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一种超低输入本底的免疫共沉淀测序(ChIP-seq)技术,用于对稀有细胞群体进行全基因组分析。

An ultra-low-input native ChIP-seq protocol for genome-wide profiling of rare cell populations.

机构信息

Department of Medical Genetics, Life Sciences Institute, The University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z3.

1] Department of Medical Genetics, Life Sciences Institute, The University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z3 [2] Biomedical Research Centre, The University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z3.

出版信息

Nat Commun. 2015 Jan 21;6:6033. doi: 10.1038/ncomms7033.

Abstract

Combined chromatin immunoprecipitation and next-generation sequencing (ChIP-seq) has enabled genome-wide epigenetic profiling of numerous cell lines and tissue types. A major limitation of ChIP-seq, however, is the large number of cells required to generate high-quality data sets, precluding the study of rare cell populations. Here, we present an ultra-low-input micrococcal nuclease-based native ChIP (ULI-NChIP) and sequencing method to generate genome-wide histone mark profiles with high resolution from as few as 10(3) cells. We demonstrate that ULI-NChIP-seq generates high-quality maps of covalent histone marks from 10(3) to 10(6) embryonic stem cells. Subsequently, we show that ULI-NChIP-seq H3K27me3 profiles generated from E13.5 primordial germ cells isolated from single male and female embryos show high similarity to recent data sets generated using 50-180 × more material. Finally, we identify sexually dimorphic H3K27me3 enrichment at specific genic promoters, thereby illustrating the utility of this method for generating high-quality and -complexity libraries from rare cell populations.

摘要

联合染色质免疫沉淀和下一代测序(ChIP-seq)已经能够对许多细胞系和组织类型进行全基因组表观遗传谱分析。然而,ChIP-seq 的一个主要限制是需要大量的细胞来生成高质量的数据集,从而排除了对稀有细胞群体的研究。在这里,我们提出了一种超低输入微球菌核酸酶的天然 ChIP(ULI-NChIP)和测序方法,从少至 10³个细胞即可生成具有高分辨率的全基因组组蛋白标记图谱。我们证明,ULI-NChIP-seq 可以从 10³到 10⁶个胚胎干细胞中生成共价组蛋白标记的高质量图谱。随后,我们表明,从单个雄性和雌性胚胎中分离的 E13.5 原始生殖细胞生成的 ULI-NChIP-seq H3K27me3 图谱与最近使用 50-180 倍以上的材料生成的数据集高度相似。最后,我们鉴定了特定基因启动子上存在性二态性 H3K27me3 富集,从而说明了该方法在从稀有细胞群体中生成高质量和高复杂度文库方面的实用性。

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