Exome sequencing and the genetic basis of complex traits. Nat Genet. 2012;44:623-630. [PMID: 22641211 DOI: 10.1038/ng.2303]

Targeted Sequencing of 10,198 Samples Confirms Abnormalities in Neuronal Activity and Implicates Voltage-Gated Sodium Channels in Schizophrenia Pathogenesis

BACKGROUND

Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms.

METHODS

We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios.

RESULTS

While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10-4) and NMDAR (p = 1.7 × 10-5) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10-4).

CONCLUSIONS

In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes.

Common Disease Is More Complex Than Implied by the Core Gene Omnigenic Model

The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up mechanisms is now overwhelming. In this context, we consider the recent "omnigenic" or "core genes" model. A key assumption of the model is that there is a relatively small number of core genes relevant to any disease. While intuitively appealing, this model may underestimate the biological complexity of common disease, and therefore, the goal to discover core genes should not guide experimental design. We consider other implications of polygenicity, concluding that a focus on patient stratification is needed to achieve the goals of precision medicine.

Benefits and Challenges of Rare Genetic Variation in Alzheimer's Disease

Purpose of Review

It is well established that sporadic Alzheimer's disease (AD) is polygenic with common and rare genetic variation alongside environmental factors contributing to disease. Here, we review our current understanding of the genetic architecture of disease, paying specific attention to rare susceptibility variants, and explore some of the limitations in rare variant detection and analysis.

Recent Findings

Rare variation has been shown to robustly associate with disease. These include potentially damaging and loss of function mutations that are easily modelled in silico, in vitro and in vivo, and represent potentially druggable targets. A number of risk genes, including TREM2, SORL1 and ABCA7 show multiple independent associations suggesting that they may influence disease via multiple mechanisms. With transcriptional regulation, inflammatory response and modification of protein production suggested to be of primary importance.

Summary

We are at the beginning of our journey of rare variant detection in AD. Whole exome sequencing has been the predominant technology of choice. While fruitful, this has introduced a number of challenges with regard to data integration. Ultimately the future of disease-associated rare variant identification lies in whole genome sequencing projects that will allow the testing of the full range of genomic variation.

New insights into the pathogenicity of non-synonymous variants through multi-level analysis

Precise classification of non-synonymous single nucleotide variants (SNVs) is a fundamental goal of clinical genetics. Next-generation sequencing technology is effective for establishing the basis of genetic diseases. However, identification of variants that are causal for genetic diseases remains a challenge. We analyzed human non-synonymous SNVs from a multilevel perspective to characterize pathogenicity. We showed that computational tools, though each having its own strength and weakness, tend to be overly dependent on the degree of conservation. For the mutations at non-degenerate sites, the amino acid sites of pathogenic substitutions show a distinct distribution in the classes of protein domains compared with the sites of benign substitutions. Overlooked disease susceptibility of genes explains in part the failures of computational tools. The more pathogenic sites observed, the more likely the gene is expressed in a high abundance or in a high tissue-specific manner, and have a high node degree of protein-protein interaction. The destroyed functions due to some false-negative mutations may arise because of a reprieve from the epigenetic repressed state which shouldn't happen in multiple biological conditions, instead of the defective protein. Our work adds more to our knowledge of non-synonymous SNVs' pathogenicity, thus will benefit the field of clinical genetics.

Discovery of rare variants implicated in schizophrenia using next-generation sequencing

Schizophrenia is a highly heritable psychiatric disorder that affects 1% of the population. Genome-wide association studies have identified common variants in candidate genes associated with schizophrenia, but the genetics mechanisms of this disorder have not yet been elucidated. The discovery of rare genetic variants that contribute to schizophrenia symptoms promises to help explain the missing heritability of the disease. Next generation sequencing techniques are revolutionizing the field of psychiatric genetics. Various statistical approaches have been developed for rare variant association testing in case-control and family studies. Targeted resequencing, whole exome sequencing and whole genome sequencing combined with these computational tools are used for the discovery of rare genetic variations in schizophrenia. The findings provide useful information for characterizing the rare mutations and elucidating the genetic mechanisms by which the variants cause schizophrenia.

Genetic Studies of Tic Disorders and Tourette Syndrome

Tourette syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead, TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progress in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES), and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.

Whole exome sequencing for the identification of CYP3A7 variants associated with tacrolimus concentrations in kidney transplant patients

The purpose of this study was to identify genotypes associated with dose-adjusted tacrolimus trough concentrations (C₀/D) in kidney transplant recipients using whole-exome sequencing (WES). This study included 147 patients administered tacrolimus, including seventy-five patients in the discovery set and seventy-two patients in the replication set. The patient genomes in the discovery set were sequenced using WES. Also, known tacrolimus pharmacokinetics-related intron variants were genotyped. Tacrolimus C₀/D was log-transformed. Sixteen variants were identified including novel CYP3A7 rs12360 and rs10211 by ANOVA. CYP3A7 rs2257401 was found to be the most significant variant among the periods by ANOVA. Seven variants including CYP3A7 rs2257401, rs12360, and rs10211 were analyzed by SNaPshot in the replication set and the effects on tacrolimus C₀/D were verified. A linear mixed model (LMM) was further performed to account for the effects of the variants and clinical factors. The combined set LMM showed that only CYP3A7 rs2257401 was associated with tacrolimus C₀/D after adjusting for patient age, albumin, and creatinine. The CYP3A7 rs2257401 genotype variant showed a significant difference on the tacrolimus C₀/D in those expressing CYP3A5, showing its own effect. The results suggest that CYP3A7 rs2257401 may serve as a significant genetic marker for tacrolimus pharmacokinetics in kidney transplantation.

Genetic predisposition to necrotizing enterocolitis in premature infants: Current knowledge, challenges, and future directions

The role of genetics in the pathogenesis of necrotizing enterocolitis (NEC) was initially informed by epidemiological data indicating differences in prevalence among different ethnic groups as well as concordance in twins. These early observations, together with major advances in genomic research, paved the way for studies that begin to reveal the contribution of genetics to NEC. Using the candidate gene or pathway approach, several potential pathogenic variants for NEC in premature infants have already been identified. More recently, genome-wide association studies and exome-sequencing based studies for NEC have been reported. These advances, however, are tempered by the lack of adequately powered replication cohorts to validate the accuracy of these discoveries. Despite many challenges, genetic research in NEC is expected to increase, providing new insights into its pathogenesis and bringing the promise of personalized care closer to reality. In this review we provide a summary of genetic studies in NEC along with defining the challenges and possible future approaches.

Detecting Rare Mutations with Heterogeneous Effects Using a Family-Based Genetic Random Field Method

The genetic etiology of many complex diseases is highly heterogeneous. A complex disease can be caused by multiple mutations within the same gene or mutations in multiple genes at various genomic loci. Although these disease-susceptibility mutations can be collectively common in the population, they are often individually rare or even private to certain families. Family-based studies are powerful for detecting rare variants enriched in families, which is an important feature for sequencing studies due to the heterogeneous nature of rare variants. In addition, family designs can provide robust protection against population stratification. Nevertheless, statistical methods for analyzing family-based sequencing data are underdeveloped, especially those accounting for heterogeneous etiology of complex diseases. In this article, we introduce a random field framework for detecting gene-phenotype associations in family-based sequencing studies, referred to as family-based genetic random field (FGRF). Similar to existing family-based association tests, FGRF could utilize within-family and between-family information separately or jointly to test an association. We demonstrate that FGRF has comparable statistical power with existing methods when there is no genetic heterogeneity, but can improve statistical power when there is genetic heterogeneity across families. The proposed method also shares the same advantages with the conventional family-based association tests (e.g., being robust to population stratification). Finally, we applied the proposed method to a sequencing data from the Minnesota Twin Family Study, and revealed several genes, including SAMD14, potentially associated with alcohol dependence.

Systematic discovery of germline cancer predisposition genes through the identification of somatic second hits

The genetic causes of cancer include both somatic mutations and inherited germline variants. Large-scale tumor sequencing has revolutionized the identification of somatic driver alterations but has had limited impact on the identification of cancer predisposition genes (CPGs). Here we present a statistical method, ALFRED, that tests Knudson's two-hit hypothesis to systematically identify CPGs from cancer genome data. Applied to ~10,000 tumor exomes the approach identifies known and putative CPGs - including the chromatin modifier NSD1 - that contribute to cancer through a combination of rare germline variants and somatic loss-of-heterozygosity (LOH). Rare germline variants in these genes contribute substantially to cancer risk, including to ~14% of ovarian carcinomas, ~7% of breast tumors, ~4% of uterine corpus endometrial carcinomas, and to a median of 2% of tumors across 17 cancer types.

A regulatory mutant on TRIM26 conferring the risk of nasopharyngeal carcinoma by inducing low immune response

The major histocompatibility complex (MHC) is most closely associated with nasopharyngeal carcinoma (NPC), but the complexity of its genome structure has proven challenging for the discovery of causal MHC loci or genes. We conducted a targeted MHC sequencing in 40 Cantonese NPC patients followed by a two‐stage replication in 1065 NPC cases and 2137 controls of Southern Chinese descendent. Quantitative RT‐PCR analysis (qRT‐PCR) was used to detect gene expression status in 108 NPC and 43 noncancerous nasopharyngeal (NP) samples. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) were used to assess the transcription factor binding site. We discovered that a novel SNP rs117565607_A at TRIM26 displayed the strongest association (OR = 1.909, Pcombined = 2.750 × 10⁻¹⁹). We also observed that TRIM26 was significantly downregulated in NPC tissue samples with genotype AA/AT than TT. Immunohistochemistry (IHC) test also found the TRIM26 protein expression in NPC tissue samples with the genotype AA/AT was lower than TT. According to computational prediction, rs117565607 locus was a binding site for the transcription factor Yin Yang 1 (YY1). We observed that the luciferase activity of YY1 which is binding to the A allele of rs117565607 was suppressed. ChIP data showed that YY1 was binding with T not A allele. Significance analysis of microarray suggested that TRIM26 downregulation was related to low immune response in NPC. We have identified a novel gene TRIM26 and a novel SNP rs117565607_A associated with NPC risk by regulating transcriptional process and established a new functional link between TRIM26 downregulation and low immune response in NPC.

Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacross P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacross P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.

High-depth whole genome sequencing of an Ashkenazi Jewish reference panel: enhancing sensitivity, accuracy, and imputation

While increasingly large reference panels for genome-wide imputation have been recently made available, the degree to which imputation accuracy can be enhanced by population-specific reference panels remains an open question. Here, we sequenced at full-depth (≥ 30×), across two platforms (Illumina X Ten and Complete Genomics, Inc.), a moderately large (n = 738) cohort of samples drawn from the Ashkenazi Jewish population. We developed a series of quality control steps to optimize sensitivity, specificity, and comprehensiveness of variant calls in the reference panel, and then tested the accuracy of imputation against target cohorts drawn from the same population. Quality control (QC) thresholds for the Illumina X Ten platform were identified that permitted highly accurate calling of single nucleotide variants across 94% of the genome. QC procedures also identified numerous regions that are poorly mapped using current reference or alternate assemblies. After stringent QC, the population-specific reference panel produced more accurate and comprehensive imputation results relative to publicly available, large cosmopolitan reference panels, especially in the range of rare variants that may be most critical to further progress in mapping of complex phenotypes. The population-specific reference panel also permitted enhanced filtering of clinically irrelevant variants from personal genomes.

Whole-Exome Sequencing in Age-Related Macular Degeneration Identifies Rare Variants in COL8A1, a Component of Bruch's Membrane

PURPOSE

Genome-wide association studies and targeted sequencing studies of candidate genes have identified common and rare variants that are associated with age-related macular degeneration (AMD). Whole-exome sequencing (WES) studies allow a more comprehensive analysis of rare coding variants across all genes of the genome and will contribute to a better understanding of the underlying disease mechanisms. To date, the number of WES studies in AMD case-control cohorts remains scarce and sample sizes are limited. To scrutinize the role of rare protein-altering variants in AMD cause, we performed the largest WES study in AMD to date in a large European cohort consisting of 1125 AMD patients and 1361 control participants.

DESIGN

Genome-wide case-control association study of WES data.

PARTICIPANTS

One thousand one hundred twenty-five AMD patients and 1361 control participants.

METHODS

A single variant association test of WES data was performed to detect variants that are associated individually with AMD. The cumulative effect of multiple rare variants with 1 gene was analyzed using a gene-based CMC burden test. Immunohistochemistry was performed to determine the localization of the Col8a1 protein in mouse eyes.

MAIN OUTCOME MEASURES

Genetic variants associated with AMD.

RESULTS

We detected significantly more rare protein-altering variants in the COL8A1 gene in patients (22/2250 alleles [1.0%]) than in control participants (11/2722 alleles [0.4%]; P = 7.07×10^-5). The association of rare variants in the COL8A1 gene is independent of the common intergenic variant (rs140647181) near the COL8A1 gene previously associated with AMD. We demonstrated that the Col8a1 protein localizes at Bruch's membrane.

CONCLUSIONS

This study supported a role for protein-altering variants in the COL8A1 gene in AMD pathogenesis. We demonstrated the presence of Col8a1 in Bruch's membrane, further supporting the role of COL8A1 variants in AMD pathogenesis. Protein-altering variants in COL8A1 may alter the integrity of Bruch's membrane, contributing to the accumulation of drusen and the development of AMD.

IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis

Insertions and deletions (indels) have been implicated in dozens of human diseases through the radical alteration of gene function by short frameshift indels as well as long indels. However, the accurate detection of these indels from next-generation sequencing data is still challenging. This is particularly true for intermediate-size indels (≥50 bp), due to the short DNA sequencing reads. Here, we developed a new method that predicts intermediate-size indels using BWA soft-clipped fragments (unmatched fragments in partially mapped reads) and unmapped reads. We report the performance comparison of our method, GATK, PINDEL and ScanIndel, using whole exome sequencing data from the same samples. False positive and false negative counts were determined through Sanger sequencing of all predicted indels across these four methods. The harmonic mean of the recall and precision, F-measure, was used to measure the performance of each method. Our method achieved the highest F-measure of 0.84 in one sample, compared to 0.56 for GATK, 0.52 for PINDEL and 0.46 for ScanIndel. Similar results were obtained in additional samples, demonstrating that our method was superior to the other methods for detecting intermediate-size indels. We believe that this methodology will contribute to the discovery of intermediate-size indels associated with human disease.

De novo mutations in GRIN1 cause extensive bilateral polymicrogyria

Polymicrogyria is a malformation of cortical development. The aetiology of polymicrogyria remains poorly understood. Using whole-exome sequencing we found de novo heterozygous missense GRIN1 mutations in 2 of 57 parent-offspring trios with polymicrogyria. We found nine further de novo missense GRIN1 mutations in additional cortical malformation patients. Shared features in the patients were extensive bilateral polymicrogyria associated with severe developmental delay, postnatal microcephaly, cortical visual impairment and intractable epilepsy. GRIN1 encodes GluN1, the essential subunit of the N-methyl-d-aspartate receptor. The polymicrogyria-associated GRIN1 mutations tended to cluster in the S2 region (part of the ligand-binding domain of GluN1) or the adjacent M3 helix. These regions are rarely mutated in the normal population or in GRIN1 patients without polymicrogyria. Using two-electrode and whole-cell voltage-clamp analysis, we showed that the polymicrogyria-associated GRIN1 mutations significantly alter the in vitro activity of the receptor. Three of the mutations increased agonist potency while one reduced proton inhibition of the receptor. These results are striking because previous GRIN1 mutations have generally caused loss of function, and because N-methyl-d-aspartate receptor agonists have been used for many years to generate animal models of polymicrogyria. Overall, our results expand the phenotypic spectrum associated with GRIN1 mutations and highlight the important role of N-methyl-d-aspartate receptor signalling in the pathogenesis of polymicrogyria.

Whole-exome sequencing and gene-based rare variant association tests suggest that PLA2G4E might be a risk gene for panic disorder

Panic disorder (PD) is characterized by recurrent and unexpected panic attacks, subsequent anticipatory anxiety, and phobic avoidance. Recent epidemiological and genetic studies have revealed that genetic factors contribute to the pathogenesis of PD. We performed whole-exome sequencing on one Japanese family, including multiple patients with panic disorder, which identified seven rare protein-altering variants. We then screened these genes in a Japanese PD case-control group (384 sporadic PD patients and 571 controls), resulting in the detection of three novel single nucleotide variants as potential candidates for PD (chr15: 42631993, T>C in GANC; chr15: 42342861, G>T in PLA2G4E; chr20: 3641457, G>C in GFRA4). Statistical analyses of these three genes showed that PLA2G4E yielded the lowest p value in gene-based rare variant association tests by Efficient and Parallelizable Association Container Toolbox algorithms; however, the p value did not reach the significance threshold in the Japanese. Likewise, in a German case-control study (96 sporadic PD patients and 96 controls), PLA2G4E showed the lowest p value but again did not reach the significance threshold. In conclusion, we failed to find any significant variants or genes responsible for the development of PD. Nonetheless, our results still leave open the possibility that rare protein-altering variants in PLA2G4E contribute to the risk of PD, considering the function of this gene.

Whole-Exome Sequencing in Adults With Chronic Kidney Disease: A Pilot Study

BACKGROUND

The utility of whole-exome sequencing (WES) for the diagnosis and management of adult-onset constitutional disorders has not been adequately studied. Genetic diagnostics may be advantageous in adults with chronic kidney disease (CKD), in whom the cause of kidney failure often remains unknown.

OBJECTIVE

To study the diagnostic utility of WES in a selected referral population of adults with CKD.

DESIGN

Observational cohort.

SETTING

A major academic medical center.

PATIENTS

92 adults with CKD of unknown cause or familial nephropathy or hypertension.

MEASUREMENTS

The diagnostic yield of WES and its potential effect on clinical management.

RESULTS

Whole-exome sequencing provided a diagnosis in 22 of 92 patients (24%), including 9 probands with CKD of unknown cause and encompassing 13 distinct genetic disorders. Among these, loss-of-function mutations were identified in PARN in 2 probands with tubulointerstitial fibrosis. PARN mutations have been implicated in a short telomere syndrome characterized by lung, bone marrow, and liver fibrosis; these findings extend the phenotype of PARN mutations to renal fibrosis. In addition, review of the American College of Medical Genetics actionable genes identified a pathogenic BRCA2 mutation in a proband who was diagnosed with breast cancer on follow-up. The results affected clinical management in most identified cases, including initiation of targeted surveillance, familial screening to guide donor selection for transplantation, and changes in therapy.

LIMITATION

The small sample size and recruitment at a tertiary care academic center limit generalizability of findings among the broader CKD population.

CONCLUSION

Whole-exome sequencing identified diagnostic mutations in a substantial number of adults with CKD of many causes. Further study of the utility of WES in the evaluation and care of patients with CKD in additional settings is warranted.

PRIMARY FUNDING SOURCE

New York State Empire Clinical Research Investigator Program, Renal Research Institute, and National Human Genome Research Institute of the National Institutes of Health.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Integrated rare variant-based risk gene prioritization in disease case-control sequencing studies

Rare variants of major effect play an important role in human complex diseases and can be discovered by sequencing-based genome-wide association studies. Here, we introduce an integrated approach that combines the rare variant association test with gene network and phenotype information to identify risk genes implicated by rare variants for human complex diseases. Our data integration method follows a 'discovery-driven' strategy without relying on prior knowledge about the disease and thus maintains the unbiased character of genome-wide association studies. Simulations reveal that our method can outperform a widely-used rare variant association test method by 2 to 3 times. In a case study of a small disease cohort, we uncovered putative risk genes and the corresponding rare variants that may act as genetic modifiers of congenital heart disease in 22q11.2 deletion syndrome patients. These variants were missed by a conventional approach that relied on the rare variant association test alone.

Case-control sequencing studies are a promising design to uncover risk genes of human complex diseases implicated by rare variants. The recent development of different types of rare variant association tests has improved the statistical power to identify disease genes that harbor risk rare variants. However, none of the recent sequencing-based genome-wide association studies identified robust disease association of rare variants or genes based on them. Due to limited sample sizes that can be feasibly achieved in real applications, current rare variant association tests can only generate marginal association signals for most risk genes. Here we proposed an integrated method that combined association signals with orthogonal biological evidence to uncover risk genes in sequencing studies. Designed to address the lack-of-power issue, our method was shown to effectively uncover risk genes with marginal association signals in data simulation. Indeed, in a real application demonstrated in our case study our method disclosed important risk genes of congenital heart disease in 22q11.2 deletion syndrome that were missed by the previous study.

Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform

Background

Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait).

Results

The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD.

Conclusions

While GS models’ prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.

Peripheral Arterial Disease Genetics: Progress to Date and Challenges Ahead

PURPOSE OF REVIEW

In this paper, we review the progress made thus far in research related to the genetics of peripheral arterial disease (PAD) by detailing efforts to date in heritability, linkage analyses, and candidate gene studies. We further summarize more contemporary genome-wide association studies (GWAS) and epigenetic studies of PAD. Finally, we review current challenges and future avenues of advanced research in PAD genetics including whole genome sequencing studies.

RECENT FINDINGS

Studies have estimated the heritability of PAD to be moderate, though the contribution to this heritability that is independent of traditional cardiovascular risk factors remains unclear. Recent efforts have identified SNPs associated with PAD in GWAS analyses, but these have yet to be replicated in independent studies. Much remains to be discovered in the field of PAD genetics. An improved understanding of the genetic foundation for PAD will allow for earlier diagnosis of disease and a more complete pathophysiological understanding of the mechanisms of the disease leading to novel therapeutic interventions. Future avenues for success will likely arise from very large-scale GWAS, whole genome sequencing, and epigenetic studies involving very well-characterized cohorts.

Progress in Genetic Studies of Tourette's Syndrome

Tourette's Syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progresses in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES) and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.

Genetic Risk Factors for Ischemic and Hemorrhagic Stroke

Understanding the genetic risk factors for stroke is an essential step to decipher the underlying mechanisms, facilitate the identification of novel therapeutic targets, and optimize the design of prevention strategies. A very small proportion of strokes are attributable to monogenic conditions, the vast majority being multifactorial, with multiple genetic and environmental risk factors of small effect size. Genome-wide association studies and large international consortia have been instrumental in finding genetic risk factors for stroke. While initial studies identified risk loci for specific stroke subtypes, more recent studies also revealed loci associated with all stroke and all ischemic stroke. Risk loci for ischemic stroke and its subtypes have been implicated in atrial fibrillation (PITX2 and ZFHX3), coronary artery disease (ABO, chr9p21, HDAC9, and ALDH2), blood pressure (ALDH2 and HDAC9), pericyte and smooth muscle cell development (FOXF2), coagulation (HABP2), carotid plaque formation (MMP12), and neuro-inflammation (TSPAN2). For hemorrhagic stroke, two loci (APOE and PMF1) have been identified.

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

BACKGROUND

Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure.

METHODS

We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008-11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003-13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken.

FINDINGS

Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10-10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10-8DHFR p=8·37 × 10-7 MTRNR2L2 p=2·15 × 10-9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10-4DHFR p=8·45 × 10-4MTRNR2L2 p=1·20 × 10-3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10-8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16-0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06-0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset.

INTERPRETATION

The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation.

FUNDING

The European Commission FP7 NeurOmics project; CHDI Foundation; the Medical Research Council UK; the Brain Research Trust; and the Guarantors of Brain.

CAGI4 Crohn's exome challenge: Marker SNP versus exome variant models for assigning risk of Crohn disease

Understanding the basis of complex trait disease is a fundamental problem in human genetics. The CAGI Crohn's Exome challenges are providing insight into the adequacy of current disease models by requiring participants to identify which of a set of individuals has been diagnosed with the disease, given exome data. For the CAGI4 round, we developed a method that used the genotypes from exome sequencing data only to impute the status of genome wide association studies marker SNPs. We then used the imputed genotypes as input to several machine learning methods that had been trained to predict disease status from marker SNP information. We achieved the best performance using Naïve Bayes and with a consensus machine learning method, obtaining an area under the curve of 0.72, larger than other methods used in CAGI4. We also developed a model that incorporated the contribution from rare missense variants in the exome data, but this performed less well. Future progress is expected to come from the use of whole genome data rather than exomes.

TEX15: A DNA repair gene associated with prostate cancer risk in Han Chinese

BACKGROUND

Both common and rare genetic variants may contribute to risk of developing prostate cancer. Genome-wide association studies (GWASs) have identified ∼100 independent, common variants associated with prostate cancer risk. However, little is known about the association of rare variants (minor allele frequency [MAF] <1%) in the genome with prostate cancer risk.

METHODS

A two-stage study was used to test the association of rare, deleterious coding variants, annotated using predictive algorithms, with prostate cancer risk in Chinese men. Predicted rare, deleterious coding variants in the Illumina HumanExome-12 v1.1 beadchip were first evaluated in 1343 prostate cancer patients and 1008 controls. Significant variants were then validated in an additional 1816 prostate cancer patients and 1549 controls.

RESULTS

In the discovery stage, 14 predicted rare, deleterious coding variants were significantly associated with prostate cancer risk (P < 0.01). In the confirmation stage, Q1631H in TEX15 (rs142485241), a DNA repair gene, was significantly associated with prostate cancer risk (P = 0.0069). The estimated odds ratio (OR) of the variant in the combined analysis was 3.24 (95% Confidence Interval 1.85-6.06), P = 8.81 × 10^-5 . Additionally, rs28756990 (V741F) at MLH3 (P = 0.06) and rs2961144 (I126V) at OR2A5 (P = 0.065) were marginally associated with prostate cancer risk in the replication stage.

CONCLUSIONS

Our study provided preliminary evidence that the rare variant Q1631H in DNA repair gene TEX15 is associated with prostate cancer risk. This finding complements known common prostate cancer risk-associated variants and suggests the possible role of DNA repair genes in prostate cancer development.

MIP-MAP: High-Throughput Mapping of Caenorhabditis elegans Temperature-Sensitive Mutants via Molecular Inversion Probes

Mutants remain a powerful means for dissecting gene function in model organisms such as Caenorhabditis elegans. Massively parallel sequencing has simplified the detection of variants after mutagenesis but determining precisely which change is responsible for phenotypic perturbation remains a key step. Genetic mapping paradigms in C. elegans rely on bulk segregant populations produced by crosses with the problematic Hawaiian wild isolate and an excess of redundant information from whole-genome sequencing (WGS). To increase the repertoire of available mutants and to simplify identification of the causal change, we performed WGS on 173 temperature-sensitive (TS) lethal mutants and devised a novel mapping method. The mapping method uses molecular inversion probes (MIP-MAP) in a targeted sequencing approach to genetic mapping, and replaces the Hawaiian strain with a Million Mutation Project strain with high genomic and phenotypic similarity to the laboratory wild-type strain N2. We validated MIP-MAP on a subset of the TS mutants using a competitive selection approach to produce TS candidate mapping intervals with a mean size < 3 Mb. MIP-MAP successfully uses a non-Hawaiian mapping strain and multiplexed libraries are sequenced at a fraction of the cost of WGS mapping approaches. Our mapping results suggest that the collection of TS mutants contains a diverse library of TS alleles for genes essential to development and reproduction. MIP-MAP is a robust method to genetically map mutations in both viable and essential genes and should be adaptable to other organisms. It may also simplify tracking of individual genotypes within population mixtures.

Critical Genomic Networks and Vasoreactive Variants in Idiopathic Pulmonary Arterial Hypertension

RATIONALE

Idiopathic pulmonary arterial hypertension (IPAH) is usually without an identified genetic cause, despite clinical and molecular similarity to bone morphogenetic protein receptor type 2 mutation-associated heritable pulmonary arterial hypertension (PAH). There is phenotypic heterogeneity in IPAH, with a minority of patients showing long-term improvement with calcium channel-blocker therapy.

OBJECTIVES

We sought to identify gene variants (GVs) underlying IPAH and determine whether GVs differ in vasodilator-responsive IPAH (VR-PAH) versus vasodilator-nonresponsive IPAH (VN-PAH).

METHODS

We performed whole-exome sequencing (WES) on 36 patients with IPAH: 17 with VR-PAH and 19 with VN-PAH. Wnt pathway differences were explored in human lung fibroblasts.

MEASUREMENTS AND MAIN RESULTS

We identified 1,369 genes with 1,580 variants unique to IPAH. We used a gene ontology approach to analyze variants and identified overrepresentation of several pathways, including cytoskeletal function and ion binding. By mapping WES data to prior genome-wide association study data, Wnt pathway genes were highlighted. Using the connectivity map to define genetic differences between VR-PAH and VN-PAH, we found enrichment in vascular smooth muscle cell contraction pathways and greater genetic variation in VR-PAH versus VN-PAH. Using human lung fibroblasts, we found increased stimulated Wnt activity in IPAH versus controls.

CONCLUSIONS

A pathway-based analysis of WES data in IPAH demonstrated multiple rare GVs that converge on key biological pathways, such as cytoskeletal function and Wnt signaling pathway. Vascular smooth muscle contraction-related genes were enriched in VR-PAH, suggesting a potentially different genetic predisposition for VR-PAH. This pathway-based approach may be applied to next-generation sequencing data in other diseases to uncover the contribution of unexpected or multiple GVs to a phenotype.

Rare RNF213 variants in the C-terminal region encompassing the RING-finger domain are associated with moyamoya angiopathy in Caucasians

Moyamoya angiopathy (MMA) is a cerebral angiopathy affecting the terminal part of internal carotid arteries. Its prevalence is 10 times higher in Japan and Korea than in Europe. In East Asian countries, moyamoya is strongly associated to the R4810K variant in the RNF213 gene that encodes for a protein containing a RING-finger and two AAA+ domains. This variant has never been detected in Caucasian MMA patients, but several rare RNF213 variants have been reported in Caucasian cases. Using a collapsing test based on exome data from 68 European MMA probands and 573 ethnically matched controls, we showed a significant association between rare missense RNF213 variants and MMA in European patients (odds ratio (OR)=2.24, 95% confidence interval (CI)=(1.19-4.11), P=0.01). Variants specific to cases had higher pathogenicity predictive scores (median of 24.2 in cases versus 9.4 in controls, P=0.029) and preferentially clustered in a C-terminal hotspot encompassing the RING-finger domain of RNF213 (P<10^-3). This association was even stronger when restricting the analysis to childhood-onset and familial cases (OR=4.54, 95% CI=(1.80-11.34), P=1.1 × 10^-3). All clinically affected relatives who were genotyped were carriers. However, the need for additional factors to develop MMA is strongly suggested by the fact that only 25% of mutation carrier relatives were clinically affected.

Exome Analysis of Rare and Common Variants within the NOD Signaling Pathway

Pediatric inflammatory bowel disease (pIBD) is a chronic heterogeneous disorder. This study looks at the burden of common and rare coding mutations within 41 genes comprising the NOD signaling pathway in pIBD patients. 136 pIBD and 106 control samples underwent whole-exome sequencing. We compared the burden of common, rare and private mutation between these two groups using the SKAT-O test. An independent replication cohort of 33 cases and 111 controls was used to validate significant findings. We observed variation in 40 of 41 genes comprising the NOD signaling pathway. Four genes were significantly associated with disease in the discovery cohort (BIRC2 p = 0.004, NFKB1 p =  0.005, NOD2 p = 0.029 and SUGT1 p = 0.047). Statistical significance was replicated for BIRC2 (p = 0.041) and NOD2 (p = 0.045) in an independent validation cohort. A gene based test on the combined discovery and replication cohort confirmed association for BIRC2 (p = 0.030). We successfully applied burden of mutation testing that jointly assesses common and rare variants, identifying two previously implicated genes (NFKB1 and NOD2) and confirmed a possible role in disease risk in a previously unreported gene (BIRC2). The identification of this novel gene provides a wider role for the inhibitor of apoptosis gene family in IBD pathogenesis.

Estimating the selective effects of heterozygous protein-truncating variants from human exome data

The dispensability of individual genes for viability has interested generations of geneticists. For some genes it is essential to maintain two functional chromosomal copies, while others may tolerate the loss of one or both copies. Exome sequence data from 60,706 individuals provide sufficient observations of rare protein truncating variants (PTVs) to make genome-wide estimates of selection against heterozygous loss of gene function. The cumulative frequency of rare deleterious PTVs is primarily determined by the balance between incoming mutations and purifying selection rather than genetic drift. This enables the estimation of the genome-wide distribution of selection coefficients for heterozygous PTVs and corresponding Bayesian estimates for individual genes. The strength of selection can discriminate the severity, age of onset, and mode of inheritance in Mendelian exome sequencing cases. We find that genes under the strongest selection are enriched in embryonic lethal mouse knockouts, putatively cell-essential genes, Mendelian disease genes, and regulators of transcription. Screening by essentiality, we find a large set of genes under strong selection that likely have critical function but have not yet been extensively annotated in published literature.

Rare DNA variants in the brain-derived neurotrophic factor gene increase risk for attention-deficit hyperactivity disorder: a next-generation sequencing study

Attention-deficit hyperactivity disorder (ADHD) is a prevalent and highly heritable disorder of childhood with negative lifetime outcomes. Although candidate gene and genome-wide association studies have identified promising common variant signals, these explain only a fraction of the heritability of ADHD. The observation that rare structural variants confer substantial risk to psychiatric disorders suggests that rare variants might explain a portion of the missing heritability for ADHD. Here we believe we performed the first large-scale next-generation targeted sequencing study of ADHD in 152 child and adolescent cases and 188 controls across an a priori set of 117 genes. A multi-marker gene-level analysis of rare (<1% frequency) single-nucleotide variants (SNVs) revealed that the gene encoding brain-derived neurotrophic factor (BDNF) was associated with ADHD at Bonferroni corrected levels. Sanger sequencing confirmed the existence of all novel rare BDNF variants. Our results implicate BDNF as a genetic risk factor for ADHD, potentially by virtue of its critical role in neurodevelopment and synaptic plasticity.

Whole-exome sequencing in individuals with multiple cardiovascular risk factors and normal coronary arteries

OBJECTIVES

Most studies on the genes involved in coronary artery disease (CAD) targeted individuals with angiographically or clinically proven CAD. Focusing on high-risk individuals with normal coronary arteries (NCA) may offer novel insights into the pathogenesis of CAD. We aimed to identify genes putatively protective for development of CAD.

METHODS

Pooled whole-exome sequencing (WES) was performed on 17 patients with multiple cardiovascular risk factors and NCA and on 17 controls with multivessel CAD. Rare NCA-unique sequence variants were subsequently individually validated using the Fluidigm platform in 100 additional CAD controls and 100 general population controls.

RESULTS

In total, 555 100 variants were detected in at least one WES pool in the study group and in none of the control WES pools. For second phase validation, we focused on rare, nonsynonymous variants, resulting in a total of 144 variants in 40 genes, of which 96 were selected for subsequent genotyping. Validation phase genotyping resulted in 19 variants in 16 genes that were found in the NCA group and in none of the CAD controls. The SPTBN5, NID2, and ADAMTSL4 genes harbored sequence variants in more than one CAD-protected patient and none of the 117 CAD controls.

CONCLUSION

Applying WES technology and focusing on individuals seemingly protected from developing CAD successfully identified 19 variants that may offer protection from CAD by undetermined mechanisms. Studying the genetics of high-risk individuals apparently protected from CAD may provide novel insights into the pathogenesis of CAD.

Whole-exome sequencing of 228 patients with sporadic Parkinson's disease

Parkinson's disease (PD) is the most common neurodegenerative movement disorder, affecting 1% of the population over 65 years characterized clinically by both motor and non-motor symptoms accompanied by the preferential loss of dopamine neurons in the substantia nigra pars compacta. Here, we sequenced the exomes of 244 Parkinson's patients selected from the Oxford Parkinson's Disease Centre Discovery Cohort and, after quality control, 228 exomes were available for analyses. The PD patient exomes were compared to 884 control exomes selected from the UK10K datasets. No single non-synonymous (NS) single nucleotide variant (SNV) nor any gene carrying a higher burden of NS SNVs was significantly associated with PD status after multiple-testing correction. However, significant enrichments of genes whose proteins have roles in the extracellular matrix were amongst the top 300 genes with the most significantly associated NS SNVs, while regions associated with PD by a recent Genome Wide Association (GWA) study were enriched in genes containing PD-associated NS SNVs. By examining genes within GWA regions possessing rare PD-associated SNVs, we identified RAD51B. The protein-product of RAD51B interacts with that of its paralogue RAD51, which is associated with congenital mirror movements phenotypes, a phenotype also comorbid with PD.

From Genomes to GENE-omes: Exome Sequencing Concept and Applications in Crop Improvement

Exome sequencing represents targeted capture and sequencing of 1-2% of 'high-value genomic regions' (subset of the genome) which are enriched for functional variants and harbors low level of repetitive regions. We discuss here an overview of exome sequencing, ways to approach plant exomes, and advantages and applicability of this powerful approach in deciphering functional regions of genomes. Though initially this approach was developed as an alternative to whole genome sequencing (WGS), but the multitude of benefits conferred by sequence capture via hybridization approaches created a niche for itself to solve many of biological riddles, particularly for resolving phylogenetic distances. The technique has also proved to be successful in understanding the basis of natural and induced molecular variation, marker development and developing genomic resources for complex, wild and non-model species, which are still intractable for WGS efforts. Thus, with profound applications of this powerful sequencing strategy, near future is expected to witness a collective expansion of both techniques, i.e., sequence capture via hybridization for evolutionary and ecological research and WGS approaches for its universal accessibility.

Global inference of disease-causing single nucleotide variants from exome sequencing data

Background

Whole exome sequencing (WES) has recently emerged as an effective approach for identifying genetic variants underlying human diseases. However, considerable time and labour is needed for careful investigation of candidate variants. Although filtration based on population frequencies and functional prediction scores could effectively remove common and neutral variants, hundreds or even thousands of rare deleterious variants still remain. In addition, current WES platforms also provide variant information in flanking noncoding regions, such as promoters, introns and splice sites. Despite of being recognized to harbour causal variants, these regions are usually ignored by current analysis pipelines.

Results

We present a novel computational method, called Glints, to overcome the above limitations. Glints is capable of identifying disease-causing SNVs in both coding and flanking noncoding regions from exome sequencing data. The principle behind Glints is that disease-causing variants should manifest their effect at both variant and gene levels. Specifically, Glints integrates 14 types of functional scores, including predictions for both coding and noncoding variants, and 9 types of association scores, which help identifying disease relevant genes. We conducted a large-scale simulation studies based on 1000 Genomes Project data and demonstrated the effectiveness of our method in both coding and flanking noncoding regions. We also applied Glints in two real exome sequencing and demonstrated its effectiveness for uncovering disease-causing SNVs. Both standalone software and web server are available at our website http://bioinfo.au.tsinghua.edu.cn/jianglab/glints.

Conclusions

Glints is effective for uncovering disease-causing SNVs in coding and flanking noncoding regions, which is supported by both simulation and real case studies. Glints is expected to be a useful tool for human genetics research based on exome sequencing data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1325-x) contains supplementary material, which is available to authorized users.

Resetting the bar: Statistical significance in whole-genome sequencing-based association studies of global populations

Genome-wide association studies (GWAS) of common disease have been hugely successful in implicating loci that modify disease risk. The bulk of these associations have proven robust and reproducible, in part due to community adoption of statistical criteria for claiming significant genotype-phenotype associations. As the cost of sequencing continues to drop, assembling large samples in global populations is becoming increasingly feasible. Sequencing studies interrogate not only common variants, as was true for genotyping-based GWAS, but variation across the full allele frequency spectrum, yielding many more (independent) statistical tests. We sought to empirically determine genome-wide significance thresholds for various analysis scenarios. Using whole-genome sequence data, we simulated sequencing-based disease studies of varying sample size and ancestry. We determined that future sequencing efforts in >2,000 samples of European, Asian, or admixed ancestry should set genome-wide significance at approximately P = 5 × 10^-9 , and studies of African samples should apply a more stringent genome-wide significance threshold of P = 1 × 10^-9 . Adoption of a revised multiple test correction will be crucial in avoiding irreproducible claims of association.

Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

BACKGROUND

Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other "-omics" and interaction data.

SCOPE OF REVIEW

1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other "-omics" and interaction data.

MAJOR CONCLUSIONS

To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other "-omics" data and interaction can better explain gene functions.

GENERAL SIGNIFICANCE

Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.

Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis

BACKGROUND

The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease. We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent coronary heart disease.

METHODS AND RESULTS

We studied a total of 25 109 European ancestry and African ancestry participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52 869 participants with common carotid intima-media thickness measured by ultrasonography within the CHARGE Consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology). Participants were genotyped for 247 870 DNA sequence variants (231 539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and carotid intima-media thickness. APOB p.Arg3527Gln was associated with 4-fold excess CAC (P=3×10^-10). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC (P=1×10^-12) and 1.4% reduced carotid intima-media thickness (P=4×10^-14) in carriers compared with noncarriers. In secondary analyses conditioning on low-density lipoprotein cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for coronary heart disease (odds ratio 0.77; P=1×10^-11).

CONCLUSIONS

Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities, as well as clinical coronary heart disease.

Low-, high-coverage, and two-stage DNA sequencing in the design of the genetic association study

Next-generation sequencing-based genetic association study (GAS) is a powerful tool to identify candidate disease variants and genomic regions. Although low-coverage sequencing offers low cost but inadequacy in calling rare variants, high coverage is able to detect essentially every variant but at a high cost. Two-stage sequencing may be an economical way to conduct GAS without losing power. In two-stage sequencing, an affordable number of samples are sequenced at high coverage as the reference panel, then to impute in a larger sample is sequenced at low coverage. As unit sequencing costs continue to decrease, investigators can now conduct GAS with more flexible sequencing depths. Here, we systematically evaluate the effect of the read depth and sample size on the variant discovery power and association power for study designs using low-coverage, high-coverage, and two-stage sequencing. We consider 12 low-coverage, 12 high-coverage, and 51 two-stage design scenarios with the read depth varying from 0.5× to 80×. With state-of-the-art simulation and analysis packages and in-house scripts, we simulate the complete study process from DNA sequencing to SNP (single nucleotide polymorphism) calling and association testing. Our results show that with appropriate allocation of sequencing effort, two-stage sequencing is an effective approach for conducting GAS. We provide practical guidelines for investigators to plan the optimum sequencing-based GAS including two-stage sequencing design given their specific constraints of sequencing investment.

Guidelines for Large-Scale Sequence-Based Complex Trait Association Studies: Lessons Learned from the NHLBI Exome Sequencing Project

Massively parallel whole-genome sequencing (WGS) data have ushered in a new era in human genetics. These data are now being used to understand the role of rare variants in complex traits and to advance the goals of precision medicine. The technological and computing advances that have enabled us to generate WGS data on thousands of individuals have also outpaced our ability to perform analyses in scientifically and statistically rigorous and thoughtful ways. The past several years have witnessed the application of whole-exome sequencing (WES) to complex traits and diseases. From our analysis of NHLBI Exome Sequencing Project (ESP) data, not only have a number of important disease and complex trait association findings emerged, but our collective experience offers some valuable lessons for WGS initiatives. These include caveats associated with generating automated pipelines for quality control and analysis of rare variants; the importance of studying minority populations; sample size requirements and efficient study designs for identifying rare-variant associations; and the significance of incidental findings in population-based genetic research. With the ESP as an example, we offer guidance and a framework on how to conduct a large-scale association study in the era of WGS.

Increasing Generality and Power of Rare-Variant Tests by Utilizing Extended Pedigrees

Recently, multiple studies have performed whole-exome or whole-genome sequencing to identify groups of rare variants associated with complex traits and diseases. They have primarily utilized case-control study designs that often require thousands of individuals to reach acceptable statistical power. Family-based studies can be more powerful because a rare variant can be enriched in an extended pedigree and segregate with the phenotype. Although many methods have been proposed for using family data to discover rare variants involved in a disease, a majority of them focus on a specific pedigree structure and are designed to analyze either binary or continuously measured outcomes. In this article, we propose RareIBD, a general and powerful approach to identifying rare variants involved in disease susceptibility. Our method can be applied to large extended families of arbitrary structure, including pedigrees with only affected individuals. The method accommodates both binary and quantitative traits. A series of simulation experiments suggest that RareIBD is a powerful test that outperforms existing approaches. In addition, our method accounts for individuals in top generations, which are not usually genotyped in extended families. In contrast to available statistical tests, RareIBD generates accurate p values even when genetic data from these individuals are missing. We applied RareIBD, as well as other methods, to two extended family datasets generated by different genotyping technologies and representing different ethnicities. The analysis of real data confirmed that RareIBD is the only method that properly controls type I error.