Single cell RNA-seq by mostly-natural sequencing by synthesis

Sean Simmons(Broad Institute), Gila Lithwick‐Yanai, Xian Adiconis(Broad Institute), Florian C. Oberstrass, Nika Iremadze, Kathryn Geiger-Schuller(Broad Institute), Pratiksha I. Thakore(Broad Institute), Chris J. Frangieh(Broad Institute), Omer Barad, Gilad Almogy, Orit Rozenblatt–Rosen(Broad Institute), Aviv Regev(Broad Institute), Doron Lipson, Joshua Z. Levin(Broad Institute)
bioRxiv (Cold Spring Harbor Laboratory)
May 29, 2022
Cited by 1Open Access
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Abstract

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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