ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data.
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BACKGROUND: Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies. METHODOLOGY/PRINCIPAL FINDINGS: ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers. CONCLUSIONS/SIGNIFICANCE: ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects. (+info)
Detection of novel amplicons in prostate cancer by comprehensive genomic profiling of prostate cancer cell lines using oligonucleotide-based arrayCGH.
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BACKGROUND: The purpose of this study was to prove the feasibility of a longmer oligonucleotide microarray platform to profile gene copy number alterations in prostate cancer cell lines and to quickly indicate novel candidate genes, which may play a role in carcinogenesis. METHODS/RESULTS AND FINDINGS: Genome-wide screening for regions of genetic gains and losses on nine prostate cancer cell lines (PC3, DU145, LNCaP, CWR22, and derived sublines) was carried out using comparative genomic hybridization on a 35,000 feature oligonucleotide microarray (arrayCGH). Compared to conventional chromosomal CGH, more deletions and small regions of gains, particularly in pericentromeric regions and regions next to the telomeres, were detected. As validation of the high-resolution of arrayCGH we further analyzed a small amplicon of 1.7 MB at 9p13.3, which was found in CWR22 and CWR22-Rv1. Increased copy number was confirmed by fluorescence in situ hybridization using the BAC clone RP11-165H19 from the amplified region comprising the two genes interleukin 11 receptor alpha (IL11-RA) and dynactin 3 (DCTN3). Using quantitative real time PCR (qPCR) we could demonstrate that IL11-RA is the gene with the highest copy number gain in the cell lines compared to DCTN3 suggesting IL11-RA to be the amplification target. Screening of 20 primary prostate carcinomas by qPCR revealed an IL11-RA copy number gain in 75% of the tumors analyzed. Gain of DCTN3 was only found in two cases together with a gain of IL11-RA. CONCLUSIONS/SIGNIFICANCE: ArrayCGH using longmer oligonucleotide microarrays is feasible for high-resolution analysis of chomosomal imbalances. Characterization of a small gained region at 9p13.3 in prostate cancer cell lines and primary prostate cancer samples by fluorescence in situ hybridization and quantitative PCR has revealed interleukin 11 receptor alpha gene as a candidate target of amplification with an amplification frequency of 75% in prostate carcinomas. Frequent amplification of IL11-RA in prostate cancer is a potential mechanism of IL11-RA overexpression in this tumor type. (+info)
The role of SMAD4 in early-onset colorectal cancer.
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Comprehensive analysis of the impact of SNPs and CNVs on human microRNAs and their regulatory genes.
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Human microRNAs (miRNAs) are potent regulators of gene expression and thus involved in a broad range of biological processes. The objective of this study was to update the properties of human miRNAs and to search for SNPs and CNVs with potential effects on them. Based on the miRBase 13.0 database, we identified 380 (53.9%) precursor miRNAs (pre-miRNAs) embedded in gene loci that are enriched in biological processes such as "neuronal activities", "cell cycle" and "protein phosphorylation" (Bonferroni p < 0.05). Gene lengths of the pre-miRNA host genes are significantly larger than other genes in the genome (p < 2.2E-16). Using data mining public resources, we performed a genome-scale search for the regulatory polymorphisms in the loci of pre-miRNAs and their related genes. Altogether, we found 187 SNPs in the pre-miRNAs, 497 consensus SNPs in the seed-matching untranslated regions of target genes, 385 CNVs harboring pre-miRNA precursors and 9 CNVs covering important miRNA processing genes. We also noticed that minimum free energy changed by pre-miRNA-residing SNPs could be ranked by the order from low to high as the SNPs in the loop domain, the SNPs in the adjacent stem and basal stem domains, and the SNPs in mature miRNA and its complementary sequence domains (p = 0.0065). With a full list of miRNA-related polymorphisms, this study will facilitate future association studies between the genetic polymorphisms in miRNA targets or pre-miRNAs and the disease susceptibility or therapeutic outcome. (+info)
A comprehensive profile of DNA copy number variations in a Korean population: identification of copy number invariant regions among Koreans.
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