A genome wide association analysis in the GENDER study

Percutaneous coronary intervention (PCI) has become an effective therapy to treat coronary artery diseases. However, one of the major drawbacks of PCI is the occurrence of restenosis in 8 to 40% of all treated patients. The GENetic Determinants of Restenosis (GENDER) project was designed to study the association between genetic polymorphisims and clinical restenosis. The discovery of genetic variants associated to the occurrence of restenosis after PCI may provide a more tailored therapy and may serve as rationale for new antirestenotic therapies. So far, several candidate gene approaches had already been performed in the GENDER samples but a Genome Wide Association Scan (GWAS) was still lacking. Here, we present preliminary results from the GWAS we are currently carrying out in the GENDER population. (Neth Heart J 2009;17:262–4.)     

Genetics of venous thrombosis: insights from a new genome wide association study

Background

Venous Thrombosis (VT) is a common multifactorial disease associated with a major public health burden. Genetics factors are known to contribute to the susceptibility of the disease but how many genes are involved and their contribution to VT risk still remain obscure. We aimed to identify genetic variants associated with VT risk.

Methodology/Principal Findings

We conducted a genome-wide association study (GWAS) based on 551,141 SNPs genotyped in 1,542 cases and 1,110 controls. Twelve SNPs reached the genome-wide significance level of 2.0×10⁻⁸ and encompassed four known VT-associated loci, ABO, F5, F11 and FGG. By means of haplotype analyses, we also provided novel arguments in favor of a role of HIVEP1, PROCR and STAB2, three loci recently hypothesized to participate in the susceptibility to VT. However, no novel VT-associated loci came out of our GWAS. Using a recently proposed statistical methodology, we also showed that common variants could explain about 35% of the genetic variance underlying VT susceptibility among which 3% could be attributable to the main identified VT loci. This analysis additionally suggested that the common variants left to be identified are not uniformly distributed across the genome and that chromosome 20, itself, could contribute to ∼7% of the total genetic variance.

Conclusions/Significance

This study might also provide a valuable source of information to expand our understanding of biological mechanisms regulating quantitative biomarkers for VT.     

MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study

Background  

The interactions of multiple single nucleotide polymorphisms (SNPs) are highly hypothesized to affect an individual's susceptibility to complex diseases. Although many works have been done to identify and quantify the importance of multi-SNP interactions, few of them could handle the genome wide data due to the combinatorial explosive search space and the difficulty to statistically evaluate the high-order interactions given limited samples.     

Haplotype analysis improved evidence for candidate genes for intramuscular fat percentage from a genome wide association study of cattle

In genome wide association studies (GWAS), haplotype analyses of SNP data are neglected in favour of single point analysis of associations. In a recent GWAS, we found that none of the known candidate genes for intramuscular fat (IMF) had been identified. In this study, data from the GWAS for these candidate genes were re-analysed as haplotypes. First, we confirmed that the methodology would find evidence for association between haplotypes in candidate genes of the calpain-calpastatin complex and musculus longissimus lumborum peak force (LLPF), because these genes had been confirmed through single point analysis in the GWAS. Then, for intramuscular fat percent (IMF), we found significant partial haplotype substitution effects for the genes ADIPOQ and CXCR4, as well as suggestive associations to the genes CEBPA, FASN, and CAPN1. Haplotypes for these genes explained 80% more of the phenotypic variance compared to the best single SNP. For some genes the analyses suggested that there was more than one causative mutation in some genes, or confirmed that some causative mutations are limited to particular subgroups of a species. Fitting the SNPs and their interactions simultaneously explained a similar amount of the phenotypic variance compared to haplotype analyses. Haplotype analysis is a neglected part of the suite of tools used to analyse GWAS data, would be a useful method to extract more information from these data sets, and may contribute to reducing the missing heritability problem.     

A genome wide association study between copy number variation （CNV） and human height in Chinese population

Copy number variation (CNV) is a type of genetic variation which may have important roles in phenotypic variability and disease susceptibility. To hunt for genetic variants underlying human height variation, we performed a genome wide CNV association study for human height in 618 Chinese unrelated subjects using Affymetrix 500K array set. After adjusting for age and sex, we found that four CNVs at 6p21.3, 8p23.3-23.2, 9p23 and 16p12.1 were associated with human height (with borderline significant p value: 0.013, 0.011, 0.024, 0.049; respectively). However, after multiple tests correction, none of them was associated with human height. We observed that the gain of copy number (more than 2 copies) at 8p23.3-23.2 was associated with lower height (normal copy number vs. gain of copy number; 161.2 cm vs. 153.7 cm, p = 0.011), which accounted for 0.9% of height variation. Loss of copy number (less than 2 copies) at 6p21.3 was associated with 0.8% lower height (loss of copy number vs. normal copy number: 154.5 cm vs. 161.1 cm, p = 0.013). Since no important genes influencing height located in CNVs at loci of 8p23.3-23.2 and 6p21.3, the two CNVs may cause the structural rearrangements of neighbored important candidate genes, thus regulates the variation of height. Our results expand our knowledge of the genetic factors underlying height variation and the biological regulation of human height.     

A genome wide association study for QTL affecting direct and maternal effects of stillbirth and dystocia in cattle

Dystocia and stillbirth are significant causes of female and neonatal death in many species and there is evidence for a genetic component to both traits. Identifying causal mutations affecting these traits through genome wide association studies could reveal the genetic pathways involved and will be a step towards targeted interventions. Norwegian Red cattle are an ideal model breed for such studies as very large numbers of records are available. We conducted a genome wide association study for direct and maternal effects of dystocia and stillbirth using almost 1 million records of these traits. Genotyping costs were minimized by genotyping the sires of the recorded cows, and using daughter averages as phenotypes. A dense marker map containing 17 343 single nucleotide polymorphisms covering all autosomal chromosomes was utilized. The genotyped sires were assigned to one of two groups in an attempt to ensure independence between the groups. Associations were only considered validated if they occurred in both groups. Strong associations were found and validated on chromosomes 4, 5, 6, 9, 12, 20, 22 and 28. The QTL region on chromosome 6 was refined using LDLA analysis. The results showed that this chromosome most probably contains two QTL for direct effect on dystocia and one for direct effect on stillbirth. Several candidate genes may be identified close to these QTL. Of these, a cluster of genes expected to affect bone and cartilage formation (i.e. SPP1, IBSP and MEPE) are of particular interest and we suggest that these genes are screened in candidate gene studies for dystocia and stillbirth in cattle as well as other species.     

A genome wide association scan of bovine tuberculosis susceptibility in Holstein-Friesian dairy cattle

Background

Bovine tuberculosis is a significant veterinary and financial problem in many parts of the world. Although many factors influence infection and progression of the disease, there is a host genetic component and dissection of this may enlighten on the wider biology of host response to tuberculosis. However, a binary phenotype of presence/absence of infection presents a noisy signal for genomewide association study.

Methodology/Principal Findings

We calculated a composite phenotype of genetic merit for TB susceptibility based on disease incidence in daughters of elite sires used for artificial insemination in the Irish dairy herd. This robust measure was compared with 44,426 SNP genotypes in the most informative 307 subjects in a genome wide association analysis. Three SNPs in a 65 kb genomic region on BTA 22 were associated (i.e. p<10⁻⁵, peaking at position 59588069, p = 4.02×10⁻⁶) with tuberculosis susceptibility.

Conclusions/Significance

A genomic region on BTA 22 was suggestively associated with tuberculosis susceptibility; it contains the taurine transporter gene SLC6A6, or TauT, which is known to function in the immune system but has not previously been investigated for its role in tuberculosis infection.     

Investigation of a genome wide association signal for obesity: synthetic association and haplotype analyses at the melanocortin 4 receptor gene locus

Background

Independent genome-wide association studies (GWAS) showed an obesogenic effect of two single nucleotide polymorphisms (SNP; rs12970134 and rs17782313) more than 150 kb downstream of the melanocortin 4 receptor gene (MC4R). It is unclear if the SNPs directly influence MC4R function or expression, or if the SNPs are on a haplotype that predisposes to obesity or includes functionally relevant genetic variation (synthetic association). As both exist, functionally relevant mutations and polymorphisms in the MC4R coding region and a robust association downstream of the gene, MC4R is an ideal model to explore synthetic association.

Methodology/Principal Findings

We analyzed a genomic region (364.9 kb) encompassing the MC4R in GWAS data of 424 obesity trios (extremely obese child/adolescent and both parents). SNP rs12970134 showed the lowest p-value (p = 0.004; relative risk for the obesity effect allele: 1.37); conditional analyses on this SNP revealed that 7 of 78 analyzed SNPs provided independent signals (p≤0.05). These 8 SNPs were used to derive two-marker haplotypes. The three best (according to p-value) haplotype combinations were chosen for confirmation in 363 independent obesity trios. The confirmed obesity effect haplotype includes SNPs 3′ and 5′ of the MC4R. Including MC4R coding variants in a joint model had almost no impact on the effect size estimators expected under synthetic association.

Conclusions/Significance

A haplotype reaching from a region 5′ of the MC4R to a region at least 150 kb from the 3′ end of the gene showed a stronger association to obesity than single SNPs. Synthetic association analyses revealed that MC4R coding variants had almost no impact on the association signal. Carriers of the haplotype should be enriched for relevant mutations outside the MC4R coding region and could thus be used for re-sequencing approaches. Our data also underscore the problems underlying the identification of relevant mutations depicted by GWAS derived SNPs.     

Crop genome‐wide association study: a harvest of biological relevance

With the advent of rapid genotyping and next‐generation sequencing technologies, genome‐wide association study (GWAS) has become a routine strategy for decoding genotype–phenotype associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype–phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many ‘hits’ obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non‐main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome‐editing technologies.     

Investigation of transferability of BovineSNP50 BeadChip from cattle to water buffalo for genome wide association study

Cattle and water buffalo belong to the same subfamily Bovinae and share chromosome banding and gene order homology. In this study, we used genome-wide Illumina BovineSNP50 BeadChip to analyze 91 DNA samples from three breeds of water buffalo (Nili-Ravi, Murrah and their crossbred with local GuangXi buffalos in China), to demonstrate the genetic divergence between cattle and water buffalo through a large single nucleotide polymorphism (SNP) transferability study at the whole genome level, and performed association analysis of functional traits in water buffalo as well. A total of 40,766 (75.5 %) bovine SNPs were found in the water buffalo genome, but 49,936 (92.5 %) were with only one allele, and finally 935 were identified to be polymorphic and useful for association analysis in water buffalo. Therefore, the genome sequences of water buffalo and cattle shared a high level of homology but the polymorphic status of the bovine SNPs varied between these two species. The different patterns of mutations between species may associate with their phenotypic divergence due to genome evolution. Among 935 bovine SNPs, we identified a total of 9 and 7 SNPs significantly associated to fertility and milk production traits in water buffalo, respectively. However, more works in larger sample size are needed in future to verify these candidate SNPs for water buffalo.     

Incorporating functional annotation information in prioritizing disease associated SNPs from genome wide association studies

With recent advances in genotyping and sequencing technologies,many disease susceptibility loci have been identified.However,much of the genetic heritability remains unexplained and the replication rate between independent studies is still low.Meanwhile,there have been increasing efforts on functional annotations of the entire human genome,such as the Encyclopedia of DNA Elements(ENCODE)project and other similar projects.It has been shown that incorporating these functional annotations to prioritize genome wide association signals may help identify true association signals.However,to our knowledge,the extent of the improvement when functional annotation data are considered has not been studied in the literature.In this article,we propose a statistical framework to estimate the improvement in replication rate with annotation data,and apply it to Crohn’s disease and DNase I hypersensitive sites.The results show that with cell line specific functional annotations,the expected replication rate is improved,but only at modest level.     

A new approach to account for the correlations among single nucleotide polymorphisms in genome: wide association studies

In genetic association studies, such as genome-wide association studies (GWAS), the number of single nucleotide polymorphisms (SNPs) can be as large as hundreds of thousands. Due to linkage disequilibrium, many SNPs are highly correlated; assuming they are independent is not valid. The commonly used multiple comparison methods, such as Bonferroni correction, are not appropriate and are too conservative when applied to GWAS. To overcome these limitations, many approaches have been proposed to estimate the so-called effective number of independent tests to account for the correlations among SNPs. However, many current effective number estimation methods are based on eigenvalues of the correlation matrix. When the dimension of the matrix is large, the numeric results may be unreliable or even unobtainable. To circumvent this obstacle and provide better estimates, we propose a new effective number estimation approach which is not based on the eigenvalues. We compare the new method with others through simulated and real data. The comparison results show that the proposed method has very good performance.     

First report on genome wide association study in western Indian population reveals host genetic factors for COVID-19 severity and outcome

Different human races across the globe responded in a different way to the SARS-CoV-2 infection leading to different disease severity. Therefore, it is anticipated that host genetic factors have a straight association with the COVID-19. We identified a total 6, 7, and 6 genomic loci for deceased-recovered, asymptomatic-recovered, and deceased-asymptomatic group comparison, respectively. Unfavourable alleles of the markers nearby the genes which are associated with lung and heart diseases such as Tumor necrosis factor superfamily (TNFSF4&18), showed noteworthy association with the disease severity and outcome for the COVID-19 patients in the western Indian population. The markers found with significant association with disease prognosis or recovery are of value in determining the individual's response to SARS-CoV-2 infection and can be used for the risk prediction in COVID-19. Besides, GWAS study in other populations from India may help to strengthen the outcome of this study.     

Detecting low frequent loss-of-function alleles in genome wide association studies with red hair color as example

Multiple loss-of-function (LOF) alleles at the same gene may influence a phenotype not only in the homozygote state when alleles are considered individually, but also in the compound heterozygote (CH) state. Such LOF alleles typically have low frequencies and moderate to large effects. Detecting such variants is of interest to the genetics community, and relevant statistical methods for detecting and quantifying their effects are sorely needed. We present a collapsed double heterozygosity (CDH) test to detect the presence of multiple LOF alleles at a gene. When causal SNPs are available, which may be the case in next generation genome sequencing studies, this CDH test has overwhelmingly higher power than single SNP analysis. When causal SNPs are not directly available such as in current GWA settings, we show the CDH test has higher power than standard single SNP analysis if tagging SNPs are in linkage disequilibrium with the underlying causal SNPs to at least a moderate degree (r²>0.1). The test is implemented for genome-wide analysis in the publically available software package GenABEL which is based on a sliding window approach. We provide the proof of principle by conducting a genome-wide CDH analysis of red hair color, a trait known to be influenced by multiple loss-of-function alleles, in a total of 7,732 Dutch individuals with hair color ascertained. The association signals at the MC1R gene locus from CDH were uniformly more significant than traditional GWA analyses (the most significant P for CDH = 3.11×10⁻¹⁴² vs. P for rs258322 = 1.33×10⁻⁶⁶). The CDH test will contribute towards finding rare LOF variants in GWAS and sequencing studies.     

Genetic dissection of soybean partial resistance to sclerotinia stem rot through genome wide association study and high throughout single nucleotide polymorphisms

Sclerotinia stem rot (SSR) is a disease of soybean [Glycine max (L.) Merr] that causes severe yield losses. We studied 185 representative soybean accessions to evaluate partial SSR resistance and sequenced these by the specific-locus amplified fragment sequencing method. In total, 22,048 single-nucleotide polymorphisms (SNPs), with minor allele frequencies (MAF) ≥5% and missing data <3%, were developed and applied to genome-wide association study of SSR responsiveness and assess linkage disequilibrium (LD) level for candidate gene selection. We identified 18 association signals related to SSR partial resistance. Among them, six overlapped the regions of previous quantitative trait loci, and twelve were novel. We identified 243 candidate genes located in the 200 kb genomic region of these peak SNPs. Based on quantitative real-time polymerase chain reaction and haplotype analysis, Glyma.03G196000 and Glyma.20G095100, encoding pentatricopeptide repeat proteins, might be important factors in the resistance response of soybean to SSR.     

Genome‐wide association study for reproductive traits in a Large White pig population

Using the PorcineSNP80 BeadChip, we performed a genome‐wide association study for seven reproductive traits, including total number born, number born alive, litter birth weight, average birth weight, gestation length, age at first service and age at first farrowing, in a population of 1207 Large White pigs. In total, we detected 12 genome‐wide significant and 41 suggestive significant SNPs associated with six reproductive traits. The proportion of phenotypic variance explained by all significant SNPs for each trait ranged from 4.46% (number born alive) to 11.49% (gestation length). Among them, 29 significant SNPs were located within known QTL regions for swine reproductive traits, such as corpus luteum number, stillborn number and litter size, of which one QTL region associated with litter size contained the ALGA0098819 SNP for total number born. Subsequently, we found that 376 functional genes contained or were near these significant SNPs. Of these, 14 genes—BHLHA15, OCM2, IL1B2, GCK, SMAD2, HABP2, PAQR5, GRB10, PRELID2, DMKN, GPI, GPIHBP1, ADCY2 and ACVR2B—were considered important candidates for swine reproductive traits based on their critical roles in embryonic development, energy metabolism and growth development. Our findings contribute to the understanding of the genetic mechanisms for reproductive traits and could have a positive effect on pig breeding programs.