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accession-icon SRP024394
Drosophila midgut regional gene expression
  • organism-icon Drosophila melanogaster
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We found that the midgut shows striking regional differentiation along its anterior-posterior axis. Ten distinct subregions differ in cell morphology, gene expression and aspects of Notch signaling. RNA from isolated regions that was analyzed by RNAseq revealed spatially regulated expression of hundreds of enzymes and other genes with likely tissue functions. Overall design: 10 midgut segments comprising from 1-3 subregions x 3 replicates from each segment = 30 samples

Publication Title

Physiological and stem cell compartmentalization within the Drosophila midgut.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE10889
Expression Profiling of the Developing Mouse Lung
  • organism-icon Mus musculus
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine 11K SubA Array (mu11ksuba)

Description

Mammalian lung development is a complex morphogenetic process, which initiates near mid-gestation and continues through early postnatal life. The lung arises as two lateral buds that emerge from the ventral foregut endoderm at ~ 9 days after fertilization (in mouse) and undergo numerous rounds of dichotomous branching to form the bronchial tree. This stage of development is referred to as the pseudoglandular phase, histologically characterized by loose mesenchyme surrounding undifferentiated epithelial tubes.

Publication Title

Expression profiling of the developing mouse lung: insights into the establishment of the extracellular matrix.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE15452
Expression data from lung of mice bearing mutations of FGFR3 and FGFR4
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Gene expression profiling of newborn lung tissue revealed few changes in compound FGFR3/FGFR4 deficient mice, consistent with their normal lung morphology at birth, suggesting the sequence of events leading to the phenotype initiates after birth in this model.

Publication Title

Fibroblast growth factor receptors control epithelial-mesenchymal interactions necessary for alveolar elastogenesis.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE7475
Inflammatory response to titanium dioxide particles exposure is enhanced during pregnancy
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Rationale: Maternal immune responses can promote allergy development in offspring. Pilot data show that neonates of mother mice exposed during pregnancy to air pollution particles have increased allergic susceptibility. Objective: We investigated whether inflammatory response to titanium dioxide (TiO2) particles earlier considered immunologically inert is enhanced during pregnancy. Methods: Pregnant BALB/c mice (or non-pregnant controls) received particle suspensions intranasally at day 14 of pregnancy. Lung inflammatory responses were evaluated 19 and 48 h after exposure. Results: Pregnant mice showed robust and persistent acute inflammatory responses after exposure to TiO2, while non-pregnant females had the expected minimal responses. Genomic profiling identified genes differentially expressed in pregnant lungs exposed to TiO2. Neonates of mothers exposed to TiO2 (but not PBS) developed increased susceptibility to allergens. Conclusion: Pregnancy enhances lung inflammatory responses to otherwise relatively innocuous inert particles.

Publication Title

Pulmonary exposure to particles during pregnancy causes increased neonatal asthma susceptibility.

Sample Metadata Fields

Sex

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accession-icon GSE105826
Targeting CDK6 and BCL2 exploits the "MYB Addiction" of Ph+ acute lymphoblastic leukemia
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Transcriptome analysis of two Ph+ acute lymphoblastic leukemia cell lines after doxycycline induced silencing of MYB.

Publication Title

Targeting CDK6 and BCL2 Exploits the "MYB Addiction" of Ph<sup>+</sup> Acute Lymphoblastic Leukemia.

Sample Metadata Fields

Cell line

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accession-icon GSE8581
Human Chronic Obstructive Pulmonary Disorder (COPD) Biomarker
  • organism-icon Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease with complex pathological features and largely unknown etiologies. Identification and validation of biomarkers for this disease could facilitate earlier diagnosis, appreciation of disease subtypes and/or determination of response to therapeutic intervention. To identify gene expression markers for COPD, we performed genome-wide expression profiling of lung tissue from 56 subjects using the Affymetrix U133 Plus 2.0 array. Lung function measurements from these subjects ranged from normal, un-obstructed to severely obstructed. Analysis of differential expression between cases (FEV1<70%, FEV1/FVC<0.7) and controls (FEV1>80%, FEV1/FVC>0.7) identified a set of 65 probe sets representing discrete markers associated with COPD. Correlation of gene expression with quantitative measures of airflow obstruction (FEV1 or FEV1/FVC) identified a set of 220 probe sets. A total of 31 probe sets were identified that showed evidence of significant correlation with quantitative traits and differential expression between cases and controls.

Publication Title

Molecular biomarkers for quantitative and discrete COPD phenotypes.

Sample Metadata Fields

Race

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accession-icon SRP079368
TADs emerge as a functionally, but not structurally privileged scale in the hierarchical folding of chromosomes
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Understanding how regulatory sequences interact in the context of chromosomal architecture is a central challenge in biology. Chromosome conformation capture revealed that mammalian chromosomes possess a rich hierarchy of structural layers, from multi-megabase compartments to sub-megabase topologically associating domains (TADs), and further down to sub-TAD loop domains. TADs appear to act as regulatory microenvironments by constraining and segregating regulatory interactions across discrete chromosomal regions. However, it is unclear whether other (or all) folding layers share similar properties, or rather TADs constitute a privileged folding scale with maximal impact on the organization of regulatory interactions. Here we present a novel parameter-free algorithm (CaTCH) that identifies hierarchical trees of chromosomal domains in Hi-C maps, stratified through their reciprocal physical insulation which is a simple and biologically relevant property. By applying CaTCH to published Hi-C datasets, we show that previously reported folding layers appear at different insulation levels. We demonstrate that although no structurally privileged folding level exists, TADs emerge as a functionally privileged scale defined by maximal enrichment of CTCF at boundaries, and maximal cell-type conservation. By measuring transcriptional output in embryonic stem cells and neural precursor cells, we show that TADs also maximize the likelihood that genes in a domain are co-regulated during differentiation. Finally, we observe that regulatory sequences occur at genomic locations corresponding to optimized mutual interactions at the scale of TADs. Our analysis thus suggests that the architectural functionality of TADs arises from the interplay between their ability to partition interactions and the genomic position of regulatory sequences. Overall design: The hybrid mouse ESC line F1-21.6 (129Sv-Cast/EiJ), previously described in (Jonkers et al., 2009), were grown on mitomycin C-inactivated MEFs in ES cell media containing 15% FBS (Gibco), 10-4 M b-mercaptoethanol (Sigma), and 1000U/ml of leukaemia inhibitory factor (LIF, Chemicon). Mouse ES cells were differentiated into neural progenitor cells (NPC) as previously described (Conti et al., 2005; Splinter et al., 2011). Total RNAs were prepared by Trizol extraction from the mouse ESC line, and for one NPC clone derived from it. Two biological replicates were collected for ESCs and NPCs. After ribosomal RNA depletion with Ribo-Zero (Illumina), RNA-seq libraries were prepared using ScriptSeq v2 kit (Illumina) following the manufacturer’s instructions. Libraries were prepared in two technical replicates per biological replicate. 50 bp single-end sequencing was performed on Illumina HiSeq 2000 instruments according to manufacturer’s instructions.

Publication Title

Reciprocal insulation analysis of Hi-C data shows that TADs represent a functionally but not structurally privileged scale in the hierarchical folding of chromosomes.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP174924
Proteasome inhibitor-induced modulation reveals the spliceosome as a specific therapeutic vulnerability in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000, Illumina HiSeq 2000

Description

Resistance to proteasome inhibitors (PIs) is a ubiquitous clinical concern in multiple myeloma (MM). We proposed that signaling-level responses after PI would reveal new means to enhance efficacy. Unbiased phosphoproteomics after the PI carfilzomib surprisingly demonstrated the most prominent phosphorylation changes on spliceosome components. Spliceosome modulation was invisible to RNA or protein abundance alone. Transcriptome analysis demonstrated broad-scale intron retention suggestive of PI-specific splicing interference. Direct spliceosome inhibition synergized with carfilzomib and showed potent anti-myeloma activity. Functional genomics and exome sequencing further supported the spliceosome as a specific vulnerabilityin myeloma. Our results propose splicing interference as an unrecognized modality of PI mechanism, reveal additional modes of spliceosome modulation, and suggest spliceosome targeting as a promising therapeutic strategy in myeloma. Overall design: We examine 1) gene expression of MM cells in response to PI and 2)alternative splicing in response to PI and comparator chemotherapeutic compound. We further investigate splice factor mechanism in MM cells, by examining alternative splicing in MM with overexpression of wild type and mutant splice factor, SRSF1

Publication Title

Proteasome inhibitor-induced modulation reveals the spliceosome as a specific therapeutic vulnerability in multiple myeloma.

Sample Metadata Fields

Cell line, Subject, Compound, Time

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accession-icon GSE78947
HCT116 gene expression analysis upon CAF stimulation
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

HCT116 colon carcinoma cells invade more the basement membrane when carcinoma-associated fibroblasts (CAFs) are present. In order to identify if CAFs induce an invasive phenotype to HCT116 cells, and therefore regulate genes expression related to invasion, we compared gene expression of HCT116 cells cultured alone or in the presence of CAFs.

Publication Title

Cancer-associated fibroblasts induce metalloprotease-independent cancer cell invasion of the basement membrane.

Sample Metadata Fields

Disease, Cell line

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accession-icon GSE14334
Transcriptomic analysis of human lung development
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We decompose the genome-wide expression patterns in 38 embryonic human lung (53-154 days post conception/dpc) into their independent, dominant directions of transcriptomic sample variation in order togain global insight of the developing human lung transcriptome.The characteristic genes and their corresponding bioontologic attribute profile for the latter were identified. We noted the overrepresentation of lung specific attributes (e.g., surfactant proteins) traditionally associated with later developmental stages, and highly ranked attributes (e.g., chemokineimmunologic processes) not previously reported nor immediately apparent in an early lung development context. We defined the 3,223gene union of the characteristic genes of the 3 most dominant sources of variation as the developing lung characteristic subtranscriptome (DLCS). It may be regarded as the minimal gene set describing the essential biology of this process. The developing lung series in this transcriptomic variation perspectiveform a contiguous trajectory with critical time points that both correlate with the 2 traditional morphologic stages overlapping -154 dpc and suggest the existence of 2 novel phases within the pseudoglandular stage. To demonstrate that this characterization is robust, we showed that the model could be used to estimate the gestational age of independent human lung tissue samples with a median absolute error of 5 days, based on the DLCS of their lung profile alone. Repeating this procedure on the homologous transcriptome profiles of developing mouse lung 1419 dpc, we were able to recover their correct developmental chronology.

Publication Title

Transcriptomic analysis of human lung development.

Sample Metadata Fields

Sex, Disease, Race

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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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