外显子组测序在人类疾病中的应用

据估计,约85%的人类遗传变异集中在蛋白编码区,因此对全部的蛋白编码区（外显子组）进行重测序,可以快速、有效地鉴定人类疾病遗传变异。以往鉴定孟德尔遗传病的致病基因多采用连锁分析结合候选定位克隆的方法,不仅耗时长,而且成功率低。2009年,科学家第一次应用外显子组测序在4名弗里曼谢尔登综合征（常染色体显性遗传病）中发现了位于MYH3中的点突变,显示出外显子组测序在孟德尔遗传病致病基因鉴定中的强大功效。就复杂疾病而言,传统的关联研究,包括全基因组关联研究（GWAS）,虽然鉴定了大量的常见变异,但对低频变异和罕见变异的检测能力十分有限;深度测序的发展为解决上述问题提供了良好的契机。本文就外显子组测序在人类疾病中的应用作一简要综述。     

Genes associated with retinitis pigmentosa and allied diseases are frequently mutated in the general population

Background

Retinitis pigmentosa and other hereditary retinal degenerations (HRD) are rare genetic diseases leading to progressive blindness. Recessive HRD are caused by mutations in more than 100 different genes. Laws of population genetics predict that, on a purely theoretical ground, such a high number of genes should translate into an extremely elevated frequency of unaffected carriers of mutations. In this study we estimate the proportion of these individuals within the general population, via the analyses of data from whole-genome sequencing.

Methodology/Principal Findings

We screened complete and high-quality genome sequences from 46 control individuals from various world populations for HRD mutations, using bioinformatic tools developed in-house. All mutations detected in silico were validated by Sanger sequencing. We identified clear-cut, null recessive HRD mutations in 10 out of the 46 unaffected individuals analyzed (∼22%).

Conclusions/Significance

Based on our data, approximately one in 4–5 individuals from the general population may be a carrier of null mutations that are responsible for HRD. This would be the highest mutation carrier frequency so far measured for a class of Mendelian disorders, especially considering that missenses and other forms of pathogenic changes were not included in our assessment. Among other things, our results indicate that the risk for a consanguineous couple of generating a child with a blinding disease is particularly high, compared to other genetic conditions.     

Design considerations for massively parallel sequencing studies of complex human disease

Massively Parallel Sequencing (MPS) allows sequencing of entire exomes and genomes to now be done at reasonable cost, and its utility for identifying genes responsible for rare Mendelian disorders has been demonstrated. However, for a complex disease, study designs need to accommodate substantial degrees of locus, allelic, and phenotypic heterogeneity, as well as complex relationships between genotype and phenotype. Such considerations include careful selection of samples for sequencing and a well-developed strategy for identifying the few "true" disease susceptibility genes from among the many irrelevant genes that will be found to harbor rare variants. To examine these issues we have performed simulation-based analyses in order to compare several strategies for MPS sequencing in complex disease. Factors examined include genetic architecture, sample size, number and relationship of individuals selected for sequencing, and a variety of filters based on variant type, multiple observations of genes and concordance of genetic variants within pedigrees. A two-stage design was assumed where genes from the MPS analysis of high-risk families are evaluated in a secondary screening phase of a larger set of probands with more modest family histories. Designs were evaluated using a cost function that assumes the cost of sequencing the whole exome is 400 times that of sequencing a single candidate gene. Results indicate that while requiring variants to be identified in multiple pedigrees and/or in multiple individuals in the same pedigree are effective strategies for reducing false positives, there is a danger of over-filtering so that most true susceptibility genes are missed. In most cases, sequencing more than two individuals per pedigree results in reduced power without any benefit in terms of reduced overall cost. Further, our results suggest that although no single strategy is optimal, simulations can provide important guidelines for study design.     

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.     

Exom-Sequenzierung zur Identifizierung von Krankheitsgenen

Next generation sequencing can be used to search for Mendelian disease genes in an unbiased manner by sequencing the entire protein-coding sequence, known as the exome. Identifying the pathogenic mutation amongst thousands of genomic variants is a major challenge, and novel variant prioritization strategies are required. The choice of these strategies depends on the availability of well-phenotyped patients and family members, the mode of inheritance, the severity of the disease and its population frequency. In this review we discuss the current strategies for Mendelian disease gene identification by exome resequencing, and we describe the lessons learned from the first exome sequencing studies. Exome sequencing is likely to become the most commonly used tool for Mendelian disease gene identification for the coming years and bears a great diagnostic potential as well.     

A novel epileptic encephalopathy mutation in KCNB1 disrupts Kv2.1 ion selectivity,expression, and localization

The epileptic encephalopathies are a group of highly heterogeneous genetic disorders. The majority of disease-causing mutations alter genes encoding voltage-gated ion channels, neurotransmitter receptors, or synaptic proteins. We have identified a novel de novo pathogenic K⁺ channel variant in an idiopathic epileptic encephalopathy family. Here, we report the effects of this mutation on channel function and heterologous expression in cell lines. We present a case report of infantile epileptic encephalopathy in a young girl, and trio-exome sequencing to determine the genetic etiology of her disorder. The patient was heterozygous for a de novo missense variant in the coding region of the KCNB1 gene, c.1133T>C. The variant encodes a V378A mutation in the α subunit of the Kv2.1 voltage-gated K⁺ channel, which is expressed at high levels in central neurons and is an important regulator of neuronal excitability. We found that expression of the V378A variant results in voltage-activated currents that are sensitive to the selective Kv2 channel blocker guangxitoxin-1E. These voltage-activated Kv2.1 V378A currents were nonselective among monovalent cations. Striking cell background–dependent differences in expression and subcellular localization of the V378A mutation were observed in heterologous cells. Further, coexpression of V378A subunits and wild-type Kv2.1 subunits reciprocally affects their respective trafficking characteristics. A recent study reported epileptic encephalopathy-linked missense variants that render Kv2.1 a tonically activated, nonselective cation channel that is not voltage activated. Our findings strengthen the correlation between mutations that result in loss of Kv2.1 ion selectivity and development of epileptic encephalopathy. However, the strong voltage sensitivity of currents from the V378A mutant indicates that the loss of voltage-sensitive gating seen in all other reported disease mutants is not required for an epileptic encephalopathy phenotype. In addition to electrophysiological differences, we suggest that defects in expression and subcellular localization of Kv2.1 V378A channels could contribute to the pathophysiology of this KCNB1 variant.     

Exome Analysis of Two Limb-Girdle Muscular Dystrophy Families: Mutations Identified and Challenges Encountered

The molecular diagnosis of muscle disorders is challenging: genetic heterogeneity (>100 causal genes for skeletal and cardiac muscle disease) precludes exhaustive clinical testing, prioritizing sequencing of specific genes is difficult due to the similarity of clinical presentation, and the number of variants returned through exome sequencing can make the identification of the disease-causing variant difficult. We have filtered variants found through exome sequencing by prioritizing variants in genes known to be involved in muscle disease while examining the quality and depth of coverage of those genes. We ascertained two families with autosomal dominant limb-girdle muscular dystrophy of unknown etiology. To identify the causal mutations in these families, we performed exome sequencing on five affected individuals using the Agilent SureSelect Human All Exon 50 Mb kit and the Illumina HiSeq 2000 (2×100 bp). We identified causative mutations in desmin (IVS3+3A>G) and filamin C (p.W2710X), and augmented the phenotype data for individuals with muscular dystrophy due to these mutations. We also discuss challenges encountered due to depth of coverage variability at specific sites and the annotation of a functionally proven splice site variant as an intronic variant.     

Genome Sequencing of Idiopathic Pulmonary Fibrosis in Conjunction with a Medical School Human Anatomy Course

Even in cases where there is no obvious family history of disease, genome sequencing may contribute to clinical diagnosis and management. Clinical application of the genome has not yet become routine, however, in part because physicians are still learning how best to utilize such information. As an educational research exercise performed in conjunction with our medical school human anatomy course, we explored the potential utility of determining the whole genome sequence of a patient who had died following a clinical diagnosis of idiopathic pulmonary fibrosis (IPF). Medical students performed dissection and whole genome sequencing of the cadaver. Gross and microscopic findings were more consistent with the fibrosing variant of nonspecific interstitial pneumonia (NSIP), as opposed to IPF per se. Variants in genes causing Mendelian disorders predisposing to IPF were not detected. However, whole genome sequencing identified several common variants associated with IPF, including a single nucleotide polymorphism (SNP), rs35705950, located in the promoter region of the gene encoding mucin glycoprotein MUC5B. The MUC5B promoter polymorphism was recently found to markedly elevate risk for IPF, though a particular association with NSIP has not been previously reported, nor has its contribution to disease risk previously been evaluated in the genome-wide context of all genetic variants. We did not identify additional predicted functional variants in a region of linkage disequilibrium (LD) adjacent to MUC5B, nor did we discover other likely risk-contributing variants elsewhere in the genome. Whole genome sequencing thus corroborates the association of rs35705950 with MUC5B dysregulation and interstitial lung disease. This novel exercise additionally served a unique mission in bridging clinical and basic science education.     

Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (～1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.     

Annotating DNA Variants Is the Next Major Goal for Human Genetics

Clinical genetic testing has undergone a dramatic transformation in the past two decades. Diagnostic laboratories that previously tested for well-established disease-causing DNA variants in a handful of genes have evolved into sequencing factories identifying thousands of variants of known and unknown medical consequence. Sorting out what does and does not cause disease in our genomes is the next great challenge in making genetics a central feature of healthcare. I propose that closing the gap in our ability to interpret variation responsible for Mendelian disorders provides a grand and unprecedented opportunity for geneticists. Human geneticists are well placed to coordinate a systematic evaluation of variants in collaboration with basic scientists and clinicians. Sharing of knowledge, data, methods, and tools will aid both researchers and healthcare workers in achieving their common goal of defining the pathogenic potential of variants. Generation of variant annotations will inform genetic testing and will deepen our understanding of gene and protein function, thereby aiding the search for molecular targeted therapies.     

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.     

Pathogenic Variants for Mendelian and Complex Traits in Exomes of 6,517 European and African Americans: Implications for the Return of Incidental Results

Exome sequencing (ES) is rapidly being deployed for use in clinical settings despite limited empirical data about the number and types of incidental results (with potential clinical utility) that could be offered for return to an individual. We analyzed deidentified ES data from 6,517 participants (2,204 African Americans and 4,313 European Americans) from the National Heart, Lung, and Blood Institute Exome Sequencing Project. We characterized the frequencies of pathogenic alleles in genes underlying Mendelian conditions commonly assessed by newborn-screening (NBS, n = 39) programs, genes associated with age-related macular degeneration (ARMD, n = 17), and genes known to influence drug response (PGx, n = 14). From these 70 genes, we identified 10,789 variants and curated them by manual review of OMIM, HGMD, locus-specific databases, or primary literature to a total of 399 validated pathogenic variants. The mean number of risk alleles per individual was 15.3. Every individual had at least five known PGx alleles, 99% of individuals had at least one ARMD risk allele, and 45% of individuals were carriers for at least one pathogenic NBS allele. The carrier burden for severe recessive childhood disorders was 0.57. Our results demonstrate that risk alleles of potential clinical utility for both Mendelian and complex traits are detectable in every individual. These findings highlight the necessity of developing guidelines and policies that consider the return of results to all individuals and underscore the need to develop innovative approaches and tools that enable individuals to exercise their choice about the return of incidental results.     

Large-scale detection of rare variants via pooled multiplexed next-generation sequencing: towards next-generation Ecotilling

Common variants, such as those identified by genome-wide association scans, explain only a small proportion of trait variation. Growing evidence suggests that rare functional variants, which are usually missed by genome-wide association scans, play an important role in determining the phenotype. We used pooled multiplexed next-generation sequencing and a customized analysis workflow to detect mutations in five candidate genes for lignin biosynthesis in 768 pooled Populus nigra accessions. We identified a total of 36 non-synonymous single nucleotide polymorphisms, one of which causes a premature stop codon. The most common variant was estimated to be present in 672 of the 1536 tested chromosomes, while the rarest was estimated to occur only once in 1536 chromosomes. Comparison with individual Sanger sequencing in a selected sub-sample confirmed that variants are identified with high sensitivity and specificity, and that the variant frequency was estimated accurately. This proposed method for identification of rare polymorphisms allows accurate detection of variation in many individuals, and is cost-effective compared to individual sequencing.     

New perspectives for the elucidation of genetic disorders

For almost 15 years, genome research has focused on the search for major risk factors in common diseases, with disappointing results. Only recently, whole-genome association studies have begun to deliver because of the introduction of high-density single-nucleotide-polymorphism arrays and massive enlargement of cohort sizes, but most of the risk factors detected account for only a small proportion of the total genetic risk, and their diagnostic value is negligible. There is reason to believe that the complexity of many "multifactorial" disorders is primarily due to genetic heterogeneity, with defects of different genes causing the same disease. Moreover, de novo copy-number variation has been identified as a major cause of mental retardation and other complex disorders, suggesting that new mutations are an important, previously overlooked factor in the etiology of complex diseases. These observations support the notion that research into the previously neglected monogenic disorders should become a priority of genome research. Because of the introduction of novel high-throughput, low-cost sequencing methods, sequencing and genotyping will soon converge, with far-reaching implications for the elucidation of genetic disease and health care.     

Discovery of allelic variants of HOXA1 and HOXB1: genetic susceptibility to autism spectrum disorders

BACKGROUND: Family studies have demonstrated that the autism spectrum disorders (ASDs) have a major genetic etiologic component, but expression and penetrance of the phenotype are variable. Mice with null mutations of Hoxa1 or Hoxb1, two genes critical to hindbrain development, have phenotypic features frequently observed in autism, but no naturally occurring variants of either gene have been identified in mammals. METHODS: By sequencing regions of genomic DNA of patients with autism spectrum disorders, we detected a substitution variant at HOXA1 and an insertion variant at HOXB1, both in coding regions of the genes. Fifty-seven individuals ascertained for a diagnosis of an ASD, along with 166 of their relatives, were typed for these variants. Two non-ASD populations were typed, and the frequency of the newly identified alleles was determined in all groups. The genotypes of the ASD families were tested for conformation to Hardy-Weinberg proportions and Mendelian expectations for gene transmission. RESULTS: The frequency of the variants was 10-25% in persons of European or African origin. In the ASD families, there was a significant deviation from the HOXA1 genotype ratios expected from Hardy-Weinberg proportions (P = 0.005). Among affected offspring, a significant deviation from Mendelian expectation in gene transmission (P = 0.011) was observed. No statistically significant effects were detected when the same analyses were applied to the HOXB1 locus, but there was evidence of an interaction between HOXA1, HOXB1, and gender in susceptibility to ASDs. CONCLUSIONS: The results support a role for HOXA1 in susceptibility to autism, and add to the existing body of evidence implicating early brain stem injury in the etiology of ASDs.     

Discovery of Rare Variants via Sequencing: Implications for the Design of Complex Trait Association Studies

There is strong evidence that rare variants are involved in complex disease etiology. The first step in implicating rare variants in disease etiology is their identification through sequencing in both randomly ascertained samples (e.g., the 1,000 Genomes Project) and samples ascertained according to disease status. We investigated to what extent rare variants will be observed across the genome and in candidate genes in randomly ascertained samples, the magnitude of variant enrichment in diseased individuals, and biases that can occur due to how variants are discovered. Although sequencing cases can enrich for casual variants, when a gene or genes are not involved in disease etiology, limiting variant discovery to cases can lead to association studies with dramatically inflated false positive rates.     

Phased whole-genome genetic risk in a family quartet using a major allele reference sequence

Whole-genome sequencing harbors unprecedented potential for characterization of individual and family genetic variation. Here, we develop a novel synthetic human reference sequence that is ethnically concordant and use it for the analysis of genomes from a nuclear family with history of familial thrombophilia. We demonstrate that the use of the major allele reference sequence results in improved genotype accuracy for disease-associated variant loci. We infer recombination sites to the lowest median resolution demonstrated to date (< 1,000 base pairs). We use family inheritance state analysis to control sequencing error and inform family-wide haplotype phasing, allowing quantification of genome-wide compound heterozygosity. We develop a sequence-based methodology for Human Leukocyte Antigen typing that contributes to disease risk prediction. Finally, we advance methods for analysis of disease and pharmacogenomic risk across the coding and non-coding genome that incorporate phased variant data. We show these methods are capable of identifying multigenic risk for inherited thrombophilia and informing the appropriate pharmacological therapy. These ethnicity-specific, family-based approaches to interpretation of genetic variation are emblematic of the next generation of genetic risk assessment using whole-genome sequencing.     

Autozygome Sequencing Expands the Horizon of Human Knockout Research and Provides Novel Insights into Human Phenotypic Variation

The use of autozygosity as a mapping tool in the search for autosomal recessive disease genes is well established. We hypothesized that autozygosity not only unmasks the recessiveness of disease causing variants, but can also reveal natural knockouts of genes with less obvious phenotypic consequences. To test this hypothesis, we exome sequenced 77 well phenotyped individuals born to first cousin parents in search of genes that are biallelically inactivated. Using a very conservative estimate, we show that each of these individuals carries biallelic inactivation of 22.8 genes on average. For many of the 169 genes that appear to be biallelically inactivated, available data support involvement in modulating metabolism, immunity, perception, external appearance and other phenotypic aspects, and appear therefore to contribute to human phenotypic variation. Other genes with biallelic inactivation may contribute in yet unknown mechanisms or may be on their way to conversion into pseudogenes due to true recent dispensability. We conclude that sequencing the autozygome is an efficient way to map the contribution of genes to human phenotypic variation that goes beyond the classical definition of disease.     

Statistical guidance for experimental design and data analysis of mutation detection in rare monogenic mendelian diseases by exome sequencing

Recently, whole-genome sequencing, especially exome sequencing, has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases. However, it is unclear whether this approach can be generalized and effectively applied to other Mendelian diseases with high locus heterogeneity. Moreover, the current exome sequencing approach has limitations such as false positive and false negative rates of mutation detection due to sequencing errors and other artifacts, but the impact of these limitations on experimental design has not been systematically analyzed. To address these questions, we present a statistical modeling framework to calculate the power, the probability of identifying truly disease-causing genes, under various inheritance models and experimental conditions, providing guidance for both proper experimental design and data analysis. Based on our model, we found that the exome sequencing approach is well-powered for mutation detection in recessive, but not dominant, Mendelian diseases with high locus heterogeneity. A disease gene responsible for as low as 5% of the disease population can be readily identified by sequencing just 200 unrelated patients. Based on these results, for identifying rare Mendelian disease genes, we propose that a viable approach is to combine, sequence, and analyze patients with the same disease together, leveraging the statistical framework presented in this work.