bioRxiv Science⌕ Search

Biology subjects

Kinnunen, L.

Publications and source records attributed to Kinnunen, L..

3 recordsLinked to original sources

Erosion of regenerative regulation: age-associated shifts in the skeletal muscle fiber epigenome and transcriptome

Skeletal muscle aging is characterized by the deterioration of muscle function, which can lead to negative quality-of-life outcomes including frailty and sarcopenia. While understanding the mechanisms of this process is increasingly important as the global population ages, previous molecular studies of skeletal muscle aging have been limited by statistical power and cell type resolution. In this study, we analyzed single-nucleus gene expression and chromatin accessibility data from 287 human skeletal muscle samples from individuals aged 20-79 years to explore sex- and cell type- specific aging effects. Across 467,126 nuclei from 13 cell types, we identify 384 age-associated genes and 4,061 age-associated chromatin regions. These age-associated molecular features are enriched for functional pathways, including metabolic processes, cell-to-cell communication, and senescence Kyoto Encyclopedia of Genes and Genomes KEGG terms. Age-associated closing chromatin was more common across fiber types and sexes than opening chromatin, and was enriched in active enhancer regions while depleted for active transcription start sites. We observe enrichment for specific transcription factor motifs in closing chromatin, including those of glucocorticoid and androgen receptors, both of which play a key role in the maintenance of healthy skeletal muscle. Together, these findings identify an age-associated regulatory shift, largely invisible in matched transcriptomic data, characterized by closing chromatin which reduces accessibility to hormone receptor binding sites and enhancer regions in the muscle fiber epigenome.

bioinformatics↗

Donor-matched iPSC model reveals context-dependent T2D genetic signals in fibro-adipogenic progenitors

Fibro-adipogenic progenitors (FAPs) in skeletal muscle have been implicated in type 2 diabetes (T2D), yet their heterogeneity and context-dependent regulation remain poorly understood. Here, we establish induced pluripotent stem cell (iPSC)-derived FAPs as a model of primary FAPs by leveraging a unique resource: iPSC lines and skeletal muscle biopsies obtained from 34 individuals, a subset of 30 profiled using single-nucleus multiomics. Donor-matched comparisons reveal iPSC-FAPs recapitulate the transcriptome, epigenome, and subtype composition of primary FAPs. Using single-nucleus multiomics, we show that high-insulin exposure drives iPSC-FAPs toward an adipogenic fate - and this adipogenic subtype is enriched for T2D GWAS signals, an enrichment undetectable at baseline. We map the T2D-associated rs3814707 non-coding signal to LTBP3, a gene that influences FAP adipogenic differentiation. These findings reveal how disease-relevant regulatory mechanisms can be masked in unstimulated cells and establish iPSC-FAPs as a powerful platform for dissecting the state-dependent biology of complex metabolic disease.

genetics↗

Interactions between genetic variation and cellular environment in skeletal muscle gene expression

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis acting genotype-environment interactions (GxE) - genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate interaction quantitative trait loci (iQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

genetics↗