SNP array detection for comparison of WGS technologies.
Ontology highlight
ABSTRACT: We sequenced two tumor/normal pairs obtained from two paediatric medulloblastoma patients (MB14 and MB24) with at least 30x coverage on all commonly used next-generation sequencing platforms for whole genome sequencing (SOLiD 4, 5500xl SOLiD, Illumina's HiSeq2000, and Complete Genomic' technology). The normal tissue samples came from venous blood. We compared their ability to call single nucleotide variations (SNVs) in whole-genome sequencing data with high confidence. As gold standard for SNV calling, we used genotypes determined by Affymetrix SNP 6.0 Array Technology (total of 907,551 SNPs after quality filtering).
Project description:We report a map of H3K4me3 - an activiting expression histone modification in C6 rat glioma cells. The data was obtained using whole genome high throughput technology. The sequencing was performed on Solid 5500xl platform.
Project description:We report a map of H3K4me3 - an activiting expression histone modification in C6 rat glioma cells. The data was obtained using whole genome high throughput technology. The sequencing was performed on Solid 5500xl platform. Examination of H3K4me3 histone modification in C6 rat glioma cell line
Project description:Distinct SCLC molecular subtypes have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1, but their origins remain unknown. To study transcriptional dynamics of MYC-driven tumor evolution and compare transcriptional states to human SCLC tumors, we performed bulk and single-cell RNA-sequencing on various timepoints of Rb1/Trp53/MycT58A (RPM) tumor cells (from Ad-Cgrp-Cre infected mice) as they progress in culture, and on RPM bulk tumors. Here, to complement these analyses we performed ~30X whole-genome sequencing (WGS) of early (day 4) and late (day 23) time-point RPM tumor cells from culture, along with a matching normal blood control to confirm complete loss of expected regions of Rb1 and Trp53. WGS analyses revealed no detectable copy number variations (CNVs), and SNV analysis suggests that minimal clonal and subclonal evolution occurs in vitro. Together, these data ultimately reveal that MYC drives the dynamic evolution of SCLC subtypes. We find that MYC promotes a temporal shift from an ASCL1-to-NEUROD1-to-YAP1+ state from a neuroendocrine cell of origin. MYC activates Notch signaling to dedifferentiate tumor cells to non-neuroendocrine fates. These findings support our overall conclusions that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.
Project description:We performed copy number analysis of high-grade osteosarcoma samples. in order to detect osteosarcoma drivers, we integrated these data with genome-wide gene expression data. We performed two different methods - a non-paired and a paired integrative analysis. Copy number analysis was performed on 32 pre-treatment high-grade osteosarcoma diagnostic biopsies, of which 29 overlapped with the 84 samples used for gene expression analyses.
Project description:High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. In order to identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e. mesenchymal stem cells (n=12) or osteoblasts (n=3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both non-paired and paired analyses, copy number aberration frequency was set to >35%. Non-paired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding non-paired analyses. Remarkably, approximately twice as many genes as found in the corresponding non-paired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic-instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis. This SuperSeries is composed of the following subset Series: GSE28974: Genome-wide gene expression profiling of mesenchymal stem cells GSE33153: Copy number analysis of high-grade osteosarcoma GSE33382: Genome-wide gene expression analysis of high-grade osteosarcoma For data processing, we refer to the individual series. We performed both non-paired and paired integrative analyses on SNP and gene expression data. Non-paired integrative analysis was performed by importing lists of differentially expressed genes into the Copy Number module of Nexus software version 5 (BioDiscovery, CA). Based on the length of the gene list, Nexus software performs a Fisher's exact test in order to determine whether the number of differentially expressed genes in a specific region with a significant copy number alteration is larger than expected by chance. Genes present in such regions of copy number alteration with FDR-adjusted P-values (Q-bounds in Nexus software) < 0.05 were returned from this integrative analysis. Nexus software only reports genes which are both gained and overexpressed, or both deleted and downregulated. For the paired integrative analysis, copy number data of all autosomal overlapping genes between the copy number and gene expression arrays were exported from Nexus software, and converted into a binary file containing all genes with a gain (1) and no gain (0), and a similar binary file for losses. As in the non-paired integrative analysis, we did not apply any restrictions on the size of copy number alterations. Gene expression data of each probe for each sample were normalized against average gene expression of the corresponding probes over all control samples (either expression data from 12 MSCs, or from 3 osteoblasts). This was performed by subtracting the average expression of the control samples from the expression levels of the sample of interest, since these are log-transformed expression values. For both analyses, only genes that were significantly differentially expressed between the 84 osteosarcoma samples and the specific control set were analyzed, in order to make sure that no genes returned from the integrative analysis were not significantly differentially expressed. Subse quently, genes that overlapped between the copy number binary files and that matched the fold change of expression (upregulation for genes with gains, and downregulation for genes with losses) were returned.
Project description:To assess the transcriptomic response of the LUAD cell line A549 to hypoxia, cells were exposed to 1% (Hx) or 21% O2 (Nx) during 24 hours. Two µg of total RNAs were depleted from ribosomal RNA with the Ribozero kit (epicenter), libraries were generated with the NEBNext Small RNA Library Prep Set for SOLiD and sequenced on SOLiD 5500XL (Life Technologies) with single-end 50bp reads. Reads were aligned to the human genome release hg19 with the LifeScope software v2.5.1 (Life Technologies) using whole transcriptome pipeline for RNA‐seq libraries with default parameters.
Project description:Generating sufficient DNA for high-throughput genetic analysis has always been a challenge for clinical settings where the amount of source DNA is limited. Multiple displacement amplification (MDA) has been proposed as a promising candidate for such situations. Previous work with lower-resolution arrays confirmed the utility of single-cell MDA products for large-size (~30 Mb) genome variation screening. We tested the performance of single-cell MDA products on the SNP 6.0 arrays to examine the performance of single-cell MDA in SNP genotyping, copy number polymorphism, de novo copy number variation (CNV) and loss of heterozygosity (LOH) analysis. Our data show that for SNP genotyping, single-cell MDA did not obtain complete genome coverage or high sequence fidelity. For CNV calling, single-cell MDA introduced stochastic amplification artifacts in log2 ratio profiles, reducing the robustness of CNV calling; however, by adjusting smooth window size, it is still possible to analyze large chromosomal aberrations, and homozygous deletions as small as 500 kb can still be identified from the noisy log2 ratio profiles. Our results also suggest that even with a modified protocol (reduction of reaction volume, addition of a molecular crowding reagent, minimization of reaction time), single-cell MDA presented little improvement over the unmodified protocol, but by increasing the number of cells as template to 5M-bM-^@M-^S10 cells, SNP 6.0 array results comparable to those of 10 ng genomic DNA MDA could be obtained. Algorithms like PICNIC improved the CNV calling, suggesting that better algorithms can better utilize single-cell MDA array results. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cell line samples, and multiple displacement samples. Genotyping, Copy number and LOH analysis of Affymetrix SNP 6.0 arrays was performed for 3 samples of unamplified cell line genomic DNA, 2 samples of DNA obtained by multiple displacement amplification from 10ng genomic DNA, 3 single-cell multiple displacement amplification (MDA) products, single cell modified MDA amplification product, 5-cell modified MDA amplification product, 10-cell modified MDA amplification product.
Project description:Renal cell carcinoma (RCC) exhibits some unusual features and genes commonly mutated in cancer are rarely mutated in clear-cell RCC (ccRCC), the most common type. The most prevalent genetic alteration in ccRCC is the inactivation of the tumor suppressor gene VHL. Using whole-genome and exome sequencing we discovered BAP1 as a novel tumor suppressor in ccRCC that shows little overlap with mutations in PBRM1, another recent tumor suppressor. Whereas VHL was mutated in 81% of the patients (142/176), PBRM1 was lost in 58% and BAP1 in 15% of the patients analyzed. All these tumor suppressor genes are located in chromosome 3p, which is partially or completely lost in most ccRCC patients. However, BAP1 but not PBRM1 loss was associated with higher Fuhrman grade and, therefore, poorer outcome. Xenograft tumors (tumorgrafts) implanted orthotopically in mice retained >92% of mutations and exhibited similar DNA copy number alterations to corresponding primary tumors. Thus, after inactivation of VHL, the acquisition of a mutation in BAP1 or PBRM1 defines a different program that might alter the fate of the patient. Our results establish the foundation for an integrated pathological and molecular genetic classification of about 70% of ccRCC patients, paving the way for subtype-specific treatments exploiting genetic vulnerabilities. The genomic DNA of clear-cell renal cell carcinoma (ccRCC) primary tumors, tumors growing in immunodeficient mice (tumorgrafts), and normal samples were labeled and hybridized to Affymetrix SNP arrays 6.0.
Project description:Lenalidome is a drug especially effective in low risk myelodysplastic syndromes (MDS) with isolated 5q deletion. However, 25% of the patients did not respond. TP53 mutations have been described to play a role in the disease progression, and karyotypic complexity also has an important impact in the outcome. We selected 53 MDS patients with 5q deletion and treated with lenalidomide and we studied by the following techniques: conventional G-banding cytogenetics (CC), single nucleotide polymorphism arrays (SNP-A) and sequencing, in order to assess their impact on treatment response and disease progression. Low karyotypic complexity (by CC), a high baseline platelet count (>280x103/L) and TP53 unmutated gene status are associated with the achievement of hematological response (P=0.005, P=0.008 and P=0.057, respectively). In a multivariate model, the most important predictors for lenalidomide failure are karyotypic complexity (P=0.014) and a platelet count below 280x103/L (P=0.042). Additionally, none of the TP53 mutated cases achieved complete cytogenetics response. Nevertheless, inclusion of defects by SNP-A did not allow for a better separation of responders and non responders. These findings constitute a useful reference data to be considered before lenalidomide treatment enrollment. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from bone marrow or peripheral blood and, in some cases, also lymphocytes CD3 isolated from peripheral blood samples. Copy number analyses of Affymetrix 250K and 6.0 SNP arrays were performed for 53 MDS with 5q deletion samples. There are also 30 samples from lymphocytes CD3 isolated from peripheral blood, which were used as germ-line DNA (control).
Project description:Integration of genomic copy number analysis (Affymetrix SNP6.0 arrays) and oncogenic RAS/RAF mutation status with clinical features and tumour progression. This study found that loss of the 9p and the CDKN2A locus with the most significantly enriched copy number aberration distinguishing serous border tumors from low grade serous carcinomas, suggesting this is a key step to tumor progression. Epithelial tissue from 57 serous borderline tumors (SBTs), 19 low grade serous carcinomas (LGSC)(data for 4 of the carcinomas have previously been submitted to GEO - Series GSE19539) and 355 high grade serous carinomas (HGSC)(TCGA, 2011; GSE19539; and 8 new) were analysed for copy number aberrations using Affymetrix SNP6.0 arrays and normalised SNP6.0 data. Stromal tissue from 38 SBT and 1 HGSC were analysed for copy number aberrations using Affymetrix SNP6.0 arrays. Matching lymphocyte DNA was availabe for 54 SBT, 3 LGSC and 1 HGSC. Sanger sequencing of KRAS, BRAF, NRAS, HRAS, ERBB2 and TP53 mutational hotspots was performed on the epithelial and stromal DNA. This information was then correlated with clinical features of the tumors.