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accession-icon GSE134807
Etv1 controls the establishment of non-overlapping motor innervation of neighboring facial muscles during development
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The motor neurons innervating the muscles of facial expression are organized into somatotopic hindbrain clusters termed subnuclei. Each of the medial, intermediate, dorsolateral, and lateral subnuclei gives rise to a specific branch of the facial motor nerve (cranial nerve VII). How subnucleus-specific gene expression could mediate the accurate development of facial nerve projections was not well understood.

Publication Title

Etv1 Controls the Establishment of Non-overlapping Motor Innervation of Neighboring Facial Muscles during Development.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE45483
HMGA1: A master regulator of tumor progression in triple-negative breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Emerging evidence suggests that tumor cells metastasize by co-opting stem cell transcriptional networks, although the molecular underpinnings of this process are poorly understood. Here, we show for the first time that the high mobility group A1 (HMGA1) gene drives metastatic progression in triple negative breast cancer cells (MDA-MB-231) by reprogramming cancer cells to a stem-like state. We discovered an HMGA1 signature in triple negative breast cancer cells that is highly enriched in embryonic stem cells. Together, these findings indicate that HMGA1 is a master regulator of tumor progression in breast cancer by reprogramming cancer cells through stem cell transcriptional networks. Future studies are needed to determine how to target HMGA1 in therapy.

Publication Title

HMGA1: a master regulator of tumor progression in triple-negative breast cancer cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE34788
Genomic signatures of a global fitness index in a multi-ethnic cohort of women
  • organism-icon Homo sapiens
  • sample-icon 119 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The rates of obesity and sedentary lifestyle are on a dramatic incline, with associated detrimental health effects among women in particular. Although exercise prescriptions are useful for overcoming these problems, success can be hampered by differential responsiveness among individuals in cardiovascular fitness indices (i.e., improvements in strength, lipids, VO2max). Genetic factors appear to play an important role in determining this inter-individual variation in responsiveness. We performed microarray analyses on mRNA in whole blood from 60 sedentary women from a multi-ethnic cohort who underwent 12 weeks of exercise, to identify gene subsets that were differentially expressed between individuals who experienced the greatest and least improvements in fitness based upon a composite fitness score index. We identified 43 transcripts in 39 unique genes (FDR<10%; FC>1.5) whose expression increased the most in high versus low premenopausal female responders. Several (TIGD7, UQCRH, PSMA6, WDR12, TFB2M, USP15) have reported associations with fitness-related phenotypes. Bioinformatic analysis of the 39 genes identified 4 miRNAs whose expression has been linked to cardiovascular diseases (ANKRD22: miR-637, LRRFIP1: miR-132, PRKAR2B: miR-92a, RSAD2:miR-192). These 39 genes were enriched in 6 biological pathways, including the oxidative phosphorylation pathway (p=8.08 x 10-3). Two genes, LRRFIP1 and SNORD30, were also identified with lower expression in high responding postmenopausal women. In summary, we identified gene signatures based on mRNA analysis that define responsiveness to exercise in a largely minority-based female cohort. Importantly, this study validates several genes/pathways previously associated with exercise responsiveness and extends these findings with additional novel genes.

Publication Title

Genomic signatures of a global fitness index in a multi-ethnic cohort of women.

Sample Metadata Fields

Sex, Race, Time

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accession-icon GSE16849
preparative changes in rat intestine and lung for birth
  • organism-icon Rattus norvegicus
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

To identify genes important in fetal preparation for birth.

Publication Title

Developmental control of the Nlrp6 inflammasome and a substrate, IL-18, in mammalian intestine.

Sample Metadata Fields

Specimen part

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accession-icon SRP094496
Correlating anatomy and function with gene expression in individual neurons by combining in vivo labeling, patch clamp and single cell RNA-seq
  • organism-icon Mus musculus
  • sample-icon 1692 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 4000

Description

The classification of neurons into distinct types is an ongoing effort aimed at revealing and understanding the diversity of the components of the nervous system. Recently available methods allow us to determine the gene expression pattern of individual neurons in the mammalian cerebral cortex to generate powerful categorization schemes. For a thorough understanding of neuronal diversity such genetic categorization schemes need to be combined with traditional classification parameters like position, axonal projection or response properties to sensory stimulation. Here we describe a method to link the gene expression of individual neurons with their position, axonal projection or sensory response properties. Neurons are labeled in vivo based on their anatomical or functional properties and, using patch clamp pipettes, their RNA individually harvested in vitro for RNAseq. With this method we can determine the genetic expression pattern of functionally and anatomically identified individual neurons. Overall design: single cortical neurons were patch clamped and the RNA harvested; single neuron mRNA profiles were generated by deep sequencing

Publication Title

Correlating Anatomy and Function with Gene Expression in Individual Neurons by Combining <i>in Vivo</i> Labeling, Patch Clamp, and Single Cell RNA-seq.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE16192
Unexpected expression of alpha- and beta-globin in mesencephalic dopaminergic neurons and glial cells
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

The mesencephalic dopaminergic (mDA) cell system is composed by two major groups of projecting cells in the Substantia Nigra (A9 neurons) and the Ventral Tegmental Area (A10 cells). A9 neurons form the nigrostriatal pathway and are involved in regulating voluntary movements and postural reflexes. Their selective degeneration leads to Parkinsons disease (PD). We used cDNA microarrays and nanoCAGE technology coupled with Laser Capture Microdissection (LCM) to characterize the intrinsic physiological properties of A9 DA neurons. Surprisingly, we found that these cells express alpha- and beta- chains of haemoglobin. Here we report that globin-immunoreactivity decorates the majority of A9 DA neurons, a subpopulation of cortical and hippocampal astrocytes as well as mature oligodendrocytes. This pattern of expression was confirmed in different mouse strains, in rat and human. This is the first report showing that haemoglobin is expressed in the Substantia Nigra of human post mortem brain. Our data suggest that the most famed oxygen-carrying globin is not exclusively restricted to the blood, but it may play a role in the normal physiology of the brain as well as in neurodegenerative disorders.

Publication Title

Unexpected expression of alpha- and beta-globin in mesencephalic dopaminergic neurons and glial cells.

Sample Metadata Fields

Cell line

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accession-icon GSE13901
Treatment of human monocyte-derived dendritic cells with Saccaromyces cerevisiae in exponential growth phase
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

In vitro experiment of stimulation of monocyte-derived dendritic cells with Saccaromyces cerevisiae in exponential growth phase. This experiment was performed to verify the comparability of microarray

Publication Title

Using pathway signatures as means of identifying similarities among microarray experiments.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE67838
Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE67826
Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition [mRNA]
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Treatment of leukemia cells with 1,25-dihydroxyvitamin D3 may overcome their differentiation block and lead to the transition from myeloblasts to monocytes. To identify microRNA-mRNA networks relevant for myeloid differentiation, we profiled the expression of mRNAs and microRNAs associated to the low- and high-density ribosomal fractions in leukemic cells and in their differentiated monocytic counterpart. Intersection between mRNAs shifted across the fractions after treatment with putative target genes of modulated microRNAs showed a series of molecular networks relevant for the monocyte cell fate determination

Publication Title

Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE107497
Genomic analysis for hematopoietic stem and progenitors cells (HSPC) generated in vitro according to ex vivo expansion protocols and their comparison with HSPC obtained fresh
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Expansion for hematopoietic cells from umbilical cord blood is a strategy for use this cell source in clinic transplants, however, it is important to know about the genomic changes that can occur in expanded cells. In order to detect global expression profiles changes in hematopoietic stem and progenitors cells generated in vitro, we analyzed hematopoietics populations obtained by FACS in fresh from umbilical cord blood. HSC (fHSC) was defined as CD34+ CD38- CD71- CD45RA- Lin- and were cocultured with stromal cell line OP-9 plus FL, SCF, IL3, IL6, TPO, GMCSF and G-CSF by 7 days, after time we repurified HSC population by FACS using same immunophenotype (ivHSC). In other hand, fresh erythroid progenitors cells (fEPC) were identified as CD34+CD38+CD71+CD45RA- Lin- and fresh myeloid progenitors cells (fMPC) were identified as CD34+CD38+CD71-CD45RA+Lin-. In vitro progenitors cells (ivEPC and ivMPC) were obtained by culturing fHSC in Stemspan serum-free media plus SCF, TPO, IL6, FL and IL3 by 10 days, after time cells were repurified by FACS using same immunophenotype for fresh progenitors. In vitro generated cells were compared with their corresponding fresh population cells.

Publication Title

Functional Integrity and Gene Expression Profiles of Human Cord Blood-Derived Hematopoietic Stem and Progenitor Cells Generated In Vitro.

Sample Metadata Fields

Specimen part

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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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