GEO series
In Vitro Modeling of Age-Related Methylation Changes with Intestinal Organoids [RNA-Seq]
GSE294963
Mus musculus
Expression profiling by high throughput sequencing
11 samples
2025/06/01
GPL30172
Summary
Intestinal organoids, three-dimensional cultures from intestinal stem cells, are a powerful model for studying aging, and DNA methylation is an accurate biological clock. Consequently, we hypothesized that organoid DNA methylation could serve as an aging metric and a valuable tool for in vitro aging research. Our initial study revealed significant DNA methylation changes, during organoid culture, with 27% of total CpG sites undergoing hypomethylation, and 11% gaining hypermethylation. Hypomethylation occurred predominantly in aging-associated genomic regions, including non-promoter, non-CpG island regions (e.g., transposable elements), while hypermethylation, in CpG islands, significantly (p < 0.001) correlated with aging. Comparison of aging-methylated sites with differentiation-specific CpG sites showed minimal overlap, indicating negligible association. Early-passage (P0 and P2) organoids, derived from 4- and 24-month-old mice, preserved aging-specific methylation patterns, with a correlation coefficient of 0.48 (p < 0.001) between methylation differences in old versus young primary cells. Conversely, long-term passaging revealed distinct methylation changes, specific to each organoid line. Some early passage organoids exhibited more hypomethylation, clustering with mid-passage (P10 - P13) organoids, while late-passage (P24 and P27) organoids entered a crisis stage with severe hypomethylation, growth arrest, and distant clustering. Transposable elements remained hypomethylated, compared to primary cells. Aging-related methylation sites continued to change with passage, and linear modeling predicted that organoids age at a rate of 0.46 months per week in culture. Treatment with decitabine reversed the methylation age of organoids, derived from 24-month-old mice. These findings suggest that organoids effectively model aging, with further research needed to assess culture-associated influences.
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