five

High-Throughput Identification of Genome-Wide Silencers in Mouse Cells Using Ss-STARR-seq

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP525049
下载链接
链接失效反馈
官方服务:
资源简介:
The majority of the mouse genome is composed of non-coding regions, which harbor numerous regulatory sequences essential for gene regulation. While extensive research has focused on enhancers that activate gene expression, the role of silencers that repress gene expression remains less explored. In this study, we conducted the first genome-wide identification of silencers in the mouse cell genome. In mouse embryonic fibroblasts (MEFs) and mouse embryonic stem cells (mESCs), we identified 89,596 and 115,165 silencers, respectively. These silencers are ubiquitously distributed across the genome and are predominantly associated with low-expression genes. Additionally, We have identified that these silencers predominantly exhibit cell-specific presence and exert their function through binding with repressive transcription factors (TFs). Furthermore, these silencers are notably enriched with the histone modification H3K9me3. In terms of biological effects, we identified a silencer within an intron of the pluripotency gene NANOG. Knockout of this silencer in (MEFs) resulted in a twofold increase in the induction efficiency of induced pluripotent stem cells (iPSCs). Collectively, our work provides the first comprehensive silencer landscape in the mouse genome and provides strong evidence for the role of silencers in the induction of iPSCs. Overall design: We identified genome-wide silencers in mouse cell lines MEFs and mESCs using Ss-STARR-seq. We then performed a joint analysis of these silencers with other multi-omics data to elucidate the fundamental characteristics of mouse silencers. Finally, we investigated the biological effects of these silencers by conducting CRISPR knockout experiments. Genome assembly mm10.
创建时间:
2025-07-02
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