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accession-icon SRP042961
X-chromosome dynamics revealed by the RNA interactome and chromosomal binding of CTCF
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon

Description

CTCF is a master regulator that plays a role in genome architecture and gene expression. A key aspect of CTCF’s mechanism involves bringing together distant genetic elements for intra- and inter-chromosomal interactions. Evidence from epigenetic processes, such as X-chromosome inactivation (XCI), suggests that CTCF may carry out its functions through interacting RNAs. Using genome-wide approaches to investigate the relationship between CTCF’s RNA interactome and its epigenomic landscape, here we report that CTCF interacts with thousands of transcripts in mouse embryonic stem cells (mESC), many in close proximity to CTCF’s genomic binding sites. Biochemical analysis demonstrates that CTCF is a high-affinity RNA binding protein that contacts RNA directly and specifically. In the XCI model, CTCF binds the active and inactive X-chromosomes allele-specifically. At the X-inactivation center, Tsix RNA binds CTCF and targets CTCF to a region associated with X-chromosome pairing. Our work implicates CTCF-RNA interactions in long-range chromosomal interactions in trans and adds a new layer of complexity to CTCF regulation. The genome-wide datasets reported here will provide a useful resource for further study of CTCF-mediated epigenomic regulation. Overall design: CTCF RNA interactome was identified by UV-crosslinking and immunoprecipitation followed by high-throughput sequencing (CLIP-seq), and was compared to CTCF''s epigenomic landscape as obtained by chromatin immunoprecipitation (ChIP-seq).

Publication Title

Locus-specific targeting to the X chromosome revealed by the RNA interactome of CTCF.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP026035
RNA-seq analysis of global RNA levels at 4 stages of directed cardiac differentiation of mouse embryonic stem cells
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

We interrogated the transcriptome using RNA-seq at several stages of an mouse embryonic stem cell to cardiomyocyte directed differentiation protocol. These four stages represent timepoints when differentiating cultures are enriched for embryonic stem cells (ESC), mesodermal cells (MES), cardiac precursors (CP), or cardiomyocytes (CM) respectively. This study revealed many dynamic patterns of mRNAs and long non-coding RNAs (lncRNAs) and identified groups of genes with similar expression patterns during differentiation. Overall design: RNA-seq analysis of global RNA levels at 4 stages of directed cardiac differentiation of mouse embryonic stem cells. Each stage in biological duplicates

Publication Title

Dynamic and coordinated epigenetic regulation of developmental transitions in the cardiac lineage.

Sample Metadata Fields

Specimen part, Cell line, Subject, Time

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accession-icon SRP135927
Efficient generation of human CA3 neurons and modeling hippocampal neuronal connectivity in vitro (single cells)
  • organism-icon Homo sapiens
  • sample-icon 507 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Despite widespread interest in using human stem cells in neurological disease modeling, a suitable model system to study human neuronal connectivity is lacking. Here, we report a protocol for efficient differentiation of hippocampal pyramidal neurons and an in vitro model for hippocampal neuronal connectivity. We developed an embryonic stem cell (ESC)- and induced pluripotent stem cell (iPSC)-based protocol to differentiate human CA3 pyramidal neurons from patterned hippocampal neural progenitor cells (NPCs). This differentiation induces a comprehensive patterning and generates multiple CA3 neuronal subtypes. The differentiated CA3 neurons are functionally active and readily form neuronal connection with dentate granule (DG) neurons in vitro, recapitulating the synaptic connectivity within the hippocampus. When we applied this neuronal co-culture approach to study connectivity in schizophrenia, we found deficits in spontaneous activity in patient iPSC derived DG–CA3 co-culture by multi-electrode array recording. In addition, both multi-electrode array recording and whole cell patch clamp electrophysiology revealed a reduction in spontaneous and evoked neuronal activity in CA3 neurons derived from schizophrenia patients. Altogether these results underscore the relevance of this new model in studying diseases with hippocampal vulnerability. Overall design: 4 technical replicates were used and later pooled together for the bioinformatic analysis.

Publication Title

Efficient Generation of CA3 Neurons from Human Pluripotent Stem Cells Enables Modeling of Hippocampal Connectivity In Vitro.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP068706
RNA-sequencing of single whole cells and nuclei from mouse dentate granule cells
  • organism-icon Mus musculus
  • sample-icon 201 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully re-capitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc, and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes . In addition, we observe a continuum of activation states, revealing a pseudo-temporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs,allowing for novel insights into neuronal activation patterns in vivo. Overall design: Examination of 1) 82 whole-cell (WC) dentate granule cells from a PTZ- or saline-treated mouse, and 2) 23 single-nuclei (SN) from dentate granule cells of a homecage (HC) mouse or 96 nuclei from a mouse exposed to a novel environment (NE)

Publication Title

Nuclear RNA-seq of single neurons reveals molecular signatures of activation.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon SRP117757
RNA sequencing of Foxd1Cre;Smo(flox/-) mutant kidneys
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: To analyze the mRNA content of Foxd1Cre;Smo(flox/-) mutant kidneys. Methods: We collected E13.5 wildtype and Foxd1Cre;Smo(flox/-) mutant kidneys and isolated RNA to do RNA-Seq. Results: Identified differentially expressed transcripts in Foxd1Cre;Smo(flox/-) mutant kidneys compared to wildtype controls. Conclusions: Our work provides novel insight into how Hedgehog signaling from stromal cells influences renal development. Overall design: RNA sequencing of Foxd1Cre;Smo(flox/-) mutant kidneys compared to controls.

Publication Title

Hedgehog-GLI signaling in <i>Foxd1-</i>positive stromal cells promotes murine nephrogenesis via TGFβ signaling.

Sample Metadata Fields

Specimen part, Subject

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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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