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accession-icon GSE43524
Microarray analysis of wildtype, Klf8gt/gt, Klf3-/- and Klf3-/- Klf8gt/gt TER119+ E13.5 fetal liver cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The aim of this experiment was to investigate the regulation of gene expression by KLF3 and KLF8 in fetal erythroid cells by analyzing single and double mutant mouse models.

Publication Title

Generation of mice deficient in both KLF3/BKLF and KLF8 reveals a genetic interaction and a role for these factors in embryonic globin gene silencing.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE34652
KGF effects on cutaneous SCC cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Keratinocyte growth factor (KGF, fibroblast growth factor-7) is a fibroblast-derived mitogen, which stimulates proliferation of epithelial cells. The expression of KGF by dermal fibroblasts is induced following injury and it promotes wound repair. However, the role of KGF in cutaneous carcinogenesis and cancer progression is not known. We have examined the role of KGF in progression of squamous cell carcinoma (SCC) of the skin.

Publication Title

Keratinocyte growth factor induces gene expression signature associated with suppression of malignant phenotype of cutaneous squamous carcinoma cells.

Sample Metadata Fields

Specimen part, Disease

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accession-icon SRP156532
Human lineage tracing enabled by mitochondrial mutations and single cell genomics [TF1_barcoding_scRNA]
  • organism-icon Homo sapiens
  • sample-icon 172 Downloadable Samples
  • Technology Badge Icon

Description

Lineage tracing provides unprecedented insights into the fate of individual cells and their progeny in complex organisms. While effective genetic approaches have been developed in vitro and in animal models, these cannot be used to interrogate human physiology in vivo. Instead, naturally occurring somatic mutations have been utilized to infer clonality and lineal relationships between cells in human tissues, but current approaches are limited by high error rates and scale, and provide little information about the state or function of the cells. Here, we show how somatic mutations in mitochondrial DNA (mtDNA) can be tracked by current single cell RNA-Seq (scRNA-Seq) or single cell ATAC-Seq (scATAC-Seq) for simultaneous analysis of single cell lineage and state. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their use as clonal markers to infer lineal relationships. We trace the lineage of human cells by somatic mtDNA mutations in a native context both in vitro and in vivo, and relate it to expression profiles and chromatin accessibility. Our approach should allow lineage tracing at a 100- to 1,000-fold greater scale than with single cell whole genome sequencing, while providing information on cell state, opening the way to chart detailed cell lineage and fate maps in human health and disease. Overall design: A population of 25 transfected TF1 cells were expanded and forwarded to a combination of 1) ATAC-seq and single cell RNA-seq. The single-cell RNA-seq data are listed here. Meta data includes heteroplasmic variant information per cell as well as the group assigned based on the lentiviral barcoding

Publication Title

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP149545
Human lineage tracing enabled by mitochondrial mutations and single cell genomics [CC100_scRNA]
  • organism-icon Homo sapiens
  • sample-icon 135 Downloadable Samples
  • Technology Badge Icon

Description

Lineage tracing provides unprecedented insights into the fate of individual cells and their progeny in complex organisms. While effective genetic approaches have been developed in vitro and in animal models, these cannot be used to interrogate human physiology in vivo. Instead, naturally occurring somatic mutations have been utilized to infer clonality and lineal relationships between cells in human tissues, but current approaches are limited by high error rates and scale, and provide little information about the state or function of the cells. Here, we show how somatic mutations in mitochondrial DNA (mtDNA) can be tracked by current single cell RNA-Seq (scRNA-Seq) or single cell ATAC-Seq (scATAC-Seq) for simultaneous analysis of single cell lineage and state. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their use as clonal markers to infer lineal relationships. We trace the lineage of human cells by somatic mtDNA mutations in a native context both in vitro and in vivo, and relate it to expression profiles and chromatin accessibility. Our approach should allow lineage tracing at a 100- to 1,000-fold greater scale than with single cell whole genome sequencing, while providing information on cell state, opening the way to chart detailed cell lineage and fate maps in human health and disease. A variety of experimental designs using cells derived from both in vitro and in vivo to determine the efficacy of using mtDNA mutations in human clonal tracing. Overall design: A population of 30 primary hematopoietic cells were expanded and forwarded to a combination of ATAC-seq and single cell RNA-seq. single cell RNA-seq samples are listed here.

Publication Title

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP149535
Human lineage tracing enabled by mitochondrial mutations and single cell genomics [TF1_clones_scRNA]
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Lineage tracing provides unprecedented insights into the fate of individual cells and their progeny in complex organisms. While effective genetic approaches have been developed in vitro and in animal models, these cannot be used to interrogate human physiology in vivo. Instead, naturally occurring somatic mutations have been utilized to infer clonality and lineal relationships between cells in human tissues, but current approaches are limited by high error rates and scale, and provide little information about the state or function of the cells. Here, we show how somatic mutations in mitochondrial DNA (mtDNA) can be tracked by current single cell RNA-Seq (scRNA-Seq) or single cell ATAC-Seq (scATAC-Seq) for simultaneous analysis of single cell lineage and state. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their use as clonal markers to infer lineal relationships. We trace the lineage of human cells by somatic mtDNA mutations in a native context both in vitro and in vivo, and relate it to expression profiles and chromatin accessibility. Our approach should allow lineage tracing at a 100- to 1,000-fold greater scale than with single cell whole genome sequencing, while providing information on cell state, opening the way to chart detailed cell lineage and fate maps in human health and disease. A variety of experimental designs using cells derived from both in vitro and in vivo to determine the efficacy of using mtDNA mutations in human clonal tracing. Overall design: Individually sorted cells from clonally derived TF1 clones (C9, D6, and G10) were processed with single cell RNA-seq (Smart-seq2)

Publication Title

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP149538
Human lineage tracing enabled by mitochondrial mutations and single cell genomics [TF1_clones_RNA]
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Lineage tracing provides unprecedented insights into the fate of individual cells and their progeny in complex organisms. While effective genetic approaches have been developed in vitro and in animal models, these cannot be used to interrogate human physiology in vivo. Instead, naturally occurring somatic mutations have been utilized to infer clonality and lineal relationships between cells in human tissues, but current approaches are limited by high error rates and scale, and provide little information about the state or function of the cells. Here, we show how somatic mutations in mitochondrial DNA (mtDNA) can be tracked by current single cell RNA-Seq (scRNA-Seq) or single cell ATAC-Seq (scATAC-Seq) for simultaneous analysis of single cell lineage and state. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their use as clonal markers to infer lineal relationships. We trace the lineage of human cells by somatic mtDNA mutations in a native context both in vitro and in vivo, and relate it to expression profiles and chromatin accessibility. Our approach should allow lineage tracing at a 100- to 1,000-fold greater scale than with single cell whole genome sequencing, while providing information on cell state, opening the way to chart detailed cell lineage and fate maps in human health and disease. A variety of experimental designs using cells derived from both in vitro and in vivo to determine the efficacy of using mtDNA mutations in human clonal tracing. Overall design: Cells from 3 separate TF1 clones (C9, D6, and G10) were processed with bulk RNA-seq (Smart-seq2)

Publication Title

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP067963
Transcriptome profiling of post-mature green seeds from Arabidopsis ddcc mutant and wild-type
  • organism-icon Arabidopsis thaliana
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The role of on-CG methylation in seed development and dormancy remains unknown. There are four genes in charge of non-CG methylation in Arabidopsis: drm1, drm2, cmt2 and cmt3. The majority of non-CG methylation in vegetative tissues, leaf, is gone in homozygous ddcc mutant line (Hume et al., 2014). To uncover the possible role of non-CG DNA methylation in seed development and dormancy, we characterized the transcriptome of ddcc mutant in Arabidopsis post-mature green seeds using Illumina sequencing. Meanwhile, post-mature green seeds from wild type were used as control. Overall design: Illumina sequencing of transcripts from post-mature green seeds of ddcc mutant and wild type. Two biological replicates were collected.

Publication Title

Similarity between soybean and <i>Arabidopsis</i> seed methylomes and loss of non-CG methylation does not affect seed development.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP104167
Western diet triggers NLRP3-dependent persistent functional reprogramming of myeloid cells [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Here we investigated whether sterile triggers of inflammation  induce trained immunity and thereby influence innate immune responses. Western diet (WD) feeding of Ldlr-/- mice induced systemic inflammation, which was undectable in serum soon after mice were shifted back to chow diet (CD). In contrast, myeloid cell responses towards innate stimuli remained broadly augmented. WD induced transcriptomic and epigenomic reprogramming of myeloid progenitor cells, leading to increased proliferation as well as enhanced innate immune and interferon responses towards in vivo LPS challenge. QTL analysis in human monocytes trained with oxidized low-density lipoprotein (oxLDL) and stimulated with LPS suggested inflammasome-mediated trained immunity. Consistently, Nlrp3-/-/Ldlr-/--deficient mice lacked WD-induced systemic inflammation or myeloid progenitor proliferation and reprogramming. Hence, NLRP3 mediates trained immunity following WD and could thereby arbitrate the potentially deleterious effects of trained immunity in inflammatory diseases. Overall design: Examination of GMPs in six different conditions by RNA-seq

Publication Title

Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP124807
Western diet triggers NLRP3-dependent persistent functional reprogramming of myeloid cells II [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Here we investigated whether sterile triggers of inflammation  induce trained immunity and thereby influence innate immune responses. Western diet (WD) feeding of Ldlr-/- mice induced systemic inflammation, which was undectable in serum soon after mice were shifted back to chow diet (CD). In contrast, myeloid cell responses towards innate stimuli remained broadly augmented. WD induced transcriptomic and epigenomic reprogramming of myeloid progenitor cells, leading to increased proliferation as well as enhanced innate immune and interferon responses towards in vivo LPS challenge. QTL analysis in human monocytes trained with oxidized low-density lipoprotein (oxLDL) and stimulated with LPS suggested inflammasome-mediated trained immunity. Consistently, Nlrp3-/-/Ldlr-/--deficient mice lacked WD-induced systemic inflammation or myeloid progenitor proliferation and reprogramming. Hence, NLRP3 mediates trained immunity following WD and could thereby arbitrate the potentially deleterious effects of trained immunity in inflammatory diseases. Overall design: Examination of GMPs in six different conditions by RNA-seq

Publication Title

Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP067454
Myc-dependent gene activation and repression in oncogene-addicted liver tumors (RNA-seq)
  • organism-icon Mus musculus
  • sample-icon 43 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Tumors driven by activation of the transcription factor Myc generally show oncogene addiction. However, the gene-expression programs that depend upon sustained Myc activity in those tumors remain unknown. We have addressed this issue in a model of liver carcinoma driven by a reversible tet-Myc transgene, combining gene expression profiling with the mapping of Myc and RNA Polymerase II on chromatin. Switching off the oncogene in advanced carcinomas revealed that Myc is required for the continuous activation and repression of distinct sets of genes, constituting no more than half of those deregulated during tumor progression, and an even smaller subset of all Myc-bound genes. We further showed that a Myc mutant unable to associate with the co-repressor protein Miz1 is defective in the initiation of liver tumorigenesis. Altogether, our data provide the first detailed analysis of a Myc-dependent transcriptional program in a fully developed carcinoma, revealing that the critical effectors of Myc in tumor maintenance must be included within defined subsets (ca. 1,300 each) of activated and repressed genes. Overall design: RNAseq samples of control liver (n=11), tet-Myc tumors (n=16), tet-Myc tumors with short-term Myc inactivation (n=8), tet-MycVD tumors (n=11)

Publication Title

Identification of MYC-Dependent Transcriptional Programs in Oncogene-Addicted Liver Tumors.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
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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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