Project description:This SuperSeries is composed of the following subset Series: GSE27940: Methylation detection Oligonucleotide Microarray Analysis: high resolution method for CpG island methylation detection 3. GSE27943: Gene Expression Array of Human Ovarian Cancer. GSE28013: Representational Oligonucleotide Microarray Analysis (ROMA) array for Copy Number Variation Detection. Refer to individual Series
Project description:We have conducted a genome-wide analysis of spontaneous copy number variation (CNV) in the laboratory mouse. We used high resolution microarrays to identify 38 CNVs between 14 colonies of the C57BL/6 strain spanning ~967 generations of inbreeding, and examined these loci in 12 additional strains. It is clear from our results that many CNVs arise through a highly non-random process: 18 of 38 were the product of recurrent mutation, and rates of change vary roughly four orders of magnitude across different loci. These recurrent CNVs are distributed throughout the genome, affect 43 genes, and fluctuate in copy number over mere hundreds of generations, observations that raise questions about their contribution to natural variation. Keywords: Representational oligonucleotide microarray analysis, comparative genomic hybridization, DNA copy number variation, structural variation, inbred mice, spontaneous mutation rate
Project description:We examined copy number changes in the genomes of B cells from 58 patients with chronic lymphocytic leukemia (CLL) using representational oligonucleotide microarray analysis (ROMA), a form of comparative genomic hybridization (CGH), at a resolution exceeding previously published studies. We observed at least one genomic lesion in each CLL sample and considerable variation in the number of abnormalities from case to case. Virtually all abnormalities previously reported were also observed here, most of whichwere indeed highly recurrent. We observed the boundaries of known events with greaterclarity and identified previously undescribed lesions, some of which were recurrent. Weprofiled the genomes of CLL cells separated by the surface marker CD38, and foundevidence of distinct subclones of CLL within the same patient. We discuss the potential applications of high resolution CGH analysis in a clinical setting. Keywords: Genetic modification, polymorphonuclear cell (PMN)
Project description:The study was carried out to identify copy number variations using array-CGH in family having three children affected with albinism (OCA1B) and the males were affected with ID. Agilent’s SureScan microarray scanner with SurePrint G3 Human CGH, 8x60K array platform was used for the study. The probes used for the experiment was approximately 60000 oligonucleotide, allowing detection of deletions above 200 Kb and duplication above 500 kb in entire human genome. CytoGenomics software used to carryout data analysis revealed CNVs in participants.
Project description:Goal: To identify copy number variation in normal individuals using high density, non-polymorphic oligonucleotide probes Background DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1kb to over 3Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. Results In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3M independent NspI restriction enzyme fragments in the 200bp to 1100bp size range, which is a several fold increase in marker density as compared to the 500K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. Conclusions Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization. Keywords: Copy number variation (CNV) detection