Single cell RNA-seq by mostly-natural sequencing by synthesis
Sean SimmonsiD, Gila Lithwick‐YanaiiD, Xian AdiconisiD, Florian C. Oberstrass, Nika IremadzeiD, Kathryn Geiger-SchulleriD, Pratiksha I. Thakore, Chris J. FrangiehiD, Omer BaradiD, Gilad Almogy, Orit Rozenblatt–RoseniD, Aviv RegeviD, Doron LipsoniD, Joshua Z. LeviniD
Abstract
Massively parallel single cell RNA-seq (scRNA-seq) for diverse applications, from cell atlases to functional screens, is increasingly limited by sequencing costs, and large-scale low-cost sequencing can open many additional applications, including patient diagnostics and drug screens. Here, we adapted and systematically benchmarked a newly developed, mostly-natural sequencing by synthesis method for scRNA-seq. 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. Our data show comparable results to existing technology, including compatibility with state-of-the-art scRNA-seq libraries independent of the sequencing technology used - thus providing an enhanced cost-effective path for large scale scRNA-seq.
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