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High-throughput muscle fiber typing from RNA sequencing data

ABSTRACT: Skeletal muscle fiber type distribution has implications for human health, muscle function and performance. This knowledge has been gathered using labor intensive and costly methodology that limited these studies. Here we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for larger number of individuals to be tested. By using single-nuclei snRNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPas staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). The correlation between the sequencing-based method and the other two were rATPas = 0.65 [0.46 – 0.84], [95% CI] and rmyosin = 0.80 [0.71 – 0.89], with p = 7.96 x 10-6 and 8.06 x 10-6 respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of ~5.000 paired end reads. This new method consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor efficient way. For the first time it is now feasible to study the association between fiber type distribution and health outcomes in large well-powered studies.

ORGANISM(S): Homo sapiens Pan troglodytes

PROVIDER: GSE190489 | GEO | 2022/07/06

REPOSITORIES: GEO

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Project description:Purpose: Next-generation sequencing (NGS) was used to select genes potentially associated with fiber-type distribution and cell size in porcine muscle tissue. Methods: The histological profile of the longissimus lumborum muscle was establish by method involving detection of NADPH dehydrogenase (diaphorase) and immunohistochemically detection of myosin chains. The muscle transcriptome sequencing was performed for 11 pigs using Illumina HiScan SQ in 50 single-end cycles. The quantifying transcript abundances was made using the RSEM supported by STAR aligner. The raw reads were aligned to the Sus scrofa reference genome (assembly Sscrofa10.2). Differentially expressed genes were detected by edgeR, baySeq and DESeq2. The RNA-seq results were validated using by qPCR. Results: The RNA-seq approach allows to identify 397 differentially expressed genes (DEGs) indicated as significant (FDR<0.05) using three software: DESeq2, edgeR and baySeq. Detected genes and pathways deregulated in muscle depend on tissue microstructure were associated with metabolic processes â?? 158 genes; cellular processes â?? 122; biological regulation â?? 62; localization â?? 51 and 35 genes with developmental processes. The detected DEGs were included in such pathways as: PI3K-Akt; FoxO and MAPK signaling pathways, regulation of actin cytoskeleton, lysine degradation and insulin signaling pathway as well as in mTOR and Hippo signaling. Conclusions: This results highlight the mainly metabolic pathways related with glucose metabolism and contraction processes of muscle cells. The comparison of whole gene expression profiles between muscles characterized by different fiber-type distribution showed that processes of growth and proliferation of different fiber types are determined by diverse molecular mechanism, which conditioned the unique histological structure of muscle tissue. The muscle (longissimus lumborum) transcriptome sequencing was performed for 11 pigs using Illumina HiScan SQ in 50 single-end cycles and in five technical repetitions.

Project description:Purpose: Reduced Representation Bisulfite Sequencing (RRBS) DNA input requirements become a challenge when working with small pools of tissue-specific cell types. We describe an application of the RRBS method to assess DNA methylation on low-DNA input from human slow-twitch (MHC I) and fast-twitch (MHC IIa) skeletal muscle fibers. Methods : Fiber-type specific (MHC I and MHC IIa muscle fibers) total DNA was extracted from vastus lateralis muscle biopsies of 8 young physically active men (~25 yrs). A total of 16 DNA samples were generated : 8 DNA samples from pure MHC I and 8 DNA samples from pure MHC IIa muscle fibers. An equal quantity of DNA (4 ng) from each sample was combined to generate a "pooled" DNA sample representing all 8 subjects for each fiber type. Two fiber-type specific "pooled" samples of 32 ng of DNA were generated for library construction and sequencing, creating a Type 1 (MHC I muscle fibers) and Type 2a (MHC IIa muscle fibers) sample. Sequencing was performed using the HiSeq 2500 (Illumina) with 50 bp paired-end read parameters. Minimum sequencing read coverage of 5 (5x) was used as the cutoff for CpG-sites inclusion in the DNA methylation analysis. Fisher’s exact test was performed on CpG-sites that overlapped (i.e. identified in both samples) Type 1 and Type 2a samples to obtain p-values that indicate the likelihood of the site being a differentially methylated CpG-site (DMS). DMS with p<0.05 were classified as hypermethylated or hypomethylated if they were more or less methylated than the Type 1 sample, which was used as the reference sample. Results: The 32 ng of DNA from fiber-type specific muscle samples (Type 1 and 2a) used in this study ensured similar sequencing quality as compared to other studies using greater DNA input (>50 ng). Mapping ratios of ~47% and bisulfite conversion rates of ~97-98% were obtained.The unique and best alignment was successfully assessed for each of 17,376,728 CpG-sites in the Type 1 sample and 17,006,993 in the Type 2a sample, which represents ~30% of the total CpG number in the human genome. We identified 143,160 differentially methylated CpG-sites (DMS) across 14,046 genes among MHC I and MHC IIa muscle fibers. The analysis revealed that some genes predominantly expressed in MHC I were hypermethylated in MHC IIa muscle fibers. Conclusion: This study validates a low-DNA input RRBS method for human skeletal muscle samples to investigate the methylation patterns at a fiber-type specific level. These are the first fiber-type specific methylation data reported from human skeletal muscle. Considering the metabolic and structural differences between MHC I and MHC IIa muscle fibers, this technique could provide novel insights into the skeletal muscle methylation profile in relation to health, performance, disease or disuse.

Project description:Introduction: The mouse skeletal muscle is composed of four distinct fiber types that differ in contractile function, number of mitochondria and metabolism. Every muscle group has a specific composition and distribution of the four fiber types. Until now, three genes (CnA, PGC1α and PPARδ) are identified that are involved in the generation of more oxidative muscle types. In the present study we searched for novel genes that are involved in specifying different muscle types. Methods: Gastrocnemius and quadriceps muscles were dissected from 20-week old C57BL/6J mice. Gene expression profiles were compared at the level of the whole-transcriptome. The diet-sensitivity of genes differentially expressed between muscle types was explored by comparing mice fed a low fat diet with mice fed a high fat diet. Results: We identified 162 differentially expressed genes in the gastrocnemius as compared with the quadriceps. Genes with the strongest regulations were markers for oxidative fiber types, Hoxd8, Hoxd9 and Hoxd10 and others involved in embryogenesis. Additionally, diet did not influence the expression levels of genes specifying muscle types. Finally, when extrapolating our data to the soleus we could not find a corresponding gene expression pattern between Hoxd8, Hoxd9 and any of the fiber-type specific markers. However, based on these gene expression patterns we could distinguish the gastrocnemius, quadriceps and soleus from each other. Conclusion: Hoxd genes and genes that are markers for the different fiber types specify muscle type in a diet-independent way The aim of the present study was to find novel genes that may play a role in specifying muscle types. Therefore we compared gene expression profiles of the gastrocnemius with the quadriceps at the level of the whole-transcriptome. Functional implications were assessed by the analyses of predefined gene sets based on Gene Ontology, biochemical, metabolic and signaling pathways. muscle-type comparison

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High-throughput muscle fiber typing from RNA sequencing data

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