A mixed-effects model of the dynamic response of muscle gene transcript expression to endurance exercise.

Altered expression of a broad range of gene transcripts after exercise reflects the specific adjustment of skeletal muscle makeup to endurance training. Towards a quantitative understanding of this molecular regulation, we aimed to build a mixed-effects model of the dynamics of co-related transcript...

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Publicado en:European Journal of Applied Physiology Vol. 113; no. 5; pp. 1279 - 1291
Autores principales: Busso, Thierry, Flück, Martin
Formato: research Journal Article
Publicado: Springer Nature May2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2013
      vid: 113
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00421-012-2547-x
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        atl: A mixed-effects model of the dynamic response of muscle gene transcript expression to endurance exercise.
      aug:
        au:
          Busso, Thierry
          Flück, Martin
        affil: Laboratoire de Physiologie de l'Exercice, Université de Lyon, Saint-Etienne, France, busso@univ-st-etienne.fr.
      sug:
        subj:
          Exercise
          Models, Biological
          Muscle, Skeletal Metabolism
          RNA
          Adult
          Gene Expression Profiling
          Male
          Oligonucleotide Array Sequence Analysis
          Time Factors
          Human
          Adult: 19-44 years
          Male
      ab: Altered expression of a broad range of gene transcripts after exercise reflects the specific adjustment of skeletal muscle makeup to endurance training. Towards a quantitative understanding of this molecular regulation, we aimed to build a mixed-effects model of the dynamics of co-related transcript responses to exercise. It was built on the assumption that transcript levels after exercise varied because of changes in the balance between transcript synthesis and degradation. It was applied to microarray data of 231 gene transcripts in vastus lateralis muscle of six subjects 1, 8 and 24 h after endurance exercise and 6-week training on a stationary bicycle. Cluster analysis was used to select groups of transcripts having highest co-correlation of their expression (r > 0.70): Group 1 comprised 45 transcripts including factors defining the oxidative and contractile phenotype and Group 2 included 39 transcripts mainly defined by factors found at the cell periphery and the extracellular space. Data from six subjects were pooled to filter experimental noise. The model fitted satisfactorily the responses of Group 1 (r (2) = 0.62 before and 0.85 after training, P < 0.001) and Group 2 (r (2) = 0.75 and 0.79, P < 0.001). Predicted variation in transcription rate induced by exercise yielded a difference in amplitude and time-to-peak response of gene transcripts between the two groups before training and with training in Group 2. The findings illustrate that a mixed-effects model of transcript responses to exercise is suitable to explore the regulation of muscle plasticity by training at the transcriptional level and indicate critical experiments needed to consolidate model parameters empirically.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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