Evidence map›Paper›PMID 31815944›Full record

ArticlePLoS computational biology2019

Automated minute scale RNA-seq of pluripotent stem cell differentiation reveals early divergence of human and mouse gene expression kinetics.

Christopher Barry, Matthew T Schmitz, Cara Argus, Jennifer M Bolin, Mitchell D Probasco, Ning Leng, Bret M Duffin, John Steill, Scott Swanson, Brian E McIntosh and 4 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Epigenetic control and manipulation of neuronal maturation timing.Current opinion in genetics & development · 2024
    Review
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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

14 authors.

Christopher BarryMorgridge Institute for Research, Madison, WI, United States of America.ORCID 0000-0002-5413-5918
Matthew T SchmitzMorgridge Institute for Research, Madison, WI, United States of America.ORCID 0000-0002-6177-8161
Cara ArgusMorgridge Institute for Research, Madison, WI, United States of America.
Jennifer M BolinMorgridge Institute for Research, Madison, WI, United States of America.
Mitchell D ProbascoMorgridge Institute for Research, Madison, WI, United States of America.
Ning LengMorgridge Institute for Research, Madison, WI, United States of America.
Bret M DuffinMorgridge Institute for Research, Madison, WI, United States of America.ORCID 0000-0002-0103-0610
John SteillMorgridge Institute for Research, Madison, WI, United States of America.ORCID 0000-0003-2994-3400
Scott SwansonMorgridge Institute for Research, Madison, WI, United States of America.ORCID 0000-0002-3314-0515
Brian E McIntoshMorgridge Institute for Research, Madison, WI, United States of America.
Ron StewartMorgridge Institute for Research, Madison, WI, United States of America.
Christina KendziorskiDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States of America.
James A ThomsonMorgridge Institute for Research, Madison, WI, United States of America.
Rhonda BacherDepartment of Biostatistics, University of Florida, Gainesville, FL, United States of America.ORCID 0000-0001-5787-476X

Funding

TrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3M
Statistical methods for spatial RNA sequencing experimentsR01GM102756 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI KENDZIORSKI, CHRISTINA · 2012 to 2024
$3.8M
Human iPS/ES Cell-Based Models for Predictive Neural Toxicity and TeratogenicityUH2TR000506 · NCATS · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI THOMSON, JAMES ALEXANDER · 2012 to 2013
$2.4M
Bio-Data Science Training ProgramT32LM012413 · NLM · UNIVERSITY OF WISCONSIN-MADISON · PI DEWEY, COLIN NOEL, GOULD, MICHAEL N · 2016 to 2020
$1.5M
NCATS NIH HHS UH2 TR000506NIAID NIH HHS U54 AI117924NIGMS NIH HHS R01 GM102756NLM NIH HHS T32 LM012413
6 · The paper itself

Abstract

Pluripotent stem cells retain the developmental timing of their species of origin in vitro, an observation that suggests the existence of a cell-intrinsic developmental clock, yet the nature and machinery of the clock remain a mystery. We hypothesize that one possible component may lie in species-specific differences in the kinetics of transcriptional responses to differentiation signals. Using a liquid-handling robot, mouse and human pluripotent stem cells were exposed to identical neural differentiation conditions and sampled for RNA-sequencing at high frequency, every 4 or 10 minutes, for the first 10 hours of differentiation to test for differences in transcriptomic response rates. The majority of initial transcriptional responses occurred within a rapid window in the first minutes of differentiation for both human and mouse stem cells. Despite similarly early onsets of gene expression changes, we observed shortened and condensed gene expression patterns in mouse pluripotent stem cells compared to protracted trends in human pluripotent stem cells. Moreover, the speed at which individual genes were upregulated, as measured by the slopes of gene expression changes over time, was significantly faster in mouse compared to human cells. These results suggest that downstream transcriptomic response kinetics to signaling cues are faster in mouse versus human cells, and may offer a partial account for the vast differences in developmental rates across species.

Indexed as

AnimalsCell DifferentiationCell LineComputational BiologyGene Expression Regulation, DevelopmentalHuman Embryonic Stem CellsHumansKineticsMiceMouse Embryonic Stem CellsPluripotent Stem CellsRegenerative MedicineRNA-SeqSpecies Specificity

Identifiers

PMID31815944
PMCPMC6922475

What OpenQuestion holds

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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.