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accession-icon GSE3854
An integrated strategy for analyzing the unique developmental program of different myoblast subtypes
  • organism-icon Drosophila melanogaster
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome Array (drosgenome1)

Description

An important but largely unmet challenge in understanding the mechanisms that govern formation of specific organs is to decipher the complex and dynamic genetic programs exhibited by the diversity of cell types within the tissue of interest. Here, we use an integrated genetic, genomic and computational strategy to comprehensively determine the molecular identities of distinct myoblast subpopulations within the Drosophila embryonic mesoderm at the time that cell fates are initially specified. A compendium of gene expression profiles was generated for primary mesodermal cells purified by flow cytometry from appropriately staged wild-type embryos and from twelve genotypes in which myogenesis was selectively and predictably perturbed. A statistical meta-analysis of these pooled datasetsbased on expected trends in gene expression and on the relative contribution of each genotype to the detection of known muscle genesprovisionally assigned hundreds of differentially expressed genes to particular myoblast subtypes. Whole embryo in situ hybridizations were then used to validate the majority of these predictions, thereby enabling true positive detection rates to be estimated for the microarray data. This combined analysis reveals that myoblasts exhibit much greater gene expression heterogeneity and overall complexity than was previously appreciated. Moreover, it implicates the involvement of large numbers of uncharacterized, differentially expressed genes in myogenic specification and subsequent morphogenesis. These findings also underscore a requirement for considerable regulatory specificity for generating diverse myoblast identities. Finally, to illustrate how the developmental functions of newly identified myoblast genes can be efficiently surveyed, a rapid RNA interference assay that can be scored in living embryos was developed and applied to selected genes. This integrated strategy for examining embryonic gene expression and function provides a substantially expanded framework for further studies of this model developmental system.

Publication Title

An integrated strategy for analyzing the unique developmental programs of different myoblast subtypes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE73022
Inflammation promotes a conversion of astrocytes into neural progenitor cells via NF-kB activation
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Brain inflammation, a common feature in neurodegenerative diseases, is a complex series of events, which can be detrimental and even lead to neuronal death. Nonetheless, several studies suggest that inflammatory signals are also positively influencing neural cell proliferation, survival, migration and differentiation. Recently, correlative studies suggested that astrocytes are able to dedifferentiate upon injury, and may thereby re-acquire neural stem cells (NSC) potential. However, the mechanism underlying this dedifferentiation process upon injury remains unclear. In this study, we find that during the early response of reactive gliosis, inflammation induces a conversion of mature astrocytes into neural progenitors. A TNF treatment induces the decrease of specific astrocyte markers, such as GFAP or genes related to glycogen metabolism, while a subset of these cells re-express immaturity markers, such as CD44, Musashi-1 and Oct4. Thus, TNF treatment results in the appearance of cells that exhibit a neural progenitor phenotype and are able to proliferate and differentiate into neurons and/or astrocytes.

Publication Title

Inflammation Promotes a Conversion of Astrocytes into Neural Progenitor Cells via NF-κB Activation.

Sample Metadata Fields

Specimen part

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accession-icon GSE76563
The study of inflammatory responses in mammalian macrophages with LPS stimulation
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE76561
LPS stimulation of human PBMC-derived macrophages
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions and its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalyzing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. Using a combination of literature information, transcription factor prediction models and genome-wide expression arrays, we inferred the regulatory network of IRG1 in mouse and human macrophages.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE76562
LPS stimulation of Mouse (RAW 264.7) macrophages
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions and its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalyzing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. Using a combination of literature information, transcription factor prediction models and genome-wide expression arrays, we inferred the regulatory network of IRG1 in mouse and human macrophages.

Publication Title

Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

Sample Metadata Fields

Specimen part

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accession-icon GSE46025
Expression data from WT and Foxo1 KO CD8+ KLRG1high or KLRG1low populations after LCMV infection
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The forkhead O transcription factors (FOXO) integrate a range of extracellular signals including growth factor signaling, inflammation, oxidative stress and nutrient availability, to substantially alter the program of gene expression and modulate cell survival, cell cycle progression, and many cell-type specific responses yet to be unraveled. Naive antigen-specific CD8+ T cells undergo a rapid expansion and arming of effector function within days of pathogen exposure, but in addition, by the peak of expansion, they form precursors to memory T cells capable of self-renewal and indefinite survival.

Publication Title

Differentiation of CD8 memory T cells depends on Foxo1.

Sample Metadata Fields

Specimen part

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accession-icon GSE70494
Epigenome-wide and Transcriptome-wide Analyses Reveal Gestational Diabetes is Associated with Alterations in the Human Leukocyte Antigen Complex
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation450 BeadChip (HumanMethylation450_15017482), Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Epigenome-wide and transcriptome-wide analyses reveal gestational diabetes is associated with alterations in the human leukocyte antigen complex.

Sample Metadata Fields

Specimen part

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accession-icon GSE70493
Epigenome-wide and Transcriptome-wide Analyses Reveal Gestational Diabetes is Associated with Alterations in the Human Leukocyte Antigen Complex [gene expression]
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20), Illumina HumanMethylation450 BeadChip (HumanMethylation450_15017482)

Description

Gestational diabetes mellitus (GDM) affects approximately 18% of pregnancies in the United States and increases the risk of adverse health outcomes in the offspring. These adult disease propensities may be set by anatomical and molecular alterations in the placenta associated with GDM. To assess the mechanistic aspects of fetal programming, we measured genome-wide methylation (Infinium HumanMethylation450 Beadchips) and expression (Affymetrix Transcriptome Microarrays) in placental tissue of 41 GDM cases and 41 matched pregnancies without maternal complications from the Harvard Epigenetic Birth Cohort. Specific transcriptional and epigenetic perturbations associated with GDM status included alterations in the major histocompatibility complex (MHC) region, which were validated in an independent cohort, the Rhode Island Child Health Study. Gene ontology enrichment among gene regulation influenced by GDM revealed an over-representation of immune response pathways among differential expression, reflecting these coordinated changes in the MHC region. Our study represents the largest investigation of transcriptomic and methylomic differences associated with GDM, providing comprehensive insight into the molecular basis of GDM induced fetal (re)programming.

Publication Title

Epigenome-wide and transcriptome-wide analyses reveal gestational diabetes is associated with alterations in the human leukocyte antigen complex.

Sample Metadata Fields

Specimen part

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accession-icon GSE30697
The Combination of a Genome-Wide Association Study of Lymphocyte Count and Analysis of Gene Expression Data Reveals Novel Asthma Candidate Genes
  • organism-icon Homo sapiens
  • sample-icon 94 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the missing heritability problem. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complementary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines (LCLs) from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility, as well as novel candidate genes enriched for functions related to T cell receptor signaling and ATP synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Publication Title

The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes.

Sample Metadata Fields

Sex

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accession-icon SRP059197
An orthologous epigenetic gene expression signature derived from differentiating embryonic stem cells identifies regulators of cardiogenesis
  • organism-icon Homo sapiens
  • sample-icon 34 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We report a time course of RNA-seq data from wild-type embryonic stem cells and embryonic stem cells in which the cardiogenic transcription factors ZNF503, ZEB2 and NKX2-5 are depleted with shRNAs differentiating along the cardiac lineage. Overall design: Biological replicates of RNA-seq data from embryonic stem cells differentiating along the cardiac lineage.

Publication Title

An Orthologous Epigenetic Gene Expression Signature Derived from Differentiating Embryonic Stem Cells Identifies Regulators of Cardiogenesis.

Sample Metadata Fields

No sample metadata fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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