Copy Number Variation Profiles Research Articles

Spectrum of large copy number variations in 26 diverse Indian populations: potential involvement in phenotypic diversity

Copy number variations (CNVs) have provided a dynamic aspect to the apparently static human genome. We have analyzed CNVs larger than 100 kb in 477 healthy individuals from 26 diverse Indian populations of different linguistic, ethnic and geographic backgrounds. These CNVRs were identified using the Affymetrix 50K Xba 240 Array. We observed 1,425 and 1,337 CNVRs in the deletion and amplification sets, respectively, after pooling data from all the populations. More than 50% of the genes encompassed entirely in CNVs had both deletions and amplifications. There was wide variability across populations not only with respect to CNV extent (ranging from 0.04-1.14% of genome under deletion and 0.11-0.86% under amplification) but also in terms of functional enrichments of processes like keratinization, serine proteases and their inhibitors, cadherins, homeobox, olfactory receptors etc. These did not correlate with linguistic, ethnic, geographic backgrounds and size of populations. Certain processes were near exclusive to deletion (serine proteases, keratinization, olfactory receptors, GPCRs) or duplication (homeobox, serine protease inhibitors, embryonic limb morphogenesis) datasets. Populations having same enriched processes were observed to contain genes from different genomic loci. Comparison of polymorphic CNVRs (5% or more) with those cataloged in Database of Genomic Variants revealed that 78% (2473) of the genes in CNVRs in Indian populations are novel. Validation of CNVs using Sequenom MassARRAY revealed extensive heterogeneity in CNV boundaries. Exploration of CNV profiles in such diverse populations would provide a widely valuable resource for understanding diversity in phenotypes and disease.

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.

Germline copy number variations in BRCA1‐associated ovarian cancer patients

We investigated characteristics of germline copy number variations (CNV) in BRCA1-associated ovarian cancer patients by comparing them to CNVs present in sporadic ovarian cancer patients. Germline CNVs in 51 BRCA1-associated, 33 sporadic ovarian cancer patients, and 47 healthy women were analyzed by both signal intensity and genotyping data using the Affymetrix Genome-Wide Human SNP Array 6.0. The total number of CNVs per genome was greater in the sporadic group (median 26, range 12-34) than in the BRCA1 group (median 21, range 11-35; post hoc P < 0.05) or normal group (median 20, range 7-32; post hoc P < 0.05). While the number of amplifications per genome was higher in the sporadic group (median 13, range 7-26) than in the BRCA1 group (median 8, range 3-23; post hoc P < 0.001), the number of deletions per genome was higher in the BRCA1 group (median 12, range 6-24) than in the sporadic group (median 9, range 3-17; post hoc P < 0.01). In addition, 31 previously unknown CNV regions were present specifically in the BRCA1 group. When we performed pathway analysis on the 241 overlapping genes mapped to these novel CNV regions, the 'purine metabolism' and '14-3-3-mediated signaling' pathways were over-represented (Fisher's exact test, P < 0.01). Our study shows that there are qualitative differences in genomic CNV profiles between BRCA1-associated and sporadic ovarian cancer patients. Further studies are necessary to clarify the significance of the genomic CNV profile unique to BRCA1-associated ovarian cancer patients.

NCBI GEO: archive for functional genomics data sets--10 years on

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Failure to Confirm CNVs as of Aetiological Significance in Twin Pairs Discordant for Schizophrenia

Copy number variations (CNVs) are common structural variations in the human genome that strongly affect genomic diversity and can play a role in the development of several diseases, including neurodevelopmental disorders. Recent reports indicate that monozygotic twins can show differential CNV profiles. We searched CNVs in monozygotic twins discordant for schizophrenia to identify susceptible loci for schizophrenia. Three pairs of monozygotic twins discordant for schizophrenia were subjected to analysis. Genomic DNA samples were extracted from peripheral blood lymphocytes. We adopted the Affymetrix Genome-Wide Human SNP (Single Nucleotide Polymorphism) Array 6.0 to detect copy number discordance using Partek Genomics Suite 6.5 beta. In three twin pairs, however, validations by quantitative PCR and DNA sequencing revealed that none of the regions had any discordance between the three twin pairs. Our results support the hypothesis that epigenetic changes or fluctuation in developmental process triggered by environmental factors mainly contribute to the pathogenesis of schizophrenia. Schizophrenia caused by strong genetics factors including copy number alteration or gene mutation may be a small subset of the clinical population.

800 Genome copy number variation and gene mutation profiling show different somatic development of colorectal cancers in young and elderly patients

800 Genome copy number variation and gene mutation profiling show different somatic development of colorectal cancers in young and elderly patients

Copy number, linkage disequilibrium and disease association in the FCGR locus

The response of a leukocyte to immune complexes (ICs) is modulated by receptors for the Fc region of IgG (FcγRs), and alterations in their affinity or function have been associated with risk of autoimmune diseases, including systemic lupus erythematosus (SLE). The low-affinity FcγR genomic locus is complex, containing regions of copy number variation (CNV) which can alter receptor expression and leukocyte responses to IgG. Combined paralogue ratio tests (PRTs) were used to distinguish three intervals within the FCGR locus which undergo CNV, and to determine FCGR gene copy number (CN). There were significant differences in FCGR3B and FCGR3A CNV profiles between Caucasian, East Asian and Kenyan populations. A previously noted association of low FCGR3B CN with SLE in Caucasians was supported [OR = 1.57 (1.08–2.27), P = 0.018], and replicated in Chinese [OR = 1.65 (1.25–2.18), P = 4 × 10−4]. There was no association of FCGR3B CNV with vasculitis, nor with malarial or bacterial infection. Linkage disequilibrium (LD) between multi-allelic FCGR3B CNV and SLE-associated SNPs in the FCGR locus was defined for the first time. Despite LD between FCGR3B CNV and a variant in FcγRIIB (I232T) which abolishes inhibitory function, both reduced CN of FCGR3B and homozygosity of the FcγRIIB-232T allele were individually strongly associated with SLE risk. Thus CN of FCGR3B, which controls IC responses and uptake by neutrophils, and variations in FCGR2B, which controls factors such as antibody production and macrophage activation, are important in SLE pathogenesis. Further interpretations of contributions to pathogenesis by FcγRs must be made in the context of LD involving CNV regions.

Abstract 112: Concurrent analysis between copy number variation and gene expression of non-smoking lung cancer females in Taiwan

Abstract Although smoking has been proved to be an important factor for lung cancer, the etiology and molecular mechanisms of non-smoking female lung cancer remain unclear. We collected paired normal and tumor lung tissues from 44 female non-smoking lung cancer patients. Copy number variation and Gene expression profiles were analyzed by Affymetrix U133plus 2.0 expression arrays and Affymetrix SNP 6.0 single nucleotide polymorphism (SNP) arrays. The data from two platforms were integrated for concurrent analyses in order to elucidate the putative molecular mechanisms. We first identified the probes located at the same region of gene expression and copy number variation (CNV). Next, we calculated the Pearson correlation coefficient to assess the association between log intensity values of mRNA expression and the corresponding averaged intensity values of SNP probes in both tumor and normal tissues. Genes were then selected based on the following two criteria: (1) the difference in expression-SNP correlations between normal and tumor tissues &amp;gt; 0.7, and (2) the absolute expression-SNP correlation of either normal or tumor &amp;gt;0.3. The selected genes were further analyzed by Ingenuity Pathway Analysis (IPA) to explore the related pathways and networks. Results of IPA showed that mitochondrial dysfunction, IGF-1 signaling, and cell cycle: G1/S checkpoint regulation pathways were significantly dysregulated in tumor tissues. The associations between lung cancer and genomic alternations in these enriched pathways have been reported previously, such as overexpression of IGF1R in IGF-1 signaling pathway might resist EGFR inhibitors used in lung cancer treatment. In summary, with the integrated data of copy number variation and expression, the concurrent analyses help to dissect lung carcinogenesis of non-smoking lung cancer females in Taiwan. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 112.

Abstract 4961: Analysis of genomic alterations in breast cancer using an automated aCGH workstation

Abstract The current sample preparation process for aCGH tests is tedious leading to errors that confound clinical results and increase re-test rates and costs. To overcome this problem, we have developed an aCGH workstation that automates the bench work from DNA labeling to array scanning. A robotic liquid handling and incubation system (ArrayPrep® Target Preparation System) automates the labeling and magnetic bead purification of 8-96 gDNA samples then loads them onto microarrays for hybridization using a rotating incubation system (Mai Tai® Hybridization System). Arrays are then post-processed using a robotic instrument (Little Dipper® Processor) for washing and drying. Previous studies have shown that the aCGH workstation generates high quality labeled gDNA and highly reproducible array data from batches of 8-96 samples. It requires less than 1hr hands-on technician time and can substantially enhance test reproducibility and lower cost (1). In this study, we examined the ability of the aCGH workstation to reproducibly detect genomic alterations in four well characterized breast cancer cell lines, MCF-7, SK-BR-3, BT-474 and MDA-MB-231 and in breast cancer tissue samples with known Her2/neu status. For each sample, replicate gDNA samples were processed using the aCGH workstation and Agilent 44K feature microarrays designed for genome-wide DNA copy number variation (CNV) profiling. The resulting array data were then analyzed for previously reported copy number alterations (CNAs) including loci within chromosomes 1q, 8q, 11q13, 17q and 20q13 (2, 3) and components of the epidermal growth factor receptor pathway affected by copy number changes (3). The results confirm that samples processed on the aCGH workstation reproducibly detect previously reported complex alterations involving multiple levels of change on chromosome arms 1p, 8q, 9p, 11q, 15q, 17q and 20q. Our data also confirmed that copy number alteration of multiple genetic loci involved in the EGF family of pathways is common in all four cell lines. The ERBB2 locus is highly amplified in the two known ERBB2-overexpressing cell lines (BT-474 and SK-BR-3). These two cell lines share amplifications at five additional gene loci, MAP2K6, CHN2, PRKCA, LIMK1 and cMYC, as previously reported (3). In summary, this initial study has shown the successful automation of the aCGH laboratory workflow for detection of genetic abnormalities at high resolution in breast cancer samples. This automated platform holds the potential to significantly improve test reliability and lower the cost of routine genetic analysis of clinical samples.

Pediatric Precursor-B ALL with BTG1 Deletions Show a Distinct Genomic Profile.

Abstract 3244Poster Board III-181Recent genome-wide profiling studies have revealed that childhood acute lymphoblastic leukemia (ALL) is characterized by recurrent microdeletions, including the cell cycle regulator CDKN2A, the B-cell differentiation genes PAX5, EBF1 and IKZF1 (Ikaros) and the anti-proliferative gene B-cell translocation gene 1 (BTG1). In a previous study, we have shown that BTG1 is an important determinant of glucocorticoid sensitivity (Van Galen et al. Blood/ ASH Annual Meeting Abstracts, 2008). In the present study we have characterized these cases in more detail and elucidated the frequency of recurrent lesions in BTG1 deletion cases. Using locus-specific MLPA screening of an unselected cohort of 305 precursor B-ALL cases, we identified 26 microdeletions (8.5%). All deletions encompassed BTG1 only. We were able to genomically profile 22 diagnosis samples using Affimetrix SNP6.0 arrays. Of these, 12 did not develop a relapse during a minimal of 4,5 years of follow up. The mean number of CNVs was 29.6 of which 10.3 gains and 22.5 losses (median size 512 kb and 115 kb respectively). BTG1 deletions were generally focal, varying in size from 104 kb to 1,4 Mb. In all but one patient the breakpoints at the 5' end of the deletion tightly clustered and subsequent fine-mapping using qPCR revealed that this breakpoint cluster was located within intron 1 of the BTG1 gene. At the 3'end of the deletion, four breakpoint clusters could be identified. Analysis of the copy number variation (CNV) profiles showed that patients with a BTG1 deletion more often harbored a deletion in IKZF1 compared to an unselected cohort of pre-B ALL cases (27% vs 7%, chi-square p=0.042). In contrast, recurrent CNVs like PAX5, EBF1 and CDKN2A/B occur in similar frequencies (23%, 9% and 32% vs 17%, 0% and 23% respectively). In addition, the BTG1 deletion cases that developed into a relapse showed significantly more often a deletion in CDKN2A/B compared to the BTG1 deletion cases that did not develop a relapse (60% vs 8%, p=0.02). Together, these data indicate that pediatric precursor-B ALL carrying BTG1 deletions have distinct genomic profiles, showing increased frequencies of deletions in IKZF1 and CDKN2A. DisclosuresNo relevant conflicts of interest to declare.

Across array comparative genomic hybridization: A strategy to reduce reference channel hybridizations

Array comparative genomic hybridization (array CGH) is widely used for studying chromosomal copy number aberrations (CNAs) on a genome-wide and high-resolution scale in heritable disorders and cancers. The aim of this study was to test if the separate channels of dual channel arrays can be interchanged (across array) to either make array CGH more sensitive and cost effective and/or to generate profiles of CNAs and copy number variations (CNVs). Therefore the BT474 breast cancer cell line was compared with a mix of normal reference DNAs hybridized on different arrays and days and DNA copy number profiles were evaluated. Quality was assessed, using regular dual channel array CGH as a standard, using four quality measures, i.e., the median absolute deviation value of chromosome 2, the amplitude of the ERBB2 gene amplification, a deletion on chromosome 9, and the deflection on chromosome 8. The quality of the across array CGH profiles matched or even surpassed the quality of regular dual channel array CGH. In addition, this across array approach was tested for genomic DNA derived from formalin-fixed paraffin-embedded tumors tissue samples, resulting in high-quality copy number profiles, comparable to regular dual channel arrays. Finally, we demonstrated this approach to obtain both CNA and CNV profiles. In summary, across array CGH avoids redundant hybridizations of the same reference material in every experiment either allowing hybridization of two test samples on one array or producing both CNA and CNV profiles simultaneously.