国家生物信息中心蒋岚等研究人员合作开发出，基于普适性微滴微流控组合索引的大规模多模态单细胞测序技术。2025年1月20日，《自然—方法学》杂志在线发表了这一研究成果。

研究人员表示，通过微滴微流控技术的单细胞组合索引测序方法提供了一种平衡成本、可扩展性、稳健性和可获取性的新兴方法。然而，现有方法通常需要为各个模态定制协议，限制了其自动化潜力和临床适用性。

为了解决这个问题，研究人员提出了UDA-seq，这是一种通用工作流程，整合了后期索引步骤，以提高通量并系统性地适应现有的基于微滴的单细胞多模态方法。UDA-seq在不同的组织和细胞类型中进行了基准测试，支持多种常见的多模态分析，包括单细胞RNA与VDJ、RNA与染色质以及RNA与CRISPR扰动的共测定。

值得注意的是，UDA-seq在单通道微滴微流控实验中高效地生成了来自三十多例冷冻临床活检样本的超过100000个高质量单细胞数据集。下游分析展示了该方法在识别与临床表型相关的稀有细胞亚群以及探索癌细胞脆弱性方面的稳健性。

附：英文原文

Title: UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing

Author: Li, Yun, Huang, Zheng, Xu, Lubin, Fan, Yanling, Ping, Jun, Li, Guochao, Chen, Yanjie, Yu, Chengwei, Wang, Qifei, Song, Turun, Lin, Tao, Liu, Mengmeng, Xu, Yangqing, Ai, Na, Meng, Xini, Qiao, Qin, Ji, Hongbin, Qin, Zhen, Jin, Shuo, Jiang, Nan, Wang, Minxian, Shu, Shaokun, Zhang, Feng, Zhang, Weiqi, Liu, Guang-Hui, Chen, Limeng, Jiang, Lan

Issue&Volume: 2025-01-20

Abstract: The use of single-cell combinatorial indexing sequencing via droplet microfluidics presents an attractive approach for balancing cost, scalability, robustness and accessibility. However, existing methods often require tailored protocols for individual modalities, limiting their automation potential and clinical applicability. To address this, we introduce UDA-seq, a universal workflow that integrates a post-indexing step to enhance throughput and systematically adapt existing droplet-based single-cell multimodal methods. UDA-seq was benchmarked across various tissue and cell types, enabling several common multimodal analyses, including single-cell co-assay of RNA and VDJ, RNA and chromatin, and RNA and CRISPR perturbation. Notably, UDA-seq facilitated the efficient generation of over 100,000 high-quality single-cell datasets from three dozen frozen clinical biopsy specimens within a single-channel droplet microfluidics experiment. Downstream analysis demonstrated the robustness of this approach in identifying rare cell subpopulations associated with clinical phenotypes and exploring the vulnerability of cancer cells.

DOI: 10.1038/s41592-024-02586-y

Source: https://www.nature.com/articles/s41592-024-02586-y