4sU metabolic labeled transcripts in 65 YRI LCLs
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE75220 | GEO | 2016/03/29
SECONDARY ACCESSION(S): PRJNA302818
REPOSITORIES: GEO
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Project description:Noncoding variants play a central role in the genetics of complex traits, but we still lack a full description of the main molecular pathways through which they act. Here we used molecular data to quantify the contribution of cis-acting genetic effects at each major stage of gene regulation from chromatin to proteins, within a population sample of Yoruba lymphoblastoid cell lines (LCLs). We performed 4sU metabolic labeled transcripts in 65 YRI LCLs to identify genetic variants that affect transcription rates. As expected, we found an important contribution of genetic variation via chromatin, contributing â¼65% of eQTLs (expression Quantitative Trait Loci). The remaining eQTLs, which are not asso- ciated with chromatin-level variation, are highly enriched in transcribed regions, and hence may affect expression through co- or post-transcriptional processes. International HapMap lymphoblastoid cell lines (LCLs) derived from YRI (Yoruba in Ibadan, Nigeria); We adapted the 4sU labelling method from (PMID 21516085). Briefly, cell cultures were grown to log phase in volumes sufficient to yield about 300 ng of 4sU-labeled RNA. Cells were incubated with 4sU for the required length of time (0, 30, or 60 minutes), then washed, pelleted, and frozen. Total RNA was extracted, and 4sU-labeled RNA was separated from total RNA using a bead-based biotin-streptavidin purification protocol. We sequenced metabolic labeled transcripts in 65 YRI LCLs 30 minutes and 60 minutes after incubation.
2016-03-29 | E-GEOD-75220 | biostudies-arrayexpress
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.
2014-12-19 | PXD001406 | Pride
Project description:Baseline microRNA (miRNA) expression was evaluated in 107 HapMap lymphoblastoid cell lines (LCLs; 53 CEU and 54 YRI) using Exiqon miRCURY LNA arrays v10.0 (Exiqon array).
2012-07-29 | GSE34406 | GEO
Project description:Glucocorticoids (GCs) are key mediators of stress response and are widely used as pharmacological agents to treat immune diseases, such as asthma and inflammatory bowel disease, and certain types of cancer. GCs act mainly by activating the GC receptor (GR), which interacts with other transcription factors to regulate gene expression. Here, we combined different functional genomics approaches to gain molecular insights into the mechanisms of action of GC. By profiling the transcriptional response to GC over time in 4 Yoruba (YRI) and 4 Tuscans (TSI) lymphoblastoid cell lines (LCLs), we suggest that the transcriptional response to GC is variable not only in time, but also in direction (positive or negative) depending on the presence of specific interacting TFs. Accordingly, when we performed ChIP-seq for GR and NF-kB in two YRI LCLs treated with GC or with vehicle control, we observed that features of GR binding sites differ for up- and down-regulated genes. Finally, we show that eQTLs that affect expression patterns only in the presence of GC are 1.9-fold more likely to occur in GR binding sites, compared to eQTLs that affect expression only in its absence. Our results indicate that genetic variation at GR and interacting transcription factors binding sites influences variability in gene expression, and attest to the power of combining different functional genomic approaches.
2013-04-01 | GSE45638 | GEO
Project description:Glucocorticoids (GCs) are key mediators of stress response and are widely used as pharmacological agents to treat immune diseases, such as asthma and inflammatory bowel disease, and certain types of cancer. GCs act mainly by activating the GC receptor (GR), which interacts with other transcription factors to regulate gene expression. Here, we combined different functional genomics approaches to gain molecular insights into the mechanisms of action of GC. By profiling the transcriptional response to GC over time in 4 Yoruba (YRI) and 4 Tuscans (TSI) lymphoblastoid cell lines (LCLs), we suggest that the transcriptional response to GC is variable not only in time, but also in direction (positive or negative) depending on the presence of specific interacting TFs. Accordingly, when we performed ChIP-seq for GR and NF-kB in two YRI LCLs treated with GC or with vehicle control, we observed that features of GR binding sites differ for up- and down-regulated genes. Finally, we show that eQTLs that affect expression patterns only in the presence of GC are 1.9-fold more likely to occur in GR binding sites, compared to eQTLs that affect expression only in its absence. Our results indicate that genetic variation at GR and interacting transcription factors binding sites influences variability in gene expression, and attest to the power of combining different functional genomic approaches.
2013-04-01 | GSE44248 | GEO
Project description:Glucocorticoids (GCs) are key mediators of stress response and are widely used as pharmacological agents to treat immune diseases, such as asthma and inflammatory bowel disease, and certain types of cancer. GCs act mainly by activating the GC receptor (GR), which interacts with other transcription factors to regulate gene expression. Here, we combined different functional genomics approaches to gain molecular insights into the mechanisms of action of GC. By profiling the transcriptional response to GC over time in 4 Yoruba (YRI) and 4 Tuscans (TSI) lymphoblastoid cell lines (LCLs), we suggest that the transcriptional response to GC is variable not only in time, but also in direction (positive or negative) depending on the presence of specific interacting TFs. Accordingly, when we performed ChIP-seq for GR and NF-kB in two YRI LCLs treated with GC or with vehicle control, we observed that features of GR binding sites differ for up- and down-regulated genes. Finally, we show that eQTLs that affect expression patterns only in the presence of GC are 1.9-fold more likely to occur in GR binding sites, compared to eQTLs that affect expression only in its absence. Our results indicate that genetic variation at GR and interacting transcription factors binding sites influences variability in gene expression, and attest to the power of combining different functional genomic approaches. GR and NFkB ChIP-seq in lymphoblastoid cell lines treated with either dexamethasone or EtOH (vehicle for dexamethasone) for 1 hour.
2013-04-01 | E-GEOD-45638 | biostudies-arrayexpress
Project description:Glucocorticoids (GCs) are key mediators of stress response and are widely used as pharmacological agents to treat immune diseases, such as asthma and inflammatory bowel disease, and certain types of cancer. GCs act mainly by activating the GC receptor (GR), which interacts with other transcription factors to regulate gene expression. Here, we combined different functional genomics approaches to gain molecular insights into the mechanisms of action of GC. By profiling the transcriptional response to GC over time in 4 Yoruba (YRI) and 4 Tuscans (TSI) lymphoblastoid cell lines (LCLs), we suggest that the transcriptional response to GC is variable not only in time, but also in direction (positive or negative) depending on the presence of specific interacting TFs. Accordingly, when we performed ChIP-seq for GR and NF-kB in two YRI LCLs treated with GC or with vehicle control, we observed that features of GR binding sites differ for up- and down-regulated genes. Finally, we show that eQTLs that affect expression patterns only in the presence of GC are 1.9-fold more likely to occur in GR binding sites, compared to eQTLs that affect expression only in its absence. Our results indicate that genetic variation at GR and interacting transcription factors binding sites influences variability in gene expression, and attest to the power of combining different functional genomic approaches. Total RNA obtained from lymphoblastoid cell lines treated with either dexamethasone or EtOH (vehicle for dexamethasone) for 2, 4, 8, 12, 16, or 24 hours.
2013-04-01 | E-GEOD-44248 | biostudies-arrayexpress
Project description:N6-methyladenosine (m6A) profiling in 60 YRI LCLs
| PRJNA515941 | ENA
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:4sU metabolic labeled transcripts in 65 YRI LCLs
| PRJNA302818 | ENA