five

Transposable Elements Lose Methylation and Gain Expression During Malignant Transformation [RNA-seq]

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP436132
下载链接
链接失效反馈
官方服务:
资源简介:
Transposable elements (TEs) are typically silenced by DNA methylation and repressive histone modifications in differentiated healthy human tissues. However, TE expression increases in a wide range of cancers and is correlated with global hypomethylation of cancer genomes. We assessed expression and DNA methylation of TEs in fibroblast cells that were serially transduced with hTERT, SV40, and HRASR24C to immortalize and then transform them, which models the different steps of the tumorigenesis process. RNA-sequencing and whole-genome bisulfite sequencing were performed at each stage of transformation. TE expression significantly increased as cells progressed through transformation, with the largest increase in expression after the final stage of transformation, consistent with data from human tumors. The upregulated TEs were dominated by endogenous retroviruses (LTRs). Most differentially methylated regions (DMRs) in all stages were hypomethylated, with the greatest hypomethylation in the final stage of transformation. A majority of the DMRs overlapped TEs from the RepeatMasker database, indicating that TEs are preferentially demethylated. Many hypomethylated TEs displayed a concordant increase in expression. Demethylation began during immortalization and continued into transformation, while upregulation of TE transcription occurred in transformation. Numerous LTR elements upregulated in the model were also identified in TCGA datasets of breast, colon, and prostate cancer. Overall, these findings indicate that transposable elements, specifically endogenous retroviruses, are demethylated and transcribed during transformation. Overall design: Comparative gene/TE expression profiling analysis of RNA-seq data for BJ fibroblast (EP) and transformation model (hTERT, SV40, HRAS)
创建时间:
2023-09-28
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作