Sensitive and specific real-time polymerase chain reaction assays to accurately determine copy number variations (CNVs) of human complement C4A, C4B, C4-long, C4-short, and RCCX modules: elucidation of C4 CNVs in 50 consanguineous subjects with defined HLA genotypes

Recent comparative genome hybridization studies revealed that hundreds to thousands of human genomic loci can have interindividual copy number variations (CNVs). One of such CNV loci in the HLA codes for the immune effector protein complement component C4. Sensitive, specific, and accurate assays to interrogate the C4 CNV and its associated polymorphisms by using submicrogram quantities of genomic DNA are needed for high throughput epidemiologic studies of C4 CNVs in autoimmune, infectious, and neurological diseases. Quantitative real-time PCR (qPCR) assays were developed using TaqMan chemistry and based on sequences specific for C4A and C4B genes, structural characteristics corresponding to the long and short forms of C4 genes, and the breakpoint region of RP-C4-CYP21-TNX (RCCX) modular duplication. Assignments for gene copy numbers were achieved by relative standard curve methods using cloned C4 genomic DNA covering 6 logs of DNA concentrations for calibrations. The accuracies of test results were cross-confirmed internally in each sample, as the sum of C4A plus C4B equals to the sum of C4L plus C4S or the total copy number of RCCX modules. These qPCR assays were applied to determine C4 CNVs from samples of 50 consanguineous subjects who were mostly homozygous in HLA genotypes. The results revealed eight HLA haplotypes with single C4 genes in monomodular RCCX that are associated with multiple autoimmune and infectious diseases and 32 bimodular, 4 trimodular, and one quadrimodular RCCX. These C4 qPCR assays are proven to be robust, sensitive, and reliable, as they have contributed to the elucidation of C4 CNVs in >1000 human samples with autoimmune and neurological diseases.     

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.     

Whole Genome Distribution and Ethnic Differentiation of Copy Number Variation in Caucasian and Asian Populations

Although copy number variation (CNV) has recently received much attention as a form of structure variation within the human genome, knowledge is still inadequate on fundamental CNV characteristics such as occurrence rate, genomic distribution and ethnic differentiation. In the present study, we used the Affymetrix GeneChip® Mapping 500K Array to discover and characterize CNVs in the human genome and to study ethnic differences of CNVs between Caucasians and Asians. Three thousand and nineteen CNVs, including 2381 CNVs in autosomes and 638 CNVs in X chromosome, from 985 Caucasian and 692 Asian individuals were identified, with a mean length of 296 kb. Among these CNVs, 190 had frequencies greater than 1% in at least one ethnic group, and 109 showed significant ethnic differences in frequencies (p<0.01). After merging overlapping CNVs, 1135 copy number variation regions (CNVRs), covering approximately 439 Mb (14.3%) of the human genome, were obtained. Our findings of ethnic differentiation of CNVs, along with the newly constructed CNV genomic map, extend our knowledge on the structural variation in the human genome and may furnish a basis for understanding the genomic differentiation of complex traits across ethnic groups.     

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.     

Short Copy Number Variations Potentially Associated with Tonic Immobility Responses in Newly Hatched Chicks

Introduction

Tonic immobility (TI) is fear-induced freezing that animals may undergo when confronted by a threat. It is principally observed in prey species as defence mechanisms. In our preliminary research, we detected large inter-individual variations in the frequency and duration of freezing behavior among newly hatched domestic chicks (Gallus gallus). In this study we aim to identify the copy number variations (CNVs) in the genome of chicks as genetic candidates that underlie the behavioral plasticity to fearful stimuli.

Methods

A total of 110 domestic chicks were used for an association study between TI responses and copy number polymorphisms. Array comparative genomic hybridization (aCGH) was conducted between chicks with high and low TI scores using an Agilent 4×180 custom microarray. We specifically focused on 3 genomic regions (>60 Mb) of chromosome 1 where previous quantitative trait loci (QTL) analysis showed significant F-values for fearful responses.

Results

ACGH successfully detected short CNVs within the regions overlapping 3 QTL peaks. Eleven of these identified loci were validated by real-time quantitative polymerase chain reaction (qPCR) as copy number polymorphisms. Although there wkas no significant p value in the correlation analysis between TI scores and the relative copy number within each breed, several CNV loci showed significant differences in the relative copy number between 2 breeds of chicken (White Leghorn and Nagoya) which had different quantitative characteristics of fear-induced responses.

Conclusion

Our data shows the potential CNVs that may be responsible for innate fear response in domestic chicks.     

拷贝数变异: 基因组多样性的新形式

基因拷贝数变异是指DNA片段大小范围从kb到Mb的亚微观突变, 是一可能具有致病性、良性或未知临床意义的基因组改变。Fosmid末端配对序列比较策略、比较基因组杂交芯片是当前较多使用的检测手段。染色体非等位的同源重排、非同源突变和非b DNA结构是造成基因组拷贝数变异的重要原因。拷贝数变异可导致不同程度的基因表达差异, 对正常表型的构成及疾病的发生发展具有一定作用。文章在总结基因拷贝数变异的认识过程和研究策略的基础上, 分析了拷贝数变异的形成和作用机制, 介绍了第一代人类基因组拷贝数变异图谱, 阐述了拷贝数变异研究的临床意义, 提示在探索疾病相关的遗传变异时不能错失拷贝数变异这一基因组多样性的新形式。     

A quantitative assay to detect α-thalassemia deletions and triplications using multiplex nested real-time quantitative polymerase chain reaction

Increasing evidence indicates that copy number variants (CNVs) have great relevance to common human diseases. In α-thalassemia, clinical phenotypes are related to genotypes, specifically copy number changes in the human α-globin gene cluster. Assays are available for high-throughput screening of unknown CNVs genome-wide and also for targeted CNV genotyping at loci associated with genetic disorders. Here we describe a universal quantitative approach based on nested real-time quantitative polymerase chain reaction for accurate determination of copy numbers at multiple particular gene loci. We used the α-globin gene as a model system, obtaining the reproducibility and sensitivity to analyze different gene copies and testing 95 DNA samples with 16 different known genotypes. Our results showed that this approach has high sensitivity and low standard deviations for correctly genotyping DNA samples containing different copy numbers of the α1 and α2 globin genes. Our method is rapid, simple, and reliable, and it could be used to simultaneously screen for α-thalassemia deletions or triplications. Moreover, it has potential as a versatile technology for the rapid genotyping of known CNVs in a targeted region.     

Origins and breakpoint analyses of copy number variations: up close and personal

Array-based methods have enabled the detection of many genomic gains and losses. These are stated as copy number variants (CNVs) and comprise up to 13% of the human genome. Based on their breakpoints and modes of formation CNVs are termed recurrent or nonrecurrent. Recurrent CNVs are flanked by low copy repeats and are of a fixed size. They arise as a result of misalignment during meiosis by a mechanism named nonallelic homologous recombination. Several of such recurrent CNVs have been linked to human diseases. Nonrecurrent CNVs, which are not flanked by low copy repeats, are of variable size and may arise via mechanisms like nonhomologous end joining and replication-based mechanisms described by the fork stalling and template switching and microhomology-mediated break-induced replication models. It is becoming clear that most disease-causing CNVs are nonrecurrent and generally arise via replication-based mechanisms. Furthermore, it is now appreciated that genomic features other than low copy repeats play a role in the formation of nonrecurrent CNVs. This review will discuss the different mechanisms of CNV formation and how high resolution analyses of CNV breakpoints have added to our knowledge of their precise structure.     

What a difference copy number variation makes

DNA copy number variation (CNV) represents a considerable source of human genetic diversity. Recently,1 a global map of copy number variation in the human genome has been drawn up which reveals not only the ubiquity but also the complexity of this type of variation. Thus, two human genomes may differ by more than 20 Mb and it is likely that the full extent of CNV still remains to be discovered. Nearly 3000 genes are associated with CNV. This high degree of variability with regard to gene copy number between two individuals challenges definitions of normality. Many CNVs are located in regions of complex genomic structure and this currently limits the extent to which these variants can be genotyped by using tagging SNPs. However, some CNVs are already amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be determined.     

Copy number polymorphism in plant genomes

Copy number variants (CNVs) are genomic rearrangements resulting from gains or losses of DNA segments. Typically, the term refers to rearrangements of sequences larger than 1 kb. This type of polymorphism has recently been shown to be a key contributor to intra-species genetic variation, along with single-nucleotide polymorphisms and short insertion-deletion polymorphisms. Over the last decade, a growing number of studies have highlighted the importance of copy number variation (CNV) as a factor affecting human phenotype and individual CNVs have been linked to risks for severe diseases. In plants, the exploration of the extent and role of CNV is still just beginning. Initial genomic analyses indicate that CNVs are prevalent in plants and have greatly affected plant genome evolution. Many CNV events have been observed in outcrossing and autogamous species. CNVs are usually found on all chromosomes, with CNV hotspots interspersed with regions of very low genetic variation. Although CNV is mainly associated with intergenic regions, many CNVs encompass protein-coding genes. The collected data suggest that CNV mainly affects the members of large families of functionally redundant genes. Thus, the effects of individual CNV events on phenotype are usually modest. Nevertheless, there are many cases in which CNVs for specific genes have been linked to important traits such as flowering time, plant height and resistance to biotic and abiotic stress. Recent reports suggest that CNVs may form rapidly in response to stress.     

Identification and functional characterization of copy number variations in diverse chicken breeds

Background

The detection and functional characterization of genomic structural variations are important for understanding the landscape of genetic variation in the chicken. A recently recognized aspect of genomic structural variation, called copy number variation (CNV), is gaining interest in chicken genomic studies. The aim of the present study was to investigate the pattern and functional characterization of CNVs in five characteristic chicken breeds, which will be important for future studies associating phenotype with chicken genome architecture.

Results

Using a commercial 385 K array-based comparative genomic hybridization (aCGH) genome array, we performed CNV discovery using 10 chicken samples from four local Chinese breeds and the French breed Houdan chicken. The female Anka broiler was used as a reference. A total of 281 copy number variation regions (CNVR) were identified, covering 12.8 Mb of polymorphic sequences or 1.07% of the entire chicken genome. The functional annotation of CNVRs indicated that these regions completely or partially overlapped with 231 genes and 1032 quantitative traits loci, suggesting these CNVs have important functions and might be promising resources for exploring differences among various breeds. In addition, we employed quantitative PCR (qPCR) to further validate several copy number variable genes, such as prolactin receptor, endothelin 3 (EDN3), suppressor of cytokine signaling 2, CD8a molecule, with important functions, and the results suggested that EDN3 might be a molecular marker for the selection of dark skin color in poultry production. Moreover, we also identified a new CNVR (chr24: 3484617–3512275), encoding the sortilin-related receptor gene, with copy number changes in only black-bone chicken.

Conclusions

Here, we report a genome-wide analysis of the CNVs in five chicken breeds using aCGH. The association between EDN3 and melanoblast proliferation was further confirmed using qPCR. These results provide additional information for understanding genomic variation and related phenotypic characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-934) contains supplementary material, which is available to authorized users.     

The contribution of de novo and rare inherited copy number changes to congenital heart disease in an unselected sample of children with conotruncal defects or hypoplastic left heart disease

Congenital heart disease (CHD) is the most common congenital malformation, with evidence of a strong genetic component. We analyzed data from 223 consecutively ascertained families, each consisting of at least one child affected by a conotruncal defect (CNT) or hypoplastic left heart disease (HLHS) and both parents. The NimbleGen HD2-2.1 comparative genomic hybridization platform was used to identify de novo and rare inherited copy number variants (CNVs). Excluding 10 cases with 22q11.2 DiGeorge deletions, we validated de novo CNVs in 8 % of 148 probands with CNTs, 12.7 % of 71 probands with HLHS and none in 4 probands with both. Only 2 % of control families showed a de novo CNV. We also identified a group of ultra-rare inherited CNVs that occurred de novo in our sample, contained a candidate gene for CHD, recurred in our sample or were present in an affected sibling. We confirmed the contribution to CHD of copy number changes in genes such as GATA4 and NODAL and identified several genes in novel recurrent CNVs that may point to novel CHD candidate loci. We also found CNVs previously associated with highly variable phenotypes and reduced penetrance, such as dup 1q21.1, dup 16p13.11, dup 15q11.2-13, dup 22q11.2, and del 2q23.1. We found that the presence of extra-cardiac anomalies was not related to the frequency of CNVs, and that there was no significant difference in CNV frequency or specificity between the probands with CNT and HLHS. In agreement with other series, we identified likely causal CNVs in 5.6 % of our total sample, half of which were de novo.     

Identification of copy number variants on human chromosome 22 in patients with a variety of clinical findings

The aims of this study were to create a copy number variant (CNV) profile of human chromosome 22 and to establish a genotype-phenotype correlation for patients with genomic abnormalities on chromosome 22. Thus, 1,654 consecutive pediatric patients with a diversity of clinical findings were evaluated by high-resolution chromosomal microarray analysis (CMA). We identified 25 individuals with abnormal CNVs on chromosome 22, representing 1.5% of the cases analyzed in this cohort. Meanwhile, we detected 1,298 benign CNVs on this chromosome in these individuals. Twenty-one of the 25 abnormal CNVs and the majority of the benign CNVs occurred through involvement of the 8 unstable genomic regions enriched with low copy repeats (LCR22A-H). The highly dynamic status of LCR22s within the 22q11 region facilitates the formation of diverse genomic abnormalities. This CNV profile provides a general perspective of the spectrum of chromosome 22 genomic imbalances and subsequently improves the CNV-phenotype correlations.     

Increased paternal age and the influence on burden of genomic copy number variation in the general population

Genomic copy number variations (CNVs) and increased parental age are both associated with the risk to develop a variety of clinical neuropsychiatric disorders such as autism, schizophrenia and bipolar disorder. At the same time, it has been shown that the rate of transmitted de novo single nucleotide mutations is increased with paternal age. To address whether paternal age also affects the burden of structural genomic deletions and duplications, we examined various types of CNV burden in a large population sample from the Netherlands. Healthy participants with parental age information (n = 6,773) were collected at different University Medical Centers. CNVs were called with the PennCNV algorithm using Illumina genome-wide SNP array data. We observed no evidence in support of a paternal age effect on CNV load in the offspring. Our results were negative for global measures as well as several proxies for de novo CNV events in this unique sample. While recent studies suggest de novo single nucleotide mutation rate to be dominated by the age of the father at conception, our results strongly suggest that at the level of global CNV burden there is no influence of increased paternal age. While it remains possible that local genomic effects may exist for specific phenotypes, this study indicates that global CNV burden and increased father’s age may be independent disease risk factors.     

Cellular context in epigenetics: quantitative multicolor imaging and automated per-cell analysis of miRNAs and their putative targets

This paper assesses the quantitative resolution of qPCR using copy number variation (CNV) as a paradigm. An error model is developed for real-time qPCR data showing how the precision of CNV determination varies with the number of replicates. Using samples with varying numbers of X chromosomes, experimental data demonstrates that real-time qPCR can readily distinguish four copes from five copies, which corresponds to a 1.25-fold difference in relative quantity. Digital PCR is considered as an alternative form of qPCR. For digital PCR, an error model is shown that relates the precision of CNV determination to the number of reaction chambers. The quantitative capability of digital PCR is illustrated with an experiment distinguishing four and five copies of the human gene MRGPRX1. For either real-time qPCR or digital PCR, practical application of these models to achieve enhanced quantitative resolution requires use of a high throughput PCR platform that can simultaneously perform thousands of reactions. Comparing the two methods, real-time qPCR has the advantage of throughput and digital PCR has the advantage of simplicity in terms of the assumptions made for data analysis.     

Molekulare Karyotypisierung in der klinischen Anwendung

Microarray technology for the detection of putative pathological submicroscopic copy number variants (CNV) has become a standard tool in the field of molecular cytogenetics in recent years. In addition to the identification of somatic CNVs in tumour genetics this technology is increasingly used for the analysis of constitutional CNVs in patients with developmental delay. Array-based genomic hybridisation increases sensitivity in comparison to more conventional technologies such as comparative genomic hybridisation (CGH). Recent developments now allow a genome-wide detection of submicroscopic chromosomal alterations, deletions and duplications smaller than 100 Kb, thus significantly increasing the detection rate of chromosomal aberrations in patients suffering from idiopathic mental retardation. Several centers are already using array technology in their routine setting in the diagnostic approach to syndromes. Therefore, this overview focuses on the similarities, as well as the differences, of several basic array techniques.     

The Role of Copy Number Variation in Susceptibility to Amyotrophic Lateral Sclerosis: Genome-Wide Association Study and Comparison with Published Loci

Background

The genetic contribution to sporadic amyotrophic lateral sclerosis (ALS) has not been fully elucidated. There are increasing efforts to characterise the role of copy number variants (CNVs) in human diseases; two previous studies concluded that CNVs may influence risk of sporadic ALS, with multiple rare CNVs more important than common CNVs. A little-explored issue surrounding genome-wide CNV association studies is that of post-calling filtering and merging of raw CNV calls. We undertook simulations to define filter thresholds and considered optimal ways of merging overlapping CNV calls for association testing, taking into consideration possibly overlapping or nested, but distinct, CNVs and boundary estimation uncertainty.

Methodology and Principal Findings

In this study we screened Illumina 300K SNP genotyping data from 730 ALS cases and 789 controls for copy number variation. Following quality control filters using thresholds defined by simulation, a total of 11321 CNV calls were made across 575 cases and 621 controls. Using region-based and gene-based association analyses, we identified several loci showing nominally significant association. However, the choice of criteria for combining calls for association testing has an impact on the ranking of the results by their significance. Several loci which were previously reported as being associated with ALS were identified here. However, of another 15 genes previously reported as exhibiting ALS-specific copy number variation, only four exhibited copy number variation in this study. Potentially interesting novel loci, including EEF1D, a translation elongation factor involved in the delivery of aminoacyl tRNAs to the ribosome (a process which has previously been implicated in genetic studies of spinal muscular atrophy) were identified but must be treated with caution due to concerns surrounding genomic location and platform suitability.

Conclusions and Significance

Interpretation of CNV association findings must take into account the effects of filtering and combining CNV calls when based on early genome-wide genotyping platforms and modest study sizes.     

Array CGH analysis of a cohort of Russian patients with intellectual disability

The use of array comparative genomic hybridization (array CGH) as a diagnostic tool in molecular genetics has facilitated the identification of many new microdeletion/microduplication syndromes (MMSs). Furthermore, this method has allowed for the identification of copy number variations (CNVs) whose pathogenic role has yet to be uncovered. Here, we report on our application of array CGH for the identification of pathogenic CNVs in 79 Russian children with intellectual disability (ID). Twenty-six pathogenic or likely pathogenic changes in copy number were detected in 22 patients (28%): 8 CNVs corresponded to known MMSs, and 17 were not associated with previously described syndromes. In this report, we describe our findings and comment on genes potentially associated with ID that are located within the CNV regions.     

Comprehensive assessment of array-based platforms and calling algorithms for detection of copy number variants

We have systematically compared copy number variant (CNV) detection on eleven microarrays to evaluate data quality and CNV calling, reproducibility, concordance across array platforms and laboratory sites, breakpoint accuracy and analysis tool variability. Different analytic tools applied to the same raw data typically yield CNV calls with <50% concordance. Moreover, reproducibility in replicate experiments is <70% for most platforms. Nevertheless, these findings should not preclude detection of large CNVs for clinical diagnostic purposes because large CNVs with poor reproducibility are found primarily in complex genomic regions and would typically be removed by standard clinical data curation. The striking differences between CNV calls from different platforms and analytic tools highlight the importance of careful assessment of experimental design in discovery and association studies and of strict data curation and filtering in diagnostics. The CNV resource presented here allows independent data evaluation and provides a means to benchmark new algorithms.