Skeletal muscle transcriptome in healthy aging

Tumasian, Robert A.; Harish, A; Kundu, Gautam; Yang, Jen‐Hao; Ubaida‐Mohien, Ceereena; González-Freire, Marta; Kaileh, Mary; Zukley, Linda; Chia, Chee W.; Lyashkov, Alexey E.; Wood, William H.; Piao, Yulan; Coletta, Christopher; Ding, Jun; Gorospe, Myriam; Sen, Ranjan; De, Supriyo; Ferrucci, Luigi

doi:10.1038/s41467-021-22168-2

Cited by 82 publications

(80 citation statements)

References 105 publications

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“…Previously published total RNA-seq data of human skeletal muscle samples from young (22–35 years) and aged (70–82) were downloaded from NCBI GEO ( Tumasian et al, 2021 ) (GEO accession: GSE164471; SRA ID: SRP300916) ( Supplementary Table S2 ). In addition, total RNA-seq data of human muscle satellite cells from young and aged donors were obtained from NCBI GEO (GEO Accession No.…”

Section: Methodsmentioning

confidence: 99%

Identification of Potential circRNA-microRNA-mRNA Regulatory Network in Skeletal Muscle

Das

Shyamal

Sinha

et al. 2021

Front. Mol. Biosci.

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Circular RNAs (circRNAs) are a newly discovered family of regulatory RNAs generated through backsplicing. Genome-wide profiling of circRNAs found that circRNAs are ubiquitously expressed and regulate gene expression by acting as a sponge for RNA-binding proteins (RBPs) and microRNAs (miRNAs). To identify circRNAs expressed in mouse skeletal muscle, we performed high-throughput RNA-sequencing of circRNA-enriched gastrocnemius muscle RNA samples, which identified more than 1,200 circRNAs. In addition, we have identified more than 14,000 and 15,000 circRNAs in aging human skeletal muscle tissue and satellite cells, respectively. A subset of abundant circRNAs was analyzed by RT-PCR, Sanger sequencing, and RNase R digestion assays to validate their expression in mouse skeletal muscle tissues. Analysis of the circRNA-miRNA-mRNA regulatory network revealed that conserved circNfix might associate with miR-204-5p, a suppressor of myocyte enhancer factor 2c (Mef2c) expression. To support the hypothesis that circNfix might regulate myogenesis by controlling Mef2c expression, silencing circNfix moderately reduced Mef2c mRNA expression and inhibited C2C12 differentiation. We propose that circNfix promotes MEF2C expression during muscle cell differentiation in part by acting as a sponge for miR-204-5p.

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Section: Methodsmentioning

confidence: 99%

Identification of Potential circRNA-microRNA-mRNA Regulatory Network in Skeletal Muscle

Das

Shyamal

Sinha

et al. 2021

Front. Mol. Biosci.

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“…Recent reports have surveyed the transcript level changes in the aging mouse skeletal muscle (Graber et al, 2021;Lin et al, 2018;Mikovic et al, 2018) or the heart (Bartling et al, 2019;Benayoun et al, 2019;Greenig et al, 2020). Separate studies have also determined the transcript (Timmons et al, 2019;Tumasian et al, 2021) and protein abundance changes (Murgia et al, 2017;Ubaida-Mohien et al, 2019a) in aging human skeletal muscles. Despite progress however, significant knowledge gaps persist.…”

Section: Introductionmentioning

confidence: 99%

“…Because proteins perform the overwhelming majority of biological processes, the results from transcriptomics data might be differentially relevant to biological processes based on how well they predict protein level. Recent large studies including GTEx (GTEx Consortium, 2020;Jiang et al, 2020), CPTAC (Krug et al, 2020;Mani et al, 2021), and GESTALT (Tumasian et al, 2021) have compared transcriptomics and proteomics data from matching tissues in large cohorts, and generally find moderate correlation between RNA and protein levels across samples. At present however, large-scale proteomics data of comparable depths remain far less accessible and common than transcriptomics data, hence there is intense interest in comparing across omics layers and identifying the transcriptomics signatures in aging and disease models that are translatable to the protein layer.…”

Section: Introductionmentioning

confidence: 99%

Transcriptome features of striated muscle aging and predictability of protein level changes

Kastury

et al. 2021

Preprint

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RNA and protein levels correlate only partially and some transcripts are better correlated with their protein counterparts than others. This suggests that in aging and disease studies, some transcriptomics markers may carry more information in predicting protein-level changes. Here we applied a computational data analysis workflow to predict which transcriptomic changes are more likely relevant to protein-level regulation in striated muscle aging. The protein predictability of each transcript is estimated from existing large proteogenomics data sets, then transferred to new total RNA sequencing data comparing skeletal muscle and cardiac muscle in young adult (~4 months) mice vs. early aging (~20 months) mice. Aging cardiac and skeletal muscles both invoke transcriptomic changes in innate immune system and mitochondria pathways but diverge in extracellular matrix processes. On an individual gene level, we identified 611 age-associated signatures in skeletal and cardiac muscles at 10% FDR, including a number of myokine and cardiokine encoding genes. We estimate that about 48% of the aging-associated transcripts may predict protein levels well (r ≥ 0.5). In parallel, a comparison of the identified aging-regulated genes with public human transcriptomics data showed that only 35-45% of the identified genes show an age-dependent expression in corresponding human tissues. Finally, integrating both protein predictability and human translatability from multiple data sources, we nominate 134 prioritized aging signatures that are predicted to correlate strongly with protein levels and that show age-dependent expression in humans. These prioritized gene signatures may hold promise to understanding heart and skeletal muscle physiology in human and mouse aging.

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“…149, 150], neurological adaptations as motoneuron survival varies with age and exercise [151], molecular probing at the single fiber and single cell level [152][153][154][155], and continued comparisons among males and females throughout the lifespan.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

The Aging Athlete: Paradigm of Healthy Aging

Gries

Trappe

2022

Int J Sports Med

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The Exercise Boom of the 1970’s resulted in the adoption of habitual exercise in a significant portion of the population. Many of these individuals are defying the cultural norms by remaining physically active and competing at a high level in their later years. The juxtaposition between masters athletes and non-exercisers demonstrate the importance of remaining physically active throughout the lifespan on physiological systems related to healthspan (years of healthy living). This includes ~50% improved maximal aerobic capacity (VO2max) and enhanced skeletal muscle health (size, function, as well as metabolic and communicative properties) compared to non-exercisers at a similar age. By taking a reductionist approach to VO2max and skeletal muscle health, we can gain insight into how aging and habitual exercise affects the aging process. Collectively, this review provides a physiological basis for the elite performances seen in masters athletes, as well as the health implications of lifelong exercise with a focus on VO2max, skeletal muscle metabolic fitness, whole muscle size and function, single muscle fiber physiology, and communicative properties of skeletal muscle. This review has significant public health implications due to the potent health benefits of habitual exercise across the lifespan.

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Skeletal muscle transcriptome in healthy aging

Cited by 82 publications

References 105 publications

Identification of Potential circRNA-microRNA-mRNA Regulatory Network in Skeletal Muscle

Identification of Potential circRNA-microRNA-mRNA Regulatory Network in Skeletal Muscle

Transcriptome features of striated muscle aging and predictability of protein level changes

The Aging Athlete: Paradigm of Healthy Aging

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