Human hair follicle transcriptome profiling: a minimally invasive tool to assess molecular adaptations upon low‐volume, high‐intensity interval training
| Autor: | Ingrid Smith, Sarah J. Wallace, Maria Y. Shiu, Jing Zhang, Shawn G. Rhind, Valerie S. Langlois |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Adult Male Physiology RNA-Seq Computational biology Biology High-Intensity Interval Training lcsh:Physiology Receptors G-Protein-Coupled Transcriptome 03 medical and health sciences muscle contraction Phosphatidylinositol 3-Kinases 0302 clinical medicine Physiology (medical) energy metabolism medicine RNA‐Seq Humans KEGG Original Research miRNA Janus Kinases lcsh:QP1-981 Gene Expression Profiling 030229 sport sciences Hair follicle Adaptation Physiological Endurance training STAT Transcription Factors 030104 developmental biology medicine.anatomical_structure Molecular Diagnostic Techniques STAT protein Signal transduction Janus kinase High-intensity interval training Hair Follicle Proto-Oncogene Proteins c-akt Biomarkers Signal Transduction |
| Zdroj: | Physiological Reports Physiological Reports, Vol 5, Iss 23, Pp n/a-n/a (2017) |
| ISSN: | 2051-817X |
| Popis: | High‐intensity interval training (HIIT) has become a popular fitness training approach under both civilian and military settings. Consisting of brief and intense exercise intervals, HIIT requires less time commitment yet is able to produce the consistent targeted physical adaptations as conventional endurance training. To effectively characterize and monitor HIIT‐induced cellular and molecular responses, a highly accessible yet comprehensive biomarker discovery source is desirable. Both gene differential expression (DE) and gene set (GS) analyses were conducted using hair follicle transcriptome established from pre and postexercise subjects upon a 10‐day HIIT program by RNA‐Seq, Comparing between pre and posttraining groups, differentially expressed protein coding genes were identified. To interpret the functional significance of the DE results, a comprehensive GS analysis approach featuring multiple algorithms was used to enrich gene ontology (GO) terms and KEGG pathways. The GS analysis revealed enriched themes such as energy metabolism, cell proliferation/growth/survival, muscle adaptations, and cytokine–cytokine interaction, all of which have been previously proposed as HIIT responses. Moreover, related cell signaling pathways were also measured. Specifically, G‐protein‐mediated signal transduction, phosphatidylinositide 3‐kinases (PI3K) – protein kinase B (PKB) and Janus kinase (JAK) – Signal Transducer and Activator of Transcription (STAT) signaling cascades were over‐represented. Additionally, the RNA‐Seq analysis also identified several HIIT‐responsive microRNAs (miRNAs) that were involved in regulating hair follicle‐specific processes, such as miR‐99a. For the first time, this study demonstrated that both existing and new biomarkers like miRNA can be explored for HIIT using the transcriptomic responses exhibited by the hair follicle. |
| Databáze: | OpenAIRE |
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