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Tabula Ageing makes public the full results behind our study of miR-29, ageing and epigenetic plasticity. Somatic cells must keep their identity while remaining able to change. miR-29 rises with ageing, falls during reprogramming and early development, and directly targets the enzymes that add and remove DNA methylation (DNMT3A, DNMT3B, the TET enzymes and TDG). Our results support a trade-off model: rising miR-29 helps hold established methylation states in place, preserving epigenetic fidelity at the expense of youthful plasticity. Lowering miR-29 in fibroblasts expands methylome remodelling in both directions, lowers epigenetic-clock estimates and increases deviation from a fibroblast methylation reference, while raising it holds the methylome in place; in cancer, low miR-29 marks tumours with lower epigenetic-age estimates but greater divergence from their tissue of origin. The platform is built for researchers in ageing, epigenetics, RNA biology and oncology who want to check a gene, miRNA or CpG site against these results, reuse them, or explore them without writing code. Original study coefficients and significance values are preserved. Exploratory views add explicitly labelled summaries, differences and profile similarities from the underlying data; these do not replace the published statistical tests.

The data span six modules, each answering one part of that question with its own samples. Ageing correlates gene and miRNA expression with donor age across 30 human tissues and ranks every gene, defining an aging-up program. Embryogenesis follows the same genes from the oocyte to embryonic stem cells, and Reprogramming compares cells progressing towards pluripotency with cells that keep a fibroblast-like state: the two settings in which the epigenome is reset rather than eroded. Evolution asks how old the miR-29 family is and whether its link with age holds in other animals, from its loci {{evoLociIn}}, to miRNA abundance with age in 11 species, to methylation of its host-gene locus across mammals. Perturbation moves from observation to experiment: miR-29 is lowered or raised in primary human fibroblasts, and the transcriptome and DNA methylome are followed over time against matched controls. Cancer, finally, follows miR-29 and the methylation enzymes across 8,428 tumours of 30 types and 429 cancer cell lines. The modules are independent and use different samples and statistics, so values are meant to be compared within a module, not across modules. In each one you can search a gene, miRNA, CpG site or cancer type, read short descriptions from plain language to technical detail, hover any point for its exact values, and use the export controls to save tables or annotated figures in the formats available in each panel. Data sources and methods are described in full under Data Sources & Methods.