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SRP132408
Arabidopsis thaliana
16 Downloadable Samples
Illumina HiSeq 2000
Description
Environmental factors shape the phenotypes of multicellular organisms. The production of stomata—the epidermal pores required for gas exchange in plants—is highly plastic, and provides a powerful platform to address environmental influence on cell differentiation [1-3]. Rising temperatures are already impacting plant growth, a trend expected to worsen in the near future [4]. High temperature inhibits stomatal production but the underlying mechanism is not known [5]. Here, we show that elevated temperature suppresses the expression of SPEECHLESS (SPCH), the bHLH transcription factor that serves as the master regulator of stomatal lineage initiation [6,7]. Our genetic and expression analyses indicate that the suppression of SPCH and stomatal production is mediated by the bHLH transcription factor PHYTOCHROME-INTERACTING FACTOR 4 (PIF4), a core component of high temperature signaling [8]. Importantly, we demonstrate that upon exposure to high temperature, PIF4 accumulates in the stomatal precursors and binds to the promoter of SPCH. In addition, we find SPCH feeds back negatively to the PIF4 gene. We propose a model where the high temperature-activated PIF4 binds and represses SPCH expression to restrict stomatal production at high temperature. Our work identifies a molecular link connecting high temperature signaling and stomatal development, and reveals a direct mechanism by which production of a specific cell lineage can be controlled by a broadly-expressed environmental signaling factor. Overall design: Gene expression profiles following 12 hr Dex-induction of control and ML1p:SPCH1-4A-expressing Arabidopsis plants grown in liquid culture. Four replicates per line at 0 and 12 hr.
Publication Title
Direct Control of SPEECHLESS by PIF4 in the High-Temperature Response of Stomatal Development.
Sample Metadata Fields
Age, Subject
View Samples- Bos taurus
- 159 Downloadable Samples
Affymetrix Bovine Genome Array (bovine)
Description
Infertility in lactating dairy cows is explained partially by the metabolic state associated with high milk production. The hypothesis was that lactating and non-lactating cows would differ in endometrial and placental transcriptomes during early pregnancy (day 28 to 42) and this difference would explain the predisposition for lactating cows to have embryonic loss at that time. Cows were either milked or not milked after calving. Reproductive [endometrium (caruncular and intercarunclar) and placenta] and liver tissues were collected on day 28, 35, and 42 of pregnancy. The primary hypothesis was rejected because no effect of lactation on mRNA abundance within reproductive tissues was found. Large differences within liver demonstrated the utility of the model to test an effect of lactation on tissue gene expression. Major changes in gene expression in reproductive tissues across time were found. Greater activation of the transcriptome for the recruitment and activation of macrophages was found in the endometrium and placenta. Changes in glucose metabolism between day 28 and 42 included greater mRNA abundance of rate-limiting genes for gluconeogenesis in intercaruncular endometrium and evidence for the establishment of aerobic glycolysis (Warburg effect) in the placenta. Temporal changes were predicted to be controlled by CSF1, PDGFB, and JUN. Production of nitric oxide and reactive oxygen species by macrophages was a mechanism to promote angiogenesis in the endometrium. Reported differences in pregnancy development for lactating versus non-lactating cows could be explained by systemic glucose availability to the conceptus and appear to be independent of the endometrial and placental transcriptomes.
Publication Title
The transcriptome of the endometrium and placenta is associated with pregnancy development but not lactation status in dairy cows.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 195 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 86 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classification is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 71 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classificatoin is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 38 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
Corticosteroids are the current standard of care to improve short_term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre_treatment predictors are lacking. We developed 123_gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA_approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring_based gene expressoin risk classificatoin is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid
Publication Title
Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 4 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Understanding Natural Killer (NK) cell anatomical distribution is key to dissect the role of these unconventional lymphocytes in physiological and disease conditions. In mouse, NK cells have been detected in various lymphoid and non-lymphoid organs, while in humans the current knowledge of NK cell distribution at steady state is mainly restricted to lymphoid tissues. The translation to humans of findings obtained in mice is facilitated by the identification of NK cell markers conserved between these two species. The Natural Cytotoxicity Receptor (NCR) NKp46 is a marker of the NK cell lineage evolutionary conserved in mammals. In mice, NKp46 is also present on rare T cell subsets and on a subset of gut Innate Lymphoid Cells (ILCs) expressing the retinoic acid receptor-related orphan receptor gammat (RORgammat) transcription factor. Here, we documented the distribution and the phenotype of human NKp46+ cells in lymphoid and non-lymphoid tissues isolated from healthy donors. Human NKp46+ cells were found in splenic red pulp, in lymph nodes, in lungs and gut lamina propria, thus mirroring mouse NKp46+ cell distribution. We identified a novel cell subset of CD56dimNKp46low cells that includes RORgammat+ILCs with a lineage-CD94-CD117brightCD127bright phenotype.We also included data regarding the genome-wide transcriptional profiles of human healthy colonic NK cells and RORgammat+ILCs.The use of NKp46 thus contributes to establish the basis for analyzing quantitative and qualitative changes of NK cell and ILC subsets in human diseases.
Publication Title
Mapping of NKp46(+) Cells in Healthy Human Lymphoid and Non-Lymphoid Tissues.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 46 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.
Sample Metadata Fields
Sex, Disease, Disease stage, Treatment
View Samples- Homo sapiens
- 47 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Myc oncogenic signature in Papillary type 2b
Publication Title
Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 46 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types.
Publication Title
Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.
Sample Metadata Fields
Sex, Disease, Disease stage
View Samples