拷贝数目变异研究进展

人类基因组中的DNA 拷贝数目变异Copy Number Variation（CNVs）一直以来都认为分布频率较低，并与疾病的发生以及不同个体对于疾病的易感性相关。随着Hapmap研究计划的顺利进行，研究者逐渐发现CNVs广泛分布于人基因组中。黑猩猩和实验室近交系的小鼠基因组也存在CNVs的广泛分布。目前已有多项研究证明了CNVs是人类基因组变异的主要原因，本综述将从CNVs的定义及其在健康人群的分布研究以及与疾病的相关性研究，CNVs的形成机制和CNVs的进化等方面对最新的CNVs研究进展做较为全面概述。     

全基因组SNPs和CNVs与精神分裂症的关联分析研究

精神分裂症（SP）是典型的复杂性多基因遗传疾病,随着人类基因组测序计划的完成和基因组单倍体图谱计划的实施,应用人类基因组中数以百万计的单核苷酸多态性（SNPs）和拷贝数变异（CNVs）遗传标记对精神分裂症进行全基因组关联分析,为进一步了解控制人类SP发生的遗传特征提供了重要的线索。本文就全基因组SNPs和CNVs与精神分裂症的关联分析研究做一综述。     

11q24-q25缺失2例临床表型及文献复习

目的应用全基因组微阵列芯片平台,对临床发现的多发性畸形患儿进行全基因组拷贝数变异（CNVs）的检测,并寻找基因型与临床表型的关系。方法采用cytogenetic whole genome芯片筛查全基因组CNVs,针对发现的CNVs进行分析,参照国际基因组CNVs多态性数据库除外正常人群多态性CNVs。结合本研究2例与已报道的Jacobsen综合征（JBS）患儿的临床表型进行比较。结果 2例患儿SNP芯片分析为11q24-q25缺失（7.5和5.6Mb）,均为末端的非单纯性缺失,例1存在12号染色体短臂的较大片段重复（11.5Mb）,例2存在11号染色体短臂的大片段重复（32.5Mb）。2例共同缺失的部分均为JBS的关键区段,但临床表型与已报道的JBS患儿有所区别。2例均表现为头面部畸形、心血管系统异常和头颅影像学异常,均未发现血液系统异常。例1还表现为隐睾,例2表现为脾肿大。结论对临床上难以诊断的多发性畸形可采用全基因组CNVs检测,以帮助明确诊断,对于丰富这一区段临床表型信息具有重要意义,尤其针对罕见疾病,更多的相似报道的后续出现,才能使建立表型-基因型关联性成为可能。     

68例智力低下/发育迟缓患儿基因组拷贝数变异分析

目的应用单核苷酸多态性微阵列技术(single nucleotide polymorphism microarray technology, SNP array)对不明原因智力低下/发育迟缓患儿进行全基因组拷贝数变异(copy number variations, CNVs)分析, 明确致病性CNVs所致染色体失衡, 并分析CNVs的致病机制, 为遗传咨询及产前诊断提供理论基础。方法根据入组标准, 收集智力低下/发育迟缓患儿68例, 应用SNP array对患儿进行染色体基因组CNVs检测, 对检出的CNVs通过对比国际公认基因组数据库, 参考美国医学遗传学与基因组学学会(ACMG)变异分类指南(2019), 判断CNVs的临床意义。结果 68例不明原因智力低下/发育迟缓患儿中, 24例患儿明确诊断, 共检出27个致病性CNVs, 包括11个重复和16个缺失, 分布于16条染色体, 涉及11种综合征。SNP array技术对不明原因的智力低下/发育迟缓患儿的诊断率为35.3%(24/68)。结论染色体基因组CNVs是导致不明原因智力低下/发育迟缓发生的主要遗传学致病原因, SNP ar...     

结构性拷贝数增加的解读标准:来自美国医学遗传学与基因组学学会(ACMG)和临床基因组资源中心(ClinGen)的建议

基因组拷贝数变异(copy number variants,CNVs)是人类遗传病的重要致病原因,也是儿科神经发育障碍和多种先天性畸形、产前胎儿超声异常等疾病的必检项目。尽管CNVs的检测技术日趋成熟,但其临床意义的解读却仍不够规范。2020年,美国医学遗传学与基因组学学会(American College of Medical Genetics and Genomics,ACMG)和临床基因组资源中心(Clinical Genome Resource,ClinGen)基于循证原则,采用定量计分,就结构性(constitutional)基因组CNVs的致病性评估和临床报告制定了推荐指南。本文对该指南中涉及拷贝数增加的分析要点进行了详细的解读,并利用6个不同类型的案例来展示如何正确使用打分系统,以鼓励临床诊断实验室根据这一专业标准对检测出的基因组变异开展解读、报告,以期提升遗传诊断报告中拷贝数增加临床评估的正确性和一致性。     

基于2型糖尿病染色体基因拷贝数变异研究

目的探讨2型糖尿病患者基因拷贝数变异(copy number variations,CNVs)在染色体上的分布数据,为该病发病机制研究提供理论基础。方法采用测序仪对2型糖尿病患者的DNA-pool进行全基因组高通量重测序,用生物学软件对测序数据进行分析。结果通过生物学分析在23对染色体上共发现4713个CNVs,其中1号染色体上分布最多,有416个CNVs;Y染色体上最少,仅有46个CNVs;其他染色体上CNVs分布数量在这两条染色体之间。结论本研究显示2型糖尿病患者基因拷贝数变异(CNVs)在染色体上广泛存在。     

单核苷酸多态性芯片与染色体核型分析在唐氏筛查高风险孕妇产前诊断中的比较研究

目的:探讨单核苷酸多态性芯片(SNP array)在唐氏筛查高风险孕妇胎儿染色体分析中的应用价值。方法:选取312例因唐氏筛查高风险的孕妇,行羊膜腔穿刺术后获得羊水,对羊水进行G显带核型分析和SNP array检测,比较核型分析与SNP array检测结果,并按年龄分组比较拷贝数变异(CNVs)的发生率差别。结果:核型分析和SNP array均准确发现2例21三体(0.64%),6例核型分析提示染色体平衡重组(1.92%)的样本经SNP array分析证实不存在重排片段重复或缺失。在303例核型正常的胎儿羊水细胞中,SNP array检测发现176例CNVs,其中良性CNVs 106例,临床意义不明确的CNVs(VOUS)61例,新发CNVs(de novo CNVs)9例,未发现已知的致病性CNVs。唐氏筛查高风险组与唐氏筛查高风险合并高龄组CNVs的分布差别无统计学意义(P0.05)。此外,本研究中首次报道14种CNVs。结论:SNP array可进一步确定核型分析的平衡易位是否存在染色体微缺失/重复。在核型正常的胎儿中,SNP array可检测出大量拷贝数异常,发现14种新的CNVs但现有数据库无法判断其临床意义,需进一步研究确认。此外,孕妇年龄对胎儿基因组中新发CNVs的发生率无明显影响。     

54例自然流产和胚胎停育的绒毛微阵列芯片结果分析

目的应用微阵列比较基因组杂交技术(array-based comparative genomic hybridization,array-CGH)检测54例自然流产和胚胎停育的绒毛的全基因组拷贝数变异(copy number variations,CNVs),探讨该技术的临床应用价值。方法采用Affymetrix Cytoscan optima芯片对54例自然流产和胚胎停育的绒毛组织进行基因组CNVs检测,用相应软件对检测结果进行分析,分析其是否具有致病性。结果全部54例标本均成功获得芯片检测结果,成功率100%。共检测出异常30例(55.6%),其中非整倍体27例(50.9%),单纯性CNVs 2例,非整倍体合并CNVs 1例,单亲二倍体1例。结论自然流产和胚胎停育的绒毛染色体微阵列比较基因组杂交检测成功率高,为临床咨询流产和胚胎停育原因提供了一种更有效地遗传学检测方法,array-CGH芯片检测是目前临床检测流产绒毛是否存在基因异常最有效的方法。     

微阵列比较基因组杂交检测和分析一例46,X0,+der(?)胎儿的全基因组拷贝数变化

目的检测和分析一例46,X0,+der(?)胎儿的全基因组拷贝数变化(CNVs),确定胎儿的核型,探讨微阵列比较基因组杂交(array-CGH)在临床细胞遗传诊断中运用的可行性和优越性。方法对胎儿进行常规G显带染色体分析,应用array-CGH芯片进行全基因组高分辨率扫描和分析,RT-qPCR验证array-CGH的结果。结果G显带染色体分析显示胎儿的核型为46,X0,+der(?)。Array-CGH显示衍生染色体为Y染色体,且不存在CNVs;另外,共检测出了118个亚显微CNVs。RT-qPCR证明array-CGH的结果是准确的。结论与传统的细胞遗传分析方法相比,array-CGH具有高分辨率、高通量和高准确性等优点,为亚显微水平染色体畸变的检测提供了一种新型的强大的分析平台。     

产前诊断胎儿泌尿系统畸形与染色体1q21.1微缺失

目的 应用微阵列比较基因组杂交技术探讨胎儿先天性泌尿系统畸形的遗传学病因.方法 选取32例经产前超声检查提示发生不同程度泌尿系统畸形并且常规G显带核型分析方法未发现异常的胎儿病例及其父母的DNA,按照标准的Affymetrix cytogenetic 2.7M芯片的操作手册进行杂交、洗涤及全基因组扫描,应用配套的CHAS软件分析结果.结果 微阵列比较基因组杂交技术检测发现9例胎儿基因组发生了不平衡的拷贝数变异(copy number variations,CNVs),检出率为28％.其中4例CNVs遗传自亲代(12.5％);2例CNVs在相关数据库中提示在正常人基因组中存在(6％);3例是新发的致病性CNVs(9％),并且这3例胎儿样本均发生了染色体1q21.1微缺失和微重复,异常片段内包含与泌尿生殖系统功能密切相关的PDZK1基因.结论 先天性泌尿系统畸形胎儿基因组发生不平衡畸变的几率约为28％,其中致病性的基因组不平衡异常约占9％.染色体1q21.1区带DNA拷贝数改变是导致先天性泌尿系统畸形的病因之一,其致病机制可能与PDZK1基因的异常表达有关.     

Noncoding copy-number variations are associated with congenital limb malformation

PurposeCopy-number variants (CNVs) are generally interpreted by linking the effects of gene dosage with phenotypes. The clinical interpretation of noncoding CNVs remains challenging. We investigated the percentage of disease-associated CNVs in patients with congenital limb malformations that affect noncoding cis-regulatory sequences versus genes sensitive to gene dosage effects.MethodsWe applied high-resolution copy-number analysis to 340 unrelated individuals with isolated limb malformation. To investigate novel candidate CNVs, we re-engineered human CNVs in mice using clustered regularly interspaced short palindromic repeats (CRISPR)–based genome editing.ResultsOf the individuals studied, 10% harbored CNVs segregating with the phenotype in the affected families. We identified 31 CNVs previously associated with congenital limb malformations and four novel candidate CNVs. Most of the disease-associated CNVs (57%) affected the noncoding cis-regulatory genome, while only 43% included a known disease gene and were likely to result from gene dosage effects. In transgenic mice harboring four novel candidate CNVs, we observed altered gene expression in all cases, indicating that the CNVs had a regulatory effect either by changing the enhancer dosage or altering the topological associating domain architecture of the genome.ConclusionOur findings suggest that CNVs affecting noncoding regulatory elements are a major cause of congenital limb malformations.     

Association of common copy number variations with diseases北大核心CSCD

Genomic polymorphisms come in various forms including single nucleotide variations, translocations, insertions and copy number variations (CNVs). As a form of structural variation, the CNVs comprise common and rare forms based on their populational frequencies. Studies have demonstrated that certain CNVs are associated with risks for neuro-developmental diseases, viral infections, chronic inflammations, and cancers. With the development of high-resolution genome typing technologies such as microarrays and whole genome sequencing, the human genomic CNVs map has been continuously improved and refined. In-depth study of CNVs not only can provide comprehensive understanding for their structural variations and genetic evolution, but also provide new insights into genetic factors contributing to such diseases. In this paper, the general characteristics, pathogenesis and detection methods for the CNVs, as well as their association with human diseases are reviewed. © 2016, West China University of Medical Sciences. All rights reserved.     

Genomic disorders 20 years on—mechanisms for clinical manifestations

Genomic disorders result from copy‐number variants (CNVs) or submicroscopic rearrangements of the genome rather than from single nucleotide variants (SNVs). Diverse technologies, including array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) microarrays, and more recently, whole genome sequencing and whole‐exome sequencing, have enabled robust genome‐wide unbiased detection of CNVs in affected individuals and in reportedly healthy controls. Sequencing of breakpoint junctions has allowed for elucidation of upstream mechanisms leading to genomic instability and resultant structural variation, whereas studies of the association between CNVs and specific diseases or susceptibility to morbid traits have enhanced our understanding of the downstream effects. In this review, we discuss the hallmarks of genomic disorders as they were defined during the first decade of the field, including genomic instability and the mechanism for rearrangement defined as nonallelic homologous recombination (NAHR); recurrent vs nonrecurrent rearrangements; and gene dosage sensitivity. Moreover, we highlight the exciting advances of the second decade of this field, including a deeper understanding of genomic instability and the mechanisms underlying complex rearrangements, mechanisms for constitutional and somatic chromosomal rearrangements, structural intra‐species polymorphisms and susceptibility to NAHR, the role of CNVs in the context of genome‐wide copy number and single nucleotide variation, and the contribution of noncoding CNVs to human disease.     

Profiling of copy number variations (CNVs) in healthy individuals from three ethnic groups using a human genome 32 K BAC-clone-based array

To further explore the extent of structural large-scale variation in the human genome, we assessed copy number variations (CNVs) in a series of 71 healthy subjects from three ethnic groups. CNVs were analyzed using comparative genomic hybridization (CGH) to a BAC array covering the human genome, using DNA extracted from peripheral blood, thus avoiding any culture-induced rearrangements. By applying a newly developed computational algorithm based on Hidden Markov modeling, we identified 1,078 autosomal CNVs, including at least two neighboring/overlapping BACs, which represent 315 distinct regions. The average size of the sequence polymorphisms was approximately 350 kb and involved in total approximately 117 Mb or approximately 3.5% of the genome. Gains were about four times more common than deletions, and segmental duplications (SDs) were overrepresented, especially in larger deletion variants. This strengthens the notion that SDs often define hotspots of chromosomal rearrangements. Over 60% of the identified autosomal rearrangements match previously reported CNVs, recognized with various platforms. However, results from chromosome X do not agree well with the previously annotated CNVs. Furthermore, data from single BACs deviating in copy number suggest that our above estimate of total variation is conservative. This report contributes to the establishment of the common baseline for CNV, which is an important resource in human genetics.     

CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing

Copy number variation (CNV) in the genome is a complex phenomenon, and not completely understood. We have developed a method, CNVnator, for CNV discovery and genotyping from read-depth (RD) analysis of personal genome sequencing. Our method is based on combining the established mean-shift approach with additional refinements (multiple-bandwidth partitioning and GC correction) to broaden the range of discovered CNVs. We calibrated CNVnator using the extensive validation performed by the 1000 Genomes Project. Because of this, we could use CNVnator for CNV discovery and genotyping in a population and characterization of atypical CNVs, such as de novo and multi-allelic events. Overall, for CNVs accessible by RD, CNVnator has high sensitivity (86%-96%), low false-discovery rate (3%-20%), high genotyping accuracy (93%-95%), and high resolution in breakpoint discovery (<200 bp in 90% of cases with high sequencing coverage). Furthermore, CNVnator is complementary in a straightforward way to split-read and read-pair approaches: It misses CNVs created by retrotransposable elements, but more than half of the validated CNVs that it identifies are not detected by split-read or read-pair. By genotyping CNVs in the CEPH, Yoruba, and Chinese-Japanese populations, we estimated that at least 11% of all CNV loci involve complex, multi-allelic events, a considerably higher estimate than reported earlier. Moreover, among these events, we observed cases with allele distribution strongly deviating from Hardy-Weinberg equilibrium, possibly implying selection on certain complex loci. Finally, by combining discovery and genotyping, we identified six potential de novo CNVs in two family trios.     

Segmental Copy-Number Variation Observed in Japanese by Array-CGH

Segmental copy-number variations (CNVs) may contribute to genetic variation in humans. In this study, we examined 80 unrelated Japanese individuals using a microarray (2,238 Bac-clones) based comparative genomic hybridization (array-CGH) assay. We found a total of 251 CNVs at 30 different regions in the genome; of these, 14 (termed 'rare' CNVs) were found individually located within distinct genomic regions of 14 individuals, while the remaining 16 CNV regions (termed 'polymorphic' CNVs) were observed in two or more individuals. The rare CNVs were confirmed by quantitative polymerase chain reactions, and characterized more precisely than in previous reports using array CGH. Distinctive features of these CNVs were observed: most prominent was that the majority of the rare CNVs presented on Bac-clones that did not overlap with regions of segmental duplication. About 90% of the polymorphic CNVs observed in this population had been previously identified, with the majority of those polymorphic CNVs located in regions of segmental duplication. It is likely, therefore, that rare and polymorphic CNVs arise through different genetic mechanisms. Since more than half of the rare CNVs are novel, it is also likely that different human populations bear different CNVs, as is the case for single-nucleotide-polymorphisms (SNPs) and insertion-deletion (indel) polymorphisms.     

Maternal copy-number variations in the DMD gene as secondary findings in noninvasive prenatal screening

PurposeNoninvasive prenatal screening (NIPS) using genome sequencing also reveals maternal copy-number variations (CNVs). Those CNVs can be clinically actionable or harmful to the fetus if inherited. CNVs in the DMD gene potentially causing dystrophinopathies are among the most commonly observed maternal CNVs. We present our experience with maternal DMD gene CNVs detected by NIPS.MethodsWe analyzed the data of maternal CNVs detected in the DMD gene revealed by NIPS.ResultsOf 26,123 NIPS analyses, 16 maternal CNVs in the DMD gene were detected (1/1632 pregnant women). Variant classification regarding pathogenicity and phenotypic severity was based on public databases, segregation analysis in the family, and prediction of the effect on the reading frame. Ten CNVs were classified as pathogenic, four as benign, and two remained unclassified.ConclusionNIPS leverages CNV screening in the general population of pregnant women. We implemented a strategy for the interpretation and the return of maternal CNVs in the DMD gene detected by NIPS.     

Identification of rare copy number variants in high burden schizophrenia families

Over the last years, genome‐wide studies consistently showed an increased burden of rare copy number variants (CNVs) in schizophrenia patients, supporting the “common disease, rare variant” hypothesis in at least a subset of patients. We hypothesize that in families with a high burden of disease, and thus probably a high genetic load influencing disease susceptibility, rare CNVs might be involved in the etiology of schizophrenia. We performed a genome‐wide CNV analysis in the index patients of eight families with multiple schizophrenia affected members, and consecutively performed a detailed family analysis for the most relevant CNVs. One index patient showed a DRD5 containing duplication. A second index patient presented with an NRXN1 containing deletion and two adjacent duplications containing MYT1L and SNTG2. Detailed analysis in the subsequent families showed segregation of the identified CNVs. With this study we show the importance of screening high burden families for rare CNVs, which will not only broaden our knowledge concerning the molecular genetic mechanisms involved in schizophrenia but also allow the use of the obtained genetic data to provide better clinical care to these families in general and to non‐symptomatic causal CNV carriers in particular. © 2013 Wiley Periodicals, Inc.     

Identification of copy number variants in horses

Copy number variants (CNVs) represent a substantial source of genetic variation in mammals. However, the occurrence of CNVs in horses and their subsequent impact on phenotypic variation is unknown. We performed a study to identify CNVs in 16 horses representing 15 distinct breeds (Equus caballus) and an individual gray donkey (Equus asinus) using a whole-exome tiling array and the array comparative genomic hybridization methodology. We identified 2368 CNVs ranging in size from 197 bp to 3.5 Mb. Merging identical CNVs from each animal yielded 775 CNV regions (CNVRs), involving 1707 protein- and RNA-coding genes. The number of CNVs per animal ranged from 55 to 347, with median and mean sizes of CNVs of 5.3 kb and 99.4 kb, respectively. Approximately 6% of the genes investigated were affected by a CNV. Biological process enrichment analysis indicated CNVs primarily affected genes involved in sensory perception, signal transduction, and metabolism. CNVs also were identified in genes regulating blood group antigens, coat color, fecundity, lactation, keratin formation, neuronal homeostasis, and height in other species. Collectively, these data are the first report of copy number variation in horses and suggest that CNVs are common in the horse genome and may modulate biological processes underlying different traits observed among horses and horse breeds.