Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing

Nat Methods. 2021 Jun;18(6):635-642. doi: 10.1038/s41592-021-01153-z. Epub 2021 May 31.

Abstract

Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed 'single-cell combinatorial fluidic indexing' (scifi). The scifi-RNA-seq assay combines one-step combinatorial preindexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Preindexing allows us to load several cells per droplet and computationally demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared with multiround combinatorial indexing, scifi-RNA-seq provides an easy and efficient workflow. Compared to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets. We benchmarked scifi-RNA-seq on various human and mouse cell lines, validated it for primary human T cells and applied it in a highly multiplexed CRISPR screen with single-cell transcriptome readout of T cell receptor activation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Line
  • Clustered Regularly Interspaced Short Palindromic Repeats
  • Cost-Benefit Analysis
  • Gene Expression Profiling / methods
  • High-Throughput Nucleotide Sequencing / economics
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mice
  • Microfluidics / methods
  • Receptors, Antigen, T-Cell / genetics
  • Single-Cell Analysis / economics
  • Single-Cell Analysis / methods
  • Transcriptome

Substances

  • Receptors, Antigen, T-Cell