ArticleSkeletal muscle2022
High-throughput muscle fiber typing from RNA sequencing data.
Article in Skeletal muscle, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.Aging cell · 2024Pooled it
- Beyond Membrane Remodeling: Organelle Crosstalk and Convergent Pathology in Centronuclear Myopathy.Muscles (Basel, Switzerland) · 2026Review
- Transcriptomic analysis reveals the impact of concurrent, resistance, and endurance training on skeletal muscle.PloS one · 2026Article
- Long-term DNA methylation changes induced by age and elevated COSkeletal muscle · 2025Article
- Characterization of SMA type II skeletal muscle from treated patients shows OXPHOS deficiency and denervation.JCI insight · 2024Article
- Differentially co-expressed myofibre transcripts associated with abnormal myofibre proportion in chronic obstructive pulmonary disease.Journal of cachexia, sarcopenia and muscle · 2024Article
- Skeletal muscle transcriptomics dissects the pathogenesis of Friedreich's ataxia.Human molecular genetics · 2023Article
- Diversity and Differential Expression of MicroRNAs in the Human Skeletal Muscle with Distinct Fiber Type Composition.Life (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
19 authors at 10 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSkeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested.
methodsBy using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22).
resultsThe correlation between the sequencing-based method and the other two were r
conclusionsThis new method ( https://github.com/OlaHanssonLab/PredictFiberType ) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.
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Registered trials
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.