全基因组外显子测序及其应用

近年来,众多研究小组开展了大量的全基因组关联研究(Genome-wide association studies,GWAS),发现并鉴定了许多与复杂疾病/性状相关联的遗传变异,为复杂疾病发病机制的研究提供了重要线索。由于GWAS的结果存在假阳性、假阴性、检测到的单核苷酸多态性很少位于功能区以及对稀有变异和结构变异不敏感等问题,导致了其应用的局限性。而新一代测序技术的进步,促进了全基因组测序和全基因组外显子测序的快速发展,为解决上述问题提供了契机。全基因组外显子测序是利用序列捕获技术将全基因组外显子区域DNA捕捉并富集后进行高通量测序的基因组分析方法。由于其具有对常见和罕见变异高灵敏度,能发现外显子区绝大部分疾病相关变异以及仅需要对约1%的基因组进行测序等优点,促使全基因组外显子测序成为鉴定孟德尔疾病的致病基因最有效的策略,也被运用于复杂疾病易感基因的研究和临床诊断中。     

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。     

Nature系列期刊导读

<正>探讨大规模基因组研究随着新一代基因组测序技术的发展,近十年来大规模基因组测序研究越来越多,由此积累出了庞大的数据群。该文从以下三方面探讨了大规模基因组研究中的大数据问题:全基因组关联研究以及外显子组测序研究中的显著性检验,以及如何使研究更具有统计学意义;外显子组突变研究对于理解和预测当前和未来人类疾病和进化的模式具有重要意义;基于基因的稀有突变研究,及其与已知疾病的     

基于新一代高通量技术的人类疾病组学研究策略

近年来,包括第二代测序技术和蛋白质谱技术等在内的新一代高通量技术越来越多的应用于解决生物学问题尤其是人类疾病的研究。这种以数据为导向,大规模、工业化的研究模式,使得从基因组水平、转录组水平、蛋白质组水平等角度对疾病展开全方位、多层次的研究成为可能。文章综述了新一代高通量技术在DNA、RNA、表观遗传、宏基因组和蛋白质组水平的人类疾病研究进展以及在转化医学领域的应用。在基因组水平上,外显子组测序是近年来持续的研究热点,随着测序成本的不断降低,全基因组重测序也越来越凸显了其在全基因组范围内检测大型结构变异的优势,并使得个人基因组引领的个体化医疗逐渐成为可能。在转录组水平,如小RNA测序技术可用来检测已知小RNA和预测新的小RNA,这些小RNA不仅可以作为疾病诊断和预后的分子标志物,在疾病治疗方面也具有无限潜力。在蛋白质组水平,如目标蛋白质组学可以有目标地测定可能与疾病相关的特定蛋白质或多肽,能够很好地应用于疾病的临床分期分型。文章进一步阐述了跨组学研究在疾病研究领域中的应用和发展趋势,借助生物信息学分析方法进行多组学整合研究,能更加系统地阐释疾病的发生及发展机理,为疾病的诊断治疗提供强有力的工具。     

《自然-通讯》:新的测序技术发现银屑病新的非编码变异

<正>新一代测序技术发现银屑病非编码变异。安徽医科大学皮肤病研究所张学军银屑病研究团队,联合复旦大学皮肤病研究所、深圳华大基因研究院、香港中文大学等科研单位,首次利用银屑病大规模全外显子测序发现疾病易感基因非编码变异。该研究的另一个科学意义在于,此前通过外显子测序技术发现编码变异在疾病发病过程中起着重要的作用,但这些看似没有意义的非编码变异,可能形成特殊的DNA结构,以此对附近功能基因的调节具有重要意义。世界著名学术期刊《自然-通讯》在线发表了这一新     

人类基因组致病SNP与良性SNP分布模式探究

基因组变异与生物学功能,乃至人体健康紧密相关。不同种类的基因组变异会对人类健康产生不同的影响,可能出现致病、良性或未知的临床症状。深入研究临床上表现为致病性或良性的基因组变异,能够有效加深我们对基因组变异与疾病发生发展的认识,对评估基因组变异所带来的影响具有一定的意义。本研究选择Clinvar数据库中与疾病相关的SNP,探究临床表现为致病与良性的SNP位点分别在基因组上的分布模式以及对蛋白序列的影响。本研究发现,致病SNP与良性SNP在外显子与内含子上的分布以及蛋白结构域内外的分布上具有非常显著差异,致病SNP在外显子和蛋白结构域内的分布密度更高。从蛋白编码区的SNP突变类型来看,致病SNP位点中的同义突变与非同义突变所占比例分别是0.64%和99.36%,而良性SNP位点中两类突变的比例相差较小,检验结果显示致病SNP位点中非同义突变更多。此外,本研究通过分析致病SNP与良性SNP中的同义突变与非同义突变在蛋白质结构域内外的分布情况,发现两类SNP变异中同义突变的分布没有显著差异,但非同义突变的分布具有显著差异,其中致病SNP变异分布在蛋白质结构域内外的比例是53.22%和46.78%,良性SNP变异分布比例为31.96%和68.04%。随后,我们对非同义突变所在基因进行了功能注释和富集分析,发现两类变异所在基因的功能范围几乎一致。     

基因拷贝数变异与人类疾病

拷贝数变异(copy number variation,CNV)是人类遗传多样性的一类重要形式。在前期的研究中,人们通过寡核苷酸分型、比较基因组杂交以及测序等技术手段,在人类基因组中鉴定出了大量拷贝数变异位点。这些变异可能是由于基因组重组或复制过程中的差错而产生。CNV在人群中的覆盖率远远高于寡核苷酸多态性(single nucleotide polymorphism,SNP),它们可以通过多种机制改变基因的表达水平,如基因剂量效应、基因断裂-融合效应,以及远距调控效应,进而引起多种人类复杂疾病。认识基因组中的拷贝数变异对于我们更好地认识基因与疾病的关系、遗传-环境因素的相互作用,以及基因组变异与物种进化的关系具有重要的意义。     

用基因组DNA剪接技术克隆SIgA相关基因

目的：克隆分泌型IgA（SIgA）相关基因--J链基因(IgJ)、多聚免疫球蛋白受体基因（pIgR）和IgA重链恒定区基因（IGHA）,为进一步构建SIgA真核表达质粒奠定基础。方法：采用本室建立的"基因组DNA剪接"技术,根据已发表的IgJ、pIgR和IGHA的核苷酸序列,通过计算机软件分别设计各个基因片段外显子的优化引物,从人外周血基因组DNA中直接扩增各基因的外显子序列;然后人工设计融合相邻外显子的融合引物,采用重叠PCR技术,把各基因片段的外显子串联起来形成全长编码序列,完成基因组DNA的体外剪接。扩增的PCR产物纯化后克隆到pGEM-T Easy Vector中,通过DNA测序对阳性克隆进行分析鉴定。结果：PCR扩增的IgJ、pIgR和IGHA基因与预期大小一致;测序结果表明本实验获得的上述基因与GenBank中的目标基因序列完全一致。结论：本文通过基因组DNA剪接技术成功克隆人类SIgA三个相关基因,提示此技术是合成多外显子cDNA的有效手段。     

肺炎衣原体分型的研究进展

肺炎衣原体与诸多慢性临床疾病相关,是否像沙眼衣原体那样存在不同的亚型导致不同的临床疾病,由此引起的肺炎衣原体亚型研究从未间断。已有学者发现世界各地分离的肺炎衣原体菌株抗原性并不一致,而新近的全基因组测序提示在不同菌株之间基因组存在差别。在AR-39基因组中首次发现整合有噬菌体基因,研究初步证明整合有噬菌体基因的肺炎衣原体与血管疾病相关。     

三倍体香蕉优良品种‘Grand Nain’全基因组变异挖掘

为全面揭示香蕉(Musa spp.)优良品种的全基因组变异类型,本研究采用高通量重测序技术,对当前香蕉主栽品种‘Grand Nain’(AAA group,Cavendish subgroup)开展全基因组重测序,测序深度53.79 X。与野生香蕉‘DH-Pahang’参考基因组比对,共检测到4 598 633个单核苷酸多态位点(SNP),484 752个小片段插入缺失位点(Indel),57 047个结构变异(SV),共导致36 277个基因变异;代谢通路分析(KEGG)发现,植物激素信号转导途径相关基因的变异最多,存在442个基因变异,其中乙烯合成和信号转导途径中1-氨基环丙烷-1-羧酸氧化酶基因(ACO)、1-氨基环丙烷-1-羧酸合成酶基因(ACS)、EIN3/EILs、ERS、RAN、EBF、EIN2等基因都存在变异。特别是序列分析发现‘Grand Nain’中的Ma ACO1基因与参考基因组相比存在2个变异位点并导致氨基酸的突变,且在A和B基因组中MaACO1基因存在2个相邻的变异位点。本研究为香蕉贮藏保鲜等相关分子标记开发、基因功能研究,以及基于基因组编辑技术的香蕉遗传改良提供依据。     

New insights into the performance of human whole-exome capture platforms

Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.     

Analysis of Downs syndrome with molecular techniques for future diagnoses

Down syndrome (DS) is a genetic disorder appeared due to the presence of trisomy in chromosome 21 in the G-group of the acrocentric region. DS is also known as non-Mendelian inheritance, due to the lack of Mendel’s laws. The disorder in children is identified through clinical symptoms and chromosomal analysis and till now there are no biochemical and molecular analyses. Presently, whole exome sequencing (WES) has largely contributed in identifying the new disease-causing genes and represented a significant breakthrough in the field of human genetics and this technique uses high throughput sequencing technologies to determine the arrangement of DNA base pairs specifying the protein coding regions of an individual’s genome. Apart from this next generation sequencing and whole genome sequencing also contribute for identifying the disease marker. From this review, the suggestion was to perform the WES is DS children to identify the marker region.     

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.     

Identification of de novo germline mutations and causal genes for sporadic diseases using trio‐based whole‐exome/genome sequencing

Whole‐genome or whole‐exome sequencing (WGS/WES) of the affected proband together with normal parents (trio) is commonly adopted to identify de novo germline mutations (DNMs) underlying sporadic cases of various genetic disorders. However, our current knowledge of the occurrence and functional effects of DNMs remains limited and accurately identifying the disease‐causing DNM from a group of irrelevant DNMs is complicated. Herein, we provide a general‐purpose discussion of important issues related to pathogenic gene identification based on trio‐based WGS/WES data. Specifically, the relevance of DNMs to human sporadic diseases, current knowledge of DNM biogenesis mechanisms, and common strategies or software tools used for DNM detection are reviewed, followed by a discussion of pathogenic gene prioritization. In addition, several key factors that may affect DNM identification accuracy and causal gene prioritization are reviewed. Based on recent major advances, this review both sheds light on how trio‐based WGS/WES technologies can play a significant role in the identification of DNMs and causal genes for sporadic diseases, and also discusses existing challenges.     

Whole genome sequencing and its applications in medical genetics

Fundamental improvement was made for genome sequencing since the next-generation sequencing (NGS) came out in the 2000s. The newer technologies make use of the power of massively-parallel short-read DNA sequencing, genome alignment and assembly methods to digitally and rapidly search the genomes on a revolutionary scale, which enable large-scale whole genome sequencing (WGS) accessible and practical for researchers. Nowadays, whole genome sequencing is more and more prevalent in detecting the genetics of diseases, studying causative relations with cancers, making genome-level comparative analysis, reconstruction of human population history, and giving clinical implications and instructions. In this review, we first give a typical pipeline of whole genome sequencing, including the lab template preparation, sequencing, genome assembling and quality control, variants calling and annotations. We compare the difference between whole genome and whole exome sequencing (WES), and explore a wide range of applications of whole genome sequencing for both mendelian diseases and complex diseases in medical genetics. We highlight the impact of whole genome sequencing in cancer studies, regulatory variant analysis, predictive medicine and precision medicine, as well as discuss the challenges of the whole genome sequencing.      

Exome Sequencing and Functional Validation in Zebrafish Identify GTDC2 Mutations as a Cause of Walker-Warburg Syndrome

Whole-exome sequencing (WES), which analyzes the coding sequence of most annotated genes in the human genome, is an ideal approach to studying fully penetrant autosomal-recessive diseases, and it has been very powerful in identifying disease-causing mutations even when enrollment of affected individuals is limited by reduced survival. In this study, we combined WES with homozygosity analysis of consanguineous pedigrees, which are informative even when a single affected individual is available, to identify genetic mutations responsible for Walker-Warburg syndrome (WWS), a genetically heterogeneous autosomal-recessive disorder that severely affects the development of the brain, eyes, and muscle. Mutations in seven genes are known to cause WWS and explain 50%-60% of cases, but multiple additional genes are expected to be mutated because unexplained cases show suggestive linkage to diverse loci. Using WES in consanguineous WWS-affected families, we found multiple deleterious mutations in GTDC2 (also known as AGO61). GTDC2's predicted role as an uncharacterized glycosyltransferase is consistent with the function of other genes that are known to be mutated in WWS and that are involved in the glycosylation of the transmembrane receptor dystroglycan. Therefore, to explore the role of GTDC2 loss of function during development, we used morpholino-mediated knockdown of its zebrafish ortholog, gtdc2. We found that gtdc2 knockdown in zebrafish replicates all WWS features (hydrocephalus, ocular defects, and muscular dystrophy), strongly suggesting that GTDC2 mutations cause WWS.     

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.     

A comprehensive biomedical variant catalogue based on whole genome sequences of 582 dogs and eight wolves

The domestic dog serves as an excellent model to investigate the genetic basis of disease. More than 400 heritable traits analogous to human diseases have been described in dogs. To further canine medical genetics research, we established the Dog Biomedical Variant Database Consortium (DBVDC) and present a comprehensive list of functionally annotated genome variants that were identified with whole genome sequencing of 582 dogs from 126 breeds and eight wolves. The genomes used in the study have a minimum coverage of 10× and an average coverage of ~24×. In total, we identified 23 133 692 single‐nucleotide variants (SNVs) and 10 048 038 short indels, including 93% undescribed variants. On average, each individual dog genome carried ～4.1 million single‐nucleotide and ~1.4 million short‐indel variants with respect to the reference genome assembly. About 2% of the variants were located in coding regions of annotated genes and loci. Variant effect classification showed 247 141 SNVs and 99 562 short indels having moderate or high impact on 11 267 protein‐coding genes. On average, each genome contained heterozygous loss‐of‐function variants in 30 potentially embryonic lethal genes and 97 genes associated with developmental disorders. More than 50 inherited disorders and traits have been unravelled using the DBVDC variant catalogue, enabling genetic testing for breeding and diagnostics. This resource of annotated variants and their corresponding genotype frequencies constitutes a highly useful tool for the identification of potential variants causative for rare inherited disorders in dogs.     

Exomsequenzierung zur Identifizierung von Krankheitsgenen für seltene Syndrome

Background

Whole exome sequencing (WES) is the state-of-the-art method for identification of pathogenic mutations in patients with a Mendelian disorder. WES comprehensively covers the coding sequence of the genome and is a fast and cost-effective technique.

Purpose

As most of the technical difficulties have been overcome for WES, the major issue is data processing and analysis to find the pathogenic sequence variation among tens of thousands of sequence changes. Bioinformatic analysis pipelines for filtering sequence variants have to be adapted according to the patients and family members examined by WES and the most likely inheritance pattern underlying the disease.

Possible approaches

Based on 4 cases, different variant prioritization strategies which led to identification of the most likely causative changes in the index patients are described.