DNA copy number variation analysis in hepatoma cell lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE77224 | GEO | 2016/02/04
SECONDARY ACCESSION(S): PRJNA310739
REPOSITORIES: GEO
Similar Datasets
Project description:We analyzed specific genes for DNA copy number variation in hepatoma cells and investigated whether these factors are related to liver cancer phenotype. Chromosome 20p, which includes the ligand for Notch pathways, Jagged1, was found to be amplified in several types of hepatoma cells. In conclusion, amplification of Jagged1 contributed to mRNA expression that activates the Jagged1-Notch signaling pathway in liver cancer and led to poor outcome. Comparative genomic hybridization arrays spotted with 1,440 bacterial artificial chromosome clones were used to assess copy number changes in 7 hepatoma cell lines and 2 non-hepatoma cell lines to identify chromosomal regions associated with the pathogenesis of liver cancer.
2016-02-04 | E-GEOD-77224 | biostudies-arrayexpress
Project description:Gene-centric CNV analysis of 24 individual paraganglioma cases identified a list of 104 genes most significantly targeted by tumor-associated alterations. The NOTCH signaling pathway was the most significantly enriched term in the list. Overexpression of the relevant NOTCH pathway proteins in sustentacular (glial), chief (neuroendocrine) and endothelial cells was confirmed by immunomorphological studies in 47 paragangliomas, including CNV-tested cases. NOTCH upregulation was observed also in cases with no evidence of CNVs at NOTCH signaling genes, suggesting altered epigenetic modulation of the pathway. Notably, this was confirmed by microRNA expression analysis, that showed tumor-associated downregulation of the miR-200s and miR-34s families, correlated to NOTCH signaling and directly targeting NOTCH1.
2013-08-21 | GSE49614 | GEO
Project description:Gene-centric CNV analysis of 24 individual paraganglioma cases identified a list of 104 genes most significantly targeted by tumor-associated alterations. The NOTCH signaling pathway was the most significantly enriched term in the list. Overexpression of the relevant NOTCH pathway proteins in sustentacular (glial), chief (neuroendocrine) and endothelial cells was confirmed by immunomorphological studies in 47 paragangliomas, including CNV-tested cases. NOTCH upregulation was observed also in cases with no evidence of CNVs at NOTCH signaling genes, suggesting altered epigenetic modulation of the pathway. Notably, this was confirmed by microRNA expression analysis, that showed tumor-associated downregulation of the miR-200s and miR-34s families, correlated to NOTCH signaling and directly targeting NOTCH1. Total DNA from paraganglioma sample compared to total DNA from paired blood sample.
2013-08-21 | E-GEOD-49614 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data. Due to the high level of noise and biases of read-count data and complexity of the WES data, existing CNV detection tools identify many false CNV segments. Besides, NGS generates a huge amount of data, requiring to use effective and efficient methods. In this work, we propose a novel segmentation algorithm based on the total variation approach to detect CNVs more precisely and efficiently using WES data. The proposed method also filters out outlier read-counts and identifies significant change points to reduce false positives. We used real and simulated data to evaluate the performance of the proposed method and compare its performance with those of other commonly used CNV detection methods. Using simulated and real data, we show that the proposed method outperforms the existing CNV detection methods in terms of accuracy and false discovery rate and has a faster runtime compared to the circular binary segmentation method.
| S-EPMC7278034 | biostudies-literature
Project description:Objective Notch signaling is re-activated in β cells from obese mice, and is causal to β cell dysfunction. Notch activity is determined in part by expression of transmembrane ligand availability in a neighboring cell. We hypothesized that β cell expression of Jagged1 determines the maladaptive Notch response and resultant β cell dysfunction in obese mice. Methods We assessed expression of Notch pathway components in diet-induced obese (DIO) or leptin receptor-deficient (db/db) mice, and performed single cell RNA sequencing (scRNAseq) in islets from patients with and without type 2 diabetes (T2D). We generated and performed glucose tolerance testing in inducible, β cell-specific Jagged1 gain-of- and loss-of-function mice. We also tested effects of monoclonal neutralizing antibodies to Jagged1 in glucose-stimulated insulin secretion (GSIS) assays in isolated islets. Results Jag1 was the only Notch ligand that tracked with increased Notch activity in DIO and db/db mice. Consistently, JAG1 tracked with Notch activity in metabolically inflexible β cells enriched in patients with T2D. Neutralizing antibodies to block Jagged1 in islets isolated from DIO and db/db mice potentiated GSIS ex vivo. To demonstrate if β cell Jagged1 is sufficient to cause glucose tolerance in vivo, we generated inducible β cell-specific Jag1 transgenic mice (β-Jag1TG), which showed impaired glucose intolerance due to reduced GSIS. However, β cell-specific Jagged1 loss-of-function (β-Jag1KO) did not protect against HFD-induced insulin secretory defects or glucose intolerance. Conclusions Jagged1 is increased in islets from obese mice and in patients with T2D, and neutralizing Jagged1 antibodies lead to improved GSIS, suggesting that inhibition of Jagged1-Notch signaling may have therapeutic benefit. However, genetic loss-of-function experiments suggest that β cells are not a likely source of the Jagged1 signal.
2024-02-23 | GSE249170 | GEO
Project description:In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies.To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments.In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs.
| S-EPMC3668900 | biostudies-other
Project description:Copy number variation is now recognized as one of the major sources of genetic variation among individuals in natural populations of any species. However, the relevance of these unexpected observations goes beyond diagnosing high diversity.Here, it is argued that the molecular rates of copy number variation, mainly the deletion rate upon variation, determine the evolutionary road of the genome regarding size. Genetic drift will govern this process only if the effective population size is lower than the inverse of the deletion rate. Otherwise, natural selection will do.
| S-EPMC5553737 | biostudies-other
Project description:Great Ape Copy Number Variation
| PRJNA144461 | ENA
Project description:Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.
| S-EPMC3245619 | biostudies-literature
Project description:Copy number variation (CNV) is a major genetic polymorphism contributing to genetic diversity and human evolution. Clinical application of CNVs for diagnostic purposes largely depends on sufficient population CNV data for accurate interpretation. CNVs from general population in currently available databases help classify CNVs of uncertain clinical significance, and benign CNVs. Earlier studies of CNV distribution in several populations worldwide showed that a significant fraction of CNVs are population specific. In this study, we characterized and analyzed CNVs in 3,017 unrelated Thai individuals genotyped with the Illumina Human610, Illumina HumanOmniexpress, or Illumina HapMap550v3 platform. We employed hidden Markov model and circular binary segmentation methods to identify CNVs, extracted 23,458 CNVs consistently identified by both algorithms, and cataloged these high confident CNVs into our publicly available Thai CNV database. Analysis of CNVs in the Thai population identified a median of eight autosomal CNVs per individual. Most CNVs (96.73%) did not overlap with any known chromosomal imbalance syndromes documented in the DECIPHER database. When compared with CNVs in the 11 HapMap3 populations, CNVs found in the Thai population shared several characteristics with CNVs characterized in HapMap3. Common CNVs in Thais had similar frequencies to those in the HapMap3 populations, and all high frequency CNVs (>20%) found in Thai individuals could also be identified in HapMap3. The majorities of CNVs discovered in the Thai population, however, were of low frequency, or uniquely identified in Thais. When performing hierarchical clustering using CNV frequencies, the CNV data were clustered into Africans, Europeans, and Asians, in line with the clustering performed with single nucleotide polymorphism (SNP) data. As CNV data are specific to origin of population, our population-specific reference database will serve as a valuable addition to the existing resources for the investigation of clinical significance of CNVs in Thais and related ethnicities.
| S-EPMC4131886 | biostudies-literature