Meta-analysis of genome-wide association studies

A beginner's guide to low-coverage whole genome sequencing for population genomics

Low-coverage whole genome sequencing (lcWGS) has emerged as a powerful and cost-effective approach for population genomic studies in both model and non-model species. However, with read depths too low to confidently call individual genotypes, lcWGS requires specialized analysis tools that explicitly account for genotype uncertainty. A growing number of such tools have become available, but it can be difficult to get an overview of what types of analyses can be performed reliably with lcWGS data, and how the distribution of sequencing effort between the number of samples analyzed and per-sample sequencing depths affects inference accuracy. In this introductory guide to lcWGS, we first illustrate how the per-sample cost for lcWGS is now comparable to RAD-seq and Pool-seq in many systems. We then provide an overview of software packages that explicitly account for genotype uncertainty in different types of population genomic inference. Next, we use both simulated and empirical data to assess the accuracy of allele frequency and genetic diversity estimation, detection of population structure, and selection scans under different sequencing strategies. Our results show that spreading a given amount of sequencing effort across more samples with lower depth per sample consistently improves the accuracy of most types of inference, with a few notable exceptions. Finally, we assess the potential for using imputation to bolster inference from lcWGS data in non-model species, and discuss current limitations and future perspectives for lcWGS-based population genomics research. With this overview, we hope to make lcWGS more approachable and stimulate its broader adoption.

Assaying NanoLuc Luciferase Activity from mRNA-Injected Xenopus Embryos

The earliest steps of animal development depend upon posttranscriptional events that drive the embryonic cell cycle and guide cell fate decisions. The analysis of post-transcriptional regulatory events has relied upon the use of chimeric reporter mRNAs that encode firefly luciferase fused to potential regulatory sequences. A new and more sensitive luciferase developed recently called NanoLuc has the potential to improve reporter studies and provide new insights into the regulation of embryonic processes. Here I describe how to create and analyze reporter mRNAs encoding NanoLuc luciferase using extracts from microinjected Xenopus embryos.

Genome-wide association meta-analysis of age at first cannabis use

BACKGROUND AND AIMS

Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants.

METHODS

A twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals.

RESULTS

The twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19-60%]. Shared and unique environmental factors explained 39% (95% CI = 20-56%) and 22% (95% CI = 16-29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high linkage disequilibrium (LD) (r2  > 0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant.

CONCLUSION

Age at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Xenopus TACC2 is a microtubule plus end-tracking protein that can promote microtubule polymerization during embryonic development

Xenopus TACC2 is a microtubule plus end–tracking protein that localizes in front of EB1 and overlaps with TACC1 and TACC3 in cultured embryonic mesenchymal cells and neuronal growth cones. TACC2 OE can promote increased microtubule polymerization in mesenchymal cells but not growth cones, suggesting cell-type specificity to its function.

Microtubule dynamics is regulated by plus end–tracking proteins (+TIPs), which localize to the plus ends of microtubules (MTs). We previously showed that TACC1 and TACC3, members of the transforming acidic coiled-coil protein family, can act as +TIPs to regulate MT dynamics in Xenopus laevis. Here we characterize TACC2 as a +TIP that localizes to MT plus ends in front of EB1 and overlapping with TACC1 and TACC3 in multiple embryonic cell types. We also show that TACC2 can promote MT polymerization in mesenchymal cells but not neuronal growth cones, thus displaying cell-type specificity. Structure–function analysis demonstrates that the C-terminal region of TACC2 is both necessary and sufficient to localize to MT plus ends and promote increased rates of MT polymerization, whereas the N-terminal region cannot bind to MT plus ends but can act in a dominant-negative capacity to reduce polymerization rates. Finally, we analyze mRNA expression patterns in Xenopus embryos for each TACC protein and observe neural enrichment of TACC3 expression compared with TACC1 and TACC2, which are also expressed in mesodermal tissues, including somites. Overall these data provide a novel assessment of all three TACC proteins as a family of +TIPs by highlighting the unique attributes of each, as well as their collective characteristics.

Jackknife-based gene-gene interactiontests for untyped SNPs

BACKGROUND

Testing gene-gene interaction in genome-wide association studies generally yields lower power than testing marginal association. Meta-analysis that combines different genotyping platforms is one method used to increase power when assessing gene-gene interactions, which requires a test for interaction on untyped SNPs. However, to date, formal statistical tests for gene-gene interaction on untyped SNPs have not been thoroughly addressed. The key concern for gene-gene interaction testing on untyped SNPs located on different chromosomes is that the pair of genes might not be independent and the current generation of imputation methods provides imputed genotypes at the marginal accuracy.

RESULTS

In this study we address this challenge and describe a novel method for testing gene-gene interaction on marginally imputed values of untyped SNPs. We show that our novel Wald-type test statistics for interactions with and without constraints in the interaction parameters follow the asymptotic distributions which are the same as those of the corresponding tests for typed SNPs. Through simulations, we show that the proposed tests properly control type I error and are more powerful than the extension of the classical dosage method to interaction tests. The increase in power results from a proper correction for the uncertainty in imputation through the variance estimator using the jackknife, one of resampling techniques. We apply the method to detect interactions between SNPs on chromosomes 5 and 15 on lung cancer data. The inclusion of the results at the untyped SNPs provides a much more detailed information at the regions of interest.

CONCLUSIONS

As demonstrated by the simulation studies and real data analysis, our approaches outperform the application of traditional dosage method to detection of gene-gene interaction in terms of power while providing control of the type I error.

DISSCO: direct imputation of summary statistics allowing covariates

BACKGROUND

Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates.

METHODS

We analytically show that in the absence of covariates, correlation among association summary statistics is indeed the same as that among the corresponding genotypes, thus serving as a theoretical justification for the recently proposed methods. We continue to prove that in the presence of covariates, correlation among association summary statistics becomes the partial correlation of the corresponding genotypes controlling for covariates. We therefore develop direct imputation of summary statistics allowing covariates (DISSCO).

RESULTS

We consider two real-life scenarios where the correlation and partial correlation likely make practical difference: (i) association studies in admixed populations; (ii) association studies in presence of other confounding covariate(s). Application of DISSCO to real datasets under both scenarios shows at least comparable, if not better, performance compared with existing correlation-based methods, particularly for lower frequency variants. For example, DISSCO can reduce the absolute deviation from the truth by 3.9-15.2% for variants with minor allele frequency <5%.

Harmonizing the classification of age-related macular degeneration in the three-continent AMD consortium

PURPOSE

To describe methods to harmonize the classification of age-related macular degeneration (AMD) phenotypes across four population-based cohort studies: the Beaver Dam Eye Study (BDES), the Blue Mountains Eye Study (BMES), the Los Angeles Latino Eye Study (LALES), and the Rotterdam Study (RS).

METHODS

AMD grading protocols, definitions of categories, and grading forms from each study were compared to determine whether there were systematic differences in AMD severity definitions and lesion categorization among the three grading centers. Each center graded the same set of 60 images using their respective systems to determine presence and severity of AMD lesions. A common 5-step AMD severity scale and definitions of lesion measurement cutpoints and early and late AMD were developed from this exercise.

RESULTS

Applying this severity scale changed the age-sex adjusted prevalence of early AMD from 18.7% to 20.3% in BDES, from 4.7% to 14.4% in BMES, from 14.1% to 15.8% in LALES, and from 7.5% to 17.1% in RS. Age-sex adjusted prevalences of late AMD remained unchanged. Comparison of each center's grades of the 60 images converted to the consortium scale showed that exact agreement of AMD severity among centers varied from 61.0-81.4%, and one-step agreement varied from 84.7-98.3%.

CONCLUSION

Harmonization of AMD classification reduced categorical differences in phenotypic definitions across the studies, resulted in a new 5-step AMD severity scale, and enhanced similarity of AMD prevalence among the four cohorts. Despite harmonization it may still be difficult to remove systematic differences in grading, if present.

Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder

Meta-analyses of bipolar disorder (BD) genome-wide association studies (GWAS) have identified several genome-wide significant signals in European-ancestry samples, but so far account for little of the inherited risk. We performed a meta-analysis of ∼750,000 high-quality genetic markers on a combined sample of ∼14,000 subjects of European and Asian-ancestry (phase I). The most significant findings were further tested in an extended sample of ∼17,700 cases and controls (phase II). The results suggest novel association findings near the genes TRANK1 (LBA1), LMAN2L and PTGFR. In phase I, the most significant single nucleotide polymorphism (SNP), rs9834970 near TRANK1, was significant at the P=2.4 × 10(-11) level, with no heterogeneity. Supportive evidence for prior association findings near ANK3 and a locus on chromosome 3p21.1 was also observed. The phase II results were similar, although the heterogeneity test became significant for several SNPs. On the basis of these results and other established risk loci, we used the method developed by Park et al. to estimate the number, and the effect size distribution, of BD risk loci that could still be found by GWAS methods. We estimate that >63,000 case-control samples would be needed to identify the ∼105 BD risk loci discoverable by GWAS, and that these will together explain <6% of the inherited risk. These results support previous GWAS findings and identify three new candidate genes for BD. Further studies are needed to replicate these findings and may potentially lead to identification of functional variants. Sample size will remain a limiting factor in the discovery of common alleles associated with BD.

Genetic architectures of psychiatric disorders: the emerging picture and its implications

Psychiatric disorders are among the most intractable enigmas in medicine. In the past 5 years, there has been unprecedented progress on the genetics of many of these conditions. In this Review, we discuss the genetics of nine cardinal psychiatric disorders (namely, Alzheimer's disease, attention-deficit hyperactivity disorder, alcohol dependence, anorexia nervosa, autism spectrum disorder, bipolar disorder, major depressive disorder, nicotine dependence and schizophrenia). Empirical approaches have yielded new hypotheses about aetiology and now provide data on the often debated genetic architectures of these conditions, which have implications for future research strategies. Further study using a balanced portfolio of methods to assess multiple forms of genetic variation is likely to yield many additional new findings.

Association of variants in FRAP1 and PDGFRA with corneal curvature in Asian populations from Singapore

Corneal curvature (CC) is a key determinant of major eye diseases, such as keratoconus, myopia and corneal astigmatism. No prior studies have discovered the genes for CC. Here we report the findings from four genome-wide association studies of CC in 10 008 samples from three population groups in Singapore. Our discovery phase surveyed 2867 Chinese and 3072 Malays, allowing us to identify two loci that were associated with CC variation: FRAP1 on chromosome 1p36.2 and PDGFRA on chromosome 4q12. These findings were subsequently replicated in a validation study involving an additional 2953 Asian Indians and a further collection of 1116 Chinese children. The effect sizes of the identified variants were consistent across all four cohorts, with seven single nucleotide polymorphisms (SNPs) in FRAP1 (lead SNP: rs17036350, meta P-value = 4.06 × 10(-13)) and six SNPs in PDGFRA (lead SNP: rs2114039, meta P-value = 1.33 × 10(-9)) attaining genome-wide significance in the SNP-based meta-analysis of the four studies. This is the first genome-wide survey of CC variation and we have identified two implicated loci in three genetically diverse Asian populations, suggesting the presence of common genetic etiology across multiple populations.