Evidence map›Paper›PMID 35733248›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Single-cell transcriptome and accessible chromatin dynamics during endocrine pancreas development.

Eliza Duvall, Cecil M Benitez, Krissie Tellez, Martin Enge, Philip T Pauerstein, Lingyu Li, Songjoon Baek, Stephen R Quake, Jason P Smith, Nathan C Sheffield and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

  1. Charting Endocrine Progenitors Across Species and Organs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Eliza DuvallLaboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892.
Cecil M BenitezDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305.
Krissie TellezDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305.ORCID 0000-0002-8892-216X
Martin EngeDepartment of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305.ORCID 0000-0001-8748-8931
Philip T PauersteinDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305.
Lingyu LiDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305.ORCID 0000-0001-6788-8620
Songjoon BaekLaboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892.ORCID 0000-0002-8452-5167
Stephen R QuakeDepartment of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305.
Jason P SmithCenter for Public Health Genomics, University of Virginia, Charlottesville, VA 22908.ORCID 0000-0002-2688-0988
Nathan C SheffieldCenter for Public Health Genomics, University of Virginia, Charlottesville, VA 22908.
Seung K KimDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305.
H Efsun ArdaLaboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892.ORCID 0000-0002-5294-2521

Funding

Identification of genomic regulatory elements in pancreas cellsZIABC011798 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ARDA, HATICE · 2018 to 2025
$10.5M
Genetic and physiologic regulation of pig islet development and functionR01DK128932 · NIDDK · STANFORD UNIVERSITY · PI BERGER, TRISH, KIM, SEUNG K · 2021 to 2024
$2.6M
In vivo systems to discover mechanisms regulating human islet alpha cell functionR01DK126482 · NIDDK · STANFORD UNIVERSITY · PI KIM, SEUNG K, MACDONALD, PATRICK · 2020 to 2023
$2.2M
A modular data analysis ecosystem using portable encapsulated projectsR35GM128636 · NIGMS · UNIVERSITY OF VIRGINIA · PI SHEFFIELD, NATHAN · 2018 to 2022
$1.9M
Intramural NIH HHS ZIA BC011798NIDDK NIH HHS R01 DK126482NIDDK NIH HHS R01 DK128932NIGMS NIH HHS R35 GM128636
6 · The paper itself

Abstract

Delineating gene regulatory networks that orchestrate cell-type specification is a continuing challenge for developmental biologists. Single-cell analyses offer opportunities to address these challenges and accelerate discovery of rare cell lineage relationships and mechanisms underlying hierarchical lineage decisions. Here, we describe the molecular analysis of mouse pancreatic endocrine cell differentiation using single-cell transcriptomics, chromatin accessibility assays coupled to genetic labeling, and cytometry-based cell purification. We uncover transcription factor networks that delineate β-, α-, and δ-cell lineages. Through genomic footprint analysis, we identify transcription factor-regulatory DNA interactions governing pancreatic cell development at unprecedented resolution. Our analysis suggests that the transcription factor Neurog3 may act as a pioneer transcription factor to specify the pancreatic endocrine lineage. These findings could improve protocols to generate replacement endocrine cells from renewable sources, like stem cells, for diabetes therapy.

Indexed as

Basic Helix-Loop-Helix ProteinsChromatinIslets of LangerhansNerve Tissue ProteinsTranscriptomeAnimalsCell DifferentiationCell LineageGene Expression Regulation, DevelopmentalMiceSingle-Cell AnalysisBasic Helix-Loop-Helix ProteinsChromatinNerve Tissue ProteinsNeurog3 protein, mouseATAC-seqNeurog3pancreasscRNA-seq

Identifiers

PMID35733248
PMCPMC9245718

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.