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基于纳米孔的组合索引进行 Atlas 规模单细胞染色质可及性研究。

Atlas-scale single-cell chromatin accessibility using nanowell-based combinatorial indexing.

机构信息

Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA.

ScaleBio, San Diego, California 92121, USA.

出版信息

Genome Res. 2023 Feb;33(2):208-217. doi: 10.1101/gr.276655.122. Epub 2023 Feb 15.

Abstract

Here we present advancements in single-cell combinatorial indexed Assay for Transposase Accessible Chromatin (sciATAC) to measure chromatin accessibility that leverage nanowell chips to achieve atlas-scale cell throughput (>10 cells) at low cost. The platform leverages the core of the sciATAC workflow where multiple indexed tagmentation reactions are performed, followed by pooling and distribution to a second set of reaction wells for polymerase chain reaction (PCR)-based indexing. In this work, we instead leverage a chip containing 5184 nanowells at the PCR stage of indexing, enabling a 52-fold improvement in scale and reduction in per-cell preparation costs. We detail three variants that balance cell throughput and depth of coverage, and apply these methods to banked mouse brain tissue, producing maps of cell types as well as neuronal subtypes that include integration with existing single-cell Assay for Transposase Accessible Chromatin (scATAC) and scRNA-seq data sets. Our optimized workflow achieves a high fraction of reads that fall within called peaks (>80%) and low cell doublet rates. The high cell coverage technique produces high unique reads per cell, while retaining high enrichment for open chromatin regions, enabling the assessment of >70,000 unique accessible loci on average for each cell profiled. When compared to current methods in the field, our technique provides similar or superior per-cell information with very low levels of cell-to-cell cross talk, and achieves this at a cost point much lower than existing assays.

摘要

在这里,我们展示了单细胞组合索引转座酶可及染色质分析(sciATAC)的进展,该方法用于测量染色质可及性,利用纳米孔芯片以低成本实现图谱规模的细胞通量(>10 个细胞)。该平台利用了 sciATAC 工作流程的核心,其中进行了多次索引的标签酶切反应,然后进行混合并分配到第二组反应孔中进行基于聚合酶链反应(PCR)的索引。在这项工作中,我们在索引的 PCR 阶段利用了一个包含 5184 个纳米孔的芯片,从而将规模扩大了 52 倍,并降低了每个细胞的准备成本。我们详细介绍了三种平衡细胞通量和覆盖深度的变体,并将这些方法应用于银行存储的小鼠脑组织,生成了细胞类型图谱以及包括与现有单细胞转座酶可及染色质分析(scATAC)和 scRNA-seq 数据集整合的神经元亚型图谱。我们优化的工作流程实现了高比例的落在已调用峰内的读取(>80%)和低细胞二聚体率。高细胞覆盖技术产生了每个细胞的高独特读取,同时保留了开放染色质区域的高富集度,从而能够评估每个细胞平均 >70,000 个独特的可及基因座。与该领域当前的方法相比,我们的技术以比现有检测方法低得多的成本提供了类似或更优的单细胞信息,并且细胞间串扰非常低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aa0/10069466/dbe2caa9d536/208f01.jpg

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