing two distinct haploid nuclei). Newly emerged strains of the wheat stem rust pathogen, Puccinia graminis f. sp. tritici (Pgt), such as Ug99, are a major threat to global food security. Here we show that Ug99 arose by somatic hybridisation and nuclear exchange between dikaryons. Fully haplotype-resolved genome assembly and DNA proximity analysis revealed that Ug99 shares one haploid nucleus genotype with a much older African lineage of Pgt, with no recombination or reassortment. Generation of genetic variation by nuclear exchange may favour the evolution of dikaryotism by providing an advantage over diploidy.
biorxiv genetics 100-200-users 2019Identification of type 2 diabetes loci in 433,540 East Asian individuals, bioRxiv, 2019-06-29
SUMMARYMeta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals innear GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.Type 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production andor secretion by the pancreatic β cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.
biorxiv genetics 100-200-users 2019Genetic screens in isogenic mammalian cell lines without single cell cloning, bioRxiv, 2019-06-23
Isogenic pairs of cell lines, which differ by a single genetic modification, are powerful tools for understanding gene function. Generating such pairs for mammalian cells, however, is labor-intensive, time-consuming, and impossible in some cell types. Here we present an approach to create isogenic pairs of cells and screen them with genome-wide CRISPR-Cas9 libraries to generate genetic interaction maps. We queried the anti-apoptotic genes BCL2L1 and MCL1, and the DNA damage repair gene PARP1, via 25 genome-wide screens across 4 cell lines. For all three genes, we identify a rich set of both expected and novel buffering and synthetic lethal interactions. Further, we compare the interactions observed in genetic space to those found when targeting these genes with small molecules and identify hits that may inform the clinical uses for these inhibitors. We anticipate that this methodology will be broadly useful to comprehensively study genes of interest across many cell types.
biorxiv genetics 0-100-users 2019