美国麻省理工学院和哈佛大学博德研究所Joshua Z. Levin研究组的一项最新研究提出，使用Ultima测序的scRNA-seq主要是自然合成测序。相关论文发表在2022年9月15日出版的《自然—生物技术》杂志上。

他们介绍了一种主要用于单细胞RNA 测序(scRNA-seq)的自然合成测序(mnSBS)方法，该方法适用于Ultima基因组学平台，并系统地将其与当前的scRNA-seq技术进行基准测试。mnSBS主要使用天然的、未修饰的核苷酸，并且仅使用一小部分荧光标记的核苷酸，从而实现了高聚合酶的持续合成能力并降低了成本。他们在四个不同技术和生物学类型的scRNA-seq案例研究中展示了成功的应用，包括5'和3'scRNA-seq、来自单个个体和多重的人外周血单核细胞，以及Perturb-Seq。

基准测试表明，基于mnSBS的scRNA-seq的结果与使用Illumina测序的结果非常相似，由于Ultima的单端读数更接近基因末端，因此与相对于注释基因边界的读数位置相关的结果略有不同比从Illumina读取。因此，该方法与独立于测序技术的最先进的scRNA-seq文库兼容。他们预计mnSBS对于具有成本效益的大规模scRNA-seq项目特别有用。

附：英文原文

Title: Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

Author: Simmons, Sean K., Lithwick-Yanai, Gila, Adiconis, Xian, Oberstrass, Florian, Iremadze, Nika, Geiger-Schuller, Kathryn, Thakore, Pratiksha I., Frangieh, Chris J., Barad, Omer, Almogy, Gilad, Rozenblatt-Rosen, Orit, Regev, Aviv, Lipson, Doron, Levin, Joshua Z.

Issue&Volume: 2022-09-15

Abstract: Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural, unmodified nucleotides and only a low fraction of fluorescently labeled nucleotides, which allows for high polymerase processivity and lower costs. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5′ and 3′ scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Benchmarking shows that results from mnSBS-based scRNA-seq are very similar to those using Illumina sequencing, with minor differences in results related to the position of reads relative to annotated gene boundaries, owing to single-end reads of Ultima being closer to gene ends than reads from Illumina. The method is thus compatible with state-of-the-art scRNA-seq libraries independent of the sequencing technology. We expect mnSBS to be of particular utility for cost-effective large-scale scRNA-seq projects.

DOI: 10.1038/s41587-022-01452-6

Source: https://www.nature.com/articles/s41587-022-01452-6