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Usage Information

Nuclear receptor/microRNA circuitry links muscle fiber type to energy metabolism
Zhenji Gan, John Rumsey, Bethany C. Hazen, Ling Lai, Teresa C. Leone, Rick B. Vega, Hui Xie, Kevin E. Conley, Johan Auwerx, Steven R. Smith, Eric N. Olson, Anastasia Kralli, Daniel P. Kelly
Zhenji Gan, John Rumsey, Bethany C. Hazen, Ling Lai, Teresa C. Leone, Rick B. Vega, Hui Xie, Kevin E. Conley, Johan Auwerx, Steven R. Smith, Eric N. Olson, Anastasia Kralli, Daniel P. Kelly
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Research Article Muscle biology

Nuclear receptor/microRNA circuitry links muscle fiber type to energy metabolism

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Abstract

The mechanisms involved in the coordinate regulation of the metabolic and structural programs controlling muscle fitness and endurance are unknown. Recently, the nuclear receptor PPARβ/δ was shown to activate muscle endurance programs in transgenic mice. In contrast, muscle-specific transgenic overexpression of the related nuclear receptor, PPARα, results in reduced capacity for endurance exercise. We took advantage of the divergent actions of PPARβ/δ and PPARα to explore the downstream regulatory circuitry that orchestrates the programs linking muscle fiber type with energy metabolism. Our results indicate that, in addition to the well-established role in transcriptional control of muscle metabolic genes, PPARβ/δ and PPARα participate in programs that exert opposing actions upon the type I fiber program through a distinct muscle microRNA (miRNA) network, dependent on the actions of another nuclear receptor, estrogen-related receptor γ (ERRγ). Gain-of-function and loss-of-function strategies in mice, together with assessment of muscle biopsies from humans, demonstrated that type I muscle fiber proportion is increased via the stimulatory actions of ERRγ on the expression of miR-499 and miR-208b. This nuclear receptor/miRNA regulatory circuit shows promise for the identification of therapeutic targets aimed at maintaining muscle fitness in a variety of chronic disease states, such as obesity, skeletal myopathies, and heart failure.

Authors

Zhenji Gan, John Rumsey, Bethany C. Hazen, Ling Lai, Teresa C. Leone, Rick B. Vega, Hui Xie, Kevin E. Conley, Johan Auwerx, Steven R. Smith, Eric N. Olson, Anastasia Kralli, Daniel P. Kelly

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Usage data is cumulative from July 2025 through July 2026.

Usage JCI PMC
Text version 1,277 93
PDF 295 32
Figure 901 4
Supplemental data 121 4
Citation downloads 189 0
Totals 2,783 133
Total Views 2,916
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ISSN: 0021-9738 (print), 1558-8238 (online)

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