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


Busso, Thierry; Flück, Martin (2013). A mixed-effects model of the dynamic response of muscle gene transcript expression to endurance exercise. European Journal of Applied Physiology, 113(5):1279-1290.

Abstract

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.

Abstract

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:May 2013
Deposited On:06 Aug 2015 06:41
Last Modified:05 Apr 2016 19:20
Publisher:Springer
ISSN:1439-6319
Publisher DOI:https://doi.org/10.1007/s00421-012-2547-x
PubMed ID:23179205

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