14982 results for "cancer studies using rna-seq"

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• Ischemic stroke in a Swedish case-control study.

  Background. Genetic risk scores (GRS), summing up the total effect of several single nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS, based on 29 SNPs discovered by genome-wide association studies (GWAS) and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other “traditional risk factors”, also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Methods and results. Twenty-nine SNPs were genotyped in 3,677 stroke cases and 2,415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the entire material, and separately for the three samples. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the entire material [OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS p=0.003] with similar trends in all three samples; LSR [1.050 (0.967-1.140)]; p=0.25], MDC [1.168 (1.060-1.288); p=0.002] and SAHLSIS [1.124 (0.997-1.267); P=0.055]. Measures of discrimination and reclassification improved marginally using the GRS. Conclusions. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

  Study EGAS00001000936

• Analysis of the Elements Involved in the Enrichment of a Panel of Genomic Regions by Nanopore Sequencing Using Adaptive Sampling

  DNA sequencing using nanopore technologies with the affordable MinION device is useful for the identification and characterization of structural variants, long haplotypes, sequencing of repetitive regions and identification of epigenetic modifications. The main limitation of this approach is the low coverage obtained, which might be avoided by adaptive sampling, a computationally controlled method of enrichment for targeted genomic regions. This study dissects the factors involved in the enrichment by adaptive sampling of a panel of 18 human genome regions containing 20 genes implicated in breast cancer sequenced in 16 patients with familial breast cancer negative for NGS screening. An average coverage of 2.0x was obtained for the whole genome and 5.1x for selected regions. Sequencing time was the main factor improving coverage. The selection of long reads (>1 Kb) did not improve the enrichment. The length of the selected region, which in our study ranged from 126 to 565 Kb, did not play a significant role in enrichment. However, the region containing PMS2 showed significantly lower coverage, which could be explained by the high number of PMS2 pseudogenes (N = 14), which were also enriched. Our study shows new evidence of enrichment obtained by adaptive sampling in a panel of genomic regions and shows parameters, the relevance of sequencing time and the role of pseudogenes, that improve the enrichment yield with no library reloading or GPU use, data useful for a more efficient application of this procedure in future studies.

  Study EGAS00001007375

• Metadata and count matrix

  The dataset contains metadata for all cells before scRNA-seq quality control and for cells passing quality control. It also contains a count matrix with Salmon gene counts for all cells passing quality control, and reconstructed B-cell receptor sequences using the computational tool BraCeR. The scRNA-seq data was generated using the Smart-seq2 protocol and sequenced on Illumina NextSeq500.

  Dataset EGAD00001006435

• EGAD00000000046

  RNA-SEQ data from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples

  Dataset EGAD00000000046

• Single-cell RNA-seq data from 3 HGSOC patient-derived organoids and corresponding tumor or ascites

  Study EGAS00001006246

• Uni_Wue_Chair of Microbiology

  Dual RNA seq datasets of M2 sequenced macrophages after chlamydia infection for 30 hours.

  Dac EGAC50000000577

• ssRNA

  single cell RNA-seq

  Dataset EGAD00001008996

• Whole genome sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Paired-end 150 basepair whole genome sequencing of 94 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Libraries were prepared using the Illumina® TruSeq™ DNA Nano library preparation method according to the manufacturer’s instructions at The University of Melbourne Centre for Cancer Research (UMCCR) using 200ng input DNA and a 550 base pair insert size. Samples were sequenced in separate batches on the Illumina® Nova-Seq 6000 according to manufacturer’s instructions (Illumina, USA). Included in this dataset are FASTQ format files containing raw read data, CRAM format files containing reads aligned to GRCh38, and VCF format files containing germline variants calls.

  Dataset EGAD50000000502

• Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD

  To investigate the mode of action and potential side-effects we analyzed differential gene expression in Postmitotic C9orf72 iPSC-Neurons by RNAseq. The cells were treated in a 2 dose regime at 10 µm in 0.1 % DMSO for 9 days. Compound treated iPSC-Neurons were washed with PBS, frozen on dry ice and stored at -80°C until RNA isolation. The RNA was isolated using miRNA Mini Kit (Qiagen) using 700 μl of Qiazol. A total of 250 ng of RNA per sample was processed for mRNA library preparation as per the manufacturer’s instructions for Illumina® Stranded mRNA Prep Ligation to be used with the IDT® for Illumina® RNA UD Indexes Set B and sequenced using NextSeq 500/550 High Output Kit v2.5 (Illumina) on NextSeq 550 (Illumina). The data was processed and analyzed using CLC genomics workbench (Version 21.0.3, Qiagen)

  Dataset EGAD00001008674

• 10X snRNA-seq data from human FCDII postoperative brain tissues with mTOR pathway mutations

  Focal cortical dysplasia type II (FCDII) is linked to mTOR pathway mutations and drug-resistant epilepsy. Using 10X snRNA-seq on postoperative FCDII brain tissues, we characterized transcriptional alterations across cell types, revealing mTOR-related dysregulation. These findings provide insights into FCDII pathology and potential therapeutic target

  Study EGAS50000000964

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• Efficacy of CDK4/6i in preclinical models of malignant pleural mesothelioma

  Assessment of antitumor activity of CDK4/6 inhibitors using in vitro and in vivo preclinical models of MPM using RNA-sequencing. We also include the genomic characterization (whole exome sequencing) of patient-derived cell lines used in the in vitro experiments.

  Study EGAS00001005352

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001004266

• CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) of CLL_24

  To explore intratumor-heterogeneity of CLL_24 using single-cell multi-omics approach, we generated single-cell CITE-seq data for CLL_24, coupling scRNA-seq and protein surface marker measurements with oligo-tagged antibodies.

  Dataset EGAD00001009174

• RNA Fusion Panel

  RNA extracted from FFPE tumour samples 368, 455, 503, and 521, sequenced using the TruSight RNA Fusion Panel

  Dataset EGAD50000000272

• Epigenomic atlas of organoid development

  To investigfate the epigenomic basis of fate decisions in the central nerveous system, we recorded a epigenomic timecourse of human brain organoid development using Cut&Tag with paired scRNA-seq. We further performed perturbation experiment inhibiting EED and profiled the response with scRNA-seq and Cut&Tag. Finally, we profiled a sample of the developing human brain using multiome sequencing and Cut&Tag. In our study, we uncover epigenomic switches during brain region diversification and show that epigenetic activation precedes gene expression during neurogenesis in organoids and in primary tissue. Lastly, we show that transcriptional repression by H3K27me3 is required to stabilize neuroectoderm induction from pluripotency.

  Study EGAS50000000155