Distribution Of Copy Number Variations Research Articles

Evaluating the genomic and sequence integrity of human ES cell lines; comparison to normal genomes

Copy number variation (CNV) is a common chromosomal alteration that can occur during in vitro cultivation of human cells and can be accompanied by the accumulation of mutations in coding region sequences. We describe here a systematic application of current molecular technologies to provide a detailed understanding of genomic and sequence profiles of human embryonic stem cell (hESC) lines that were derived under GMP-compliant conditions. We first examined the overall chromosomal integrity using cytogenetic techniques to determine chromosome count, and to detect the presence of cytogenetically aberrant cells in the culture (mosaicism). Assays of copy number variation, using both microarray and sequence-based analyses, provide a detailed view genomic variation in these lines and shows that in early passage cultures of these lines, the size range and distribution of CNVs are entirely consistent with those seen in the genomes of normal individuals. Similarly, genome sequencing shows variation within these lines that is completely within the range seen in normal genomes. Important gene classes, such as tumor suppressors and genetic disease genes, do not display overtly disruptive mutations that could affect the overall safety of cell-based therapeutics. Complete sequence also allows the analysis of important transplantation antigens, such as ABO and HLA types. The combined application of cytogenetic and molecular technologies provides a detailed understanding of genomic and sequence profiles of GMP produced ES lines for potential use as therapeutic agents.

Distribution of copy number variations in Alzheimer's disease

Distribution of copy number variations in Alzheimer's disease

Characterization of autosomal copy-number variation in African Americans: the HyperGEN Study

African Americans are a genetically diverse population with a high burden of many, common heritable diseases. However, our understanding of genetic variation in African Americans is substandard because of a lack of published population-based genetic studies. We report the distribution of copy-number variation (CNV) in African Americans collected as part of the Hypertension Genetic Epidemiology Network (HyperGEN) using the Affymetrix 6.0 array and the CNV calling algorithms Birdsuite and PennCNV. We present population estimates of CNV from 446 unrelated African-American subjects randomly selected from the 451 families collected within HyperGEN. Although the majority of CNVs discovered were individually rare, we found the frequency of CNVs to be collectively high. We identified a total of 11 070 CNVs greater than 10 kb passing quality control criteria that were called by both algorithms - leading to an average of 24.8 CNVs per person covering 2214 kb (median). We identified 1541 unique copy-number variable regions, 309 of which did not overlap with the Database of Genomic Variants. These results provide further insight into the distribution of CNV in African Americans.

Homozygous deletion of the UGT2B17 gene is not associated with osteoporosis risk in elderly Caucasian women

Previously, homozygous deletion of the UGT2B17 gene has shown association with hip fracture. Using a high-throughput qRT-PCR assay, we genotyped UGT2B17 copy number variation (CNV) in 1,347 elderly Caucasian women and examined for effects on bone phenotypes. We found no evidence of association between UGT2B17 CNV and osteoporosis risk in this population. Genetic studies of osteoporosis commonly examine SNPs in candidate genes or whole genome analyses, but insertions and deletions of DNA, collectively called CNV, also comprise a large amount of the genetic variability between individuals. Previously, homozygous deletion of the UGT2B17 gene in CNV 4q13.2, which encodes an enzyme that mediates the glucuronidation of steroid hormones, has shown association with the risk of hip fracture. We used a quantitative real-time PCR assay for genotyping the UGT2B17 CNV in a well-characterized population study of 1,347 Caucasian women aged 75.2 ± 2.7 years (mean ± SD), to assess the effect of the CNV on bone mass density (BMD) at the total hip site and osteoporosis risk. The UGT2B17 CNV distribution was consistent with the expected Hardy-Weinberg distribution and not different from frequencies previously reported in a Caucasian population. Data from ANCOVA of age- and weight-adjusted BMD for UGT2B17 CNV genotype showed no significant difference between genotype groups. Individuals with homozygous or heterozygous deletion of the UGT2B17 gene showed no increased risk of incident fragility fracture. These data suggest that quantitative real-time PCR is a rapid and efficient technique for determination of candidate CNVs, including the UGT2B17 CNV; however, we found no evidence of an effect of UGT2B17 CNV on osteoporosis risk in elderly Caucasian women.

Genomic copy number variations in three Southeast Asian populations

Research on the role of copy number variations (CNVs) in the genetic risk of diseases in Asian populations has been hampered by a relative lack of reference CNV maps for Asian populations outside the East Asians. In this article, we report the population characteristics of CNVs in Chinese, Malay, and Asian Indian populations in Singapore. Using the Illumina Human 1M Beadchip array, we identify 1,174 CNV loci in these populations that corroborated with findings when the same samples were typed on the Affymetrix 6.0 platform. We identify 441 novel loci not previously reported in the Database of Genomic Variations (DGV). We observe a considerable number of loci that span all three populations and were previously unreported, as well as population-specific loci that are quite common in the respective populations. From this we observe the distribution of CNVs in the Asian Indian population to be considerably different from the Chinese and Malay populations. About half of the deletion loci and three-quarters of duplication loci overlap UCSC genes. Tens of loci show population differentiation and overlap with genes previously known to be associated with genetic risk of diseases. One of these loci is the CYP2A6 deletion, previously linked to reduced susceptibility to lung cancer.

Copy number variation of FCGR3A rather than FCGR3B and FCGR2B is associated with susceptibility to anti-GBM disease

Anti-glomerular basement membrane antibody disease (anti-GBM disease) is a rare disorder characteristic of universally poor outcome. Fcgamma receptors (FcgammaRs) play important roles in anti-GBM disease based on evidence from animal models. Copy number variation (CNV) influences disease susceptibility. The FcgammaRs genes show CNV, and CNV of the FCGR3B gene is associated with glomerulonephritis in systemic lupus erythematosus and anti-neutrophil cytoplasmic antibody-associated small vasculitis. Here, we investigated CNV of three FCGR genes, including two (FCGR3A and FCGR3B) for activating FcgammaRs and one (FCGR2B) for inhibitory FcgammaR by duplex quantitative real-time PCR. Copy numbers were analyzed by Applied Biosystems CopyCaller Software v1.0. We first demonstrated the distribution of CNV of FCGR3A, FCGR3B and no CNV of FCGR2B in Chinese population (including 47 anti-GBM patients and 146 healthy controls). The frequency of CNV of FCGR3A was observed to be significantly higher than matched healthy controls (27.7 versus 12.3%, P = 0.013, odds ratio 1.21-6.10). Considering previous report about gene knock-out animal models and CNV effect of FCGR3A, we thus propose that CNV in members of FCGR family should have different roles in the pathogenesis of human anti-GBM disease.

Microarray-Based Genomic DNA Profiling Technologies in Clinical Molecular Diagnostics

Microarray-based genomic DNA profiling (MGDP) technologies are rapidly moving from translational research to clinical diagnostics and have revolutionized medical practices. Such technologies have shown great advantages in detecting genomic imbalances associated with genomic disorders and single-gene diseases. We discuss the development and applications of the major array platforms that are being used in both academic and commercial laboratories. Although no standardized platform is expected to emerge soon, comprehensive oligonucleotide microarray platforms-both comparative genomic hybridization arrays and genotyping hybrid arrays-are rapidly becoming the methods of choice for their demonstrated analytical validity in detecting genomic imbalances, for their flexibility in incorporating customized designs and updates, and for the advantage of being easily manufactured. Copy number variants (CNVs), the form of genomic deletions/duplications detected through MGDP, are a common etiology for a variety of clinical phenotypes. The widespread distribution of CNVs poses great challenges in interpretation. A broad survey of CNVs in the healthy population, combined with the data accumulated from the patient population in clinical laboratories, will provide a better understanding of the nature of CNVs and enhance the power of identifying genetic risk factors for medical conditions. MGDP technologies for molecular diagnostics are still at an early stage but are rapidly evolving. We are in the process of extensive clinical validation and utility evaluation of different array designs and technical platforms. CNVs of currently unknown importance will be a rich source of novel discoveries.

Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in approximately 2500 individuals by using Illumina SNP data, with an emphasis on "hotspots" prone to recurrent mutations. We find variants larger than 500 kb in 5%-10% of individuals and variants greater than 1 Mb in 1%-2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%-1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.

Contribution of Fcγ receptor IIIA gene 158V/F polymorphism and copy number variation to the risk of ACPA-positive rheumatoid arthritis

Background:Fcγ receptors (FcγRs) are potent immune modulators. FcγR genes encompass a complex region, polymorphic by both single nucleotide polymorphisms (SNPs) and copy number variation (CNV). The heterogeneity of rheumatoid arthritis...

On the frequency of copy number variants

Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission. Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates.

Genotype, haplotype and copy-number variation in worldwide human populations

Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected--including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas--the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.

Variation of CNV distribution in five different ethnic populations

Recent studies have revealed a new type of variation in the human genome encompassing relatively large genomic segments (∼100 kb–2.5 Mb), commonly referred to as copy number variation (CNV). The full nature and extent of CNV and its frequency in different ethnic populations is still largely unknown. In this study we surveyed a set of 12 CNVs previously detected by array-CGH. More than 300 individuals from five different ethnic populations, including three distinct European, one Asian and one African population, were tested for the occurrence of CNV using multiplex ligation-dependent probe amplification (MLPA). Seven of these loci indeed showed CNV, i.e., showed copy numbers that deviated from the population median. More precise estimations of the actual genomic copy numbers for (part of) the NSF gene locus, revealed copy numbers ranging from two to at least seven. Additionally, significant inter-population differences in the distribution of these copy numbers were observed. These data suggest that insight into absolute DNA copy numbers for loci exhibiting CNV is required to determine their potential contribution to normal phenotypic variation and, in addition, disease susceptibility.

Copy-number variation in control population cohorts

Copy-number variation (CNV) is the most prevalent type of structural variation in the human genome, and contributes significantly to genetic heterogeneity. It has already been recognized that some CNVs can contribute to human phenotype, including rare genomic disorders and Mendelian diseases. Other CNVs are now amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be more readily determined. Population studies and reference databases for control and disease-associated samples are required to provide an information resource about CNV frequencies and their relative contribution to phenotypic outcomes. The relatively high cost of screening individual samples has tended to limit the number of controls assayed, and use of the data has often been hampered by the variety of technology platforms and analysis techniques. As a result, there is still a paucity of data on population frequency and distribution of CNVs, particularly for those that are rare. Here, we provide an example of how to discover new CNVs from existing genotype data from large-scale genetic epidemiological studies. We also discuss the need to expand surveys of CNV in different population-based cohorts and to apply the information to studies of human variation and disease.

Mutational and selective effects on copy-number variants in the human genome

Comprehensive descriptions of large insertion/deletion or segmental duplication polymorphisms (SDs) in the human genome have recently been generated. These annotations, known collectively as structural or copy-number variants (CNVs), include thousands of discrete genomic regions and span hundreds of millions of nucleotides. Here we review the genomic distribution of CNVs, which is strongly correlated with gene, repeat and segmental duplication content. We explore the evolutionary mechanisms giving rise to this nonrandom distribution, considering the available data on both human polymorphisms and the fixed changes that differentiate humans from other species. It is likely that mutational biases, selective effects and interactions between these forces all contribute substantially to the spectrum of human copy-number variation. Although defining these variants with nucleotide-level precision remains a largely unmet but critical challenge, our understanding of their potential medical impact and evolutionary importance is rapidly emerging.