3931 results for "*geneti*"

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• High Altitude Pulmonary Hypertension

  The Central Asian Kyrgyz highland population provides a unique opportunity to address genetic diversity and understand the genetic mechanisms underlying hypoxia-induced high altitude pulmonary hypertension (HAPH). While a significant fraction of the population is unaffected, there are susceptible individuals who display HAPH in the absence of any lung, cardiac or hematologic disease. We report herein the analysis of the whole genome sequencing of healthy individuals compared with HAPH patients and other controls. In this study, 34 male individuals from Central Asian Kyrgyz highland are sequenced with Illumina HiSeq 2000 with mean-coverage of 30X.

  Dataset EGAD00001004308

• Oxidative phosphorylation is a key ontogenetic feature of monocyte immunometabolism promoting myeloid differentiation after birth

  The dataset consists of 12 samples of monocytes, which were analyzed using RNA-sequencing (RNA-seq). These samples were categorized into four distinct groups, each comprising three samples. The dataset was designed to investigate the transcriptomic and metabolic profiles of monocytes across different age groups and stimulation conditions. 3 neonatal controls, 3 neonatal LPS stimulated, 3 adult controls and 3 adult LPS stimulated samples.

  Dataset EGAD00001011340

• Mechanisms of patient response to Dabrafenib in Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)*NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]*CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Dataset EGAD00001001375

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004413

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004416

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS)

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Dataset EGAD00001001901

• March 2016 update of Whole genome bisulfite sequencing assay data (bams) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2016 update of Whole genome bisulfite sequencing assay data (bams) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001987

• Ovarian Cancer Organoid Biobank - RNASeq data

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004509

• Determination of cell specific regulatory enhancers in hematopoetic models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10, led by NS) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. Units of 475 ml of AB will be obtained from consenting volunteers of the Cambridge BioResource (CBR), a panel of 10,000 healthy volunteers local to Cambridge who have already consented to participate in biomedical research and of whom biological samples (DNA, plasma, serum) and lifestyle data have been deposited in a repository and database, respectively. We are requesting funding from the Human Diversity project to sequence the genomes of the 200 CBR volunteers at low pass (6x coverage). Nuclei, DNA and RNA will be recovered from the purified cells and made available for RNA-seq, DNA-seq and ChIP-seq and genomic DNA for entire genome sequencing will be recovered from the DNA repository.

  Dataset EGAD00001002205