小柯机器人

美国霍华德休斯医学研究所Steven Henikoff团队近期取得重要工作进展，他们研究使用MulTI-Tag在单细胞分辨率下对表观遗传概况进行多因素分析。相关论文2022年10月31日在线发表于《自然—生物技术》杂志上。

研究人员通过标记进行多靶点识别（MulTI-Tag），这是一种抗体条形码方法，用于在单个细胞中同时分析多个染色质特征。研究人员对MulTI-Tag进行了优化，以保持高灵敏度和特异性。他们证明在同一个细胞中最多可以检测三种组蛋白修饰：H3K27me3、H3K4me1/2和H3K36me3。研究人员应用MulTI-Tag来分辨不同的细胞类型和发育轨迹；区分与分化结果相关的活性和抑制性元素调节使用的独特、协调模式；发现组蛋白标记之间的关联。多因素表观遗传学分析为全面描述发育和疾病中的细胞特异性基因调控图谱带来了希望。

据介绍 ，位点分辨率的染色质分析发现定义细胞类型和发育轨迹的基因调控特征，但在同一样本中绘制和比较不同的染色质相关蛋白仍然具有挑战性。

附：英文原文

Title: Multifactorial profiling of epigenetic landscapes at single-cell resolution using MulTI-Tag

Author: Meers, Michael P., Llagas, Geneva, Janssens, Derek H., Codomo, Christine A., Henikoff, Steven

Issue&Volume: 2022-10-31

Abstract: Chromatin profiling at locus resolution uncovers gene regulatory features that define cell types and developmental trajectories, but it remains challenging to map and compare different chromatin-associated proteins in the same sample. Here we describe Multiple Target Identification by Tagmentation (MulTI-Tag), an antibody barcoding approach for profiling multiple chromatin features simultaneously in single cells. We optimized MulTI-Tag to retain high sensitivity and specificity, and we demonstrate detection of up to three histone modifications in the same cell: H3K27me3, H3K4me1/2 and H3K36me3. We apply MulTI-Tag to resolve distinct cell types and developmental trajectories; to distinguish unique, coordinated patterns of active and repressive element regulatory usage associated with differentiation outcomes; and to uncover associations between histone marks. Multifactorial epigenetic profiling holds promise for comprehensively characterizing cell-specific gene regulatory landscapes in development and disease.

DOI: 10.1038/s41587-022-01522-9

Source: https://www.nature.com/articles/s41587-022-01522-9

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex