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accession-icon SRP007823
Dynamic Transformations of Genome-wide Epigenetic Marking and Transcriptional Control Establish T Cell Identity [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

T cell development comprises a stepwise process of commitment from a multipotent precursor. To define molecular mechanisms controlling this progression, we probed five stages spanning the commitment process using deep sequencing RNA-seq and ChIP-seq methods to track genome-wide shifts in transcription, cohorts of active transcription factor genes, histone modifications at diverse classes of cis-regulatory elements, and binding patterns of GATA-3 and PU.1, transcription factors with complementary roles in T-cell development. The results locate potential promoter-distal cis-elements in play and reveal both activation sites and diverse mechanisms of repression that silence genes used in alternative lineages. Histone marking is dynamic and reversible, and while permissive marks anticipate, repressive marks often lag behind changes in transcription. In vivo binding of PU.1 and GATA-3 relative to epigenetic marking reveals distinctive, factor-specific rules for recruitment of these crucial transcription factors to different subsets of their potential sites, dependent on dose and developmental context. Overall design: Genome-wide expression profiles, global distributions of three different histone modifications, and global occupancies of two transcription factors were examined in five developmentally related immature T populations. High throughput sequencing generated on average 9-30 million of mappable reads (single-read) for each ChIP-seq sample, and 10-15 million (single-read) for RNA-seq. Independent biological replicates were analyzed for individual populations. Terminology: FLDN1_RNA-seq_sample1 and FLDN1_RNA-seq_sample2 are independent biological replicates for the same cell type.

Publication Title

Dynamic transformations of genome-wide epigenetic marking and transcriptional control establish T cell identity.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP071547
Dynamic gene regulatory networks of human myeloid differentiation [RNA-seq]
  • organism-icon Homo sapiens
  • sample-icon 96 Downloadable Samples
  • Technology Badge IconNextSeq500

Description

We utilize gene expression and open chromatin footprinting data to build a gene regulatory network of key transcription factors that capture the cell and time-specific regulatory programs specified during human myeloid differentiation. Overall design: RNA-seq profiling of undifferentiated HL-60, differentiating macrophage, neutrophil, monocyte, and monocyte-derived macrophage cells.

Publication Title

Dynamic Gene Regulatory Networks of Human Myeloid Differentiation.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP092251
Integrative analysis of single-cell ATAC-seq and RNA-seq using Self-Organizing Maps [scRNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 568 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We have developed a computational approach that uses self-organizing maps for integrative genomic analysis. We utilize this approach to identify the single-cell chromatin and transcriptomic profiles during mouse pre-B cell differentiation. Overall design: We use the C1 Fluidigm system to profile gene expression and chromatin accessibility in single-cells during pre-B cell differentiation.

Publication Title

Building gene regulatory networks from scATAC-seq and scRNA-seq using Linked Self Organizing Maps.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP072875
Single-nucleus RNA-seq on undifferentiated human KD3 myoblasts and differentiated myotubes and mononucleated cells.
  • organism-icon Homo sapiens
  • sample-icon 253 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We report the application of single-nucleus-based sequencing technology for high-throughput profiling of transcriptome in immortazalized human myoblast KD3. By obtaining over sixty billion bases of sequence from mRNA, we generated comprehensive transcriptome profiles from KD3 undifferentiated myoblast and differentiated multi-nucleated myotube and mono-nucleated cells. We find that the data from single-nucleus RNA-seq is consistent with the transcriptome from single-cell RNA-seq. The pri-mRNA expression characterized by single-nucleus RNA-seq can reflect the actual miRNA level in the whole cell. Overall design: Examination of transcriptome in 1 cell type in 3 differential stages.

Publication Title

Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity.

Sample Metadata Fields

Subject

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accession-icon GSE71668
Expression data from TCF7L1 Over-expression during primitive streak-like differentiation in H9 human embryonic stem cells
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We used microarray analysis to profile the function of TCF7L1 in human embryonic stem cells.

Publication Title

TCF7L1 suppresses primitive streak gene expression to support human embryonic stem cell pluripotency.

Sample Metadata Fields

Cell line

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accession-icon GSE69911
Expression data from TCF7L1 siRNA knockdown in H9 human embryonic stem cells
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We used microarray analysis to profile the function of TCF7L1 in human embryonic stem cells.

Publication Title

TCF7L1 suppresses primitive streak gene expression to support human embryonic stem cell pluripotency.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP092099
BCL11B AND COMBINATORIAL RESOLUTION OF CELL FATE IN THE T-CELL GENE REGULATORY NETWORK
  • organism-icon Mus musculus
  • sample-icon 45 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We report the RNA-seq results from mouse T-cell precursors in different developmental stages including DN1, DN2a, DN2b, DN3 and DP in order to study the gene regulation network in T cell development. Some of the samples also have certain kind of perturbations, such as Bcl11b knockout and the treatment of Notch signaling pathway inhibitor GSI, in order to study the roles of these factors in T cell development. Overall design: Examine the transcriptome of 47 mouse T-cell precursor samples from five developmental stages (DN1, DN2a, DN2b, DN3 and DP). Among them, 19 have Bcl11b knockout and 4 have GSI treatment.

Publication Title

Bcl11b and combinatorial resolution of cell fate in the T-cell gene regulatory network.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP097094
Role of Microglial C5aR1 in the Arctic Alzheimer's Disease Mouse Model
  • organism-icon Mus musculus
  • sample-icon 31 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

C5aR1, a receptor for the complement activation proinflammatory fragment, C5a, is primarily expressed on cells of the myeloid lineage, and to a lesser extent on endothelial cells and neurons in brain. Previous work demonstrated C5aR1 antagonist, PMX205, decreased amyloid pathology and suppressed cognitive deficits in Alzheimer Disease (AD) mouse models. In the Arctic AD mouse model, genetic deletion of C5aR1 prevented behavior deficits at 10 months. However, the molecular mechanisms of this protection has not been definitively demonstrated. To understand the role of microglial C5aR1 in the Arctic AD mouse model, we have taken advantage of the CX3CR1GFP and CCR2RFP reporter mice to distinguish microglia as GFP-positive and infiltrating monocytes as GFP and RFP positive, for subsequent transcriptome analysis on specifically sorted myeloid populations from wild type and AD mouse models. Immunohistochemical analysis of mice aged to 2, 5, 7 and 10 months showed no change in amyloid beta (Ab) deposition in the Arctic C5aR1 knockout (KO) mice relative to that seen in the Arctic mice. Of importance, no CCR2+ monocytes/macrophages were found near the plaques in the Arctic brain with or without C5aR1. RNA-seq analysis on microglia from these mice identified inflammation related genes as differentially expressed, with increased expression in the Arctic mice relative to wildtype and decreased expression in the Arctic/C5aR1KO relative to Arctic. In addition, phagosomal-lysosomal proteins and protein degradation pathways that were increased in the Arctic mice were further increased in the Arctic/C5aR1KO mice. These data are consistent with a microglial polarization state with restricted induction of inflammatory genes and enhancement of clearance pathways. Overall design: Microglia mRNA profiles of wildtype (WT), C5aR1 knockout (C5aR1KO), Arctic (ARC) and Arctic C5aR1 knockout (ARCKO) mice at 2, 5, 7 and 10-11 month. Duplicates were sequenced for each genotype on Illumina HiSeq 2500 platform.

Publication Title

Prevention of C5aR1 signaling delays microglial inflammatory polarization, favors clearance pathways and suppresses cognitive loss.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon GSE52244
Exon-expression profiling of CD4+ T cells derived from HTLV-1-infected individuals with or without malignancy
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

T-cell clones were obtained by limiting dilution culture of PBMC of HTLV-1 carriers. Exon expression profiling was performed using Affymetrix exon array (Affymetrix Human Exon 1.0 ST Array) according to the manufacturer's instructions. Gene version of CEL files 01 to 12 are presented in GSE46518.

Publication Title

HTLV-1-infected CD4+ T-cells display alternative exon usages that culminate in adult T-cell leukemia.

Sample Metadata Fields

Specimen part

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accession-icon SRP092075
Generation of human microglia-like cells to study neurological disease
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Microglia play important roles in developmental and homeostatic brain function, and influence the establishment and progression of many neurological disorders. Here, we demonstrate that renewable human iPSCs can be efficiently differentiated to microglial-like cells (iMGL) to study neurological diseases, such as Alzheimer''s disease (AD). We find that iMGLs develop in vitro similarly to microglia in vivo and whole transcriptome analysis demonstrates that they are highly similar to adult and fetal human microglia. Functional assessment of iMGLs reveal that they secrete cytokines in response to inflammatory stimuli, migrate and undergo calcium transients, and robustly phagocytose CNS substrates. We also show novel use of iMGLs to examine the effects of fibrillar Aß and brain-derived tau oligomers on AD-related gene expression and to interrogate mechanisms involved in synaptic pruning. Taken together, these findings demonstrate that iMGLs can be used in high-throughput studies of microglial function, providing important new insight into human neurological disease. Overall design: Human cells were collected and analyzed for gene expression using RNA-seq.

Publication Title

iPSC-Derived Human Microglia-like Cells to Study Neurological Diseases.

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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