Multi-omics dataset of TGF-β-induced EMT in breast cancer

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This dataset comprises matched whole-genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) data to investigate epigenetic and transcriptional dynamics during epithelial–mesenchymal transition (EMT). EMT was induced using TGF-β treatment, with samples collected at defined time points representing pre-treatment, during treatment, and post-treatment stages. The RNA-seq data were generated from two breast cancer cell lines, MCF7 and MDA-MB-231, across three time points (pre-treatment Day 0, during treatment Day 6, and post-treatment Day 12) to characterise EMT-associated transcriptional changes. These data were used for differential expression analysis, visualised by volcano plots, and for proportion-based gene enrichment analysis to identify key biological pathways involved in EMT progression. The WGBS data were generated from the MCF7 cell line and consist of two datasets: (i) raw genomic DNA from the control condition (Day 0), and (ii) gold-based desorption-enriched DNA samples collected at Day 0, Day 6, and Day 12 following TGF-β treatment. The raw control WGBS data were used to quantify promoter region methylation by measuring changes in amplicon-specific β values relative to an average of three healthy controls from the Human Methylome Atlas. The desorption-enriched WGBS data enable assessment of Methylscape-associated enrichment, particularly in hypermethylated genomic regions during EMT progression. Together, this multi-omics dataset supports integrative analysis of epigenetic and transcriptional reprogramming during EMT and provides a resource for studying Methylscape dynamics in cancer progression.