Evidence map›Paper›PMID 37328521›Full record

ArticleScientific data2023

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Jiehan Li, Christopher Jin, Stefan Gustafsson, Abhiram Rao, Martin Wabitsch, Chong Y Park, Thomas Quertermous, Joshua W Knowles, Ewa Bielczyk-Maczynska

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Anti-obesity peptides from food: Production, evaluation, sources, and commercialization.Comprehensive reviews in food science and food safety · 2025
    Review
  8. Loss ofbioRxiv : the preprint server for biology · 2024
    Article
  9. Article
4 · The record

Corrections and comments

  • Update of
    2023
5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Jiehan Li *Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Christopher Jin *Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Stefan GustafssonClinical Epidemiology Unit, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Abhiram RaoDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Martin WabitschDepartment of Pediatrics and Adolescent Medicine, Center for Rare Endocrine Diseases, Division of Pediatric Endocrinology and Diabetes, Ulm University Medical Centre, Ulm, 89075, Germany.ORCID 0000-0001-6795-8430
Chong Y ParkDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Thomas QuertermousDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Joshua W KnowlesDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA. knowlej@stanford.edu.
Ewa Bielczyk-MaczynskaDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA. ewabm@stanford.edu.
Cardiovascular Institute of the South · USStanford University · USUppsala University · SE

Funding

Stanford Islet Research CoreP30DK116074 · NIDDK · STANFORD UNIVERSITY · PI Seung K Kim · 2017 to 2026
$19.5M
Stanford Center for Connecting DNA Variants to Function and PhenotypeUM1HG011972 · NHGRI · STANFORD UNIVERSITY · PI JESSE M ENGREITZ, THOMAS QUERTERMOUS · 2021 to 2026
$10.5M
Causal variant association mechanisms in TCF21 binding coronary disease lociR01HL134817 · NHLBI · STANFORD UNIVERSITY · PI THOMAS QUERTERMOUS · 2017 to 2026
$6.2M
The SMAD3 signaling network in coronary artery disease riskR01HL139478 · NHLBI · STANFORD UNIVERSITY · PI THOMAS QUERTERMOUS · 2018 to 2026
$3.7M
Characterization of novel insulin resistance genes by gene editing, high-throughput phenotyping and in vivo studiesR01DK120565 · NIDDK · STANFORD UNIVERSITY · PI KNOWLES, JOSHUA WILEY · 2019 to 2023
$3.2M
PDGFD regulates a transcriptional network to modulate smooth muscle cell transition and coronary artery disease riskR01HL156846 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2021 to 2024
$2.7M
Identifying tobacco-genetic interactions through study of the aryl hydrocarbon receptor pathway.R01HL151535 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2021 to 2024
$2.7M
Mechanisms of NAT2 Regulation of Insulin Resistance and Mitochondrial DysfunctionR01DK116750 · NIDDK · STANFORD UNIVERSITY · PI KNOWLES, JOSHUA WILEY · 2019 to 2023
$2.4M
Beyond GWAS of insulin resistance: An integrated approach to translate genetic association to functionR01DK106236 · NIDDK · STANFORD UNIVERSITY · PI KNOWLES, JOSHUA WILEY · 2016 to 2020
$2.4M
Molecular Mechanisms of Insulin Resistance Associated LociR01DK107437 · NIDDK · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2016 to 2019
$2.2M
LncRNA Transcriptional Mechanisms of Coronary Artery Disease RiskR01HL145708 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2019 to 2022
$1.6M
American Heart Association-American Stroke Association 18POST34030448NHGRI NIH HHS UM1 HG011972NHLBI NIH HHS R01 HL134817NHLBI NIH HHS R01 HL139478NHLBI NIH HHS R01 HL145708NHLBI NIH HHS R01 HL151535NHLBI NIH HHS R01 HL156846NIDDK NIH HHS P30 DK116074NIDDK NIH HHS R01 DK106236NIDDK NIH HHS R01 DK107437NIDDK NIH HHS R01 DK116750NIDDK NIH HHS R01 DK120565
6 · The paper itself

Abstract

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on these widely used in vitro models of human and mouse adipogenesis, and on cell-to-cell variability during this process.

Indexed as

AdipogenesisSingle-Cell Gene Expression AnalysisTranscriptomeAdipocytesAdipose TissueAnimalsCell DifferentiationHumansMice

Identifiers

PMID37328521
PMCPMC10275883
OpenAlexW4380992854

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.