Copy Number Variants in the Kallikrein Gene Cluster

The kallikrein gene family (KLK1-KLK15) is the largest contiguous group of protease genes within the human genome and is associated with both risk and outcome of cancer and other diseases. We searched for copy number variants in all KLK genes using quantitative PCR analysis and analysis of inheritance patterns of single nucleotide polymorphisms. Two deletions were identified: one 2235-bp deletion in KLK9 present in 1.2% of alleles, and one 3394-bp deletion in KLK15 present in 4.0% of alleles. Each deletion eliminated one complete exon and created out-of-frame coding that eliminated the catalytic triad of the resulting truncated gene product, which therefore likely is a non-functional protein. Deletion breakpoints identified by DNA sequencing located the KLK9 deletion breakpoint to a long interspersed element (LINE) repeated sequence, while the deletion in KLK15 is located in a single copy sequence. To search for an association between each deletion and risk of prostate cancer (PC), we analyzed a cohort of 667 biopsied men (266 PC cases and 401 men with no evidence of PC at biopsy) using short deletion-specific PCR assays. There was no association between evidence of PC in this cohort and the presence of either gene deletion. Haplotyping revealed a single origin of each deletion, with most recent common ancestor estimates of 3000-8000 and 6000-14 000 years for the deletions in KLK9 and KLK15, respectively. The presence of the deletions on the same haplotypes in 1000 Genomes data of both European and African populations indicate an early origin of both deletions. The old age in combination with homozygous presence of loss-of-function variants suggests that some kallikrein-related peptidases have non-essential functions.     

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a clinical diagnostic service laboratory. DNA extracted from a patient’s sample (blood, saliva or other tissue types) is labeled with a fluorochrome (either cyanine 5 or cyanine 3). A reference DNA sample is labeled with the opposite fluorochrome. There follows a cleanup step to remove unincorporated nucleotides before the labeled DNAs are mixed and resuspended in a hybridization buffer and applied to an array comprising ~60,000 oligonucleotide probes from loci across the genome, with high probe density in clinically important areas. Following hybridization, the arrays are washed, then scanned and the resulting images are analyzed to measure the red and green fluorescence for each probe. Software is used to assess the quality of each probe measurement, calculate the ratio of red to green fluorescence and detect potential copy number variants.     

儿童孤独症与拷贝数变异的研究

儿童孤独症是一种复杂的神经发育性障碍,患儿常表现有认知、情感和行为等多方面的异常,主要临床表现为社会交往障碍,言语交流障碍,重复刻板行为。孤独症多起病于三岁之前,男女发病比例约为4:1,患儿常伴有明显的精神发育迟滞。近年来,其发病率呈现逐年上升的趋势,最新的流行病学调查显示孤独症在美国的患病率约为9.1‰。据公认的假说"常见疾病-常见变异"推测,孤独症的风险等位基因和其他复杂疾病一样,在普通人群中将会变得很常见。由于该病起病早,难以进行早期识别,而且尚无特效药或方法可以彻底治愈这种病症,因而给社会及患儿家庭带来了沉重的负担。目前其发病原因和机制尚不明确,但关于儿童孤独症的双生子研究和家系研究都显示它是一个高度遗传性疾病,而且很多证据都表明孤独症是受多因素影响的遗传性疾病,近年来关于孤独症和拷贝数变异(CNVS)研究的报道越来越多,本文将主要就儿童孤独症的拷贝数变异研究现状和最新进展进行论述。     

Copy Number Variants in German Patients with Schizophrenia

Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1∶150 to 1∶1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina''s BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ≥30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.     

Endometriosis Is Associated with Rare Copy Number Variants

Endometriosis is a complex gynecological condition that affects 6–10% of women in their reproductive years and is defined by the presence of endometrial glands and stroma outside the uterus. Twin, family, and genome-wide association (GWA) studies have confirmed a genetic role, yet only a small part of the genetic risk can be explained by SNP variation. Copy number variants (CNVs) account for a greater portion of human genetic variation than SNPs and include more recent mutations of large effect. CNVs, likely to be prominent in conditions with decreased reproductive fitness, have not previously been examined as a genetic contributor to endometriosis. Here we employ a high-density genotyping microarray in a genome-wide survey of CNVs in a case-control population that includes 2,126 surgically confirmed endometriosis cases and 17,974 population controls of European ancestry. We apply stringent quality filters to reduce the false positive rate common to many CNV-detection algorithms from 77.7% to 7.3% without noticeable reduction in the true positive rate. We detected no differences in the CNV landscape between cases and controls on the global level which showed an average of 1.92 CNVs per individual with an average size of 142.3 kb. On the local level we identify 22 CNV-regions at the nominal significance threshold (P<0.05), which is greater than the 8.15 CNV-regions expected based on permutation analysis (P<0.001). Three CNV''s passed a genome-wide P-value threshold of 9.3×10⁻⁴; a deletion at SGCZ on 8p22 (P = 7.3×10⁻⁴, OR = 8.5, Cl = 2.3–31.7), a deletion in MALRD1 on 10p12.31 (P = 5.6×10⁻⁴, OR = 14.1, Cl = 2.7–90.9), and a deletion at 11q14.1 (P = 5.7×10⁻⁴, OR = 33.8, Cl = 3.3–1651). Two SNPs within the 22 CNVRs show significant genotypic association with endometriosis after adjusting for multiple testing; rs758316 in DPP6 on 7q36.2 (P = 0.0045) and rs4837864 in ASTN2 on 9q33.1 (P = 0.0002). Together, the CNV-loci are detected in 6.9% of affected women compared to 2.1% in the general population.     

Rare Copy Number Variants Are a Common Cause of Short Stature

Human growth has an estimated heritability of about 80%–90%. Nevertheless, the underlying cause of shortness of stature remains unknown in the majority of individuals. Genome-wide association studies (GWAS) showed that both common single nucleotide polymorphisms and copy number variants (CNVs) contribute to height variation under a polygenic model, although explaining only a small fraction of overall genetic variability in the general population. Under the hypothesis that severe forms of growth retardation might also be caused by major gene effects, we searched for rare CNVs in 200 families, 92 sporadic and 108 familial, with idiopathic short stature compared to 820 control individuals. Although similar in number, patients had overall significantly larger CNVs (p-value<1×10⁻⁷). In a gene-based analysis of all non-polymorphic CNVs>50 kb for gene function, tissue expression, and murine knock-out phenotypes, we identified 10 duplications and 10 deletions ranging in size from 109 kb to 14 Mb, of which 7 were de novo (p<0.03) and 13 inherited from the likewise affected parent but absent in controls. Patients with these likely disease causing 20 CNVs were smaller than the remaining group (p<0.01). Eleven (55%) of these CNVs either overlapped with known microaberration syndromes associated with short stature or contained GWAS loci for height. Haploinsufficiency (HI) score and further expression profiling suggested dosage sensitivity of major growth-related genes at these loci. Overall 10% of patients carried a disease-causing CNV indicating that, like in neurodevelopmental disorders, rare CNVs are a frequent cause of severe growth retardation.     

A Genome-Wide Assessment of the Role of Untagged Copy Number Variants in Type 1 Diabetes

Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability.     

一种基于二代测序拷贝数变异检测的新方法

区域捕获测序是针对基因组特定区段如对MHC(Major histocompatibility complex)区域、外显子区域等测序的有效手段,但是由于捕获测序中探针设计不均匀而造成区域内测序深度变异很大,因此,与基于全基因组的测序数据相比,其拷贝数变异的检测难度更大.目前已经出现了捕获测序下拷贝数变异(copy number variations,CNV)的检测方法,但对CNV的检测准确性仍然很低,特别是对于低频率CNV来说效果极差.因此,本研究开发了一个新的拷贝数变异检测方法,其特点是:(1)以区域内划分的区间为单位检测区间内的CNV,而不是直接对每个个体检测CNV;(2)全面利用群体内所有个体信息,通过区间内read深度在群体的分布规律来检测CNV的分离规律,假设区间内只有1个CNV,那么区间内的read深度将服从三峰的混合正态分布.将该方法应用于21 327个银屑病个体区域捕获测序的CNV检测中,结果表明,XHMM,ExomeDepth和本方法跟金标准重叠的窗口总数与金标准总窗口数的百分比(即重叠率)分别是7％、18％和62％.与XHMM和ExomeDepth相比,新方法在区间内CNV检测覆盖度可以分别提高55个百分点和44个百分点.本研究完善拷贝数变异检测方法,为疾病的诊断治疗提供一定的理论依据.     

Contribution of Rare Copy Number Variants to Isolated Human Malformations

Background

Congenital malformations are present in approximately 2–3% of liveborn babies and 20% of stillborn fetuses. The mechanisms underlying the majority of sporadic and isolated congenital malformations are poorly understood, although it is hypothesized that the accumulation of rare genetic, genomic and epigenetic variants converge to deregulate developmental networks.

Methodology/Principal Findings

We selected samples from 95 fetuses with congenital malformations not ascribed to a specific syndrome (68 with isolated malformations, 27 with multiple malformations). Karyotyping and Multiplex Ligation-dependent Probe Amplification (MLPA) discarded recurrent genomic and cytogenetic rearrangements. DNA extracted from the affected tissue (46%) or from lung or liver (54%) was analyzed by molecular karyotyping. Validations and inheritance were obtained by MLPA. We identified 22 rare copy number variants (CNV) [>100 kb, either absent (n = 7) or very uncommon (n = 15, <1/2,000) in the control population] in 20/95 fetuses with congenital malformations (21%), including 11 deletions and 11 duplications. One of the 9 tested rearrangements was de novo while the remaining were inherited from a healthy parent. The highest frequency was observed in fetuses with heart hypoplasia (8/17, 62.5%), with two events previously related with the phenotype. Double events hitting candidate genes were detected in two samples with brain malformations. Globally, the burden of deletions was significantly higher in fetuses with malformations compared to controls.

Conclusions/Significance

Our data reveal a significant contribution of rare deletion-type CNV, mostly inherited but also de novo, to human congenital malformations, especially heart hypoplasia, and reinforce the hypothesis of a multifactorial etiology in most cases.     

High-Throughput Multiplex Sequencing to Discover Copy Number Variants in Drosophila

Copy number variation (CNV) contributes in phenotypically relevant ways to the genetic variability of many organisms. Cost-effective genomewide methods for identifying copy number variation are necessary to elucidate the contribution that these structural variants make to the genomes of model organisms. We have developed a novel approach for the identification of copy number variation by next generation sequencing. As a proof of concept our method has been applied to map the deletions of three Drosophila deficiency strains. We demonstrate that low sequence coverage is sufficient for identifying and mapping large deletions at kilobase resolution, suggesting that data generated from high-throughput sequencing experiments are sufficient for simultaneously analyzing many strains. Genomic DNA from two Drosophila deficiency stocks was barcoded and sequenced in multiplex, and the breakpoints associated with each deletion were successfully identified. The approach we describe is immediately applicable to the systematic exploration of copy number variation in model organisms and humans.STRUCTURAL variation is known to contribute extensively to the genetic variability of humans, mammals, and many model organisms. One class of structural variant, termed copy number variation (CNV), includes deletions, duplications, insertions, and genomic rearrangements which affect the number of occurrences of a specific DNA sequence present in the genome (Redon et al. 2006). CNV is known to occur extensively in the Drosophila genome with functionally significant consequences (Bridges 1936; Dopman and Hartl 2007; Tibshirani and Wang 2008; Zhou et al. 2008). In one study of 15 Drosophila strains, as many as 10% of genes were observed to harbor CNVs (Emerson et al. 2008). Cryptic CNVs that affect the phenotype observed in a model organism have the potential to confound research on multiple levels. For example, a recent report indicates that terminal deletions on chromosome (chr) 2L are frequent among deficiency kit stocks with mutations on the second chromosome and that the associated deletion of lgl has distorted the results of several previous studies (Roegiers et al. 2009). Despite widespread existence of CNV, the biological consequences of this phenomenon remain largely unexplored due to the lack of efficient tools for detection and characterization.Until recently, comparative genomic hybridization with whole-genome tiling arrays (array-CGH) was the primary method for characterizing CNVs (Carter 2007); however, several limitations for this platform reduce its efficacy and efficiency. First, cross-hybridization and reliance on intensity scores lead to data that are difficult to interpret. Second, custom array design and optimization is labor intensive and costly. Third, array-CGH methods can only detect CNV, not other complex rearrangements such as balanced translocations and inversions. Finally, the overall cost of array-CGH methods is relatively high, particularly when high-resolution, whole-genome tiling arrays are employed.Direct sequencing using next-generation technology has several advantages that make it a potentially powerful alternative to array-CGH for identifying genomic structural variations, including deletions, duplications, and rearrangements (Campbell et al. 2008; Chiang et al. 2009). First, high-throughput sequencing methods overcome the inherent limitations of cross-hybridization and provide a digital count of sequence representation. Second, no prior knowledge or design work is necessary. Third, using paired-end sequencing it is possible to identify complex structural variations. Finally, the current cost of CNV discovery by sequencing is comparable or lower than that of array-CGH and is continuing to decline.In this report, we describe a sequencing-based strategy for high-throughput, cost-effective, genomewide characterization of structural variation at fine resolution by employing the Illumina sequencing platform. Deletions in three deficiency fly stocks were successfully characterized and the associated breakpoints were accurately determined. As we demonstrate, high-throughput sequencing provides an ideal and cost-effective platform for CNV characterization.     

Haplotype Phasing and Inheritance of Copy Number Variants in Nuclear Families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.     

Development and Validation of a Next-Generation Sequencing Assay for BRCA1 and BRCA2 Variants for the Clinical Laboratory

The objective of this study was to design and validate a next-generation sequencing assay (NGS) to detect BRCA1 and BRCA2 mutations. We developed an assay using random shearing of genomic DNA followed by RNA bait tile hybridization and NGS sequencing on both the Illumina MiSeq and Ion Personal Gene Machine (PGM). We determined that the MiSeq Reporter software supplied with the instrument could not detect deletions greater than 9 base pairs. Therefore, we developed an alternative alignment and variant calling software, Quest Sequencing Analysis Pipeline (QSAP), that was capable of detecting large deletions and insertions. In validation studies, we used DNA from 27 stem cell lines, all with known deleterious BRCA1 or BRCA2 mutations, and DNA from 67 consented control individuals who had a total of 352 benign variants. Both the MiSeq/QSAP combination and PGM/Torrent Suite combination had 100% sensitivity for the 379 known variants in the validation series. However, the PGM/Torrent Suite combination had a lower intra- and inter-assay precision of 96.2% and 96.7%, respectively when compared to the MiSeq/QSAP combination of 100% and 99.4%, respectively. All PGM/Torrent Suite inconsistencies were false-positive variant assignments. We began commercial testing using both platforms and in the first 521 clinical samples MiSeq/QSAP had 100% sensitivity for BRCA1/2 variants, including a 64-bp deletion and a 10-bp insertion not identified by PGM/Torrent Suite, which also suffered from a high false-positive rate. Neither the MiSeq nor PGM platform with their supplied alignment and variant calling software are appropriate for a clinical laboratory BRCA sequencing test. We have developed an NGS BRCA1/2 sequencing assay, MiSeq/QSAP, with 100% analytic sensitivity and specificity in the validation set consisting of 379 variants. The MiSeq/QSAP combination has sufficient performance for use in a clinical laboratory.     

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method

Purpose

The analysis of MET gene copy number (CN) has been considered to be a potential biomarker to predict the response to MET-targeted therapies in various cancers. However, the current standard methods to determine MET CN are SNP 6.0 in the genomic DNA of cancer cell lines and fluorescence in situ hybridization (FISH) in tumor models, respectively, which are costly and require advanced technical skills and result in relatively subjective judgments. Therefore, we employed a novel method, droplet digital PCR (ddPCR), to determine the MET gene copy number with high accuracy and precision.

Methods

The genomic DNA of cancer cell lines or tumor models were tested and compared with the MET gene CN and MET/CEN-7 ratio determined by SNP 6.0 and FISH, respectively.

Results

In cell lines, the linear association of the MET CN detected by ddPCR and SNP 6.0 is strong (Pearson correlation = 0.867). In tumor models, the MET CN detected by ddPCR was significantly different between the MET gene amplification and non-amplification groups according to FISH (mean: 15.4 vs 2.1; P = 0.044). Given that MET gene amplification is defined as MET CN >5.5 by ddPCR, the concordance rate between ddPCR and FISH was 98.0%, and Cohen''s kappa coefficient was 0.760 (95% CI, 0.498–1.000; P <0.001).

Conclusions

The results demonstrated that the ddPCR method has the potential to quantify the MET gene copy number with high precision and accuracy as compared with the results from SNP 6.0 and FISH in cancer cell lines and tumor samples, respectively.     

Copy Number Variation Analysis in Familial BRCA1/2-Negative Finnish Breast and Ovarian Cancer

Background

Inherited factors predisposing individuals to breast and ovarian cancer are largely unidentified in a majority of families with hereditary breast and ovarian cancer (HBOC). We aimed to identify germline copy number variations (CNVs) contributing to HBOC susceptibility in the Finnish population.

Methods

A cohort of 84 HBOC individuals (negative for BRCA1/2-founder mutations and pre-screened for the most common breast cancer genes) and 36 healthy controls were analysed with a genome-wide SNP array. CNV-affecting genes were further studied by Gene Ontology term enrichment, pathway analyses, and database searches to reveal genes with potential for breast and ovarian cancer predisposition. CNVs that were considered to be important were validated and genotyped in 20 additional HBOC individuals (6 CNVs) and in additional healthy controls (5 CNVs) by qPCR.

Results

An intronic deletion in the EPHA3 receptor tyrosine kinase was enriched in HBOC individuals (12 of 101, 11.9%) compared with controls (27 of 432, 6.3%) (OR = 1.96; P = 0.055). EPHA3 was identified in several enriched molecular functions including receptor activity. Both a novel intronic deletion in the CSMD1 tumor suppressor gene and a homozygous intergenic deletion at 5q15 were identified in 1 of 101 (1.0%) HBOC individuals but were very rare (1 of 436, 0.2% and 1 of 899, 0.1%, respectively) in healthy controls suggesting that these variants confer disease susceptibility.

Conclusion

This study reveals new information regarding the germline CNVs that likely contribute to HBOC susceptibility in Finland. This information may be used to facilitate the genetic counselling of HBOC individuals but the preliminary results warrant additional studies of a larger study group.     

Rare De Novo Copy Number Variants in Patients with Congenital Pulmonary Atresia

Background

Ongoing studies using genomic microarrays and next-generation sequencing have demonstrated that the genetic contributions to cardiovascular diseases have been significantly ignored in the past. The aim of this study was to identify rare copy number variants in individuals with congenital pulmonary atresia (PA).

Methods and Results

Based on the hypothesis that rare structural variants encompassing key genes play an important role in heart development in PA patients, we performed high-resolution genome-wide microarrays for copy number variations (CNVs) in 82 PA patient-parent trios and 189 controls with an Illumina SNP array platform. CNVs were identified in 17/82 patients (20.7%), and eight of these CNVs (9.8%) are considered potentially pathogenic. Five de novo CNVs occurred at two known congenital heart disease (CHD) loci (16p13.1 and 22q11.2). Two de novo CNVs that may affect folate and vitamin B₁₂ metabolism were identified for the first time. A de novo 1-Mb deletion at 17p13.2 may represent a rare genomic disorder that involves mild intellectual disability and associated facial features.

Conclusions

Rare CNVs contribute to the pathogenesis of PA (9.8%), suggesting that the causes of PA are heterogeneous and pleiotropic. Together with previous data from animal models, our results might help identify a link between CHD and folate-mediated one-carbon metabolism (FOCM). With the accumulation of high-resolution SNP array data, these previously undescribed rare CNVs may help reveal critical gene(s) in CHD and may provide novel insights about CHD pathogenesis.     

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 ~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.