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Record W2975061401 · doi:10.1371/journal.pone.0222946

Gene expression profiling of skeletal myogenesis in human embryonic stem cells reveals a potential cascade of transcription factors regulating stages of myogenesis, including quiescent/activated satellite cell-like gene expression

2019· article· en· W2975061401 on OpenAlexafffund
Michael Shelton, Morten Ritso, Daniel O’Neil, Avetik Kocharyan, Michael A. Rudnicki, William L. Stanford, Ilona S. Skerjanc, Alexandre Blais

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of HealthOntario Institute for Regenerative MedicineCanada Research ChairsUniversity of OttawaStem Cell NetworkCanadian Institutes of Health ResearchCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaMuscular Dystrophy Association
KeywordsMyogenesisBiologyEmbryonic stem cellCell biologyGene expressionGene expression profilingTranscription factorRegulation of gene expressionGeneStem cellGenetics

Abstract

fetched live from OpenAlex

Human embryonic stem cell (hESC)-derived skeletal muscle progenitors (SMP)-defined as PAX7-expressing cells with myogenic potential-can provide an abundant source of donor material for muscle stem cell therapy. As in vitro myogenesis is decoupled from in vivo timing and 3D-embryo structure, it is important to characterize what stage or type of muscle is modeled in culture. Here, gene expression profiling is analyzed in hESCs over a 50 day skeletal myogenesis protocol and compared to datasets of other hESC-derived skeletal muscle and adult murine satellite cells. Furthermore, day 2 cultures differentiated with high or lower concentrations of CHIR99021, a GSK3A/GSK3B inhibitor, were contrasted. Expression profiling of the 50 day time course identified successively expressed gene subsets involved in mesoderm/paraxial mesoderm induction, somitogenesis, and skeletal muscle commitment/formation which could be regulated by a putative cascade of transcription factors. Initiating differentiation with higher CHIR99021 concentrations significantly increased expression of MSGN1 and TGFB-superfamily genes, notably NODAL, resulting in enhanced paraxial mesoderm and reduced ectoderm/neuronal gene expression. Comparison to adult satellite cells revealed that genes expressed in 50-day cultures correlated better with those expressed by quiescent or early activated satellite cells, which have the greatest therapeutic potential. Day 50 cultures were similar to other hESC-derived skeletal muscle and both expressed known and novel SMP surface proteins. Overall, a putative cascade of transcription factors has been identified which regulates four stages of myogenesis. Subsets of these factors were upregulated by high CHIR99021 or their binding sites were significantly over-represented during SMP activation, ranging from quiescent to late-activated stages. This analysis serves as a resource to further study the progression of in vitro skeletal myogenesis and could be mined to identify novel markers of pluripotent-derived SMPs or regulatory transcription/growth factors. Finally, 50-day hESC-derived SMPs appear similar to quiescent/early activated satellite cells, suggesting they possess therapeutic potential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.238
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2019
Admission routes2
Has abstractyes

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