A transcriptome atlas of leg muscles from healthy human volunteers reveals molecular and cellular signatures associated with muscle location

Abstract

Skeletal muscles support the stability and mobility of the skeleton but differ in biomechanical properties and physiological functions. The intrinsic factors that regulate muscle-specific characteristics are poorly understood. To study these, we constructed a large atlas of RNA-seq profiles from six leg muscles and two locations from one muscle, using biopsies from 20 healthy young males. We identified differential expression patterns and cellular composition across the seven tissues using three bioinformatics approaches confirmed by large-scale newly developed quantitative immune-histology procedures. With all three procedures, the muscle samples clustered into three groups congruent with their anatomical location. Concomitant with genes marking oxidative metabolism, genes marking fast- or slow-twitch myofibers differed between the three groups. The groups of muscles with higher expression of slow-twitch genes were enriched in endothelial cells and showed higher capillary content. In addition, expression profiles of Homeobox (HOX) transcription factors differed between the three groups and were confirmed by spatial RNA hybridization. We created an open-source graphical interface to explore and visualize the leg muscle atlas (https://tabbassidaloii.shinyapps.io/muscleAtlasShinyApp/). Our study reveals molecular specialization of human leg muscles and provides a novel resource to study muscle-specific molecular features, which could be linked with (patho)physiological processes.

Quantitative analysis of myofiber type composition in human and mouse skeletal muscles

“…However, it allows recognizing hybrids, which are implicated in aging. 13 Myofiber type clusters differ between muscle groups in both mouse and human, 1 , 17 , 18 although not fully understood, it could suggest a relevance for muscle physiology and function.

Figure 9 The distribution of three measurements defined to assess segmentation certainty (A and B) The density plots of Mean, Mean_boundary, and StdDev_boundary across all the samples before (panel A) and after filtering (panel B).

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“…However, it allows recognizing hybrids, which are implicated in aging. 13 Myofiber type clusters differ between muscle groups in both mouse and human, 1 , 17 , 18 although not fully understood, it could suggest a relevance for muscle physiology and function.…”

“…Human muscle biopsies from healthy male subjects (aged 18–32) were used from a study detailed in Abbassi-Daloii et al . 1 The study was approved by the local Medical Ethical Review Board of The Hague Zuid-West and the Erasmus Medical Centre and conducted in accordance with the ethical standards stated in the 1964 Declaration of Helsinki and its later amendments (ABR number: NL54081.098.16). All subjects provided written informed consent prior to participation.…”

The dawn of the functional genomics era in muscle physiology

“…Indeed, a combination of microarray and NGS-based experiments, assaying gene expression, DNA and histone epigenetic modifications, have profiled SkM in a multitude of contexts including loss/growth of muscle (Fisher et al, 2017;Viggars et al, 2023), acute and chronic exercise (Pillon et al, 2020;Seaborne et al, 2018aSeaborne et al, , 2018bShimizu & Kawano, 2022;Turner et al, 2019), lifestyle diseases (e.g. type 2 diabetes mellitus (Ribel-Madsen et al, 2012;Williams et al, 2020)), genetic diseases (Gonorazky et al, 2016), ageing (Ruple et al, 2021), sex-specific effects (Landen et al, 2019(Landen et al, , 2021 and anatomical location (Abbassi-Daloii et al, 2023). The use of traditional 'omic' strategies to profile and/or characterise the macromolecular landscape of SkM has typically focused on assaying SkM samples as biopsy homogenates (e.g.…”

Diffusion‐tensor magnetic resonance imaging captures increased skeletal muscle fibre diameters in Becker muscular dystrophy

“…Laminin images were automatically quantified using a set of Fiji macros (v1.51), 21 as previously described. 22 The minimum Feret diameter, perimeter, circularity and cross-sectional area (CSA) were obtained per myofibre for selected samples, and measurements in pixels were converted to micrometres. Circularity and CSA measurements were used for quality control (Data S1).…”