Mathematical analysis of copy number variation in a DNA sample using digital PCR on a nanofluidic device

Copy Number Variations (CNVs) of regions of the human genome have been associated with multiple diseases. We present an algorithm which is mathematically sound and computationally efficient to accurately analyze CNV in a DNA sample utilizing a nanofluidic device, known as the digital array. This numerical algorithm is utilized to compute copy number variation and the associated statistical confidence interval and is based on results from probability theory and statistics. We also provide formulas which can be used as close approximations.     

Determination of gene copy number and genotype of transgenic Arabidopsis thaliana by competitive PCR

A simple and rapid method is described for determining the integrated T-DNA copy number and the genotype in transgenic Arabidopsis thaliana by two-step competitive PCR. First, the amount of genomic DNA in the extracts, obtained from an individual A. thaliana transformant, was accurately determined by the 1st competitive PCR using a known single copy gene, 4HPPD (4-hydroxyphenylpyruvate dioxygenase), as a target. Second, the number of T-DNA copies per genome was estimated by quantifying the NPTII gene, which was involved in the T-DNA, by the 2nd competitive PCR using exactly the same amount of genomic DNA for each sample. The estimated copy number and genotype obtained by this procedure were identical to those determined by Southern blot analysis and segregation analysis.     

Precision-mapping and statistical validation of quantitative trait loci by machine learning

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.     

Studying copy number variations using a nanofluidic platform

Copy number variations (CNVs) in the human genome are conventionally detected using high-throughput scanning technologies, such as comparative genomic hybridization and high-density single nucleotide polymorphism (SNP) microarrays, or relatively low-throughput techniques, such as quantitative polymerase chain reaction (PCR). All these approaches are limited in resolution and can at best distinguish a twofold (or 50%) difference in copy number. We have developed a new technology to study copy numbers using a platform known as the digital array, a nanofluidic biochip capable of accurately quantitating genes of interest in DNA samples. We have evaluated the digital array's performance using a model system, to show that this technology is exquisitely sensitive, capable of differentiating as little as a 15% difference in gene copy number (or between 6 and 7 copies of a target gene). We have also analyzed commercial DNA samples for their CYP2D6 copy numbers and confirmed that our results were consistent with those obtained independently using conventional techniques. In a screening experiment with breast cancer and normal DNA samples, the ERBB2 gene was found to be amplified in about 35% of breast cancer samples. The use of the digital array enables accurate measurement of gene copy numbers and is of significant value in CNV studies.     

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。     

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.     

A high-resolution map of segmental DNA copy number variation in the mouse genome

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.     

A novel multiplex fluorescent competitive PCR for copy number variation detection

The copy number variation (CNV) is an important genetic marker in cancer and other diseases. To detect CNVs of specific genetic loci, the multiplex ligation-dependent probe amplification (MLPA) is an appropriate approach, but the experimental optimization and probe synthesis are still great challenges. The multiplex competitive PCR is an alternative method for CNV detection. However, the construction of internal competitive template and establishment of a stable multiplex PCR system are the main limiting factors for this method. Here, we introduce a novel multiplex fluorescent competitive PCR (NMFC-PCR) for detecting CNVs. In this method, the blunt hairpin primers are used to rapidly establish a stable multiplex PCR system due to the reduction of non-specific amplification, and limited cycles' amplification is used to obtain the internal competitive template instead of artificial synthesis. With this method, we tested 21 clinical samples with potential LIM homeobox 1 (LHX1) or T-box 6 (TBX6) deletion. Every three segments located on the LHX1 and TBX6 were selected as the target regions, while two segments located on X-chromosome and five segments located on autosome were selected as the reference regions for detecting CNVs. The results showed that the gender information of 21 samples can be accurately inferred by the copy number ratio (CNR) of X-chromosomal reference region to autosomal reference region (X/A), and 2 samples had one copy of LHX1 and 9 samples had one copy of TBX6. To evaluate the accuracy of NMFC-PCR, 5 random samples with CNV were also detected by array-based comparative genomic hybridization (aCGH), and the results of aCGH were consistent with the NMFC-PCR results. To further assess the performance of NMFC-PCR, 60 normal samples were simultaneously tested. The results showed that the gender results were exactly the same as known information, and CNVs of LHX1 or TBX6 were not found. In conclusion, the method is a cheap, efficient, accurate, and convenient competitive PCR method for CNV detection.     

Quantitative analysis of total mitochondrial DNA: competitive polymerase chain reaction versus real-time polymerase chain reaction

An efficient and effective method for quantification of small amounts of nucleic acids contained within a sample specimen would be an important diagnostic tool for determining the content of mitochondrial DNA (mtDNA) in situations where the depletion thereof may be a contributing factor to the exhibited pathology phenotype. This study compares two quantification assays for calculating the total mtDNA molecule number per nanogram of total genomic DNA isolated from human blood, through the amplification of a 613-bp region on the mtDNA molecule. In one case, the mtDNA copy number was calculated by standard competitive polymerase chain reaction (PCR) technique that involves co-amplification of target DNA with various dilutions of a nonhomologous internal competitor that has the same primer binding sites as the target sequence, and subsequent determination of an equivalence point of target and competitor concentrations. In the second method, the calculation of copy number involved extrapolation from the fluorescence versus copy number standard curve generated by real-time PCR using various dilutions of the target amplicon sequence. While the mtDNA copy number was comparable using the two methods (4.92 +/- 1.01 x 10(4) molecules/ng total genomic DNA using competitive PCR vs 4.90 +/- 0.84 x 10(4) molecules/ng total genomic DNA using real-time PCR), both inter- and intraexperimental variance were significantly lower using the real-time PCR analysis. On the basis of reproducibility, assay complexity, and overall efficiency, including the time requirement and number of PCR reactions necessary for the analysis of a single sample, we recommend the real-time PCR quantification method described here, as its versatility and effectiveness will undoubtedly be of great use in various kinds of research related to mitochondrial DNA damage- and depletion-associated disorders.     

Simple and Versatile Molecular Method of Copy-Number Measurement Using Cloned Competitors

Variations and alterations of copy numbers (CNVs and CNAs) carry disease susceptibility and drug responsiveness implications. Although there are many molecular methods to measure copy numbers, sensitivity, reproducibility, cost, and time issues remain. In the present study, we were able to solve those problems utilizing our modified real competitive PCR method with cloned competitors (mrcPCR). First, the mrcPCR for ERBB2 copy number was established, and the results were comparable to current standard methods but with a shorter assay time and a lower cost. Second, the mrcPCR assays for 24 drug-target genes were established, and the results in a panel of NCI-60 cells were comparable to those from real-time PCR and microarray. Third, the mrcPCR results for FCGR3A and the FCGR3B CNVs were comparable to those by the paralog ratio test (PRT), but without PRT''s limitations. These results suggest that mrcPCR is comparable to the currently available standard or the most sensitive methods. In addition, mrcPCR would be invaluable for measurement of CNVs in genes with variants of similar structures, because combination of the other methods is not necessary, along with its other advantages such as short assay time, small sample amount requirement, and applicability to all sequences and genes.     

Genome-Wide Profiling of Structural Genomic Variations in Korean HapMap Individuals

Background

Structural genomic variation study, along with microarray technology development has provided many genomic resources related with architecture of human genome, and led to the fact that human genome structure is a lot more complicated than previously thought.

Methodology/Principal Findings

In the case of International HapMap Project, Epstein-Barr various immortalized cell lines were preferably used over blood in order to get a larger number of genomic DNA. However, genomic aberration stemming from immortalization process, biased representation of the donor tissue, and culture process may influence the accuracy of SNP genotypes. In order to identify chromosome aberrations including loss of heterozygosity (LOH), large-scale and small-scale copy number variations, we used Illumina HumanHap500 BeadChip (555,352 markers) on Korean HapMap individuals (n = 90) to obtain Log R ratio and B allele frequency information, and then utilized the data with various programs including Illumina ChromoZone, cnvParition and PennCNV. As a result, we identified 28 LOHs (>3 mb) and 35 large-scale CNVs (>1 mb), with 4 samples having completely duplicated chromosome. In addition, after checking the sample quality (standard deviation of log R ratio <0.30), we selected 79 samples and used both signal intensity and B allele frequency simultaneously for identification of small-scale CNVs (<1 mb) to discover 4,989 small-scale CNVs. Identified CNVs in this study were successfully validated using visual examination of the genoplot images, overlapping analysis with previously reported CNVs in DGV, and quantitative PCR.

Conclusion/Significance

In this study, we describe the result of the identified chromosome aberrations in Korean HapMap individuals, and expect that these findings will provide more meaningful information on the human genome.     

Impact of whole genome amplification on analysis of copy number variants

Large-scale copy number variants (CNVs) have recently been recognized to play a role in human genome variation and disease. Approaches for analysis of CNVs in small samples such as microdissected tissues can be confounded by limited amounts of material. To facilitate analyses of such samples, whole genome amplification (WGA) techniques were developed. In this study, we explored the impact of Phi29 multiple-strand displacement amplification on detection of CNVs using oligonucleotide arrays. We extracted DNA from fresh frozen lymph node samples and used this for amplification and analysis on the Affymetrix Mapping 500k SNP array platform. We demonstrated that the WGA procedure introduces hundreds of potentially confounding CNV artifacts that can obscure detection of bona fide variants. Our analysis indicates that many artifacts are reproducible, and may correlate with proximity to chromosome ends and GC content. Pair-wise comparison of amplified products considerably reduced the number of apparent artifacts and partially restored the ability to detect real CNVs. Our results suggest WGA material may be appropriate for copy number analysis when amplified samples are compared to similarly amplified samples and that only the CNVs with the greatest significance values detected by such comparisons are likely to be representative of the unamplified samples.     

Clinical significance of germline copy number variation in susceptibility of human diseases

Germline copy number variation (CNV) is considered to be an important form of human genetic polymorphisms. Previous studies have identified amounts of CNVs in human genome by advanced technologies, such as comparative genomic hybridization, single nucleotide genotyping, and high-throughput sequencing. CNV is speculated to be derived from multiple mechanisms, such as nonallelic homologous recombination (NAHR) and nonhomologous end-joining (NHEJ). CNVs cover a much larger genome scale than single nucleotide polymorphisms (SNPs), and may alter gene expression levels by means of gene dosage, gene fusion, gene disruption, and long-range regulation effects, thus affecting individual phenotypes and playing crucial roles in human pathogenesis. The number of studies linking CNVs with common complex diseases has increased dramatically in recent years. Here, we provide a comprehensive review of the current understanding of germline CNVs, and summarize the association of germline CNVs with the susceptibility to a wide variety of human diseases that were identified in recent years. We also propose potential issues that should be addressed in future studies.     

Sample degradation leads to false-positive copy number variation calls in multiplex real-time polymerase chain reaction assays

The recent implication of genomic copy number variations (CNVs) in multiple human genetic disorders has led to increased interest in CNV discovery technologies. There is a growing consensus that, in addition to the method used for detection, at least one additional technology should be employed for validation. Real-time quantitative polymerase chain reaction (qPCR) analysis, incorporating a normal (2N) copy number standard, is commonly used as a means of validating CNVs. Whereas it has previously been reported that formalin-fixed paraffin-embedded (FFPE) DNA samples can yield spurious CNV calls in real-time qPCR assays, here we report that sample degradation under standard laboratory storage conditions generates a significant increase in false-positive CNV results. Results suggest the possibility of biased degradation among genomic regions and emphasize the need to assess sample integrity immediately prior to real-time qPCR experiments.     

An optimized microarray platform for assaying genomic variation in <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> field populations

We present an optimized probe design for copy number variation (CNV) and SNP genotyping in the Plasmodium falciparum genome. We demonstrate that variable length and isothermal probes are superior to static length probes. We show that sample preparation and hybridization conditions mitigate the effects of host DNA contamination in field samples. The microarray and workflow presented can be used to identify CNVs and SNPs with 95% accuracy in a single hybridization, in field samples containing up to 92% human DNA contamination.     

Enhancer Chip: Detecting Human Copy Number Variations in Regulatory Elements

Critical functional properties are embedded in the non-coding portion of the human genome. Recent successful studies have shown that variations in distant-acting gene enhancer sequences can contribute to disease. In fact, various disorders, such as thalassaemias, preaxial polydactyly or susceptibility to Hirschsprung’s disease, may be the result of rearrangements of enhancer elements. We have analyzed the distribution of enhancer loci in the genome and compared their localization to that of previously described copy-number variations (CNVs). These data suggest a negative selection of copy number variable enhancers. To identify CNVs covering enhancer elements, we have developed a simple and cost-effective test. Here we describe the gene selection, design strategy and experimental validation of a customized oligonucleotide Array-Based Comparative Genomic Hybridization (aCGH), designated Enhancer Chip. It has been designed to investigate CNVs, allowing the analysis of all the genome with a 300 Kb resolution and specific disease regions (telomeres, centromeres and selected disease loci) at a tenfold higher resolution. Moreover, this is the first aCGH able to test over 1,250 enhancers, in order to investigate their potential pathogenic role. Validation experiments have demonstrated that Enhancer Chip efficiently detects duplications and deletions covering enhancer loci, demonstrating that it is a powerful instrument to detect and characterize copy number variable enhancers.     

Copy number variation and disease resistance in plants

Plant genome diversity varies from single nucleotide polymorphisms to large-scale deletions, insertions, duplications, or re-arrangements. These re-arrangements of sequences resulting from duplication, gains or losses of DNA segments are termed copy number variations (CNVs). During the last decade, numerous studies have emphasized the importance of CNVs as a factor affecting human phenotype; in particular, CNVs have been associated with risks for several severe diseases. In plants, the exploration of the extent and role of CNVs in resistance against pathogens and pests is just beginning. Since CNVs are likely to be associated with disease resistance in plants, an understanding of the distribution of CNVs could assist in the identification of novel plant disease-resistance genes. In this paper, we review existing information about CNVs; their importance, role and function, as well as their association with disease resistance in plants.     

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.