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accession-icon GSE11843
RNA species bound by deiminated and non-deiminated MA-Brent-1 (bhatt-affy-mouse-581641)
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We have identified loss of deiminated MA-Brent-1 (an RNA and export binding protein) in the retinal ganglion cells (RGCs) in multiple sclerosis and in glaucoma eyes compared to normal controls. Deimination refers to posttranslational modification of protein bound arginine (not free arginine) in citrulline. Our preliminary studies suggest binding of different repertoire of RNA by non-deiminated and deiminated MA-Brent-1. In vitro, in neurites of cultured RGCs and hippocampal neurons, the select mRNA translation is enhanced by addition of deiminated but not non-deiminated MA-Brent-1. These observations suggest that lack of deiminated MA-Brent-1 has consequences for protein synthesis, remodeling and plasticity of RGCs/neurons. Identification of RNA species bound by deiminated and non-deiminated MA-Brent-1 will enable us there further verification and determining the role that deimination plays in biological function of MA-Brent-1 in multiple sclerosis and glaucoma. To summarize identification of RNA species bound by deiminated and non deiminated MA-Brent-1 will enable us to gain further insight into role of deimination in the overall disease process.

Publication Title

The role of deimination in ATP5b mRNA transport in a transgenic mouse model of multiple sclerosis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE114469
Expression data from NPY Y1R-deficient osteoblastic cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

NPY signalling via osteoblastic Y1 receptors has been shown to control bone mass but also contributes significantly to the control of whole-body insulin secretion and glucose homeostasis in mice through the release of novel factor(s) which are different from the previously implicated osteocalcin.

Publication Title

Osteoglycin, a novel coordinator of bone and glucose homeostasis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP052978
Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and cardiac-specific Bmi1 deletion [human]
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

To explore the primary cause of Dilated Cardiomyopathy in heart samples from DCM-diagnosed patients who had undergone heart transplant (hDCM), we set out to identify differentially expressed genes by massively parallel sequencing of heart samples. Overall design: Methods: Heart mRNA profiles from DCM-diagnosed patients who had undergone heart transplant (hDCM) were generated by deep sequencing, in triplicate, using Illumina GAIIx.

Publication Title

Bmi1 limits dilated cardiomyopathy and heart failure by inhibiting cardiac senescence.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP051396
Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and cardiac-specific Bmi1 deletion [mouse]
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

To explore the primary cause of Dilated Cardiomyopathy in Bmi1-null mice, we set out to identify differentially expressed genes by massively parallel sequencing of heart samples from Bmi1f/f;aMHCTM-Cretg/+ mice versus aMHCTM-Cretg/+ control mice (17 weeks postinduction). Overall design: Methods: Heart mRNA profiles of 17-weeks post-induction Bmi1f/f; MHCTM-Cretg/+ mice and MHCTM-Cretg/+ control mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. Sequence reads were pre-processed with Cutadapt 1.2.1, to remove TruSeq adapters and mapped on the mouse transcriptome (Ensembl gene-build GRCm38.v70) using RSEM v1.2.3. The Bioconductor package EdgeR was used to normalize data with TMM and to test for differential expression of genes using GLM.

Publication Title

Bmi1 limits dilated cardiomyopathy and heart failure by inhibiting cardiac senescence.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP069726
CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Analysis of chromatin architecture suggests that the 3D structure of the genome plays a major role in regulating gene expression, orchestrating the compartmentalization of chromatin and facilitating specific enhancer-promoter interactions. However, the mechanisms that control this structuring of the genome are not fully understood. We have addressed this issue by analyzing the role of CTCF, a major architectural factor in chromatin structure, in the embryonic heart. Loss of CTCF triggered an overall downregulation of the cardiac developmental program, suggesting that CTCF facilitates enhancer-promoter interactions in the developing heart. Detailed analysis of the IrxA gene cluster showed that CTCF loss leads to disruption of the heart-specific regulatory domain that surrounds Irx4, resulting in changes in expression of IrxA cluster genes and neighboring genes. In contrast to the critical role proposed for CTCF in organizing large-scale chromatin domains, our results show that CTCF preferentially mediates local regulatory interactions. Overall design: RNAseq of mouse embryonic E10.5 hearts in three conditions: 1) control (labeled as WT), 2) heterozygous (labeled as HET) and 3) homozygous (labeled as KO). Three replicates were performed for each condition, each consisting of a pool of 6 hearts. Tissue was mechanically disaggregated and RNA extracted with trizol and purified through columns.

Publication Title

CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP045046
Transcriptome profiling of developing photoreceptor subtypes reveals candidate genes for avian photoreceptor diversification
  • organism-icon Gallus gallus
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: Avian photoreceptors are a diverse class of neurons, comprised of four single cones, the two members of the double cone, and rods. Many distinctive features of photoreceptor subtypes, including spectral tuning, oil droplet size and pigmentation, synaptic targets and spatial patterning, have been well characterized, but the molecular mechanisms underlying these attributes have not been explored. Furthermore, the signaling events and transcriptional regulators driving the differentiation of these diverse photoreceptors are currently unknown. Methods: To identify genes specifically expressed in distinct chicken (Gallus gallus) photoreceptor subtypes, we developed fluorescent reporters that label photoreceptor subpopulations, isolated these subpopulations using fluorescence-activated cell sorting, subjected them to next-generation sequencing, and conducted differential expression analysis. Results: We identified hundreds of differentially expressed genes from photoreceptor subpopulations labeled with rhodopsin, red opsin, green opsin, and violet opsin reporters. These genes are involved in a variety of processes, including phototransduction, transcriptional regulation, cell adhesion, maintenance of intra- and extra-cellular structure, and metabolism. Of particular note are a variety of differentially expressed transcription factors, which may drive and maintain photoreceptor diversity, and cell adhesion molecules that may mediate spatial patterning of photoreceptors and act to establish retinal circuitry. Conclusions: These analyses provide a framework for future studies that will dissect the role of these various factors in the differentiation of avian photoreceptor subtypes. Overall design: mRNA expression profiling of 5 pairs of photoreceptor subtypes isolated from chicken retinal explants, 3 replicates per sample

Publication Title

Transcriptome profiling of developing photoreceptor subtypes reveals candidate genes involved in avian photoreceptor diversification.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE4201
Zebrafish microRNA miR-430 promotes deadenylation and clearance of maternal mRNAs
  • organism-icon Danio rerio
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Zebrafish Genome Array (zebrafish)

Description

MicroRNAs comprise 1-3% of all vertebrate genes, but their in vivo functions and mechanisms of action remain largely unknown. Zebrafish miR-430 is expressed at the onset of zygotic transcription and regulates morphogenesis during early development. Using a microarray approach and in vivo target validation, we find that miR-430 directly regulates several hundred target mRNAs. Targets are highly enriched for maternal mRNAs that accumulate in the absence of miR-430. We also show that miR-430 accelerates the deadenylation of target mRNAs. These results suggest that miR-430 facilitates the deadenylation and clearance of maternal mRNAs during early embryogenesis.

Publication Title

Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP023533
Integrated analysis of microRNA and mRNA expression and association with HIF binding in MCF-7 cells under hypoxia (miRNA-Seq)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Purpose: We aimed to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression. Methods: microRNA sequencing data and gene expression microarray data were generated from MCF-7 cells submitted to an hypoxia timecourse (16h, 32h and 48h at 1% Oxygen). Data was integrated to 500 published high-stringency HIF binding sites identified in MCF-7 cells. Results: We identified 41 microRNAs significantly up- and 28 down- regulated, of which 38 mature and 20 star forms are reported in conjunction with hypoxia for the first time. HIF-1a and HIF-2a binding sites within 50kb distance of microRNA loci were found by integration of HIF ChIP-seq data, showing overall association between binding sites and up-regulation. Gene expression profiling analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts playing a role in microRNA processing were found regulated by hypoxia, of which two were HIF dependent. Conclusions: The data support the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level. HIF is involved at both levels, regulating the transcription of certain microRNAs and also the expression of key elements of the microRNA processing pathway. Overall design: microRNA-seq profiles of MCF-7 exposed to hypoxia (1% Oxygen) for 16h (2 replicates), 32h (2 replicates) and 48h (2 replicates) and to normoxia (2 replicates) were generated using Illumina sequencing platform.

Publication Title

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

Sample Metadata Fields

Cell line, Treatment, Subject, Time

View Samples
accession-icon SRP047192
Quantitative profiling of long noncoding RNAs with targeted RNA sequencing.
  • organism-icon Homo sapiens
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We compared the performance of conventional RNAseq with RNA Capture Sequencing (CaptureSeq) to assemble and quantify known RNA spike-Ins and human transcripts. We find CaptureSeq to be superior for the detection and quantification of the 37% lowest expressed genes, and comparable for the next 45% of moderately expressed genes. CaptureSeq contributes only minor technical variation and measures differential gene expression accurately. We demonstrate these advantages by the targeted sequencing of long noncoding RNAs across 20 human tissues, expanding previous annotations two-fold and simultaneously generating a quantitative atlas of expression. This analysis confirms the use of CaptureSeq as an important method for transcriptional profiling. Overall design: Long noncoding RNA assembly and expression is analysed by targeted RNA sequencing for 20 human tissues and 4 human cell lines

Publication Title

Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18155
Malignant Germ Cell Tumors Display Common microRNA Profiles Resulting in Global Changes in Expression of mRNA Targets
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Comparison of miRNA expression profiles in malignant germ cell tumors compared to non-malignant control group.

Publication Title

Malignant germ cell tumors display common microRNA profiles resulting in global changes in expression of messenger RNA targets.

Sample Metadata Fields

Sex, Age

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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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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