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accession-icon SRP148477
Single cell RNA sequencing of B cells from allergic individuals
  • organism-icon Homo sapiens
  • sample-icon 973 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

IgE antibodies mediate the symptoms of allergic reactions, yet these antibodies and the cells that produce them remain enigmatic due to their scarcity in humans. To address this, we have isolated single B cells of all isotypes, including rare IgE producing B cells, from the peripheral blood of food allergic individuals. Using single cell RNA sequencing (scRNA-seq) we have characterized the gene expression, splicing, and heavy and light chain antibody sequences of these cells.

Publication Title

High-affinity allergen-specific human antibodies cloned from single IgE B cell transcriptomes.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon SRP068021
Single cell RNAseq of electrophysiologically characterized neurons of the hippocampus
  • organism-icon Mus musculus
  • sample-icon 103 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Recent advances in single-cell RNAseq technologies are enabling new cell type classifications. For neurons, electrophysiological properties traditionally guide cell type classification but correlating RNAseq data with electrophysiological parameters has been difficult. Here we demonstrate RNAseq of electrophysiologically and synaptically characterized individual, patched neurons in the hippocampal CA1-region and subiculum, and relate the resulting transcriptome data to their electrical and synaptic properties. In this analysis, we explored the hypothesis that precise combinatorial interactions between matching cell-adhesion and signaling molecules shape synapse specificity. In analyzing interneurons and pyramidal neurons that are synaptically connected, we identified two independent, developmentally regulated networks of interacting genes encoding cell-adhesion, exocytosis and signal-transduction molecules. In this manner, our data allow postulating a presumed cell-adhesion and signaling code, which may explain neuronal connectivity at the molecular level. Our approach enables correlating electrophysiological with molecular properties of neurons, and suggests new avenues towards understanding synaptic specificity. Overall design: These data include 15 tissue samples (including 3 independent replicas in 5 developmental stages) as well as 93 single-cell samples (including CA1 cholecystokinin, parvalbumin, and pyramidal neurons as well as subiculum burst and regular firing pyramidal neurons).

Publication Title

Single-cell RNAseq reveals cell adhesion molecule profiles in electrophysiologically defined neurons.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon SRP170963
Deep single-cell RNAseq of postnatal day 7 microglia from wild type and Trem2 knockout brains
  • organism-icon Mus musculus
  • sample-icon 365 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We generated single-cell RNAseq profiles of 369 microglia (183 from wild type and 186 from Trem2 knock-out), sorted in the gate CD45lowCD11+ or CD45lowCD11+Gpnmb+Clec7a+ (PAM enrichment), to compare gene expression of wild type vs. Trem2 knock-out microglia on the postnatal day 7. Single cells were FACS index sorted from the whole brain followed by Smart-seq2 library preparation and Illumina Nextseq (sequence depth > 1 million per cell). A total of 334 cells passed quality control for data analysis. Microglia in the Trem2 knock-out contained a similar PAM population with characteristic gene expression, suggesting that the presence of early postnatal PAM do not depend on TREM2. Overall design: Single microglia were FACS sorted from male animals (C57BL/6J background) into 96-well plates. Libraries were prepared with a semi-automated Smart-seq2 protocol. Three QC criteria were used (Y=passed, N=not passed), and only cells that passed all three criteria were used for downstream analysis.

Publication Title

Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP170964
Deep single-cell RNAseq of Gpnmb+Clec7a+ microglia from postnatal day 7 cerebellum
  • organism-icon Mus musculus
  • sample-icon 143 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We generated single-cell RNAseq profiles of 143 microglia, sorted in the gate CD45lowCD11+Gpnmb+Clec7a+, from postnatal day 7 cerebellum to validate the newly identified “proliferative region-associated microglia (PAM)” (Gpnmb and Clec7a are PAM surface markers). Single cells were FACS index sorted followed by Smart-seq2 library preparation and Illumina Nextseq (sequence depth > 1 million per cell). These cells showed characteristic PAM gene expression and clustered together with other PAM cells sequenced in the same study. Overall design: Single microglia were FACS sorted from pooled male animal samples (C57BL/6N) into 96-well plates. Libraries were prepared with a semi-automated Smart-seq2 protocol. All 143 cells passed the three QC criteria (Y=passed).

Publication Title

Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP170960
Bulk RNA-seq of adult homeostatic microglia from 4 brain regions
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

To compare microglial regional heterogeneity, we generated bulk RNA-seq profiles of postnatal day 60 microglia, sorted by TMEM119+ (also CD45lowCD11b+), from cortex (CTX), cerebellum (CB), hippocampus (HIP), striatum (STR) regions. For each sample, 3000 microglia were FACS sorted into RLT lysis buffer for total RNA extraction, followed by Smart-seq library preparation and Illumina Nextseq (sequence depth 10-20 million per sample). Consistent with our scRNA-seq data, samples from 4 regions were highly correlated (R>0.99), and individual samples did not cluster according to tissue origins, suggesting striking similarities between homeostatic microglia from different brain regions. Moreover, we could not detect any differentially expressed genes (FDR < 0.05) between regions from the bulk samples. These data suggest that classical adult microglia with homeostatic signatures (e.g. Tmem119), as the most dominant microglial population in the healthy brain, have little transcriptomic heterogeneity across brain regions. Overall design: TMEM119+ microglia (3000 cells each sample) from a given region were FACS sorted from pooled male animal samples (C57BL/6N) into RLT lysis buffer in Eppendorf tubes. Three replicates were done for each region. Libraries were prepared following the Smart-seq protocol (v4 ultra low input RNA kit). All samples were barcoded and pooled together for Illumina Nextseq sequencing.

Publication Title

Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP194241
Single cell analysis of human fetal liver captures the transcriptional profile of hepatobiliary hybrid progenitors
  • organism-icon Homo sapiens
  • sample-icon 492 Downloadable Samples
  • Technology Badge Icon

Description

The liver parenchyma is composed of hepatocytes and bile duct epithelial cells (BECs). Controversy exists regarding the cellular origin of human liver parenchymal tissue generation during embryonic development, homeostasis or repair. Here we report the existence of a hepatobiliary hybrid progenitor (HHyP) population in human fetal liver using single-cell RNA sequencing. HHyPs are anatomically restricted to the ductal plate of fetal liver and maintain a unique transcriptional profile distinct from fetal hepatocytes, mature hepatocytes and mature BECs. In addition, molecular heterogenicity within the EpCAM+ population of freshly isolated fetal and adult human liver reveals diverse gene expression signatures of hepatic and biliary lineage potential. Finally, we FACS isolated fetal HHyPs and confirmed their hybrid progenitor phenotype in vivo. Our study suggests that hepatobiliary progenitor cells previously identified in mice also exist in humans, and can be distinguished from other parenchymal populations, including mature BECs, by distinct gene expression profiles. Overall design: Primary samples from 5 2nd trimester human fetal livers and 3 uninjured adult human livers for single cell RNA sequencing by Smartseq2.

Publication Title

Single cell analysis of human foetal liver captures the transcriptional profile of hepatobiliary hybrid progenitors.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP061537
Cell type-specific HITS-CLIP reveals differential RNA processing in motor neurons
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina Genome Analyzer IIx, Illumina HiSeq 1000, Illumina Genome Analyzer II

Description

We report cell type specific Nova HITS-CLIP using BAC-transgenic lines expressing GFP-Nova under the motor neuron specific choline acetyltransferase (Chat) promoter. By comparing transcriptome wide Nova binding map in motor neurons and that in the whole spinal cord, we identified differential Nova binding sites in motor neurons, which correlate with motor neuron specific RNA processing. Overall design: 14 total samples were analyzed. For HITS-CLIP, 4 biological replicates were performed for each BAC-transgenic line, as well as the whole spinal cord. For RNA-seq, 2 biological repliates were performed on the whole spinal cord.

Publication Title

Cell type-specific CLIP reveals that NOVA regulates cytoskeleton interactions in motoneurons.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-153
Transcription profiling of prop-1 and Ghrhr mutations in gene expression during normal aging in mice (Ames dwarf and Little mice)
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Effects of the prop-1 and Ghrhr mutations in gene expression during normal aging in mice.

Publication Title

Gene expression profile of long-lived Ames dwarf mice and Little mice.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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accession-icon E-MEXP-347
Transcription profiling of long-lived Ames dwarf mice investigating the loss of liver sexual dimorphism
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Gender-specific alterations in gene expression and loss of liver sexual dimorphism in the long-lived Ames dwarf mice.

Publication Title

Gender-specific alterations in gene expression and loss of liver sexual dimorphism in the long-lived Ames dwarf mice.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE20427
Characterization of hepatic gene expression during liver regeneration in response to partial hepatectomy
  • organism-icon Mus musculus
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Elevated interferon gamma signaling contributes to impaired regeneration in the aged liver.

Sample Metadata Fields

Sex, Treatment

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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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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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