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Platform

accession-icon GSE23359
BW25113 with DNA and azlocillin
  • organism-icon Escherichia coli k-12
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

BW25113 wild type cells grown to OD = 0.8 in LB, add 2 ug/mL nalidixic acid or 10 ug/mL azlocillin for 90 min. Control was without any antibiotic.

Publication Title

Cryptic prophages help bacteria cope with adverse environments.

Sample Metadata Fields

Treatment

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accession-icon GSE19263
Identifying Y candidate genes
  • organism-icon Arabidopsis thaliana
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

The circadian clock generates biological rhythms with a period of approximately 24 hours. Using microarray experiments, we have previously shown that approximately 16% of the Arabidopsis genome is regulated in a circadian manner (Edwards et al., 2006). Previous work from our lab in modelling the molecular oscillator of Arabidopsis introduced a hypothetical component Y into an evening loop of the clock gene network (Locke et al., 2005). GIGANTEA (GI) was suggested as a strong candidate for Y based on genetic evidence and its close matching of the expression profile predicted by the mathematical modelling. Recent experimental evidence suggests that GI may only partially account for the function of Y. Thus, we are undertaking a genomics approach to identify other candidate genes that match the predicted expression profile of Y. Samples were taken from wild type and lhy cca1 double mutant seedlings from 4 timepoints around the night to day transition (-15mins, +15mins, +30mins and +60mins) after 9 days of growth in 18:6 light dark cycles. We aim to identify genes showing the light induction response predicted for Y around dawn.

Publication Title

The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops.

Sample Metadata Fields

Specimen part, Time

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accession-icon SRP064177
Transcriptional regulation by Set1 H3K4 methyltransferase and Jhd2 H3K4 demethylase
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Histone H3K4 methylation is connected to gene transcription from yeast to humans, but its mechanistic role in transcription and chromatin dynamics remains poorly understood. Here, we investigated the functions for Set1 and Jhd2, the sole H3K4 methyltransferase and H3K4 demethylase, respectively, in S. cerevisiae. Our data show that Set1 and Jhd2 predominantly co-regulate transcription. To further understand the role for H3K4 methylation, we overexpressed Flag epitope-tagged SET1-G990E (a dominant hyperactive allele of SET1) in yeast using the constitutive ADH1 promoter (ADH1p). As a control, we also overexpressed Flag epitope-tagged wild type SET1 in yeast. Analysis of gene expression in set1-null, jhd2-null and wild type SET1 or hypeactive SET1-G990E overexpressing mutants together revealed that the transcriptional regulation at a sub-set of genes, inclduing those governing glycogen metabolism and ribosome biogenesis, is highly sensitive to any change (i.e., loss or gain) in H3K4 methylation levels. Overall, we find combined activities of Set1 and Jhd2 via dynamic modulation of H3K4 methylation contribute to positive or negative transcriptional regulation at shared target genes. Overall design: Gene expression changes were generated from five different yeast strains representing wild type control, set1 null and jhd2 null mutants, and wild type SET1 or dominant hyperacive SET1-G990E overexpressing mutants. Three independent biological samples were grown for each strain, total RNA was isolated, libraries were prepared, sequenced, and analyzed separately.

Publication Title

Counteracting H3K4 methylation modulators Set1 and Jhd2 co-regulate chromatin dynamics and gene transcription.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP033135
Pseudo-temporal ordering of individual cells reveals regulators of differentiation
  • organism-icon Homo sapiens
  • sample-icon 384 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500, IlluminaHiSeq2000

Description

Single-cell expression profiling by RNA-Seq promises to exploit cell-to-cell variation in gene expression to reveal regulatory circuitry governing cell differentiation and other biological processes. Here, we describe Monocle, a novel unsupervised algorithm for ordering cells by progress through differentiation that dramatically increases temporal resolution of expression measurements. This reordering unmasks switch-like changes in expression of key regulatory factors, reveals sequentially organized waves of gene regulation, and exposes regulators of cell differentiation. A functional screen confirms that a number of these regulators dramatically alter the efficiency of myoblast differentiation, demonstrating that single-cell expression analysis with Monocle can uncover new regulators even in well-studied systems. Overall design: We selected primary human myoblasts as a model system of cell differentiation to investigate whether ordering cells by progress revealed new regulators of the process. We sequenced RNA-Seq libraries from each of several hundred cells taken over a time-course of serum-induced differentiation. Please note that this dataset is a single-cell RNA-Seq data set, and each cell comes from a capture plate. Thus, each well of the plate was scored and flagged with several QC criteria prior to library construction, which are provided as sample characteristics; CONTROL indicates that this library is a off-chip tube control library constructed from RNA of approximately 250 cells and ''DEBRIS'' indicates that the well contained visible debris (and may or may not include a cell). Libraries marked DEBRIS thus cannot be confirmed to come from a single cell.

Publication Title

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP143395
Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 134 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina Genome Analyzer IIx, Illumina HiSeq 2000

Description

Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The Assay for Transposase Accessible Chromatin (ATAC)-seq, coupled with transcription-factor motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to influence gene expression modeling.   We rigorously test our methods in the context of T Helper Cell Type  17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources (plentiful gene expression data, TF knock-outs and ChIP-seq experiments).  In this resource-rich mammalian setting our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF KO, ChIP-seq). We highlight new roles for individual TFs and groups of TFs (“TF-TF modules”) in Th17 gene regulation.  Given the popularity of ATAC-seq (a widely adapted protocol with high resolution and low sample input requirements),  we anticipate that application of our methods will improve TRN inference in new mammalian systems and be of particular use for rare, uncharacterized cell types. Overall design: Gene expression (RNA-seq) of naive and Th17- and Th0-polarized CD4 T Cells

Publication Title

Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE92994
Critical role of the transcription factors IRF1 and BATF in preparing the chromatin landscape during Type 1 regulatory cell differentiation
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Mouse Genome 430A Array (htmg430a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Critical role of IRF1 and BATF in forming chromatin landscape during type 1 regulatory cell differentiation.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon SRP095844
Critical role of the transcription factors IRF1 and BATF in preparing the chromatin landscape during Type 1 regulatory cell differentiation [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Type 1 regulatory T (Tr1) cells are induced by interleukin-27 (IL-27) and have critical roles in the control of autoimmunity and resolution of inflammation. Here, we show that the transcription factors IRF1 and BATF are induced early during treatment with IL-27 and are required for the differentiation and function of Tr1 cells in vitro and in vivo. Epigenetic and transcriptional analyses reveal that both transcription factors influence chromatin accessibility and expression of genes required for Tr1 cell function. IRF1 and BATF deficiencies uniquely alter the chromatin landscape, suggesting that these factors serve a pioneering function during Tr1 cell differentiation. Overall design: Transcriptinal analysis of IL27-induced of WT, Irf1 KO, and Batf KO cells

Publication Title

Critical role of IRF1 and BATF in forming chromatin landscape during type 1 regulatory cell differentiation.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE92940
Expression data for wildtype CD4+ T cells cells differentiated in Tr1 conditions for 2 hours
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Mouse Genome 430A Array (htmg430a)

Description

Type 1 regulatory T (Tr1) cells are induced by the interleukin-27 (IL-27) and have critical roles in the control of autoimmunity and resolution of inflammation. Here, we show that the transcription factors IRF1 and BATF are induced early during treatment with IL-27 and are required for the differentiation and function of Tr1 cells in vitro and in vivo . Epigenetic and transcriptional analyses reveal that both transcription factors influence chromatin accessibility and expression of genes required for Tr1 cell function. IRF1 and BATF deficiencies uniquely alter the chromatin landscape, suggesting that these factors serve a pioneering function during Tr1 cell differentiation.

Publication Title

Critical role of IRF1 and BATF in forming chromatin landscape during type 1 regulatory cell differentiation.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE81964
Norrin-dependent gene expression in murine cerebellar granule neuron progenitors and Patched medulloblastoma
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Norrin/Frizzled4 signalling in the preneoplastic niche blocks medulloblastoma initiation.

Sample Metadata Fields

Specimen part

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accession-icon GSE81962
Norrin-dependent gene expression in cerebellar granule neuron progenitors
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Medulloblastoma (MB), a tumor of the cerebellum, is the most common malignant brain tumor in children. One third of all human MB exhibits a gene expression signature of Sonic hedgehog (Shh) signaling. Hedgehog (Hh) pathway inhibitors have shown efficacy in clinical trials for MB, however, tumors develop resistance to these compounds, highlighting the need to identify additional therapeutic targets for treatment. We have identified a role for Norrin signaling in tumor initiation in the Patched (Ptch) mouse model of MB. Norrin is a secreted factor that functions as an atypical Wnt by binding to the Frizzled4 (Fzd4) receptor on endothelial cells to activate canonical beta-catenin-mediated Wnt signaling pathway. In the cerebellum, activation of Norrin/Fzd4 signaling is required for the establishment and maintenance of the blood brain barrier (BBB). We have identified a role for Norrin signaling in the stroma as a potent tumor inhibitory signal. Inactivation of Norrin in Ptch+/- mice significantly shortens latency and increases MB incidence. This phenotype is associated with an increased frequency of pre-tumor lesions and their conversion to malignancy. In this context, loss of Norrin signalling in endothelial cells is associated with an accelerated transition to a pro-tumor stroma characterized by vascular permeability, inflammation and angiogenic remodelling. Accordingly, loss of Ndp significantly alters the stromal gene expression signature of established Ptch MB.

Publication Title

Norrin/Frizzled4 signalling in the preneoplastic niche blocks medulloblastoma initiation.

Sample Metadata Fields

Specimen part

View Samples

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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