Design considerations for massively parallel sequencing studies of complex human disease

The Genetic Architecture of Non-Syndromic Rhegmatogenous Retinal Detachment

Rhegmatogenous retinal detachment (RRD) is the most common form of retinal detachment (RD), affecting 1 in 10,000 patients per year. The condition has significant ocular morbidity, with a sizeable proportion of patients obtaining poor visual outcomes. Despite this, the genetics underpinning Idiopathic Retinal Detachment (IRD) remain poorly understood; this is likely due to small sample sizes in relevant studies. The majority of research pertains to the well-characterised Mende lian syndromes, such as Sticklers and Wagners, associated with RRD. Nevertheless, in recent years, there has been an increasing body of literature identifying the common genetic mutations and mechanisms associated with IRD. Several recent Genomic Wide Association Studies (GWAS) studies have identified a number of genetic loci related to the development of IRD. Our review aims to provide an up-to-date summary of the significant genetic mechanisms and associations of Idiopathic RRD.

A role for the MEGF6 gene in predisposition to osteoporosis

Osteoporosis is a common skeletal disorder characterized by deterioration of bone tissue. The set of genetic factors contributing to osteoporosis is not completely specified. High-risk osteoporosis pedigrees were analyzed to identify genes that may confer susceptibility to disease. Candidate predisposition variants were identified initially by whole exome sequencing of affected-relative pairs, approximately cousins, from 10 pedigrees. Variants were filtered on the basis of population frequency, concordance between pairs of cousins, affecting a gene associated with osteoporosis, and likelihood to have functionally damaging, pathogenic consequences. Subsequently, variants were tested for segregation in 68 additional relatives of the index carriers. A rare variant in MEGF6 (rs755467862) showed strong evidence of segregation with the disease phenotype. Predicted protein folding indicated the variant (Cys200Tyr) may disrupt structure of an EGF-like calcium-binding domain of MEGF6. Functional analyses demonstrated that complete loss of the paralogous genes megf6a and megf6b in zebrafish resulted in significant delay of cartilage and bone formation. Segregation analyses, in silico protein structure modeling, and functional assays support a role for MEGF6 in predisposition to osteoporosis.

A Review of Whole-Exome Sequencing Efforts Toward Hereditary Breast Cancer Susceptibility Gene Discovery

Inherited genetic risk factors contribute toward breast cancer (BC) onset. BC risk variants can be divided into three categories of penetrance (high, moderate, and low) that reflect the probability of developing the disease. Traditional BC susceptibility gene discovery approaches that searched for high- and moderate-risk variants in familial BC cases have had limited success; to date, these risk variants explain only ∼30% of familial BC cases. Next-generation sequencing technologies can be used to search for novel high and moderate BC risk variants, and this manuscript reviews 12 familial BC whole-exome sequencing efforts. Study design, filtering strategies, and segregation and validation analyses are discussed. Overall, only a modest number of novel BC risk genes were identified, and 90% and 97% of the exome-sequenced families and cases, respectively, had no BC risk variants reported. It is important to learn from these studies and consider alternate strategies in order to make further advances. The discovery of new BC susceptibility genes is critical for improved risk assessment and to provide insight toward disease mechanisms for the development of more effective therapies.

On the design and analysis of next-generation sequencing genotyping for a cohort with haplotype-informative reads

Next-generation sequencing (NGS) technologies, which can provide base-pair resolution genetic information for all types of genetic variations, are increasingly used in genetics research. However, due to the complex nature of NGS technologies and analytics and their relatively high cost, investigators face practical challenges for both design and analysis. These challenges are further complicated by recent methodological developments that make it possible to use haplotype information in sequencing reads. In light of these developments, we conducted comprehensive simulations to evaluate the effects of sequencing coverage, insert size of paired-end reads, and sample size on genotype calling and haplotype phasing in NGS studies. In contrast to previous studies that typically use idealized scenarios to tease out the effects of individual design and analytic decisions, we used a complete analytical pipeline from read mapping and variant detection to genotype calling and haplotype phasing so that we can assess the joint effects of multiple decisions and thus make more realistic recommendations to investigators. Consistent with previous studies, we found that the use of haplotype information in reads can improve the accuracy of genotype calling and haplotype phasing, and we also found that a mixture of short and long insert sizes of paired-end reads may offer even greater accuracy. However, this benefit is only clear in high coverage sequencing where variant detection is close to perfect. Finally, we observed that LD-based refinement methods do not always outperform single site based methods for genotype calling. Therefore, we should choose analytical methods that are appropriate to the sequencing coverage and sample size in order to use haplotype information in sequencing reads.

Living laboratory: whole-genome sequencing as a learning healthcare enterprise

With the proliferation of affordable large-scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large-scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype-phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta-analyses, we propose leveraging nascent clinical-research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real-life challenges posed by whole-genome sequencing, such as establishing the clinical actionability of genetic variants, returning 'off-target' results to families, developing effective service delivery models and monitoring long-term outcomes.

Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers

Approximately half of the familial aggregation of breast cancer remains unexplained. A multiple-case breast cancer family exome-sequencing study identified three likely pathogenic mutations in RINT1 (NM_021930.4) not present in public sequencing databases: RINT1 c.343C>T (p.Q115X), c.1132_1134del (p.M378del), and c.1207G>T (p.D403Y). On the basis of this finding, a population-based case-control mutation-screening study was conducted that identified 29 carriers of rare (minor allele frequency < 0.5%), likely pathogenic variants: 23 in 1,313 early-onset breast cancer cases and six in 1,123 frequency-matched controls [OR, 3.24; 95% confidence interval (CI), 1.29-8.17; P = 0.013]. RINT1 mutation screening of probands from 798 multiple-case breast cancer families identified four additional carriers of rare genetic variants. Analysis of the incidence of first primary cancers in families of women carrying RINT1 mutations estimated that carriers were at increased risk of Lynch syndrome-spectrum cancers [standardized incidence ratio (SIR), 3.35; 95% CI, 1.7-6.0; P = 0.005], particularly for relatives diagnosed with cancer under the age of 60 years (SIR, 10.9; 95% CI, 4.7-21; P = 0.0003).

SIGNIFICANCE

The work described in this study adds RINT1 to the growing list of genes in which rare sequence variants are associated with intermediate levels of breast cancer risk. Given that RINT1 is also associated with a spectrum of cancers with mismatch repair defects, these findings have clinical applications and raise interesting biological questions.

A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.

Whole exome sequencing of distant relatives in multiplex families implicates rare variants in candidate genes for oral clefts

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.

Statistical power and significance testing in large-scale genetic studies

Significance testing was developed as an objective method for summarizing statistical evidence for a hypothesis. It has been widely adopted in genetic studies, including genome-wide association studies and, more recently, exome sequencing studies. However, significance testing in both genome-wide and exome-wide studies must adopt stringent significance thresholds to allow multiple testing, and it is useful only when studies have adequate statistical power, which depends on the characteristics of the phenotype and the putative genetic variant, as well as the study design. Here, we review the principles and applications of significance testing and power calculation, including recently proposed gene-based tests for rare variants.

Inferring rare disease risk variants based on exact probabilities of sharing by multiple affected relatives

MOTIVATION

Family-based designs are regaining popularity for genomic sequencing studies because they provide a way to test cosegregation with disease of variants that are too rare in the population to be tested individually in a conventional case-control study.

RESULTS

Where only a few affected subjects per family are sequenced, the probability that any variant would be shared by all affected relatives-given it occurred in any one family member-provides evidence against the null hypothesis of a complete absence of linkage and association. A P-value can be obtained as the sum of the probabilities of sharing events as (or more) extreme in one or more families. We generalize an existing closed-form expression for exact sharing probabilities to more than two relatives per family. When pedigree founders are related, we show that an approximation of sharing probabilities based on empirical estimates of kinship among founders obtained from genome-wide marker data is accurate for low levels of kinship. We also propose a more generally applicable approach based on Monte Carlo simulations. We applied this method to a study of 55 multiplex families with apparent non-syndromic forms of oral clefts from four distinct populations, with whole exome sequences available for two or three affected members per family. The rare single nucleotide variant rs149253049 in ADAMTS9 shared by affected relatives in three Indian families achieved significance after correcting for multiple comparisons ([Formula: see text]).

AVAILABILITY AND IMPLEMENTATION

Source code and binaries of the R package RVsharing are freely available for download at http://cran.r-project.org/web/packages/RVsharing/index.html.

CONTACT

alexandre.bureau@msp.ulaval.ca or ingo@jhu.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Enrichment of target sequences for next-generation sequencing applications in research and diagnostics

Targeted re-sequencing such as gene panel sequencing (GPS) has become very popular in medical genetics, both for research projects and in diagnostic settings. The technical principles of the different enrichment methods have been reviewed several times before; however, new enrichment products are constantly entering the market, and researchers are often puzzled about the requirement to take decisions about long-term commitments, both for the enrichment product and the sequencing technology. This review summarizes important considerations for the experimental design and provides helpful recommendations in choosing the best sequencing strategy for various research projects and diagnostic applications.

Identification of novel variants in colorectal cancer families by high-throughput exome sequencing

BACKGROUND

Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants.

METHODS

We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign.

RESULTS

We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively.

CONCLUSIONS

Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility.

IMPACT

Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk.

Exome sequencing of senescence-accelerated mice (SAM) reveals deleterious mutations in degenerative disease-causing genes

BACKGROUND

Senescence-accelerated mice (SAM) are a series of mouse strains originally derived from unexpected crosses between AKR/J and unknown mice, from which phenotypically distinct senescence-prone (SAMP) and -resistant (SAMR) inbred strains were subsequently established. Although SAMP strains have been widely used for aging research focusing on their short life spans and various age-related phenotypes, such as immune dysfunction, osteoporosis, and brain atrophy, the responsible gene mutations have not yet been fully elucidated.

RESULTS

To identify mutations specific to SAMP strains, we performed whole exome sequencing of 6 SAMP and 3 SAMR strains. This analysis revealed 32,019 to 38,925 single-nucleotide variants in the coding region of each SAM strain. We detected Ogg1 p.R304W and Mbd4 p.D129N deleterious mutations in all 6 of the SAMP strains but not in the SAMR or AKR/J strains. Moreover, we extracted 31 SAMP-specific novel deleterious mutations. In all SAMP strains except SAMP8, we detected a p.R473W missense mutation in the Ldb3 gene, which has been associated with myofibrillar myopathy. In 3 SAMP strains (SAMP3, SAMP10, and SAMP11), we identified a p.R167C missense mutation in the Prx gene, in which mutations causing hereditary motor and sensory neuropathy (Dejerine-Sottas syndrome) have been identified. In SAMP6 we detected a p.S540fs frame-shift mutation in the Il4ra gene, a mutation potentially causative of ulcerative colitis and osteoporosis.

CONCLUSIONS

Our data indicate that different combinations of mutations in disease-causing genes may be responsible for the various phenotypes of SAMP strains.

Predisposition gene identification in common cancers by exome sequencing: insights from familial breast cancer

The genetic component of breast cancer predisposition remains largely unexplained. Candidate gene case-control resequencing has identified predisposition genes characterised by rare, protein truncating mutations that confer moderate risks of disease. In theory, exome sequencing should yield additional genes of this class. Here, we explore the feasibility and design considerations of this approach. We performed exome sequencing in 50 individuals with familial breast cancer, applying frequency and protein function filters to identify variants most likely to be pathogenic. We identified 867,378 variants that passed the call quality filters of which 1,296 variants passed the frequency and protein truncation filters. The median number of validated, rare, protein truncating variants was 10 in individuals with, and without, mutations in known genes. The functional candidacy of mutated genes was similar in both groups. Without prior knowledge, the known genes would not have been recognisable as breast cancer predisposition genes. Everyone carries multiple rare mutations that are plausibly related to disease. Exome sequencing in common conditions will therefore require intelligent sample and variant prioritisation strategies in large case-control studies to deliver robust genetic evidence of disease association.

Single Nucleotide Polymorphism (SNP) Detection and Genotype Calling from Massively Parallel Sequencing (MPS) Data

Massively parallel sequencing (MPS), since its debut in 2005, has transformed the field of genomic studies. These new sequencing technologies have resulted in the successful identification of causal variants for several rare Mendelian disorders. They have also begun to deliver on their promise to explain some of the missing heritability from genome-wide association studies (GWAS) of complex traits. We anticipate a rapidly growing number of MPS-based studies for a diverse range of applications in the near future. One crucial and nearly inevitable step is to detect SNPs and call genotypes at the detected polymorphic sites from the sequencing data. Here, we review statistical methods that have been proposed in the past five years for this purpose. In addition, we discuss emerging issues and future directions related to SNP detection and genotype calling from MPS data.