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Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state

机译:单细胞ChIP-seq显示由染色质状态定义的细胞亚群

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Chromatin profiling provides a versatile means to investigate functional genomic elements and their regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. Here we combine microfluidics, DNA barcoding and sequencing to collect chromatin data at single-cell resolution. We demonstrate the utility of the technology by assaying thousands of individual cells and using the data to deconvolute a mixture of ES cells, fibroblasts and hematopoietic progenitors into high-quality chromatin state maps for each cell type. The data from each single cell are sparse, comprising on the order of 1,000 unique reads. However, by assaying thousands of ES cells, we identify a spectrum of subpopulations defined by differences in chromatin signatures of pluripotency and differentiation priming. We corroborate these findings by comparison to orthogonal single-cell gene expression data. Our method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone.
机译:染色质谱分析为研究功能基因组元件及其调控提供了一种通用手段。但是,当前的方法产生的整体轮廓对细胞间的变化不敏感。在这里,我们结合微流控技术,DNA条形码和测序技术,以单细胞分辨率收集染色质数据。我们通过分析成千上万的单个细胞并使用数据将ES细胞,成纤维细胞和造血祖细胞的混合物解卷积为每种细胞类型的高质量染色质状态图,证明了该技术的实用性。来自每个单个单元的数据稀疏,包括大约1000次唯一读取。但是,通过分析成千上万个ES细胞,我们确定了由多能性和分化启动染色质特征不同的亚群。我们通过与正交单细胞基因表达数据进行比较来证实这些发现。我们用于单细胞分析的方法揭示了表观遗传异质性的各个方面,这些方面不能仅通过转录分析来捕获。

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