Evidence map›Paper›PMID 32459995›Full record

ArticleCell stem cell2020

A Multiplexed Barcodelet Single-Cell RNA-Seq Approach Elucidates Combinatorial Signaling Pathways that Drive ESC Differentiation.

Grace Hui Ting Yeo, Lin Lin, Celine Yueyue Qi, Minsun Cha, David K Gifford, Richard I Sherwood

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell stem cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

13 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. iScience · 2024
    Article
  8. Models of Congenital Adrenal Hyperplasia for Gene Therapies Testing.International journal of molecular sciences · 2023
    Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Using CRISPR to understand and manipulate gene regulation.Development (Cambridge, England) · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Grace Hui Ting YeoDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Lin LinDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Hubrecht Institute, 3584 CT Utrecht, the Netherlands.
Celine Yueyue QiDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Minsun ChaDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
David K GiffordDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: gifford@mit.edu.
Richard I SherwoodDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Hubrecht Institute, 3584 CT Utrecht, the Netherlands. Electronic address: rsherwood@rics.bwh.harvard.edu.
Harvard University · USMassachusetts Institute of Technology · USBrigham and Women's Hospital · US

Funding

Transcriptional Regulation of Stem Cell Differentiation into Motor NeuronsP01NS055923 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GIFFORD, DAVID K · 2006 to 2010
$6.6M
High-Throughput Native Context Mapping and Modeling of Regulatory DNAR01HG008754 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GIFFORD, DAVID K · 2016 to 2019
$2.7M
High-throughput methods for elucidating the control of chromatin accessibilityR01HG008363 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GIFFORD, DAVID K · 2015 to 2017
$2.3M
Distal enhancers controlling motor neuron gene expression programR01NS109217 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WICHTERLE, HYNEK · 2019 to 2022
$2.1M
Predictive transcription factor modeling to program endodermal cell fatesK01DK101684 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI SHERWOOD, RICHARD I · 2014 to 2018
$670k
Systematic unlocking of airway stem cell differentiation programR21OD025309 · OD · BRIGHAM AND WOMEN'S HOSPITAL · PI SHERWOOD, RICHARD I · 2019 to 2020
$462k
NHGRI NIH HHS R01 HG008363NHGRI NIH HHS R01 HG008754NIDDK NIH HHS K01 DK101684NIH HHS R21 OD025309NINDS NIH HHS P01 NS055923NINDS NIH HHS R01 NS109217
6 · The paper itself

Abstract

Empirical optimization of stem cell differentiation protocols is time consuming, is laborintensive, and typically does not comprehensively interrogate all relevant signaling pathways. Here we describe barcodelet single-cell RNA sequencing (barRNA-seq), which enables systematic exploration of cellular perturbations by tagging individual cells with RNA "barcodelets" to identify them on the basis of the treatments they receive. We apply barRNA-seq to simultaneously manipulate up to seven developmental pathways and study effects on embryonic stem cell (ESC) germ layer specification and mesodermal specification, uncovering combinatorial effects of signaling pathway activation on gene expression. We further develop a data-driven framework for identifying combinatorial signaling perturbations that drive cells toward specific fates, including several annotated in an existing scRNA-seq gastrulation atlas, and use this approach to guide ESC differentiation into a notochord-like population. We expect that barRNA-seq will have broad utility for investigating and understanding how cooperative signaling pathways drive cell fate acquisition.

Indexed as

Embryonic Stem CellsSignal TransductionCell DifferentiationGerm LayersRNA-SeqSingle-Cell Analysiscomputational modelingdirected differentiationembryonic developmentembryonic stem cellsingle cell RNA-seq

Identifiers

PMID32459995
PMCPMC7398619
OpenAlexW3029625958

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.