Human hair follicle transcriptome profiling: a minimally invasive tool to assess molecular adaptations upon low‐volume, high‐intensity interval training

Abstract

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.

Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness

“…We calculated pathway enrichment statistics using a rank-based test and statistics from element-specific results to evaluate if genes or noncoding elements that are part of a predefined biologically coherent set are enriched in our ranked list of accelerated regions. Using numerous gene sets associated with hair growth, such as KRTs, KRTAPs, hair follicle expressed genes (Zhang et al, 2017), skin-expressed genes (Papatheodorou et al, 2018), and Gene Ontology (GO) (Ashburner et al, 2000), Mouse Genome Informatics (MGI) (Eppig et al, 2015), and canonical hair-annotated genes (Liberzon et al, 2011), we indeed find that our results are highly enriched for hair-related functions (Supp. File 5).…”

“…All genesets except hair follicle are from the GTEx tissue expression database. Hair follicle genes are the top 70 most highly expressed genes from (Zhang et al, 2017) hair follicle RNA sequencing that are not ubiquitously expressed across GTEx tissue types. on the state of being hairless or the transition from haired to hairlessi.e.…”

“…No genes had significant evolutionary rate shifts in coding sequence except OLFM4, which evolves faster in hairless species. In pink are genes with hair-related functions in the literature (citations: ELF3 (Blumenberg, 2013), FOXC1 (Lay et al, 2016), CCL13 (Michel et al, 2017;Suárez-Fariñas et al, 2015), CCL1 (Nagao et al, 2012), DSG1 (Zhang et al, 2017), GSG1 (Aya, Shimokawa, & Doi, 2009), MIR205HG (D. Wang et al, 2013), FOXQ1 (Ashburner et al, 2000;Carbon et al, 2019)). The chromosomal region around mir205 shows a large number of CNEs accelerated in hairless species, as seen for RERconverge and Bayes factor scores.…”

Hair follicle miRNAs: a novel biomarker for primary blast Induced-Mild traumatic brain injury

“…As such, an effective molecular biomarker system that is both effective and reflective of mTBI is needed. As demonstrated previously, the mammalian hair follicle is one such robust system for biomarker assessments (Zhang et al, 2014(Zhang et al, , 2017(Zhang et al, , 2018.…”

“…Mammalian hair follicles respond to primary blast-derived mTBI on a transcriptome level and genes related to ionic flux, cellular stress signal transduction, cell proliferation, apoptosis, immune responses, and regulation of the central nervous system are differentially expressed (Zhang et al, 2014(Zhang et al, , 2017. Due to their ubiquitous expression patterns and stability, miRNAs have been explored as potential biomarkers and therapeutic targets for diseases (Mitchell et al, 2008;Wang, 2009;Adachi et al, 2010;Hanke et al, 2010).…”