five

Robust detection of chromosomal contacts from small cell numbers using low-input Capture-C. Mus musculus

收藏
NIAID Data Ecosystem2026-03-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA387734
下载链接
链接失效反馈
官方服务:
资源简介:
Chromosome conformation capture (3C) techniques are crucial to understanding tissue-specific regulation of gene expression, but current methods generally require large numbers of cells. This hampers the investigation of chromatin structure in rare cell populations. We present two new low-input Capture-C protocols that generate high-quality, reproducible interaction profiles from fewer than 20,000 cells, and show that these are not biased by PCR amplification or the degree of formaldehyde fixation. Overall design: The Capture-C technologies combine 3C library preparation with oligonucleotide capture for the desired viewpoint restriction fragments. In this case, the promoters of alpha-globin, beta-globin and Slc25a37 were used as viewpoints. To optimise Capture-C technology for small cell numbers, we developed Low-Input (LI) Capture-C and Tag-Capture-C, and performed experiments with both protocols using 200 ng, 100 ng and 50 ng mouse erythroid 3C libraries, all in triplicates. In the reduced cross-linking experiments, we compared NG Capture-C interactions profiles generated from primary mouse erythroid cells fixed with 5%, 4%, 3%, 2%, 1%, 0.5% or 0% formaldehyde. Experiments were performed in technical duplicates.

染色质构象捕获(Chromosome conformation capture, 3C)技术对于解析组织特异性基因表达调控机制至关重要,但现有方法通常需要大量细胞,这极大限制了对稀有细胞群体中染色质结构的研究。本研究开发了两种新型低起始量捕获C(Capture-C)实验方案,可从不足20000个细胞中获取高质量、可重复的染色质相互作用图谱,且研究表明该方案不受PCR扩增或甲醛固定程度的影响。实验整体设计:捕获C(Capture-C)技术将3C文库制备与针对目标视角限制性酶切片段的寡核苷酸捕获技术相结合。本研究中,我们以α-珠蛋白、β-珠蛋白及Slc25a37的启动子作为视角位点。为优化捕获C技术以适配少量细胞样本,我们开发了低起始量(LI)捕获C(Capture-C)与标签捕获C(Tag-Capture-C)两种方案,并分别使用200 ng、100 ng、50 ng的小鼠红系3C文库对两种方案进行实验验证,每组均设置三次重复。在降低交联强度的实验中,我们比较了用5%、4%、3%、2%、1%、0.5%或0%甲醛固定的原代小鼠红系细胞所产生的NG捕获C(Capture-C)相互作用图谱,实验均设置技术重复两次。
创建时间:
2017-05-24
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