Identification of frequent chromosome copy-number polymorphisms by use of high-resolution single-nucleotide-polymorphism arrays.
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ABSTRACT:
SUBMITTER: Wirtenberger M
PROVIDER: S-EPMC1380295 | biostudies-literature | 2006 Mar
REPOSITORIES: biostudies-literature
Publications
Identification of frequent chromosome copy-number polymorphisms by use of high-resolution single-nucleotide-polymorphism arrays.
Wirtenberger Michael M Hemminki Kari K Burwinkel Barbara B
American journal of human genetics 20060301 3
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Project description:BackgroundThe identification of copy number aberration in the human genome is an important area in cancer research. We develop a model for determining genomic copy numbers using high-density single nucleotide polymorphism genotyping microarrays. The method is based on a Bayesian spatial normal mixture model with an unknown number of components corresponding to true copy numbers. A reversible jump Markov chain Monte Carlo algorithm is used to implement the model and perform posterior inference.ResultsThe performance of the algorithm is examined on both simulated and real cancer data, and it is compared with the popular CNAG algorithm for copy number detection.ConclusionsWe demonstrate that our Bayesian mixture model performs at least as well as the hidden Markov model based CNAG algorithm and in certain cases does better. One of the added advantages of our method is the flexibility of modeling normal cell contamination in tumor samples.
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Project description:Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.
| S-EPMC2875020 | biostudies-literature
Project description:Whole-genome analysis using high-density single-nucleotide-polymorphism oligonucleotide arrays allows identification of microdeletions, microduplications, and uniparental disomies. We studied 67 children with unexplained mental retardation with normal karyotypes, as assessed by G-banded chromosome analyses. Their DNAs were analyzed with Affymetrix 100K arrays. We detected 11 copy-number variations that most likely are causative of mental retardation, because they either arose de novo (9 cases) and/or overlapped with known microdeletions (2 cases). The eight deletions and three duplications varied in size from 200 kb to 7.5 Mb. Of the 11 copy-number variations, 5 were flanked by low-copy repeats. Two of those, on chromosomes 15q25.2 and Xp22.31, have not been described before and have a high probability of being causative of new deletion and duplication syndromes, respectively. In one patient, we found a deletion affecting only a single gene, MBD5, which codes for the methyl-CpG-binding domain protein 5. In addition to the 67 children, we investigated 4 mentally retarded children with apparent balanced translocations and detected four deletions at breakpoint regions ranging in size from 1.1 to 14 Mb.
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Project description:To identify genomic abnormalities characteristic of pancreatic ductal adenocarcinoma (PDAC) in vivo, a panel of 27 microdissected PDAC specimens were analysed using high-density microarrays representing approximately 116 000 single nucleotide polymorphism (SNP) loci. We detected frequent gains of 1q, 2, 3, 5, 7p, 8q, 11, 14q and 17q (> or =78% of cases), and losses of 1p, 3p, 6, 9p, 13q, 14q, 17p and 18q (> or =44%). Although the results were comparable with those from array CGH, regions of those genetic changes were defined more accurately by SNP arrays. Integrating the Ensembl public data, we have generated 'gene' copy number indices that facilitate the search for novel candidates involved in pancreatic carcinogenesis. Copy numbers in a subset of the genes were validated using quantitative real-time PCR. The SKAP2/SCAP2 gene (7p15.2), which belongs to the src family kinases, was most frequently (63%) amplified in our sample set and its recurrent overexpression (67%) was confirmed by reverse transcription-PCR. Furthermore, fluorescence in situ hybridization and in situ RNA hybridization analyses for this gene have demonstrated a significant correlation between DNA copy number and mRNA expression level in an independent sample set (P<0.001). These findings indicate that the dysregulation of SKAP2/SCAP2, which is mostly caused by its increased gene copy number, is likely to be associated with the development of PDAC.
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Project description:Primary intraocular lymphoma (PIOL) is a rare lymphoma. Because of difficulties in obtaining tissue samples, little is known about the disease's genetic features. In order to clarify these features, we carried out single nucleotide polymorphism array karyotyping of IOL using genomic DNA extracted from vitreous fluid. We analyzed 33 samples of IOLs consisting of 16 PIOLs, 12 IOLs with a central nervous system (CNS) lesion at diagnosis (IOCNSL), and five secondary IOLs following systemic lymphoma. All were B-cell type. We identified recurrent copy number (CN) gain regions in PIOLs, most frequently on chromosome 1q followed by 18q and 19q. Chromosome 6q was the most frequent loss region. Although these CN gain regions of PIOL were in common with those of IOCNSL, loss of 6q22.33 containing PTPRK and 9p21.3 containing CDKN2A were more frequently deleted in IOCNSL. Large CN loss in 6q was detected in three of four PIOL patients who had early CNS development and short survival periods, whereas long-term survivors did not have such deletions. There was a correlation between gain of the IL-10 gene located on 1q and intravitreal interleukin-10 concentration, which was higher in IOL than in benign uveitis. The results suggest that IOCNSL is a highly malignant form of PIOL that infiltrates into the CNS at an early stage. They also indicate that genetic differences between PIOL and primary CNS lymphoma need to be clarified.
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Project description:BackgroundSingle nucleotide polymorphisms (SNPs) have been used extensively in genetics and epidemiology studies. Traditionally, SNPs that did not pass the Hardy-Weinberg equilibrium (HWE) test were excluded from these analyses. Many investigators have addressed possible causes for departure from HWE, including genotyping errors, population admixture and segmental duplication. Recent large-scale surveys have revealed abundant structural variations in the human genome, including copy number variations (CNVs). This suggests that a significant number of SNPs must be within these regions, which may cause deviation from HWE.ResultsWe performed a Bayesian analysis on the potential effect of copy number variation, segmental duplication and genotyping errors on the behavior of SNPs. Our results suggest that copy number variation is a major factor of HWE violation for SNPs with a small minor allele frequency, when the sample size is large and the genotyping error rate is 0~1%.ConclusionsOur study provides the posterior probability that a SNP falls in a CNV or a segmental duplication, given the observed allele frequency of the SNP, sample size and the significance level of HWE testing.
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Project description:BackgroundIn this study we integrated the CNV (copy number variation) and WssGWAS (weighted single-step approach for genome-wide association) analyses to increase the knowledge about number of piglets born alive, an economically important reproductive trait with significant impact on production efficiency of pigs.ResultsA total of 3892 samples were genotyped with the Porcine SNP80 BeadChip. After quality control, a total of 57,962 high-quality SNPs from 3520 Duroc pigs were retained. The PennCNV algorithm identified 46,118 CNVs, which were aggregated by overlapping in 425 CNV regions (CNVRs) ranging from 2.5 Kb to 9718.4 Kb and covering 197 Mb (~ 7.01%) of the pig autosomal genome. The WssGWAS identified 16 genomic regions explaining more than 1% of the additive genetic variance for number of piglets born alive. The overlap between CNVR and WssGWAS analyses identified common regions on SSC2 (4.2-5.2 Mb), SSC3 (3.9-4.9 Mb), SSC12 (56.6-57.6 Mb), and SSC17 (17.3-18.3 Mb). Those regions are known for harboring important causative variants for pig reproductive traits based on their crucial functions in fertilization, development of gametes and embryos. Functional analysis by the Panther software identified 13 gene ontology biological processes significantly represented in this study such as reproduction, developmental process, cellular component organization or biogenesis, and immune system process, which plays relevant roles in swine reproductive traits.ConclusionOur research helps to improve the understanding of the genetic architecture of number of piglets born alive, given that the combination of GWAS and CNV analyses allows for a more efficient identification of the genomic regions and biological processes associated with this trait in Duroc pigs. Pig breeding programs could potentially benefit from a more accurate discovery of important genomic regions.
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Project description:Female human ESC-lines can carry active X-chromosomes (Xa) or an XIST-RNA- coated inactive X-chromosome (Xi XIST+ ). Additionally, many ESC-lines have abnormal X-chromosome-inactivation (XCI)-states where the Xi no longer expresses XIST-RNA and has transcriptionally active regions (eroded Xi=Xe). The fate of each XCI-state upon differentiation is unclear because individual lines often contain a mixture of XCI-states. Here, we established homogeneous XiXa, XeXa, and XaXa ESC-lines. We found that these lines were unable to initiate XIST-expression and X-chromosome- wide silencing upon differentiation indicating that the ESC XCI-state is maintained in differentiated cells. Consequently, differentiated XeXa and XaXa cells displayed higher levels of X-linked gene-expression than XiXa cells. Although global transcriptional compensation between X-chromosomes and autosomes is not required for female ESC-differentiation, the degree of X-chromosome- silencing influences differentiation efficiencies. Our data suggest that the Xi XIST+ Xa state is inherent to human ESCs and that all other XCI-states, including XaXa, are abnormal and arise during ESC-derivation or maintenance.
2016-12-15 | GSE91072 | GEO
Project description:Copy number variations (CNVs) alter the transcriptional and translational levels of genes by disrupting the coding structure and this burden of CNVs seems to be a significant contributor to phenotypic variations. Therefore it was necessary to assess the complexities of CNV burden on the coding genome. A total of 1715 individuals from 12 populations were used for CNV analysis in the present investigation. Analysis was performed using Affymetrix Genome-Wide Human SNP Array 6·0 chip and CytoScan High-Density arrays. CNVs were more frequently observed in the coding region than in the non-coding region. CNVs were observed vastly more frequently in the coding region than the non-coding region. CNVs were found to be enriched in the regions containing functional genes (83-96%) compared with the regions containing pseudogenes (4-17%). CNVs across the genome of an individual showed multiple hits across many genes, whose proteins interact physically and function under the same pathway. We identified varying numbers of proteins and degrees of interactions within protein complexes of single individual genomes. This study represents the first draft of a population-specific CNV genes map as well as a cross-populational map. The complex relationship of CNVs on genes and their physically interacting partners unravels many complexities involved in phenotype expression. This study identifies four mechanisms contributing to the complexities caused by the presence of multiple CNVs across many genes in the coding part of the genome.
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Project description:Microarray data is subject to noise and systematic variation that negatively affects the resolution of copy number analysis. We describe Rawcopy, an R package for processing of Affymetrix CytoScan HD, CytoScan 750k and SNP 6.0 microarray raw intensities (CEL files). Noise characteristics of a large number of reference samples are used to estimate log ratio and B-allele frequency for total and allele-specific copy number analysis. Rawcopy achieves better signal-to-noise ratio and higher proportion of validated alterations than commonly used free and proprietary alternatives. In addition, Rawcopy visualizes each microarray sample for assessment of technical quality, patient identity and genome-wide absolute copy number states. Software and instructions are available at http://rawcopy.org.
| S-EPMC5086940 | biostudies-literature