Common CNV Regions Research Articles

A Polynesian-specific copy number variant encompassing the MICA gene associates with gout.

Gout is of particularly high prevalence in the Māori and Pacific (Polynesian) populations of Aotearoa New Zealand (NZ). Here, we investigated the contribution of common population-specific copy number variation (CNV) to gout in the Aotearoa NZ Polynesian population. Microarray-generated genome-wide genotype data from Aotearoa NZ Polynesian individuals with (n = 1196) and without (n = 1249) gout were analyzed. Comparator population groups were 552 individuals of European ancestry and 1962 of Han Chinese ancestry. Levels of circulating major histocompatibility complex (MHC) class I polypeptide-related sequence A (MICA) were measured by enzyme-linked immunosorbent assay. Fifty-four CNV regions (CNVRs) appearing in at least 10 individuals were detected, of which seven common (>2%) CNVRs were specific to or amplified in Polynesian people. A burden test of these seven revealed associations of insertion/deletion with gout (odds ratio (OR) 95% confidence interval [CI] = 1.80 [1.01; 3.22], P = 0.046). Individually testing of the seven CNVRs for association with gout revealed nominal association of CNVR1 with gout in Western Polynesian (Chr6: 31.36-31.45Mb, OR = 1.72 [1.03; 2.92], P = 0.04), CNVR6 in the meta-analyzed Polynesian sample sets (Chr1: 196.75-196.92Mb, OR = 1.86 [1.16; 3.00], P = 0.01) and CNVR9 in Western Polynesian (Chr1: 189.35-189.54Mb, OR = 2.75 [1.15; 7.13], P = 0.03). Analysis of European gout genetic association data demonstrated a signal of association at the CNVR1 locus that was an expression quantitative trait locus for MICA. The most common CNVR (CNVR1) includes deletion of the MICA gene, encoding an immunomodulatory protein. Expression of MICA was reduced in the serum of individuals with the deletion. In summary, we provide evidence for the association of CNVR1 containing MICA with gout in Polynesian people, implicating class I MHC-mediated antigen presentation in gout.

Discovering Copy Number Variation in Dual-Purpose XinJiang Brown Cattle.

Copy number variants (CNVs), which are a class of structural variant, can be important in relating genomic variation to phenotype. The primary aims of this study were to discover the common CNV regions (CNVRs) in the dual-purpose XinJiang-Brown cattle population and to detect differences between CNVs inferred using the ARS-UCD 1.2 (ARS) or the UMD 3.1 (UMD) genome assemblies based on the 150K SNP (Single Nucleotide Polymorphisms) Chip. PennCNV and CNVPartition methods were applied to calculate the deviation of the standardized signal intensity of SNPs markers to detect CNV status. Following the discovery of CNVs, we used the R package HandyCNV to generate and visualize CNVRs, compare CNVs and CNVRs between genome assemblies, and identify consensus genes using annotation resources. We identified 38 consensus CNVRs using the ARS assembly with 1.95% whole genome coverage, and 33 consensus CNVRs using the UMD assembly with 1.46% whole genome coverage using PennCNV and CNVPartition. We identified 37 genes that intersected 13 common CNVs (>5% frequency), these included functionally interesting genes such as GBP4 for which an increased copy number has been negatively associated with cattle stature, and the BoLA gene family which has been linked to the immune response and adaption of cattle. The ARS map file of the GGP Bovine 150K Bead Chip maps the genomic position of more SNPs with increased accuracy compared to the UMD map file. Comparison of the CNVRs identified between the two reference assemblies suggests the newly released ARS reference assembly is better for CNV detection. In spite of this, different CNV detection methods can complement each other to generate a larger number of CNVRs than using a single approach and can highlight more genes of interest.

Integrated Functional Analysis Implicates Syndromic and Rare Copy Number Variation Genes as Prominent Molecular Players in Pathogenesis of Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are caused by disrupted neurodevelopment leading to socio-communication and behavioural abnormalities. Although genetic anomalies like Copy Number Variations (CNV) have been implicated in ASD, their overall genomic landscape and pathogenicity remain elusive. Therefore, we created a CNV map for ASD using 9337 cases and 5650 controls from SFARI database, statistically marked genomic regions with high and low frequencies of CNVs (i.e., common and rare CNV regions respectively), performed gene function enrichment for CNV genes, built functional networks, pathways and examined their expression in brain tissues. Information thus obtained were cumulatively integrated using a weighted scoring strategy to rank CNV regions by their neuro-functional attributes. Subsequently, we mapped 105 genic CNV regions across 20 chromosomes. They encompassed 537 genes, of which only 59 (11%) genes were identified with Single Nucleotide Variations (SNV) in ASD subjects through sequencing and functional studies, which indicated that diverse sets of genes were affected by CNVs and SNVs in ASD. Overall, syndromic CNV regions displayed the most prominent neuronal functions. While common CNV regions were found in loci 15q11.2, 16p11.2, 22q11.21, 15q13.2–13.3, rare CNV regions in loci 4p16.3, 9q34.3, 7q11.23, 17p11.2 contributed significantly to protein interaction networks and were highly expressed in brain. Enriched CNV genes were clustered in six functional categories with either direct roles in neurodevelopment or auxiliary roles like cellular signalling via MAPK pathway, cytoskeletal organization and transport or immune regulation. Mechanisms through which these molecular systems could independently or in combination trigger an ASD phenotype were predicted.

Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk.

Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk. CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression. Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10-5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10-47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10-2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10-5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10-7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10-5). Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression. Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.

Abstract 2287: Precise common and rare germline CNV calling with GATK

Abstract We propose, implement, and evaluate a novel method (GATK gCNV) for accurate discovery of rare and common copy-number variations (CNVs) from read-depth data obtained from whole genome sequencing (WGS), whole exome sequencing (WES), or custom gene panels. GATK gCNV utilizes a sophisticated Bayesian model to learn bias factors arising from sequencing and library preparation. This model accounts for ploidy of sex chromosomes and autosomal aneuploidies, treats GC bias probabilistically, and automatically determines the necessary level of model complexity in a data-driven manner. Unlike most existing read-depth methods, GATK gCNV maintains a high level of sensitivity in common CNV regions, due to a hierarchical hidden Markov model used for accurate genotyping of multi-allelic loci. Furthermore, GATK gCNV performs bias modeling and CNV discovery simultaneously and self-consistently, resulting in significantly improved sensitivity and precision. Our implementation utilizes the PyMC3/Theano framework for performing automatic differentiation variational inference (ADVI). In addition, GATK gCNV automatically scatters large tasks across multiple machines using the Cromwell/WDL framework, enabling the scalable processing of large cohorts. We use GATK gCNV to compute copy-number transmission and de novo rates in a cohort of WES trios and observe consistency with observed population metrics. Furthermore, we benchmark GATK gCNV for sensitivity, precision, and reproducibility of both rare and common CNV calls. Using a cohort of WES blood normal samples from The Cancer Genome Atlas (TCGA), we show that GATK gCNV calls are in remarkable concordance with Genome STRiP calls on matched WGS data and gCNV substantially outperforms XHMM and CODEX. We also validate GATK gCNV calls on WGS data against calls made using PacBio long reads. Citation Format: Mehrtash Babadi, Samuel K. Lee, Andrey Smirnov, Lee Lichtenstein, Laura D. Gauthier, Daniel P. Howrigan, Timothy Poterba. Precise common and rare germline CNV calling with GATK [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2287.

Genome-wide association study of copy number variation with lung function identifies a novel signal of association near BANP for forced vital capacity.

BackgroundGenome-wide association studies of Single Nucleotide Polymorphisms (SNPs) have identified 55 SNPs associated with lung function. However, little is known about the effect of copy number variants (CNVs) on lung function, although CNVs represent a significant proportion of human genetic polymorphism. To assess the effect of CNVs on lung function quantitative traits, we measured copy number at 2788 previously characterised, common copy number variable regions in 6 independent cohorts (n = 24,237) using intensity data from SNP genotyping experiments. We developed a pipeline for genome-wide association analysis and meta-analysis of CNV genotypes measured across multiple studies using SNP genotype array intensity data from different platform technologies. We then undertook cohort-level genome-wide association studies of CNV with lung function in a subset of 4 cohorts (n < =12,403) with lung function measurements and meta-analysed the results. Follow-up was undertaken for CNVs which were well tagged by SNPs, in up to 146,871 individuals.ResultsWe generated robust copy number calls for 1962 out of 2788 (70 %) known CNV regions genome-wide, with 1103 measured with compatible class frequencies in at least 2 cohorts. We report a novel CNV association (discovery P = 0.0007) with Forced Vital Capacity (FVC) downstream of BANP on chromosome 16 that shows evidence of replication by a tag SNP in two independent studies (replication P = 0.004). In addition, we provide suggestive evidence (discovery P = 0.0002) for a role of complex copy number variation at a previously reported lung function locus, containing the rootletin gene CROCC, that is not tagged by SNPs.ConclusionsWe demonstrate how common CNV regions can be reliably and consistently called across cohorts, using an existing calling algorithm and rigorous quality control steps, using SNP genotyping array intensity data. Although many common biallelic CNV regions were well-tagged by common SNPs, we also identified associations with untagged mulitallelic CNV regions thereby illustrating the potential of our approach to identify some of the missing heritability of complex traits.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0423-0) contains supplementary material, which is available to authorized users.

A genome-wide scan of copy number variants using high-density SNPs in Brown Swiss dairy cattle

Detecting genetic variation such as Copy Number Variants (CNVs) in cattle provides the opportunity to study their association with quantitative traits. CNVs are DNA sequences of 50bp up to several Mb long, which can vary in copy number in comparison with a reference genome. The aim of this study was to investigate CNVs in 1410 samples of the Brown Swiss cattle breed using Illumina Bovine HD SNP chip information, which includes 777,962 SNPs. After stringent quality control, CNVs were called with the Golden Helix SVS 8.3.1 (SVS) and PennCNV software and were summarized to CNV regions (CNVRs) at a population level (i.e. overlapping CNVs), using BEDTools. Additionally, common CNVRs between the two software were set as consensus regions. Genes within consensus CNVRs were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. In order to validate these results, quantitative PCRs were executed on 15 selected CNVRs.The SVS software identified 25,030 CNVs summarized to 398 CNVRs, which comprised 30 gains, 344 losses and 24 complex CNVRs (i.e. containing both losses and gains), covering 3.92% of the bovine genome. The PennCNV software identified 62,341 CNVs summarized to 5578 CNVRs, which comprised 2638 gains, 2404 losses and 537 complex CNVRs, covering 7.68% of the bovine genome. The length of these CNVRs ranged from 1244bp to 1,381,355bp. A total of 563 consensus CNVRs were found covering 2.29% of the UMD 3.1 bovine genome assembly. Of these, 24 were gains, 300 were losses and 239 were complex CNVRs. A total of 775 official gene IDs were annotated in the consensus CNVRs. Among the 537 genes with functional information, the GO and pathway analysis was reported for those who clustered with a p-value <0.05. The quantitative PCRs successfully validated 14 (93.33%) of the selected CNVRs.The result of this study is the first comprehensive genomic analysis of the Brown Swiss breed based on the Illumina Bovine HD SNP chip on such a large number of animals that enriches the CNV map in the bovine genome. These findings also provide valuable information for further CNV studies. Finally, the results of the CNVR map delivers new information for functional, health and productive traits considered in selection programs of the Brown Swiss breed.

Identification of copy number variations in three Chinese horse breeds using 70K single nucleotide polymorphism BeadChip array.

Copy number variation (CNV), an essential form of genetic variation, has been increasingly recognized as one promising genetic marker in the analysis of animal genomes. Here, we used the Equine 70K single nucleotide polymorphism genotyping array for the genome-wide detection of CNVs in 96 horses from three diverse Chinese breeds: Debao pony (DB), Mongolian horse (MG) and Yili horse (YL). A total of 287 CNVs were determined and merged into 122 CNV regions (CNVRs) ranging from 199bp to 2344kb in size and distributed in a heterogeneous manner on chromosomes. These CNVRs were integrated with seven existing reports to generate a composite genome-wide dataset of 1558 equine CNVRs, revealing 69 (56.6%) novel CNVRs. The majority (69.7%) of the 122 CNVRs overlapped with 438 genes, whereas 30.3% were located in intergenic regions. Most of these genes were associated with common CNVRs, which were shared by divergent horse breeds. As many as 60, 42 and 91 genes overlapping with the breed-specific ss were identified in DB, MG and YL respectively. Among these genes, FGF11, SPEM1, PPARG, CIDEB, HIVEP1 and GALR may have potential relevance to breed-specific traits. These findings provide valuable information for understanding the equine genome and facilitating association studies of economically important traits with equine CNVRs in the future.

CNV analysis in the Lithuanian population.

BackgroundAlthough copy number variation (CNV) has received much attention, knowledge about the characteristics of CNVs such as occurrence rate and distribution in the genome between populations and within the same population is still insufficient. In this study, Illumina 770 K HumanOmniExpress-12 v1.0 (and v1.1) arrays were used to examine the diversity and distribution of CNVs in 286 unrelated individuals from the two main ethnolinguistic groups of the Lithuanian population (Aukštaičiai and Žemaičiai) (see Additional file 3). For primary data analysis, the Illumina GenomeStudio™ Genotyping Module v1.9 and two algorithms, cnvPartition 3.2.0 and QuantiSNP 2.0, were used to identify high-confidence CNVs.ResultsA total of 478 autosomal CNVs were detected by both algorithms, and those were clustered in 87 copy number variation regions (CNVRs), spanning ~12.5 Mb of the genome (see Table 1). At least 8.6 % of the CNVRs were unique and had not been reported in the Database of Genomic Variants. Most CNVRs (57.5 %) were rare, with a frequency of <1 %, whereas common CNVRs with at least 5 % frequency made up only 1.1 % of all CNVRs identified. About 49 % of non-singleton CNVRs were shared between Aukštaičiai and Žemaičiai, and the remaining CNVRs were specific to each group. Many of the CNVs detected (66 %) overlapped with known UCSC gene regions.ConclusionsThe ethnolinguistic groups of the Lithuanian population could not be differentiated based on CNV profiles, which may reflect their geographical proximity and suggest the homogeneity of the Lithuanian population. In addition, putative novel CNVs unique to the Lithuanian population were identified. The results of our study enhance the CNV map of the Lithuanian population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0373-6) contains supplementary material, which is available to authorized users.

GENOME-WIDE MAPPING OF COPY NUMBER VARIATIONS IN COMMERCIAL HYBRID PIGS USING A HIGH-DENSITY SNP GENOTYPING ARRAY.

Copy number variations (CNVs) are important forms of structural variation in human and animals and can be considered as a major genetic component of phenotypic diversity. Here we used the Illumina PorcineSNP60 BeadChip V2 and a DLY [Duroc x (Large White x Landrace)] commercial hybrid population to identify 272 CNVs belonging to 165 CNV regions (CNVRs), of which 66 are new. As CNVRs are specific to origin of population, our DLY-specific data is an important complementary to the existing CNV map in the pig genome. Eight CNVRs were selected. for validation by quantitative real-time PCR (qRT-PCR) and the accurate rate was high (87.25%). Gene function analysis suggested that a common CNVR may play an important role in multiple traits, including growth rate and carcass quality.

Genomic characteristics of miscarriage copy number variants.

Studies of copy number variants (CNVs) in miscarriages are rare in comparison to post-natal cases with developmental abnormalities. The overall characteristics of miscarriage CNVs (size, gene content and function) are therefore largely unexplored. Our goal was to assess and compare the characteristics of CNVs identified in 101 euploid miscarriages from four high-resolution array studies that documented both common miscarriage CNVs (i.e. CNVs found in controls from the Database of Genomic Variants, DGV) and rare miscarriage CNVs (not reported in DGV). Our miscarriage analysis included 24 rare CNVs with 93 genes, and 372 common CNVs (merged into 119 common CNV regions; CNVRs) with 354 genes. The rare and common CNVs were comparable in size (median size of ∼ 0.16 and 0.14 Mb, respectively); however, rare CNVs showed a significantly higher gene density, with 56 genes/Mb in rare and 24 genes/Mb in common CNVs (P = 0.03). Rare CNVs also had two times more genes with mouse knock-out models which were reported for 42% of rare and 19% of common CNV genes. No specific pathway enrichment was noted for 24 rare CNV genes, but common CNV genes showed significant enrichment in genes from immune-response related pathways and pregnancy/reproduction-related biological processes. Our analysis of CNVs from euploid miscarriages suggests that both rare and common CNVs could have a role in miscarriage by impacting pregnancy-related genes or pathways. Cataloguing of all CNVs and detailed description of their characteristics (e.g. gene content, genomic breakpoints) is desirable in the future for better understanding of their relevance to pregnancy loss.

Differential genomic alterations in normal and cancerous lung cells in response to chronic inflammation

Although chronic inflammation increases the risk of carcinogenesis, there have been few reports of genome-wide screening for chromosomal alterations and DNA damage, such as mutations and strand breaks, induced by chronic inflammation. This study utilized high-resolution comparative genomic hybridization to detect copy number variations (CNVs) between normal and cancerous lung cells treated with tumor necrosis factor-alpha (TNF-α) for 24 weeks to induce chronic inflammation. Ingenuity Pathway Analysis was used to analyze the functions of genes located at the common CNV regions that were induced by chronic inflammation. The results shown that TNF-α induced more CNVs in normal lung cells than in cancerous lung cells. Moreover, Ingenuity Pathway Analysis was used to analyze the function of genes located at the common CNV regions get involved in cancer progression, DNA repair and inflammatory disease. In conclusion, chronic inflammation might be one of a set of factors which transform normal lung cells into tumor cells.

Deletion Variants of RABGAP1L, 10q21.3, and C4 Are Associated With the Risk of Systemic Lupus Erythematosus in Korean Women

Several copy number variations (CNVs) have been found to be associated with systemic lupus erythematosus (SLE) through the target gene approach. However, genome-wide features of CNVs and their role in the risk of SLE remain unknown. The aim of this study was to identify SLE-associated CNVs in Korean women. Genome-wide assessments of CNVs were performed in 382 SLE patients and 191 control subjects, using an Illumina HumanHap610 BeadChip genotyping platform. SLE-associated CNV regions that were identified by genome-wide association study (GWAS) were replicated in quantitative polymerase chain reaction (PCR) and deletion-typing PCR analyses in an independent sample set comprising 564 SLE patients and 511 control subjects. Of 144 common CNV regions, 3 deletion-type CNV regions in 1q25.1, 8q23.3, and 10q21.3 were found to be significantly associated with SLE by GWAS analysis. In the independent replication, the CNV regions in 1q25.1 (RABGAP1L) and 10q21.3 were successfully replicated (odds ratio [OR] 1.30, P=0.038 and OR 1.90, P=3.6×10(-5), respectively), and the associations were confirmed again by deletion-typing PCR. The CNV region in the C4 gene, which showed a potential association in the discovery stage, was included in the replication analysis and was found to be significantly associated with the risk of SLE (OR 1.88, P=0.01). Through deletion-typing PCR, the exact sizes and breakpoint sequences of the deletions were defined. Individuals with the deletions in all 3 loci (RABGAP1L, 10q21.3, and C4) had a much higher risk of SLE than did those without any deletions in the 3 loci (OR 5.52, P=3.9×10(-4)). These CNV regions can be useful to identify the pathogenic mechanisms of SLE, and might be used to more accurately predict the risk of SLE by taking into consideration their synergistic effects on disease susceptibility.

Large common deletions associate with mortality at old age.

Copy-number variants (CNVs) are a source of genetic variation that increasingly are associated with human disease. However, the role of CNVs in human lifespan is to date unknown. To identify CNVs that influence mortality at old age, we analyzed genome-wide CNV data in 5178 participants of Rotterdam Study (RS1) and positive findings were evaluated in 1714 participants of the second cohort of the Rotterdam Study (RS2) and in 4550 participants of Framingham Heart Study (FHS). First, we assessed the total burden of rare (frequency <1%) and common (frequency >1%) CNVs for association with mortality during follow-up. These analyses were repeated by stratifying CNVs by type and size. Secondly, we assessed individual common CNV regions (CNVR) for association with mortality. We observed that the burden of common but not of rare CNVs influences mortality. A higher burden of large (≥ 500 kb) common deletions associated with 4% higher mortality [hazard ratio (HR) per CNV 1.04, 95% confidence interval (CI) 1.02-1.07, P = 5.82 × 10(-5)] in the 11 442 participants of RS1, RS2 and FHS. In the analysis of 312 individual common CNVRs, we identified two regions (11p15.5; 14q21.3) that associated with higher mortality in these cohorts. The 11p15.5 region (combined HR 1.59, 95% CI 1.31-1.93, P = 2.87 × 10(-6)) encompasses 41 genes, of which some have previously been related to longevity, whereas the 14q21.3 region (combined HR 1.57, 95% CI 1.19-2.07, P = 1.53 × 10(-3)) does not encompass any genes. In conclusion, the burden of large common deletions, as well as common CNVs in 11p15.5 and 14q21.3 region, associate with higher mortality.

The Genetic Effect of Copy Number Variations on the Risk of Alcoholism in a Korean Population

Alcoholism, a chronic behavioral disorder characterized by excessive alcohol consumption, has been a leading cause of morbidity and premature death. This condition is believed to be influenced by genetic factors. As copy number variation (CNV) has been recently discovered in human genome, genomic diversity of human genome is more frequent than previously thought. Many studies have reported evidences that CNV is associated with the development of complex diseases. In this study, we hypothesized that CNV can predict the risk of alcoholism. Using the Illumina HumanHap660W-Quad BeadChip (∼660 k markers), genome-wide genotyping was performed to obtain signal and allelic intensities from 116 alcoholic cases and 1,022 healthy controls (total n = 1,138) in a Korean population. To identify alcoholism-associated CNV regions, we performed a genome-wide association analysis, using multivariate logistic regression model controlling for age and gender. We identified a total of 255,732 individual CNVs and 3,261 CNV regions (1,067 common CNV regions, frequency > 1%) in this study. Results from multivariate logistic regression showed that the chr20:61195302-61195978 regions were significantly associated with the risk of alcoholism after multiple corrections (p = 5.02E-05, p(corr) = 0.04). Most of the identified variations in this study overlapped with the previously reported CNVs in the Database of Genomic Variants (95.3%). The identified CNVs, which encompassed 3,226 functional genes, were significantly enriched in the cellular part, in the membrane-bound organelle, in the cell part, in developmental processes, in cell communication, in neurological system process, in sensory perception of smell and chemical stimulus, and in olfactory receptor activity. This is the first genome-wide association study to investigate the relationship between common CNV and alcoholism. Our results suggest that the newly identified CNV regions may contribute to the development of alcoholism.

Data-driven approach to detect common copy-number variations and frequency profiles in a population-based Korean cohort

To date, hundreds of thousands of copy-number variation (CNV) data have been reported using various platforms. The proportion of Asians in these data is, however, relatively small as compared with that of other ethnic groups, such as Caucasians and Yorubas. Because of limitations in platform resolution and the high noise level in signal intensity, in most CNV studies (particularly those using single nucleotide polymorphism arrays), the average number of CNVs in an individual is less than the number of known CNVs. In this study, we ascertained reliable, common CNV regions (CNVRs) and identified actual frequency rates in the Korean population to provide more CNV information. We performed two-stage analyses for detecting structural variations with two platforms. We discovered 576 common CNVRs (88 CNV segments on average in an individual), and 87% (501 of 576) of these CNVRs overlapped by ≥1 bp with previously validated CNV events. Interestingly, from the frequency analysis of CNV profiles, 52 of 576 CNVRs had a frequency rate of <1% in the 8842 individuals. Compared with other common CNV studies, this study found six common CNVRs that were not reported in previous CNV studies. In conclusion, we propose the data-driven detection approach to discover common CNVRs including those of unreported in the previous Korean CNV study while minimizing false positives. Through our approach, we successfully discovered more common CNVRs than previous Korean CNV study and conducted frequency analysis. These results will be a valuable resource for the effective level of CNVs in the Korean population.

A Definitive Haplotype Map as Determined by Genotyping Duplicated Haploid Genomes Finds a Predominant Haplotype Preference at Copy-Number Variation Events

The majority of complete hydatidiform moles (CHMs) harbor duplicated haploid genomes that originate from sperm. This makes CHMs more advantageous than conventional diploid cells for determining haplotypes of SNPs and copy-number variations (CNVs), because all of the genetic variants in a CHM genome are homozygous. Here we report SNP and CNV haplotype structures determined by analysis of 100 CHMs from Japanese subjects via high-density DNA arrays. The obtained haplotype map should be useful as a reference for the haplotype structure of Asian populations. We resolved common CNV regions (merged CNV segments across the examined samples) into CNV events (clusters of CNV segments) on the basis of mutual overlap and found that the haplotype backgrounds of different CNV events within the same CNV region were predominantly similar, perhaps because of inherent structural instability.

Identification of Genome-wide Copy Number Variations and a Family-based Association Study of Avellino Corneal Dystrophy

To determine the association of identified copy number variations (CNVs) in whole genome with the risk of Avellino corneal dystrophy (ACD) in a Korean population. Case-control study. A total of 146 patients with ACD and 226 control subjects. A total of 193 trios were genotyped by the Illumina HumanHapCNV370-Duo BeadChip (370,404 markers) (Illumina, Inc., San Diego, CA). The intensity signal (log R ratio) and allelic intensity ratio (B allele frequency) of each marker in all individuals were obtained by Illumina BeadStudio software (Illumina, Inc.). To obtain authentic CNVs in this study, we performed a family-based CNV validation and family-based boundary mapping using the PennCNV algorithm, which incorporates multiple factors, including total log R ratio, B allele frequency, and family information, based on an integrated hidden Markov model. Statistical comparison and identification of CNVs between case and control using family information. We identified 27,267 individual trio CNVs with a median size of 16.2 kb, aggregated in 2245 CNV regions. Most of the identified trio CNVs in this study showed well-defined CNV boundaries and overlapped with those in the Database of Genomic Variants (DGV) (83.4% in number and 79.2% in length). With the common CNV regions (264 CNV regions >5%), we performed a family-based association test with the risk of ACD. Two CNV regions (chr6:29978470-29987783 and chr14:59896944-59916129) were significantly associated with the risk of ACD (P=0.05-0.003 and P=0.008, respectively). This study describes the first results of a genome-wide association analysis of individual CNVs with the risk of ACD and shows that 2 novel CNV loci may be involved in the risk of ACD. The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Genome-wide Association Study in a High-Risk Isolate for Multiple Sclerosis Reveals Associated Variants in STAT3 Gene

Genetic risk for multiple sclerosis (MS) is thought to involve both common and rare risk alleles. Recent GWAS and subsequent meta-analysis have established the critical role of the HLA locus and identified new common variants associated to MS. These variants have small odds ratios (ORs) and explain only a fraction of the genetic risk. To expose potentially rare, high-impact alleles, we conducted a GWAS of 68 distantly related cases and 136 controls from a high-risk internal isolate of Finland with increased prevalence and familial occurrence of MS. The top 27 loci with p < 10(-4) were tested in 711 cases and 1029 controls from Finland, and the top two findings were validated in 3859 cases and 9110 controls from more heterogeneous populations. SNP (rs744166) within the STAT3 gene was associated to MS (p = 2.75 x 10(-10), OR 0.87, confidence interval 0.83-0.91). The protective haplotype for MS in STAT3 is a risk allele for Crohn disease, implying that STAT3 represents a shared risk locus for at least two autoimmune diseases. This study also demonstrates the potential of special isolated populations in search for variants contributing to complex traits.

Identification of SNP markers for common CNV regions and association analysis of risk of subarachnoid aneurysmal hemorrhage in Japanese population

Copy number variation (CNV) is emerging as a new tool for understanding human genomic variation, but its relationship with human disease is not yet fully understood. The data for a total of 317,503 genotypes were collected for a genome-wide association study of subarachnoid aneurismal hemorrhage (SAH) in a Japanese population (cases and controls, n=497) using Illumina HumanHap300 BeadChip®. To identify multi-allelic CNV markers, we visually inspected all genotype clusters of 317,503 SNP markers covering the whole genome using Illumina’s BeadStudio 3.0® software. As a result, we identified 597 multi-allelic CNV markers for common (copy loss frequency>0.05) CNV regions in a Japanese population (n=497). The identified CNV markers shared the following characteristics: enrichment of Hardy–Weinberg disequilibria, Mendelian inconsistency among families, and high missing genotype rate. All annotated information for those markers is summarized in our database (http://www.snp-genetics.com/user/srch.htm). In addition, we performed case-control association analyses of identified multi-allelic CNV markers with the risk of subarachnoid aneurysmal hemorrhage. One SNP marker (rs1242541) within a CNV region neighboring the Sel-1 suppressor of lin-12-like protein (SEL1L) was significantly associated with a risk of SAH (P=0.0006). We also validated the CNV around rs1242541 using real-time quantitative polymerase chain reaction (PCR). Information and methods used in this study would be helpful for accurate genotyping of SNPs on CNV regions, which could be used for association analysis of SNP markers within CNV regions.