高强度间歇运动中长、短休息时间对马骨骼肌转录组反应的影响。

IF 2.5 4区 生物学 Q3 CELL BIOLOGY
Physiological genomics Pub Date : 2025-01-01 Epub Date: 2024-12-11 DOI:10.1152/physiolgenomics.00066.2024
Kenya Takahashi, Kazutaka Mukai, Yuji Takahashi, Yusaku Ebisuda, Hideo Hatta, Yu Kitaoka
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引用次数: 0

摘要

本研究的目的是阐明骨骼肌转录组反应独特的休息时间在高强度间歇运动。纯种马以最大摄氧量(10.7-12.5 m/s)进行三次1分钟的运动,以1.7 m/s的速度步行15分钟(长)或2分钟(短)。在运动前和运动后4小时采集臀中肌,用于RNA测序。我们分别使用DEseq2分析(错误发现率(FDR)截止值= 0.05,最小折叠变化值= 1.5)鉴定了1756个和1421个差异表达基因对长和短协议的响应。总的转录反应是部分一致的,在两种方案中有43% (n=949)的基因发生了改变,而没有观察到不一致的方向变化。基于基因本体生物学过程术语的K-means聚类和基因集富集分析表明,与肌肉适应和发育相关的基因在不同运动条件下均上调;与免疫和细胞因子反应相关的基因在较长时间后表达上调,蛋白质折叠和温度反应在较短时间后高表达。我们发现11个基因在短方案中上调幅度较大,1个基因在长方案中上调幅度较大,其中GNA13、SPART、PHAF1和PTX3被确定为骨骼肌重塑的潜在候选基因。我们的研究结果表明,依赖于间歇运动模式的代谢波动改变会调节骨骼肌基因表达,因此休息间隔长度可能是优化骨骼肌适应的重要考虑因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of long- and short-rest periods during high-intensity interval exercise on transcriptomic responses in equine skeletal muscle.

The purpose of this study was to elucidate the skeletal muscle transcriptomic response unique to rest duration during high-intensity interval exercise. Thoroughbred horses performed three 1-min bouts of exercise at their maximal oxygen uptake (10.7-12.5 m/s), separated by 15 min (long) or 2 min (short) walking at 1.7 m/s. Gluteus medius muscle was collected before and at 4 h after the exercise and used for RNA sequencing. We identified 1,756 and 1,421 differentially expressed genes in response to the long and short protocols, respectively, using DEseq2 analysis [false discovery rate (FDR) cutoff = 0.05, minimal fold change = 1.5]. The overall transcriptional response was partially aligned, with 43% (n = 949) of genes altered in both protocols, whereas no discordant directional changes were observed. K-means clustering and gene set enrichment analyses based on Gene Ontology biological process terms showed that genes associated with muscle adaptation and development were upregulated regardless of exercise conditions; genes related to immune and cytokine responses were more upregulated following the long protocol, and protein folding and temperature response were highly expressed after the short protocol. We found that 11 genes were upregulated to a greater extent by the short protocol and one was by the long protocol, with GNA13, SPART, PHAF1, and PTX3 identified as potential candidates for skeletal muscle remodeling. Our results suggest that altered metabolic fluctuations dependent on the intermittent pattern of interval exercise modulate skeletal muscle gene expression, and therefore, rest interval length could be an important consideration in optimizing skeletal muscle adaptation.NEW & NOTEWORTHY This is the first study to address the comparison of transcriptional responses to high-intensity interval exercise with two different rest periods in skeletal muscle. The expression of genes related to metabolic adaptations altered in both conditions, while genes associated with immune and cytokine responses and protein folding and temperature response were varied with the length of the rest period. These results provide evidence for rest duration-specific transcriptional response to high-intensity interval training.

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来源期刊
Physiological genomics
Physiological genomics 生物-生理学
CiteScore
6.10
自引率
0.00%
发文量
46
审稿时长
4-8 weeks
期刊介绍: The Physiological Genomics publishes original papers, reviews and rapid reports in a wide area of research focused on uncovering the links between genes and physiology at all levels of biological organization. Articles on topics ranging from single genes to the whole genome and their links to the physiology of humans, any model organism, organ, tissue or cell are welcome. Areas of interest include complex polygenic traits preferably of importance to human health and gene-function relationships of disease processes. Specifically, the Journal has dedicated Sections focused on genome-wide association studies (GWAS) to function, cardiovascular, renal, metabolic and neurological systems, exercise physiology, pharmacogenomics, clinical, translational and genomics for precision medicine, comparative and statistical genomics and databases. For further details on research themes covered within these Sections, please refer to the descriptions given under each Section.
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