近日，美国麻省理工学院和哈佛大学教授Jason D. Buenrostro及数字生物集团Ronald Lebofsky研究团队，研制了基于液滴的大规模单细胞染色质可达性组合索引。 相关论文发表在2019年8月出版的《自然—生物技术》杂志上。

该项研究中，该课题组研究人员开发了一种高质量（每个细胞10⁵个核片段）的基于液滴 - 微流控的方法，用于单细胞染色质开放性分析。研究者通过这种液滴单细胞分析方法，对转座酶可接近的染色质测序（dscATAC-seq），进而测定了46,653个成年小鼠大脑的细胞，用于细胞类型和调控序列的无偏发现。小组通过与组合标引测序（dsciATAC-seq）相结合，进一步提高了该平台的通量，从而实现了大规模的单细胞研究。研究小组测定了136,463个处在静息和刺激状态的人体骨髓来源细胞的染色质易访问性，在单细胞水平上揭示了不同细胞类型及处在不同刺激条件下，顺式和反式调控的变化规律，证明了该方法的实用性。总的来说，该课题组研究人员绘制了510,123个单细胞特征图谱，证明这个液滴平台的可扩展性和灵活性。

据悉，伴随科学技术的进步，单细胞水平表观基因组图谱的绘制得到了有效发展。然而现有方法的通量与质量限制了其应用范围。

附：英文原文

Title: Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility

Author: Caleb A. Lareau, Fabiana M. Duarte, Jennifer G. Chew, Vinay K. Kartha, Zach D. Burkett, Andrew S. Kohlway, Dmitry Pokholok, Martin J. Aryee, Frank J. Steemers, Ronald Lebofsky, Jason D. Buenrostro

Issue&Volume: Volume 37，Issue8

Abstract: Recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution; however, the throughput and quality of these methods have limited their widespread adoption. Here we describe a high-quality (105 nuclear fragments per cell) droplet-microfluidics-based method for single-cell profiling of chromatin accessibility. We use this approach, named droplet single-cell assay for transposase-accessible chromatin using sequencing (dscATAC-seq), to assay 46,653 cells for the unbiased discovery of cell types and regulatory elements in adult mouse brain. We further increase the throughput of this platform by combining it with combinatorial indexing (dsciATAC-seq), enabling single-cell studies at a massive scale. We demonstrate the utility of this approach by measuring chromatin accessibility across 136,463 resting and stimulated human bone marrow-derived cells to reveal changes in the cis- and trans-regulatory landscape across cell types and under stimulatory conditions at single-cell resolution. Altogether, we describe a total of 510,123 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

DOI: 10.1038/s41587-019-0147-6

Source:https://www.nature.com/articles/s41587-019-0147-6