Nature Communications (Oct 2024)

Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling

  • Bing Wu,
  • Hayley M. Bennett,
  • Xin Ye,
  • Akshayalakshmi Sridhar,
  • Celine Eidenschenk,
  • Christine Everett,
  • Evgeniya V. Nazarova,
  • Hsu-Hsin Chen,
  • Ivana K. Kim,
  • Margaret Deangelis,
  • Leah A. Owen,
  • Cynthia Chen,
  • Julia Lau,
  • Minyi Shi,
  • Jessica M. Lund,
  • Ana Xavier-Magalhães,
  • Neha Patel,
  • Yuxin Liang,
  • Zora Modrusan,
  • Spyros Darmanis

DOI
https://doi.org/10.1038/s41467-024-53227-z
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 12

Abstract

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Abstract Multiomic profiling of single cells by sequencing is a powerful technique for investigating cellular diversity. Existing droplet-based microfluidic methods produce many cell-free droplets, underutilizing bead barcodes and reagents. Combinatorial indexing on microplates is more efficient for barcoding but labor-intensive. Here we present Overloading And unpacKing (OAK), which uses a droplet-based barcoding system for initial compartmentalization followed by a second aliquoting round to achieve combinatorial indexing. We demonstrate OAK’s versatility with single-cell RNA sequencing as well as paired single-nucleus RNA sequencing and accessible chromatin profiling. We further showcase OAK’s performance on complex samples, including differentiated bronchial epithelial cells and primary retinal tissue. Finally, we examine transcriptomic responses of over 400,000 melanoma cells to a RAF inhibitor, belvarafenib, discovering a rare resistant cell population (0.12%). OAK’s ultra-high throughput, broad compatibility, high sensitivity, and simplified procedures make it a powerful tool for large-scale molecular analysis, even for rare cells.