{"doi":"10.1101/2025.10.29.685384","title":"The Age-Dependent Resident Myonuclear Multi-Omic Response to a Skeletal Muscle Hypertrophic Stimulus","abstract":"Abstract A detailed analysis of how muscle fiber nuclei (myonuclei) respond to a hypertrophic stimulus would provide a critical step toward understanding compromised skeletal muscle plasticity with age. We used recombination-independent doxycycline-inducible myonucleus-specific fluorescent labelling, tissue RNA-sequencing, myonuclear DNA methylation analysis, multi-omic integration, and single myonucleus RNA-sequencing to define the molecular characteristics of adult (6-8 month) and aged (24 month) murine skeletal muscle after acute mechanical overload (MOV). In adult and aged MOV muscles, we found that: 1) similarities in the transcriptional response to loading – specifically in metabolism genes – were partly explained by a post-transcriptional microRNA-mediated mechanism, which we corroborated using an inducible muscle fiber-specific miR-1 knockout model, 2) differences in age-dependent transcriptional responses were linked to the magnitude and location of differential DNA methylation in resident myonuclei, specifically around hypertrophy-associated genes such as Myc , Runx1 , Mybph , Ankrd1, collagen genes, and minichromosome maintenance genes, 3) adult and aged resident myonuclear transcriptomes had differing enrichment for innervation-related transcripts as well as unique transcriptional profiles in an Atf3+ “sarcomere assembly” population after MOV, and 4) cellular deconvolution analysis supports a role for neuromuscular junction regulation in age-specific hypertrophic adaptation. These data are a roadmap for uncovering molecular targets to enhance aged muscle adaptability.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":556865,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9571,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":868300,"name":"Ronald G. Jones","orcid":null,"position":1,"is_corresponding":false},{"id":942083,"name":"Ana Regina Cabrera","orcid":"0000-0002-9811-3585","position":2,"is_corresponding":false},{"id":678353,"name":"Francielly Morena da Silva","orcid":"0000-0001-5019-2125","position":3,"is_corresponding":false},{"id":321274,"name":"Nicholas P. Greene","orcid":"0000-0001-9621-2005","position":4,"is_corresponding":false},{"id":282076,"name":"John J. McCarthy","orcid":"0000-0003-4522-5601","position":5,"is_corresponding":false},{"id":669282,"name":"Ahmed Ismaeel","orcid":"0000-0003-4025-3945","position":6,"is_corresponding":false},{"id":559626,"name":"Yuan Wen","orcid":"0000-0002-3210-1629","position":7,"is_corresponding":false},{"id":282073,"name":"Kevin A. Murach","orcid":"0000-0003-2783-7137","position":8,"is_corresponding":false},{"id":1065610,"name":"Pieter J. Koopmans","orcid":"0000-0002-4797-5265","position":0,"is_corresponding":true}],"reference_count":126,"raw_metadata":null,"created_at":"2026-07-19T02:55:13.130091Z","pmid":"41279683","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}