Discovery and characterization of variance QTLs in human induced pluripotent stem cells
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ABSTRACT:
PROVIDER: PRJNA486542 | ENA |
REPOSITORIES: ENA
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Project description:Quantification of gene expression levels at the single cell level has revealed that gene expression can vary substantially even across a population of homogeneous cells. However, it is currently unclear what genomic features control variation in gene expression levels, and whether common genetic variants may impact gene expression variation. Here, we take a genome-wide approach to identify expression variance quantitative trait loci (vQTLs). To this end, we generated single cell RNA-seq (scRNA-seq) data from induced pluripotent stem cells (iPSCs) derived from 53 Yoruba individuals. We collected data for a median of 95 cells per individual and a total of 5,447 single cells, and identified 241 mean expression QTLs (eQTLs) at 10% FDR, of which 82% replicate in bulk RNA-seq data from the same individuals. We further identified 14 vQTLs at 10% FDR, but demonstrate that these can also be explained as effects on mean expression. Our study suggests that dispersion QTLs (dQTLs), which could alter the variance of expression independently of the mean, have systematically smaller effect sizes than eQTLs. We estimate that at least 300 cells per individual and 400 individuals would be required to have modest power to detect the strongest dQTLs in iPSCs. These results will guide the design of future studies on understanding the genetic control of gene expression variance.
2018-09-21 | GSE118723 | GEO
Project description: Not available
| S-EPMC6474585 | biostudies-literature
Project description:Transcriptional profiles were generated for lymphocyte samples from 1,240 randomly ascertained, mostly non-diseased Mexican American participants in the San Antonio Family Heart Study. Research findings related to the genetic regulation of expression levels are published in the following article: Goring et al. 2007. Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nature Genetics, in press. Further information about the data are available at http://www.sfbrgenetics.org/SanAntonioFamilyHeartStudy/expressionProfiling.
2008-01-01 | E-TABM-305 | biostudies-arrayexpress
Project description:Variance in microarray studies has been widely discussed as a critical topic of the identification of differentially expressed gene; however, few studies have addressed the influence of estimating variance. To break intra- and inter-individual variance in clinical studies down to three levels: technical, anatomic, and individual, we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of “inter-individual variable genes” were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduce/eliminate the effects of underestimated variance. Our data demonstrates that an appropriate evaluation of variance is critical in selecting significant genes of differential expression. If the estimation of precise variance has not been adequately considered in the experimental design, using a higher fold change criteria is one possible solution to overcome the difficulties associated with the identification of significant genes, but it paid by losing the number of selected genes.
2011-03-02 | GSE27646 | GEO
Project description:mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts are generally assumed to follow a Poisson distribution in which the variance is equal to the mean. However, it is common in observed count data with biological variation for over-dispersion to be present, i.e., for the variance to be greater than the mean.
2012-07-17 | GSE29022 | GEO
Project description:mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts are generally assumed to follow a Poisson distribution in which the variance is equal to the mean. However, it is common in observed count data with biological variation for over-dispersion to be present, i.e., for the variance to be greater than the mean. examination of technical and biological variance in mRNA-seq count data
2012-07-16 | E-GEOD-29022 | biostudies-arrayexpress
Project description:We have combined large-scale mRNA expression and gene mapping methods to identify genes and loci that control hematopoietic stem cell (HSC) functioning. mRNA expression levels were measured in purified HSC isolated from a panel of densely genotyped recombinant inbred mouse strains. Quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts were mapped. Comparison of the physical transcript position with the location of the controlling QTL identified polymorphic cis-acting stem cell genes. In addition, multiple trans-acting control loci were highlighted that modify expression of large numbers of genes. These groups of co-regulated transcripts identify pathways that specify variation in stem cells. We illustrate this concept with the identification of strong candidate genes involved with HSC turnover. We compared expression QTLs in HSC and brain from the same animals, and document both shared and tissue-specific QTLs. Our data are accessible through WebQTL, a web-based interface that allows custom genetic linkage analysis and identification of co-regulated transcripts.
2007-11-16 | E-GEOD-2031 | biostudies-arrayexpress
Project description:A collection of budding yeast wild types grown in parallel to 1,484 budding yeast deletion mutants to assess day-to-day variance. Related to series GSE42526 and GSE42527.
2014-04-24 | GSE45115 | GEO
Project description:Chronic infantile neurological cutaneous and articular (CINCA) syndrome is an IL-1-driven autoinflammatory disorder caused mainly by NLRP3 mutations. The pathogenesis of CINCA syndrome patients who carry NLRP3 mutations as somatic mosaicism has not been precisely described because of the difficulty in separating individual cells based on the presence or absence of the mutation. Here, we report the generation of NLRP3-mutant and non-mutant induced pluripotent stem cell (iPSC) lines from two CINCA syndrome patients with somatic mosaicism, and describe their differentiation into macrophages (iPS-MPs). We found that mutant cells are predominantly responsible for the pathogenesis in these mosaic patients because only mutant iPS-MPs showed the disease relevant phenotype of abnormal IL-1M-NM-2 secretion. We also confirmed that the existing anti-inflammatory compounds inhibited the abnormal IL-1M-NM-2 secretion, indicating that mutant iPS-MPs are applicable for drug screening for CINCA syndrome and other NLRP3-related inflammatory conditions. Our results illustrate that patient-derived iPSCs are useful for dissecting somatic mosaicism, and that NLRP3-mutant iPSCs can provide a valuable platform for drug discovery for multiple NLRP3-related disorders. To characterize iPS and differentiated cells, RNA expression profiles were evaluated by microarray analysis.We analyzed iPC cells and macrophage from healthy volunteers and CINCA syndrome patients. Human ES cella and fibroblasts were used as control.
2012-06-10 | E-GEOD-38626 | biostudies-arrayexpress
Project description:The integration of cell metabolism with signalling pathways, transcription factor networks and epigenetic mediators is critical in coordinating molecular and cellular events during embryogenesis. Induced pluripotent stem cells (IPSCs) are an established model for embryogenesis, germ layer specification and cell lineage differentiation, advancing the study of human embryonic development and the translation of innovations in drug discovery, disease modelling and cell-based therapies. The metabolic regulation of IPSC pluripotency is mediated by balancing glycolysis and oxidative phosphorylation, but there is a paucity of data regarding the influence of individual metabolite changes during cell lineage differentiation. We used <sup>1</sup>H NMR metabolite fingerprinting and footprinting to monitor metabolite levels as IPSCs are directed in a three-stage protocol through primitive streak/mesendoderm, mesoderm and chondrogenic populations. Metabolite changes were associated with central metabolism, with aerobic glycolysis predominant in IPSC, elevated oxidative phosphorylation during differentiation and fatty acid oxidation and ketone body use in chondrogenic cells. Metabolites were also implicated in the epigenetic regulation of pluripotency, cell signalling and biosynthetic pathways. Our results show that <sup>1</sup>H NMR metabolomics is an effective tool for monitoring metabolite changes during the differentiation of pluripotent cells with implications on optimising media and environmental parameters for the study of embryogenesis and translational applications.
2023-05-24 | MTBLS4854 | MetaboLights