Scholarlink

<p>The bio-molecular changes of exercise, and how to best optimize them for improved performance, are an important human health research question. A recent study by the Molecular Transducers of Physical Activity Consortium (MoTrPAC) used a cohort of Rattus norvegicus to produce a whole-organism molecular map of the temporal effects of endurance exercise training. This dataset, encompassing hundreds of assays across 19 different tissues, can be used to evaluate the predictive power of gene expression, understand isoform-level changes in response to exercise, and with modern tools can be examined for associations with viral infection. Our analysis of the RNA-seq data reveals that gene expression can accurately predict the amount of exercise a rat was trained in. Additionally, we find biologically relevant isoform-level differences in expression that are masked in gene-level analysis. Finally, we find a potential novel virus that may negatively impact physiological measurements. This more comprehensive analysis provides a blueprint for directing similar analyses with respect to physiological perturbations across organisms.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Transcriptomic responses to endurance exercise training in rats

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月21日

查看全文
  • Conrad Oakes,
  • Lior Pachter

摘要

The bio-molecular changes of exercise, and how to best optimize them for improved performance, are an important human health research question. A recent study by the Molecular Transducers of Physical Activity Consortium (MoTrPAC) used a cohort of Rattus norvegicus to produce a whole-organism molecular map of the temporal effects of endurance exercise training. This dataset, encompassing hundreds of assays across 19 different tissues, can be used to evaluate the predictive power of gene expression, understand isoform-level changes in response to exercise, and with modern tools can be examined for associations with viral infection. Our analysis of the RNA-seq data reveals that gene expression can accurately predict the amount of exercise a rat was trained in. Additionally, we find biologically relevant isoform-level differences in expression that are masked in gene-level analysis. Finally, we find a potential novel virus that may negatively impact physiological measurements. This more comprehensive analysis provides a blueprint for directing similar analyses with respect to physiological perturbations across organisms.