Gene expression from CEPH-Utah,CHB+JPT, and YRI individuals to examine gene expression correlation
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE12526 | GEO | 2009/08/13
SECONDARY ACCESSION(S): PRJNA112931
REPOSITORIES: GEO
Similar Datasets
Project description:We used microarrays to examine gene expression levels in individuals from different populations (cephgp, chb, jpt, yri). The chb and jpt populations are combined in the analysis. We measured gene expression levels in 295 lymphoblastoid cell lines representing 4 ethnically-distinct populations. For some cell lines, RNA extracts were hybridized twice, representing technical replicates. For these cell lines, we take the average signal intensity as a measure of relative abundance of a gene.
2009-08-13 | E-GEOD-12526 | biostudies-arrayexpress
Project description:HapMap CHB and JPT samples
2009-07-27 | GSE16895 | GEO
Project description:Expression level of genes in lymphoblasts from individuals in three HapMap populations (CEU, CHB, JPT) were compared. More than 1,000 genes were found to be significantly different (Pc<0.05) in mean expression level between the CEU and CHB+JPT samples. Experiment Overall Design: Gene expression analysis using Affymetrix Human Focus arrays; comparison of expression levels of genes by t-test.
2008-06-14 | E-GEOD-5859 | biostudies-arrayexpress
Project description:Expression level of genes in lymphoblasts from individuals in three HapMap populations (CEU, CHB, JPT) were compared. More than 1,000 genes were found to be significantly different (Pc<0.05) in mean expression level between the CEU and CHB+JPT samples. Keywords: Comparison of Gene Expression Profiles from Lymphoblastoid cells
2007-01-07 | GSE5859 | GEO
Project description:Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype-phenotype relationships in human cells. These cell lines have been used to search for genetic variants that are associated with drug response as well as with more basic cellular traits such as RNA levels. In setting out to extend such studies by searching for genetic variants contributing to drug response, we observed that phenotypes in LCLs were, in our lab and others, significantly affected by experimental confounders (i.e. in vitro growth rate, metabolic state, and relative levels of the Epstein-Barr virus used to transform the cells). As we did not find any SNPs associated with genome-wide significance to drug response, we evaluated whether incorporating RNA expression levels (and eQTLs) in the analysis could increase power to detect such effects. As previously shown, cis-acting eQTLs were detectable for a sizeable fraction of RNAs and baseline levels of many RNAs predicted response to several drugs. However, we found only limited evidence that SNPs influenced drug response through their effect on expression of RNA. Efforts to use LCLs to map genes underlying cellular traits will require great care to control experimental confounders, unbiased methods for integrating and interpreting such multi-dimensional data, and much larger sample sizes than have been applied to date. Experiment Overall Design: We studied 269 cell lines densely genotyped by the International HapMap Project [31]. Cell lines were cultured and characterized at baseline for a variety of cellular phenotypes including growth rate, ATP levels, mitochondrial DNA copy number, EBV copy number, and measures of B-cell relevant cell surface receptors and cytokine levels. Each cell line was exposed in 384-well plates to a range of doses for each of seven drugs selected based on their divergent mechanisms of action and importance in clinical use for treatment of B-cell diseases, focusing on anti-cancer agents: 5-fluorouracil (5FU), methotrexate (MTX), simvastatin, SAHA, 6-mercaptopurine (6MP), rapamycin, and bortezomib. Drug response was measured using Celltiter Glo, an ATP-activated intracellular luminescent marker that, when compared to mock-treated control wells, can represent relative levels of cellular viability and metabolic activity. RNA was collected at baseline and RNA transcript levels were measured genome-wide on the Affymetrix platform. Baseline characterization and plating for drug response experiments was performed using batches of 90 cell lines from each HapMap analysis panel (CEU, JPT / CHB, and YRI) on each of three experiment days. The order of cell lines within each panel was randomized to avoid inducing artificial intra-familial correlation. Each drug was tested at a range of doses around the expected IC50 as reported for the drug by the NCI DTP; each dose of drug was tested in two wells per plate and on two separate plates. These replicate measurements for each cell line allowed assessment of intra-experimental variation. To evaluate day-to-day (i.e. inter-experimental) variation in all traits, a subset of 90 cell lines (30 from each of the three HapMap panels) was grown from a fresh aliquot and the entire experiment was repeated. To evaluate the effect of technical error on measured RNA levels, a set of 22 RNAs previously expression profiled (using Illumina HumanChip) at Wellcome Trust Sanger Institute (WTSI) (generously provided by Emmanouil T. Dermatsakis) was included in expression profiling at the Broad on Affymetrix arrays. Data can be downloaded from the Broad Institute web site: (http://www.broad.mit.edu/~yelensky/cell_lines_paper/). Please see Materials and Methods for details of QC, normalization, etc.
2008-06-19 | E-GEOD-11582 | biostudies-arrayexpress
Project description:Gene expression from CEPH-Utah,CHB+JPT, and YRI individuals to examine gene expression correlation
| PRJNA112931 | ENA
Project description:HapMap samples
2009-07-27 | GSE17213 | GEO
Project description:Given that diseases associated with anti-SSA/Ro autoantibodies such as systemic lupus erythematosus and Sjögren’s syndrome are linked with an upregulation of IFN and type I IFN-stimulated genes, including Sialic Acid-Binding Ig-Like Lectin 1 (Siglec-1), a receptor on monocytes/macrophages, recent attention has focused on a potential role for IFN and IFN-stimulated genes in the pathogenesis of congenital heart block (CHB). Accordingly, three approaches were leveraged to address the association of IFN, IFN-stimulated genes, and the phenotype of macrophages in affected fetal cardiac tissue: a) cultured healthy human macrophages transfected with hY3, an anti-SSA/Ro-associated single-stranded RNA, b) RNA isolated from freshly sorted human leukocytes/macrophages after Langendorff perfusion of three fetal hearts dying with CHB and three healthy gestational age-matched hearts, and c) autopsy tissue from three additional human CHB hearts and one healthy heart. TLR ligation of macrophages with hY3 led to the upregulation of a panel of IFN transcripts, including SIGLEC1, a result corroborated using qPCR. Utilizing independent and agnostic bioinformatics approaches, CD45+CD11c+ and CD45+CD11c- human leukocytes flow sorted from the CHB hearts highly expressed type I IFN response genes inclusive of SIGLEC1. Furthermore, Siglec-1 expression was identified in the septal region of several affected fetal hearts. These data now provide a link between IFN, IFN-stimulated genes, and the inflammatory and possibly fibrosing components of CHB, positioning Siglec-1-positive macrophages as integral to the process.
2018-10-24 | GSE121699 | GEO