Dataset Information

Oligonucleotide-based arrayCGH

ABSTRACT: Array-based comparative genomic hybridisation is a high-resolution method for measuring chromosomal copy number changes. Here we present a validated protocol using in-house spotted oligonucleotide libraries for array CGH. This oligo array CGH platform yields reproducible results and is capable of detecting single copy gains, multi-copy amplifications as well as homozygous and heterozygous deletions as small as 100 kb with high resolution. A human oligonucleotide library was printed on amine binding slides. Arrays were hybridised using a hybstation and analysed using BleuFuse feature extraction software, with over 95% of spots passing quality control. The protocol allows as little as 300 ng of input DNA without the need for amplification or target reduction and a 90% reduction of Cot1-DNA without compromising quality. High quality results have also been obtained with DNA from archival tissue. Finally, in addition to human oligo arrays, we have applied the protocol successfully to mouse oligo arrays. We believe that this oligo-based platform using “off-the-shelf” oligo-libraries provides an easy accessible alternative to BAC arrays for CGH, which is cost-effective, available at high resolution and easily implemented for any sequenced organism without compromising the quality of the results. Keywords: comparative genomic hybridization, oligonucleotide,

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE3264 | GEO | 2005/12/19

SECONDARY ACCESSION(S): PRJNA92921

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:BACKGROUND: Cervical carcinoma develops as a result of multiple genetic alterations. Different studies investigated genomic alterations in cervical cancer mainly by means of metaphase comparative genomic hybridization (mCGH) and microsatellite marker analysis for the detection of loss of heterozygosity (LOH). Currently, high throughput methods such as array comparative genomic hybridization (array CGH), single nucleotide polymorphism array (SNP array) and gene expression arrays are available to study genome-wide alterations. Integration of these 3 platforms allows detection of genomic alterations at high resolution and investigation of an association between copy number changes and expression. RESULTS: Genome-wide copy number and genotype analysis of 10 cervical cancer cell lines by array CGH and SNP array showed highly complex large-scale alterations. A comparison between array CGH and SNP array revealed that the overall concordance in detection of the same areas with copy number alterations (CNA) was above 90%. The use of SNP arrays demonstrated that about 75% of LOH events would not have been found by methods which screen for copy number changes, such as array CGH, since these were LOH events without CNA. Regions frequently targeted by CNA, as determined by array CGH, such as amplification of 5p and 20q, and loss of 8p were confirmed by fluorescent in situ hybridization (FISH). Genome-wide, we did not find a correlation between copy-number and gene expression. At chromosome arm 5p however, 22% of the genes were significantly upregulated in cell lines with amplifications as compared to cell lines without amplifications, as measured by gene expression arrays. For 3 genes, SKP2, ANKH and TRIO, expression differences were confirmed by quantitative real-time PCR (qRT-PCR). CONCLUSION: This study showed that copy number data retrieved from either array CGH or SNP array are comparable and that the integration of genome-wide LOH, copy number and gene expression is useful for the identification of gene specific targets that could be relevant for the development and progression in cervical cancer. Keywords: DNA copynumber RNA expression correlation

Project description:Background: Osteosarcoma (OS) tumors and derived cell lines are characterized by complex chromosomal abnormalities. The availability of molecular genome profiling techniques such as array CGH have markedly enabled the high-resolution genome analysis of tumor genomes, as well as helped elucidate the mechanisms leading to their complexity. The identification of tumor-specific genomic profiles is currently the focus of many array CGH studies, but there have been no analyses to date documenting the genomic signatures consistent with chromosomal instability mechanisms in OS. Results: In this study we utilized high-resolution oligonucleotide array CGH to interrogate recurrent signatures of genomic imbalance in 10 OS tumors that were consistent with the breakage fusion bridge(BFB) mechanism. Comparative analysis of the tumors showed that they exhibited varying levels of genomic imbalance. The analysis also highlighted three chromosomal regions (6p21 ~ p22, 8q24 and 17p11.2 ~ p12) that were consistently involved in high level gain or amplification events. These three regions have been previously shown by us to be not only involved in high-level imbalance in OS-derived cell lines, but also to exhibit similar imbalance profiles consistent with BFB-related events. Karyotype and dual-color FISH analysis showed that repeated rearrangements of these unstable chromosomes through BFB cycles may create a heterogeneous pattern of copy number alterations. Conclusions: This genome-wide analysis is the first to utilize oligonucleotide array CGH and FISH analysis to derive possible genomic signatures of chromosomal instability in OS tumors. Perpetuation of the BFB cycle will create a heterogeneous pattern of copy number alterations by repeated rearrangement of the unstable tumor genome., thereby generating diverse phenotypes The resulting phenotypic diversity can generate tumors with a propensity for an aggressive disease course. A better understanding of the underlying mechanisms events leading to tumor development could result in the identification of prognostic markers and therapeutic targets. Keywords: osteosarcoma, chromosomal instability, gene amplification, breakage-fusion-bridge cycle, oligonucleotide array comparative genomic hybridization

Dataset Information

Oligonucleotide-based arrayCGH

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure