Evidence map›Paper›PMID 31753917›Full record

ArticleThe Journal of biological chemistry2019

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Darren M Blackburn, Felicia Lazure, Aldo H Corchado, Theodore J Perkins, Hamed S Najafabadi, Vahab D Soleimani

Abstract read
In one paragraph

Article in The Journal of biological chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
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  3. Article
  4. Article
  5. Review
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  7. Article
  8. Epigenetic control of skeletal muscle atrophy.Cellular & molecular biology letters · 2024
    Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Transcriptional networks controlling stromal cell differentiation.Nature reviews. Molecular cell biology · 2021
    Review
  14. Cells · 2021
    Article
  15. Article
  16. Single-Cell RNAseq Analysis of lncRNAs.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  17. Article
  18. Degenerative and regenerative pathways underlying Duchenne muscular dystrophy revealed by single-nucleus RNA sequencing.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  19. Article
  20. Article
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

6 authors.

Darren M BlackburnDepartment of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada.
Felicia LazureDepartment of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada.
Aldo H CorchadoDepartment of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada.
Theodore J PerkinsSprott Center for Stem Cell Research, Ottawa Hospital Research Institute, Ottawa, Ontario K1H 8L6, Canada.
Hamed S NajafabadiDepartment of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada.
Vahab D SoleimaniDepartment of Human Genetics, McGill University, Montreal, Quebec H3A 0C7, Canada Vahab.soleimani@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber isolation with Switching Mechanism at 5' end of RNA Template (SMART) technology. Using smfRNA-Seq, we first determined the genes that are expressed in the whole muscle, including in nonmyogenic cells. We also analyzed the differences in the transcriptome of myofibers from young and old mice to validate the effectiveness of this new method. Our results suggest that aging leads to significant changes in the expression of metabolic genes, such as

Indexed as

AgingAnimalsCell SeparationGene Expression ProfilingGene LibraryGenomeMiceMuscle Fibers, SkeletalMuscle, SkeletalRNA, MessengerSequence Analysis, RNASingle-Cell AnalysisTranscriptomeRNA, Messengergene expressionmolecular biologymolecular cell biologymuscleRNASMART-Seq

Identifiers

PMID31753917
PMCPMC6937554

What OpenQuestion holds

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Registered trials

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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.