Single-cell genomics assays have emerged as a dominant platform for interrogating complex biological systems. Methods to capture various properties at the single-cell level typically suffer a tradeoff between cell count and information content, which is defined by the number of unique and usable reads acquired per cell. We and others have described workflows that utilize single-cell combinatorial indexing (sci), leveraging transposase-based library construction to assess a variety of genomic properties in high throughput; however, these techniques often produce sparse coverage for the property of interest. Here, we describe a novel adaptor-switching strategy, s3, capable of producing one-to-two order-of-magnitude improvements in usable reads obtained per cell for chromatin accessibility (s3-ATAC), whole genome sequencing (s3-WGS), and whole genome plus chromatin conformation (s3-GCC), while retaining the same high-throughput capabilities of predecessor sci technologies. We apply s3 to produce high-coverage single-cell ATAC-seq profiles of mouse brain and human cortex tissue; and whole genome and chromatin contact maps for two low-passage patient-derived cell lines from a primary pancreatic tumor.

中文翻译：

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高内涵单细胞组合索引

单细胞基因组学检测已成为询问复杂生物系统的主要平台。在单细胞级别捕获各种属性的方法通常会在细胞计数和信息内容之间进行权衡，这是由每个细胞获取的唯一且可用的读数的数量来定义的。我们和其他人描述了利用单细胞组合索引（sci），利用基于转座酶的文库构建来评估高通量的各种基因组特性的工作流程。但是，这些技术通常会针对感兴趣的属性产生稀疏的覆盖范围。在这里，我们描述了一种新颖的转接器切换策略s3，它能够在染色质可及性（s3-ATAC），全基因组测序（s3-WGS）的每个细胞获得的可用读数中产生一到两个数量级的改善，以及整个基因组加上染色质构象（s3-GCC），同时保留了与先前科学技术相同的高通量功能。我们应用s3产生小鼠脑和人类皮质组织的高覆盖率单细胞ATAC-seq谱；以及来自原发性胰腺肿瘤的两种低代患者来源细胞系的全基因组和染色质接触图。