Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
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GROUP CONDITION SAMPLES
Human CD31-CD45-CD107
GSM4473088 GSM4473089 GSM4473090
GSM4473091 GSM4473092 GSM4473093
Description

Submission Date: Apr 12, 2020

Summary: The tunica adventitia of vessels within adipose tissue (AT) represents a heterogenous microanatomical niche for multipotent mesenchymal precursor cells. To investigate this heterogeneity, cell surface antibody array among CD34+ human adventicytes identified 13 novel antigens enriched within perivascular mesenchyme, including the endolysomal associated protein CD107a (LAMP1). Membranous CD107a can be used to divide perivascular / adventitial precursor cells into functional relevant subsets. CD107alow cells from human AT demonstrated high colony forming efficiency, osteoprogenitor cell frequency, and osteogenic potential. Conversely, CD107ahigh cells demonstrated heightened adipoprogenitor cell frequency and adipogenic potential. Knockdown experiments did not identity a functional role for CD107a in osteo/adipogenic differentiation. Instead, CD107a protein trafficking to the cell surface was associated with exocytosis during early adipogenic differentiation. Bulk and single cell RNA Sequencing suggested that CD107alow cells represent a precursor population for CD107ahigh cells. Functional roles for CD107alow/high subsets were confirmed in transplantation experiments. Intramuscular transplantation of CD107alow cells yielded increased bone formation in comparison to their CD107ahigh counterparts. Further, CD107alow cells induced spine fusion whereas their CD107ahigh counterparts did not. In sum, cell surface CD107a in mesenchymal progenitors correlates with exocytosis during early adipogenesis, and can be used to divide osteo- from adipogenic progenitor cells within human fat tissue.

GEO Accession ID: GSE148519

PMID: 33044169

Description

Submission Date: Apr 12, 2020

Summary: The tunica adventitia of vessels within adipose tissue (AT) represents a heterogenous microanatomical niche for multipotent mesenchymal precursor cells. To investigate this heterogeneity, cell surface antibody array among CD34+ human adventicytes identified 13 novel antigens enriched within perivascular mesenchyme, including the endolysomal associated protein CD107a (LAMP1). Membranous CD107a can be used to divide perivascular / adventitial precursor cells into functional relevant subsets. CD107alow cells from human AT demonstrated high colony forming efficiency, osteoprogenitor cell frequency, and osteogenic potential. Conversely, CD107ahigh cells demonstrated heightened adipoprogenitor cell frequency and adipogenic potential. Knockdown experiments did not identity a functional role for CD107a in osteo/adipogenic differentiation. Instead, CD107a protein trafficking to the cell surface was associated with exocytosis during early adipogenic differentiation. Bulk and single cell RNA Sequencing suggested that CD107alow cells represent a precursor population for CD107ahigh cells. Functional roles for CD107alow/high subsets were confirmed in transplantation experiments. Intramuscular transplantation of CD107alow cells yielded increased bone formation in comparison to their CD107ahigh counterparts. Further, CD107alow cells induced spine fusion whereas their CD107ahigh counterparts did not. In sum, cell surface CD107a in mesenchymal progenitors correlates with exocytosis during early adipogenesis, and can be used to divide osteo- from adipogenic progenitor cells within human fat tissue.

GEO Accession ID: GSE148519

PMID: 33044169

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

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Perturbation Condition

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Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.