外显子组测序技术在人类疾病研究中的应用

外显子组测序是针对基因组中的蛋白质编码区,靶向富集外显子区域测序,以发现疾病相关遗传变异的技术。该技术近年越来越多地应用于发现人类基因组低频变异、鉴定单基因遗传病致病基因和肿瘤等复杂疾病易感基因研究,成为人类疾病相关变异研究的重要工具。综述了外显子组测序技术的基本原理及其在人类疾病相关基因研究中的应用。     

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。     

全基因组测序及其在遗传性疾病研究及诊断中的应用

最近,随着测序成本的不断降低,数据分析策略的不断提升,全基因组测序（whole-genome sequencing,WGS）已经在癌症、孟德尔遗传病、复杂疾病的致病基因检测中得到了一定运用,并逐步走向了临床诊断。全基因组测序不但可以检测编码区和非编码区的点突变（SNVs）和插入缺失（InDels）,还可以在全基因组范围内检测拷贝数变异（copy number variation,CNV）以及结构变异（structure variation,SV）。本文详细地介绍了全基因组测序的标准生物信息分析流程与方法,及其在疾病研究、临床诊断中的应用,并对全基因组测序在医学遗传学中的应用与研究进展,以及数据分析方面面临的挑战进行了概述。     

高通量测序筛查多巴反应性肌张力障碍家系突变基因

快速发展的高通量测序技术使遗传病家系突变基因的筛查鉴定成为可能,本研究通过全外显子测序、生物信息分析和PCR-测序技术筛选一个多巴反应性肌张力障碍(DRD)家系中可能的致病突变位点,从1 005个低频位点中选出在3个疾病个体至少有一个杂合突变的9个候选SNP,再通过DRD家系12个个体PCR扩增测序验证,新发现突变基因SLC18A1可能是该DRD家系的致病基因。此外,PCR和Sanger测序发现高通量外显子测序和信息分析的SNP分型准确性可高达96.3%,是一种遗传病家系突变基因筛查鉴定高效、准确的方法。     

一种基于二代测序辨识短串联重复序列长度变异的新方法及其在人类遗传疾病研究中的应用

二代测序技术的涌现推动了基因组学研究,特别是在疾病相关的遗传变异研究中发挥了重要作用．虽然大多数遗传变异类型都可以借助于各种二代测序分析工具进行检测,但是仍然存在局限性,比如短串联重复序列的长度变异．许多遗传疾病是由短串联重复序列的长度扩张导致的,尤其是亨廷顿病等多种神经系统疾病．然而,现在几乎没有工具能够利用二代测序检测长度大于测序读长的短串联重复序列变异．为了突破这一限制,我们开发了一个全新的方法,该方法基于双末端二代测序辨识短串联重复序列长度变异,并可估计其扩张长度,将其应用于一项基于全外显子组测序的运动神经元疾病临床研究中,成功地鉴定出致病的短串联重复序列长度扩张．该方法首次原创性地利用测序读长覆盖深度特征来解决短串联重复序列变异检测问题,在人类遗传疾病研究中具有广泛的应用价值,并且对于其他二代测序分析方法的开发具有启发性意义．     

一种基于二代测序辨识短串联重复序列长度变异的新方法及其在人类遗传疾病研究中的应用（英文）

二代测序技术的涌现推动了基因组学研究,特别是在疾病相关的遗传变异研究中发挥了重要作用.虽然大多数遗传变异类型都可以借助于各种二代测序分析工具进行检测,但是仍然存在局限性,比如短串联重复序列的长度变异.许多遗传疾病是由短串联重复序列的长度扩张导致的,尤其是亨廷顿病等多种神经系统疾病.然而,现在几乎没有工具能够利用二代测序检测长度大于测序读长的短串联重复序列变异.为了突破这一限制,我们开发了一个全新的方法,该方法基于双末端二代测序辨识短串联重复序列长度变异,并可估计其扩张长度,将其应用于一项基于全外显子组测序的运动神经元疾病临床研究中,成功地鉴定出致病的短串联重复序列长度扩张.该方法首次原创性地利用测序读长覆盖深度特征来解决短串联重复序列变异检测问题,在人类遗传疾病研究中具有广泛的应用价值,并且对于其他二代测序分析方法的开发具有启发性意义.     

稻瘟菌WD重复功能域中SSR的变异及其对蛋白结构的影响

含WD重复功能域的蛋白能够参与信号传导、转录调控、RNA剪切、细胞的凋亡等多种功能,在病原菌与寄主植物蛋白互作的过程中扮演着重要的角色。本研究分析了稻瘟病菌基因组中94个WD功能域基因编码区和调控区中SSR的组成、分布,并检测了7个蛋白编码区中SSR的变异及其对蛋白二级结构的影响。结果表明,WD功能域基因的编码区和调控区中都含有大量的SSR,但是SSR在这些基因的外显子区、内含子区、5’一UTR和3’一UTR区中SSR的组成和分布均不相同;编码区中三碱基和六碱基SSR分布较多,这些SSR基序大都表现为GC含量较高和其所编码的亲水性氨基酸出现的频率远远高于疏水性氨基酸的特点。且检测的7个WD功能域基因的编码区中的SSR位点均具有丰富的多态性,通过Antheprot（DPM）软件预测发现：SSR的变异对蛋白的二级结构有一定影响。这暗示着SSR的变异对致病相关基因的变异起着十分重要的作用。     

重大生殖疾病的分子机制研究

重大生殖疾病是一组严重影响生殖健康,病因和临床表现高度异质的疾病群,其中女性常见的有多囊卵巢综合征(PCOS)、卵巢早衰(POF)等,遗传因素在疾病的发生发展中起到重要作用。近年来,依靠高通量技术,如全基因组关联分析、全外显子组测序等,我国在重大生殖疾病的遗传学研究中取得了重要进展,主要包括对PCOS和POF大样本散发病例及其对照进行全基因组关联研究、家系患者的全外显子组或全基因组测序研究等,鉴定出多个遗传易感位点,获得大量候选基因的信息。虽然这些研究结果为解析疾病提供了大量线索,但是也提出了更多挑战。如何深入研究这些易感位点在疾病中的致病机制,及其在复杂疾病诊治中的转化应用成为日后的工作重点,现就相关分子机制研究进展做一简要论述。     

《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     

苹果酸度相关基因MdPH1的克隆、表达及亚细胞定位分析

以苹果属（Malus）植物沧江海棠（M.ombrophila Hand.-Mazz）的果实为材料,对其发育过程中苹果酸的含量进行测定,并结合转录组测序的方法筛选控制果实酸度的候选基因。结果显示：MdPH1候选基因的编码区包含2829 bp,编码942个氨基酸;基因组序列全长为4269 bp,包含8个外显子和7个内含子。对10份苹果种质资源中PH1基因序列的分析结果表明,该基因序列中存在22个单核苷酸多态性（SNP）,其中13个位于内含子区,9个位于外显子区;位于最后一个外显子上SNP（G/A）的变异导致了编码氨基酸从缬氨酸变为异亮氨酸。MdPH1蛋白包含8个跨膜结构域,其中蛋白N端包含3个跨膜结构域,C端包含5个跨膜结构域。系统进化分析结果显示,苹果中的PH家族成员与梨（Pyrus communis L.）中的PH家族成员聚集成一簇。组织特异性表达结果发现,MdPH1基因在苹果果实中的表达量最高,其次是叶、花和根,茎中表达量最低。亚细胞定位分析表明MdPH1蛋白定位于液泡膜上。     

Exome sequencing and arrayCGH detection of gene sequence and copy number variation between ILS and ISS mouse strains

It has been well documented that genetic factors can influence predisposition to develop alcoholism. While the underlying genomic changes may be of several types, two of the most common and disease associated are copy number variations (CNVs) and sequence alterations of protein coding regions. The goal of this study was to identify CNVs and single-nucleotide polymorphisms that occur in gene coding regions that may play a role in influencing the risk of an individual developing alcoholism. Toward this end, two mouse strains were used that have been selectively bred based on their differential sensitivity to alcohol: the Inbred long sleep (ILS) and Inbred short sleep (ISS) mouse strains. Differences in initial response to alcohol have been linked to risk for alcoholism, and the ILS/ISS strains are used to investigate the genetics of initial sensitivity to alcohol. Array comparative genomic hybridization (arrayCGH) and exome sequencing were conducted to identify CNVs and gene coding sequence differences, respectively, between ILS and ISS mice. Mouse arrayCGH was performed using catalog Agilent 1 × 244 k mouse arrays. Subsequently, exome sequencing was carried out using an Illumina HiSeq 2000 instrument. ArrayCGH detected 74 CNVs that were strain-specific (38 ILS/36 ISS), including several ISS-specific deletions that contained genes implicated in brain function and neurotransmitter release. Among several interesting coding variations detected by exome sequencing was the gain of a premature stop codon in the alpha-amylase 2B (AMY2B) gene specifically in the ILS strain. In total, exome sequencing detected 2,597 and 1,768 strain-specific exonic gene variants in the ILS and ISS mice, respectively. This study represents the most comprehensive and detailed genomic comparison of ILS and ISS mouse strains to date. The two complementary genome-wide approaches identified strain-specific CNVs and gene coding sequence variations that should provide strong candidates to contribute to the alcohol-related phenotypic differences associated with these strains.     

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.     

Exome sequencing as a tool for Mendelian disease gene discovery

Exome sequencing - the targeted sequencing of the subset of the human genome that is protein coding - is a powerful and cost-effective new tool for dissecting the genetic basis of diseases and traits that have proved to be intractable to conventional gene-discovery strategies. Over the past 2 years, experimental and analytical approaches relating to exome sequencing have established a rich framework for discovering the genes underlying unsolved Mendelian disorders. Additionally, exome sequencing is being adapted to explore the extent to which rare alleles explain the heritability of complex diseases and health-related traits. These advances also set the stage for applying exome and whole-genome sequencing to facilitate clinical diagnosis and personalized disease-risk profiling.     

Biomedical impact of splicing mutations revealed through exome sequencing

Splicing is a cellular mechanism, which dictates eukaryotic gene expression by removing the noncoding introns and ligating the coding exons in the form of a messenger RNA molecule. Alternative splicing (AS) adds a major level of complexity to this mechanism and thus to the regulation of gene expression. This widespread cellular phenomenon generates multiple messenger RNA isoforms from a single gene, by utilizing alternative splice sites and promoting different exon-intron inclusions and exclusions. AS greatly increases the coding potential of eukaryotic genomes and hence contributes to the diversity of eukaryotic proteomes. Mutations that lead to disruptions of either constitutive splicing or AS cause several diseases, among which are myotonic dystrophy and cystic fibrosis. Aberrant splicing is also well established in cancer states. Identification of rare novel mutations associated with splice-site recognition, and splicing regulation in general, could provide further insight into genetic mechanisms of rare diseases. Here, disease relevance of aberrant splicing is reviewed, and the new methodological approach of starting from disease phenotype, employing exome sequencing and identifying rare mutations affecting splicing regulation is described. Exome sequencing has emerged as a reliable method for finding sequence variations associated with various disease states. To date, genetic studies using exome sequencing to find disease-causing mutations have focused on the discovery of nonsynonymous single nucleotide polymorphisms that alter amino acids or introduce early stop codons, or on the use of exome sequencing as a means to genotype known single nucleotide polymorphisms. The involvement of splicing mutations in inherited diseases has received little attention and thus likely occurs more frequently than currently estimated. Studies of exome sequencing followed by molecular and bioinformatic analyses have great potential to reveal the high impact of splicing mutations underlying human disease.     

Variant detection sensitivity and biases in whole genome and exome sequencing

Background

Less than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions.

Results

We have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS.

Conclusions

From an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-247) contains supplementary material, which is available to authorized users.     

Estimation of Copy Number Alterations from Exome Sequencing Data

Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.     

Exome sequencing reveals comprehensive genomic alterations across eight cancer cell lines

It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the "exome") can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ～95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies.     

Genome wide association studies and prion disease

Over the last decade remarkable advances in genotyping and sequencing technology have resulted in hundreds of novel gene associations with disease. These have typically involved high frequency alleles in common diseases and with the advent of next generation sequencing, disease causing recessive mutations in rare inherited syndromes. Here we discuss the impact of these advances and other gene discovery methods in the prion diseases. Several quantitative trait loci in mouse have been mapped and their human counterparts analysed (HECTD2, CPNE8); other candidate genes regions have been chosen for functional reasons (SPRN, CTSD). Human genome wide association has been done in variant Creutzfeldt-Jakob disease (CJD) and are ongoing in larger collections of sporadic CJD with findings around, but not clearly beyond, the levels of statistical significance required in these studies (THRB-RARB, STMN2). Future work will include closer integration of animal and human genetic studies, larger and combined genome wide association, analysis of structural genetic variantion and next generation sequencing studies involving the entire coding exome or genome.     

Performance comparison of exome DNA sequencing technologies

Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. We present a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. Our results suggest that the Nimblegen platform, which is the only one to use high-density overlapping baits, covers fewer genomic regions than the other platforms but requires the least amount of sequencing to sensitively detect small variants. Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina captures untranslated regions, which are not targeted by the Nimblegen and Agilent platforms. We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect additional small variants missed by WGS.