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GSE9889
Drosophila melanogaster
20 Downloadable Samples
Affymetrix Drosophila Genome Array (drosgenome1)
Description
The conserved Mef2 transcription factor is a major regulator of gene expression and differentiation. Recent genomic studies have identified a large number of mef2-regulated target genes with distinct temporal expression profiles during Drosophila myogenesis. However, the question remains as to how a single transcription factor can control such diverse patterns of gene expression. The aim of this project was to investigate whether there are genes with different mef2-requirements for their expression during muscle differentiation in vivo during the development of Drosophila melanogaster.
Publication Title
mef2 activity levels differentially affect gene expression during Drosophila muscle development.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
The coupling between cell-cycle exit and onset of differentiation is a common feature throughout the developing nervous system, but the mechanisms that link these processes are mostly unknown. Although the transcription factor Pax6 was implicated in both proliferation and differentiation of multiple regions within the CNS, its contribution to the transition between these successive states remains elusive. To gain insight into the role of Pax6 during the transition from proliferating progenitors to differentiating precursors, we investigated cell-cycle and transcriptomic changes occurring in Pax6- retinal progenitor cells (RPCs). Our analyses revealed a unique cell-cycle phenotype of the Pax6-deficient RPCs, which included a reduced number of cells in the S phase, an increased number of cells exiting the cell cycle, and delayed differentiation kinetics of Pax6- precursors. These alterations were accompanied by co-expression of factors that promote (Ccnd1, Ccnd2, Ccnd3) and inhibit (P27kip1 and P27kip2) the cell cycle. Further characterization of the changes in transcription profile of the Pax6-deficient RPCs revealed abrogated expression of multiple factors which are known to be involved in regulating proliferation of RPCs, including the transcription factors Vsx2, Nr2e1, Plagl1 and Hedgehog signaling. These findings provide novel insight into the molecular mechanism mediating the pleiotropic activity of Pax6 in RPCs. The results further suggest that rather than conveying a linear effect on RPCs, such as promoting their proliferation and inhibiting their differentiation, Pax6 regulates multiple transcriptional networks which function simultaneously, thereby conferring the capacity to proliferate, assume multiple cell fates and execute the differentiation program into retinal lineages.
Publication Title
Pax6 is required for normal cell-cycle exit and the differentiation kinetics of retinal progenitor cells.
Sample Metadata Fields
Specimen part
View Samples- Rattus norvegicus
- 12 Downloadable Samples
Illumina HiSeq 2000
Description
RNA-Sequencing of the trigeminal nucleus caudalis and spinal cord, dorsal horn in male naive rats (Wistar Han) of 10 weeks old Overall design: 6 naive rats were killed after 2 weeks of arrival, both trigeminal nucleus caudalis and spinal cord dorsal horn were dissected using laser capture microdissection of each rat.
Publication Title
Transcriptomic profiling of trigeminal nucleus caudalis and spinal cord dorsal horn.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Objectives and goals: The causes and molecular pathology of ovarian cancer are essentially unknown. However, it is generally understood that serous ovarian borderline tumors (SBOT) and well differentiated (WD) serous ovarian carcinomas (SC) have a similar tumorigenetic pathway, distinct from moderately (MD) and poorly differentiated (PD) SC. The aim of this study was to identify mRNAs differentially expressed between MD/PD SC, SBOT and superficial scrapings from normal ovaries (SNO),and to correlate these mRNAs with clinical parameters.
Publication Title
ZNF385B and VEGFA are strongly differentially expressed in serous ovarian carcinomas and correlate with survival.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 12 Downloadable Samples
- NextSeq 500
Description
We report the application of RNA sequencing for transcriptome analysis of virus infected tissues, enabling the study of tissue responses to infection Overall design: Transcriptome analysis of 2 different tissues infected with two different viruses
Publication Title
Correction for Weisblum et al., "Zika Virus Infects Early- and Midgestation Human Maternal Decidual Tissues, Inducing Distinct Innate Tissue Responses in the Maternal-Fetal Interface".
Sample Metadata Fields
Specimen part, Subject, Time
View Samples- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Clariom S Human array (clariomshuman)
Description
Tanning is a skin protection mechanism against UV radiation. Pigment production initiates hours after exposure, and the mechanism controlling this delay was unknown. Here we reveal a skin UV-protection timer, governed by damped oscillatory dynamics of the melanocyte master regulator, MITF, which after UV exposure, synchronizes regulatory programs, first cell survival and later pigmentation. Remarkably, the same amount of UV dosage resulted in higher pigmentation of human skin when given every-other day compared to daily exposure. Daily UV exposure appears to perturb MITF dynamics, thus re-ordering the survival and pigmentation programs. This demonstrates that the skin is more sensitive to frequency than quantity of UV exposure. Mathematical modeling identified a double negative regulatory loop involving HIF1a and microRNA-148a that regulates MITF dynamics. Our study suggests evolutionary leverage of the UV-protection timer, as it evolved to induce maximum protection with minimum damage for the reduction of skin cancer risk.
Publication Title
UV-Protection Timer Controls Linkage between Stress and Pigmentation Skin Protection Systems.
Sample Metadata Fields
Time
View Samples- Homo sapiens
- 189 Downloadable Samples
- Illumina HiSeq 2500, Illumina HiSeq 2000
Description
Fibroblasts synthesize the extracellular matrix of connective tissue and play an essential role in maintaining tissue integrity. We have previously shown that mouse skin connective tissue, the dermis, is comprised of functionally distinct fibroblast lineages. However, the extent of fibroblast heterogeneity in human skin is unknown. Here, using a combination of spatial transcriptional profiling of human and mouse dermis and single cell transcriptional profiling of human dermal fibroblasts, we show that there are at least four distinct fibroblast populations in adult human skin. We define markers permitting prospective isolation of these cells and show that although marker expression is rapidly lost in culture, different fibroblast subpopulations retain distinct functionality in terms of Wnt signalling, T cell communication and the ability to support human epidermal reconstitution in organotypic culture. Furthermore, while some fibroblast subpopulations are spatially segregated, others are not. These findings have profound implications for normal wound healing and diseases characterized by excessive fibrosis, and suggest that ex vivo expansion or in vivo ablation of specific fibroblast subpopulations may have therapeutic applications. Overall design: Spatial RNA sequencing of human papillary versus reticular dermis for 3 individuals, and single cell RNA sequencing of dermal fibroblasts for a single individual.
Publication Title
Spatial and Single-Cell Transcriptional Profiling Identifies Functionally Distinct Human Dermal Fibroblast Subpopulations.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Gene 2.0 ST Array (mogene20st)
Description
Expression data from P2 mouse fibroblasts sorted for CD26, Sca1 and Dlk1. We have sorted mouse fibroblasts using the different lineages markers
Publication Title
Spatial and Single-Cell Transcriptional Profiling Identifies Functionally Distinct Human Dermal Fibroblast Subpopulations.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Agilent-028005 SurePrint G3 Mouse GE 8x60K Microarray (Probe Name version)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Retinoic acid is essential for Th1 cell lineage stability and prevents transition to a Th17 cell program.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 2.0 ST Array (mogene20st), Agilent-028005 SurePrint G3 Mouse GE 8x60K Microarray (Probe Name version)
Description
CD4+ T cells differentiate into phenotypically distinct T-helper cells upon antigenic stimulation. Regulation of plasticity between these CD4+ T-cell lineages is critical for immune homeostasis and prevention of autoimmune diseases. However, the factors that regulate lineage stability are largely unknown. Here we investigate a role for retinoic acid (RA) in the regulation of lineage stability using T helper 1 (Th1) cells, traditionally considered the most phenotypically stable Th subset. We found that RA, through its receptor RARa, sustains stable expression of Th1 lineage specifying genes as well as repressing genes that instruct Th17 cell fate. RA signaling is essential for limiting Th1 cell conversion into Th17 effectors and for preventing pathogenic Th17 responses in vivo. Our studies identify RA-RARa as a key component of the regulatory network governing Th1 cell fate and define a new paradigm for the development of pathogenic Th17 cells. These findings have important implications for autoimmune diseases in which dysregulated Th1-Th17 responses are observed.
Publication Title
Retinoic acid is essential for Th1 cell lineage stability and prevents transition to a Th17 cell program.
Sample Metadata Fields
No sample metadata fields
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