SNP array analysis of single cell genomes
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Michael McConnell
PROVIDER: E-GEOD-51538 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Publications
Mosaic copy number variation in human neurons.
McConnell Michael J MJ Lindberg Michael R MR Brennand Kristen J KJ Piper Julia C JC Voet Thierry T Cowing-Zitron Chris C Shumilina Svetlana S Lasken Roger S RS Vermeesch Joris R JR Hall Ira M IM Gage Fred H FH
Science (New York, N.Y.) 20131101 6158
We used single-cell genomic approaches to map DNA copy number variation (CNV) in neurons obtained from human induced pluripotent stem cell (hiPSC) lines and postmortem human brains. We identified aneuploid neurons, as well as numerous subchromosomal CNVs in euploid neurons. Neurotypic hiPSC-derived neurons had larger CNVs than fibroblasts, and several large deletions were found in hiPSC-derived neurons but not in matched neural progenitor cells. Single-cell sequencing of endogenous human frontal ...[more]
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Project description:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array. Affymetrix 100K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1). Affymetrix 500K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Forty-eight normal samples were downloaded from the Affymetrix website (http://www.affymetrix.com/support/technical/byproduct.affx?product=500k) and analyzed at the same time. One CEL file for each set (Sty and Nsp) with the median signal intensity across the set was selected as the reference array. The dChip-normalized signal intensities were converted to log2 ratios and segmented as follows. For each autosomal probe set, the log2 tumor/normal ratio of each tumor sample was calculated using the average intensity for each probe set in the normal set. For Chromosome X, the average of the 20 normal female samples was used. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1).
2010-12-16 | E-GEOD-26075 | biostudies-arrayexpress
Project description:In the majority of colorectal cancers (CRC) under clinical suspicion for a hereditary cause, the disease-causing genetic factors are still to be discovered. In order to identify such genetic factors we stringently selected a discovery cohort of 41 CRC index patients with microsatellite-stable tumors. All patients were below 40 years of age at diagnosis and/or exhibited an overt family history. We employed genome-wide copy number profiling using high-resolution SNP-based array CGH on germline DNA, which resulted in the identification of novel copy number variants (CNVs) in 6 patients (15%) encompassing, among others, the cadherin gene CDH18, the bone morphogenetic protein antagonist family gene GREM1, and the breakpoint cluster region gene BCR. In addition, two genomic deletions were encountered encompassing two microRNA genes, hsa-mir-491/KIAA1797 and hsa-mir-646/AK309218. None of these CNVs has previously been reported in relation to CRC predisposition in humans, nor were they encountered in large control cohorts (>1,600 unaffected individuals). Since several of these newly identified candidate genes may be functionally linked to CRC development, our results illustrate the potential of this approach for the identification of novel candidate genes involved in CRC predisposition. Copy number detection was performed using CNAG2.0 software for 250k SNP arrays and using the Affymetrix Genotyping Console v2.1 software for SNP 6.0 arrays, Reference genomes are included in this data set. Germline genomic DNA from 41 patients with early-onset microsatellite stable colorectal cancer was hybridized on Affymetrix Nsp/6.0 SNP-based arrays according to manufacturer's procedures.
2010-11-01 | E-GEOD-13429 | biostudies-arrayexpress
Project description:Hypothesis: Non-small cell lung cancer (NSCLC) is characterized by a multitude of genetic aberrations with unknown clinical impact. In this study, we aimed to identify gene copy number changes that correlate with clinical outcome in NSCLC. To maximize the chance to identify clinically relevant events, we applied a strategy involving two prognostically extreme patient groups. Results: Genetic aberrations were strongly associated with tumor histology. In adenocarcinoma (n=50), gene copy number gains on chromosome 8q21-q24.3 (177 genes) were more frequent in long-term survivors. In squamous cell carcinoma (n=28), gains on chromosome 14q23.1-24.3 (133 genes) were associated with shorter survival, whereas losses in a neighboring region, 14q31.1-32.33 (110 genes), correlated with favorable outcome. In accordance with copy number gains and losses, mRNA expression levels of corresponding genes were increased or decreased, respectively. Conclusion: Comprehensive tumor profiling permits the integration of genomic, histologic and clinical data. We identified gene copy number gains and losses, with corresponding changes in mRNA levels, that were associated with prognosis in adenocarcinoma and squamous cell carcinoma of the lung. Short-term (<20 months; n=53) and long-term survivors (>58 months;n=47) were selected from a clinically well-characterized NSCLC patient cohort with available fresh-frozen tumor specimens. The samples were analyzed using high-resolution SNP-array technology. The molecular data was combined with information on clinical parameters.
2011-11-01 | E-GEOD-28572 | biostudies-arrayexpress
Project description:Primitive neuro-ectodermal tumours (PNET) of the supratentorial region are rare, highly malignant embryonal brain tumours affecting young children. Although supratentorial PNET (sPNET) are histologically similar to infratentorial PNET/medulloblastoma, sPNET have more aggressive clinical phenotypes, which suggest sPNET represents distinct biological entities. In contrast to considerable progress in understanding the signalling pathways involved in medulloblastoma, little is known about sPNET pathogenesis. Prior low resolution CGH (comparative genomic hybridization) studies indicate sPNET have frequent genomic imbalances and copy number aberrations (CNAs). To define genes involved in sPNET pathogenesis, we utilized the Affymetrix 250K Nsp SNP (single nucleotide polymorphism) analysis to identify genes targeted by recurrent CNAs in primary human sPNET samples. Copy number analysis was conducted on 39 primary PNET samples. Select target genes were validated by genomic and/or RT-PCR. Our analysis revealed frequent CNA across the sPNET genome, encompassing large and focal chromosome segments, and corroborated previous reports that isochromosome 17q, an abnormality found in ~ 30% of medulloblastoma, is rare in sPNET. Keywords: single nucleotide polymorphism array, disease state analysis A total of 56 primary sPNET samples were collected for this study from The Hospital for Sick Children, John Hopkins University, St. Jude Research Hospital, University of Cambridge, Children’s Hospital Boston, Virginia Commonwealth University, Instituto nazionale per lo studio e la cura dei tumori, and Texas Children’s Hospital, with local Institutional Research Ethics Board approval. Pineoblastoma and rhaboid tumours were specifically excluded, leaving 52 samples, 39 of which had good quality DNA available. These samples, in addition to 28 diploid reference samples (a gift from Dr. S. Scherer, University of Toronto), were analyzed on the Affymetrix GeneChip Mapping 250K Nsp SNP array. Due to sample availability at the time the arrays were run, the diploid reference samples analyzed on the Sty arrays are different from reference samples analyzed on the Nsp arrays.
2009-12-21 | E-GEOD-14087 | biostudies-arrayexpress
Project description:A common aim of pharmacogenomic studies that employ genome-wide assays on panels of cancers is the unbiased discovery of genomic alterations that are associated with clinical outcome and drug response. Previous investigations of lapatinib, a selective dual-kinase inhibitor of EGFR and HER2 tyrosine kinases, have demonstrated predictable relationships between the activity of these genes and response. Under the hypothesis that additional genes may play a role in promoting sensitivity, a predictive model for lapatinib sensitivity was constructed from genome-wide DNA copy number data from 24 cancer cell lines. An optimal predictive model, which consists of aberrations at nine distinct genetic loci, includes gains of HER2, EGFR, and loss of CDKN2A. This model, which achieved area under the Receiver Operating Characteristic (ROC) curve of ~0.85 (80% confidence interval: 0.70–0.98; P<0.01), and correctly classified the sensitivity status of 8/10 head and neck cancer cell lines. This study demonstrates that previously described biomarkers of lapatinib sensitivity, including copy number gains of EGFR and HER2, can be discovered as powerful predictors of response using novel genomic assays in an unbiased manner. Further, these results demonstrate the utility of DNA copy number profiles in pharmacogenomic studies. Keywords: Comparative Genomic Hybridization Basal DNA copy number profiles were derived from Affymetrix 'SNP chips' for a panel of 34 tumor derived cell lines. Each of these cell lines were tested for their degree of sensitivity to lapatinib. Specific DNA alterations associating with lapatinib sensitivity were identified using a training set consisting of 24 of these lines. A predictive model was constructed from these loci. The remaining 10 lines were used to test the model performance. A panel of chips (n = 12) assayed with germline DNA served as a reference in order to calculate the test/reference ratios reported in the Sample table VALUE columns. The 'reference' Samples for the 500K and 100K assays are as follows: 500K: GSM188024, GSM188025, GSM188026, GSM188027, GSM188028, GSM188029, GSM188030, GSM188031, GSM188032, GSM188033, GSM188034, GSM188035, GSM188048, GSM188049, GSM188050, GSM188051, GSM188052, GSM188053, GSM188054, GSM188055, GSM188056, GSM188057, GSM188058, GSM188059 100K: GSM187950, GSM187951, GSM187952, GSM187953, GSM187954, GSM187955, GSM187956, GSM187957, GSM187958, GSM187959, GSM187960, GSM187961, GSM187949, GSM187948, GSM187946, GSM187947, GSM187945, GSM187944, GSM187943, GSM187942, GSM187941, GSM187940, GSM187939, GSM187938
2008-03-10 | E-GEOD-9585 | biostudies-arrayexpress
Project description:Methods of comprehensive microarray based analyses of single cell DNA are rapidly emerging. Whole genome amplification (WGA) remains a critical component for these methods to be successful. A number of commercially available WGA kits have been independently utilized in previous single cell microarray studies. However, direct comparison of their performance on single cells has not been conducted. The present study demonstrates that among previously published methods, a single cell GenomePlex WGA protocol provides the best combination of speed and accuracy for SNP microarray based copy number analysis when compared to a REPLI-g or GenomiPhi based protocol. Alternatively, for applications that do not have constraints on turn-around time and that are directed at accurate genotyping rather than copy number assignments, a REPLI-g based protocol may provide the best solution. Affymetrix SNP arrays were processed according to the manufacturer's directions on DNA extracted from human fibroblast cell lines and single fibroblast cells. Afflymetrix SNP array analysis was successfully completed on 46 lymphocyte single cell samples, 8 gDNA extracted from cell lines, 11 reference gDNA extracted from cell lines and 3 reference gDNA samples from the RMA of New Jersey DNA bank. GSM617116 to GSM617129: CEL files were processed using GTYPE version 4 (Affymetrix Inc., Genotyping Console 4.0 Manual) using the DM algorithm for genotype calls. Copy number and loss of heterozygosity were calculated from CHP files using CNAT version 4.1 (Affymetrix Inc., Genotyping Console 4.0 Manual) analysis against a reference set consisting of three normal females from in house gDNA bank, 11 normal females from Coriel cell lines and 16 normal females from the HapMap database (www.hapmap.org). The 16 normal females are NA10855, NA10863, NA11832, NA12057, NA12234, NA12717, NA12813, NA18505, NA18508, NA18517, NA19137, NA19152, NE00088, NE00091, NE00403, and NE01119.
2010-12-20 | E-GEOD-24690 | biostudies-arrayexpress
Project description:Primitive neuro-ectodermal tumours (PNET) of the supratentorial region are rare, highly malignant embryonal brain tumours affecting young children. Although supratentorial PNET (sPNET) are histologically similar to infratentorial PNET/medulloblastoma, sPNET have more aggressive clinical phenotypes, which suggest sPNET represents distinct biological entities. In contrast to considerable progress in understanding the signalling pathways involved in medulloblastoma, little is known about sPNET pathogenesis. Here we identify a focal amplicon on chr19q13.41 that houses two polycistronic microRNA clusters. Functional analysese indicates that the microRNA clusters may promote oncogenesis in part by modulating cell survival. Copy number analysis was also performed on an overlapping set of PNET tumours, also available on GEO with accession code GSE14087. Keywords: single nucleotide polymorphism array, pediatric brain cancer A primitive neuroectodermal tumour sample with matched blood from the University of Cambridge was analyzed on the Affymetrix GeneChip Mapping 250K Nsp SNP array.
2010-04-03 | E-GEOD-14248 | biostudies-arrayexpress
Project description:Methods for haplotyping and DNA copy number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required that substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP-genotypes (AA, AB, BB), and DNA copy number profiling remains difficult as true DNA copy number aberrations have to be discriminated from WGA-artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by deciphering WGA-distorted SNP B-allele fractions, using a process we coin haplarithmisis. We demonstrate clinical precision of the method on single cells biopsied from human embryos to diagnose disease alleles genome wide, we advance and facilitate the detection of numerical and structural chromosomal anomalies in single cells, and can distinguish meiotic from mitotic segregation errors in a single assay. The samples of a reference family were applied for optimisation of single-cell genotyping using Affymetrix SNP-arrays prior to downstream analysis. Specifically, the reference family delivers genomic DNA samples isolated from peripheral blood of two siblings 'S1' and 'S2', the mother and father of these siblings, as well as of the maternal grandmother and grandfather. Of individuals ‘S1’ and ‘S2’, six EBV-transformed lymphoblastoid single cells were isolated of which three were whole-genome amplified using MDA and three using PicoPlex. These WGA-products were hybridized to Affymetrix NspI 250K SNP-arrays following the protocol as recommended by the company. Subsequently, the SNP-probe signals were interpreted by different genotyping algorithms (see data processing). Based on overall performance, it was decided to use the Dynamic Model (DM) for interpreting Affymetrix SNP-probe signals of single cells.
2015-05-15 | E-GEOD-60907 | biostudies-arrayexpress
Project description:We studied twenty-eight growth restricted patients (twenty-two with Silver-Russell syndrome, OMIM#180860) and their parents with the Affymetrix 250K Sty SNP microarray. All patients were molecularly undefined, and thus the aim was to look for copy number alterations that might contribute to the growth restriction. Aberrations found in parents were used to reduce the list of interesting variations to de novo variants.
2009-09-06 | E-MTAB-56 | biostudies-arrayexpress
Project description:The accurate mapping of recurring DNA copy number aberrations (CNAs), a hallmark feature of the cancer genome, has facilitated the discovery of tumor suppressor genes and oncogenes. Microarray-based assays designed to detect these chromosomal copy number alterations on a genome-wide and high-resolution scale have emerged as a cornerstone technology in the genomic era. The diversity of commercially-available platforms prompted a systematic comparison of five copy number profiling assays for their ability to detect 2-fold copy number gain and loss (4n or 1n, respectively) as well as focal high-amplitude CNAs. Here, using a collection of established human melanoma cell lines, we defined the reproducibility, absolute signals, signal:noise, false-positive and false-negative rates for each of the five assays against ground-truth defined by Spectral Karyotyping (SKY), in addition to comparing the concordance of CNAs detection by two high-resolution Agilent and Affymetrix microarray platforms. Our analyses concluded that the Agilentâs 60mer oligo-microarray with probe design optimized for genomic hybridization offers the highest sensitivity and specificity [area under Receiver Operator Characteristic (ROC) curve >0.99] while Affymetrixâs SNP microarray appears to offer better detection of CNAs in gene-poor region. Availability of these comparison results should guide study design decisions and facilitate further computational development. Keywords: comparative genomic hybridization We generated copy number profiles of a defined set of tumor cell lines on five oligo-microarray-based assays of three platforms (Agilent, Affymetrix and NimbleGen) and determined the reproducibility, signal and noise as well as sensitivity and specificity of each in detecting two-fold signals based on SKY-defined aberrations as ground-truth for comparison. In addition, high-density microarray assays from Agilent and Affymetrix platforms were further compared for definition of CNAs in an independent dataset using published analytical approaches. All arrays were run from the same DNA harvest from respective cell lines. Each array was run according to the protocol of the manufacturer.
2010-05-26 | E-GEOD-7822 | biostudies-arrayexpress