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

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. We generated and analysed single cell RNA-seq (10x Chromium) data for 4 samples. 1) PBMC sample with 3' technology, 2) PBMC sample (same as 1) with 5' single cell technology, 3) a mixture of PBMCs from 8 individuals with 5' technology, and 4) a mixture of 8 Perturb-seq samples (mixed using cell hashing) with 3' technology. For each we sequenced with both Illumina and Ultima sequencing.