English

An optimized protocol for single cell transcriptional profiling by combinatorial indexing

Genomics 2022-01-07 v4

Abstract

Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a "tiny sci-*" protocol for experiments where input is extremely limited.

Keywords

Cite

@article{arxiv.2110.15400,
  title  = {An optimized protocol for single cell transcriptional profiling by combinatorial indexing},
  author = {Beth K. Martin and Chengxiang Qiu and Eva Nichols and Melissa Phung and Rula Green-Gladden and Sanjay Srivatsan and Ronnie Blecher-Gonen and Brian J. Beliveau and Cole Trapnell and Junyue Cao and Jay Shendure},
  journal= {arXiv preprint arXiv:2110.15400},
  year   = {2022}
}

Comments

fixed a couple errors

R2 v1 2026-06-24T07:16:45.265Z