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.

Single-cell sequencing approaches need to balance sensitivity, throughput and experimental complexity. Here the authors combine droplet-based microfluidics and combinatorial indexing to develop OAK, a versatile method for ultra-high throughput single-cell multiomic profiling.

Details

Title
Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling
Author
Wu, Bing 1 ; Bennett, Hayley M. 1   VIAFID ORCID Logo  ; Ye, Xin 2 ; Sridhar, Akshayalakshmi 3 ; Eidenschenk, Celine 4 ; Everett, Christine 4 ; Nazarova, Evgeniya V. 5 ; Chen, Hsu-Hsin 3 ; Kim, Ivana K. 6   VIAFID ORCID Logo  ; Deangelis, Margaret 7 ; Owen, Leah A. 8 ; Chen, Cynthia 9 ; Lau, Julia 9 ; Shi, Minyi 9 ; Lund, Jessica M. 9 ; Xavier-Magalhães, Ana 9 ; Patel, Neha 9 ; Liang, Yuxin 9 ; Modrusan, Zora 9 ; Darmanis, Spyros 9   VIAFID ORCID Logo 

 Genentech, Department of Proteomic and Genomic Technologies, South San Francisco, USA (ISNI:0000 0004 5899 3818) 
 Genentech, Department of Discovery Oncology, South San Francisco, USA (ISNI:0000 0004 5899 3818) 
 Genentech, Department of Human Pathobiology & OMNI Reverse Translation, South San Francisco, USA (ISNI:0000 0004 5899 3818) 
 Genentech, Department of Functional Genomics, South San Francisco, USA (ISNI:0000 0004 5899 3818) 
 Genentech, Department of Immunology Discovery, South San Francisco, USA (ISNI:0000 0004 5899 3818) 
 Harvard Medical School, Retina Service, Massachusetts Eye & Ear, Department of Ophthalmology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
 University at Buffalo, Department of Ophthalmology, Ross Eye Institute; Department of Biochemistry; Neuroscience Graduate Program; Genetics, Genomics and Bioinformatics Graduate Program, Jacobs School of Medicine and Biomedical Sciences, State University of New York, Buffalo, USA (GRID:grid.273335.3) (ISNI:0000 0004 1936 9887) 
 The University of Utah, Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, Salt Lake City, USA (GRID:grid.223827.e) (ISNI:0000 0001 2193 0096) 
 Genentech, Department of Proteomic and Genomic Technologies, South San Francisco, USA (GRID:grid.223827.e) (ISNI:0000 0004 5899 3818) 
Pages
9146
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3119818797
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.