bioRxivMolecular BiologyPreprint
Single-Molecule Barcoding Technology for Single-Cell Genomics
Ivan García-BassetsiD, Guoya Mo, Yu XiaiD, Tsai-Chin Wu, Immanuel MekuriaiD, Veronika MikhaylovaiD, Madison Rzepka, Tetsuya Kawamura, Peter L. ChangiD, Amber Paasch, Long Pham, Surya Shiv Venugopal, Sandra Patricia SancheziD, Janaína Sena de SouzaiD, Likun YaoiD, Sifeng GuiD, Zsolt BodaiiD, Alexis C. KomoriD, Alysson Renato MuotriiD, Joy WangiD, Yong WangiD, Ming LeiiD, Angels Almenar‐QueraltiD, Zhoutao Chen
Abstract
Recent advances in barcoding technologies have significantly enhanced the scalability of single-cell genomic experiments. However, large-scale experiments are still rare due to high costs, complex logistics, and laborintensive procedures. To facilitate the routine application of the largest scalability, it is critical to simplify the production and use of barcoding reagents. Here, we introduce AmpliDrop, a technology that initiates the barcoding process using a pool of inexpensive single-copy barcodes and integrates barcode multiplicity generation with tagging of cellular content into a single reaction driven by DNA polymerase during library preparation. The barcoding reactions are compartmentalized using an electronic pipette or a robotic or standalone liquid handling system. These innovations eliminate the need for barcoded beads and complex combinatorial indexing workflows and provide flexibility for a wide range of scales and tube formats, as well as compatibility with automation. We show that AmpliDrop is capable of capturing transcriptomes and chromatin accessibility, and it can also be adapted for user-customized applications, including antibody-based protein detection, bacterial or viral DNA detection, and CRISPR perturbations without dual guide RNA-expression vectors. We validated AmpliDrop by investigating the influence of short-term static culturing on cell composition in human forebrain organoids, revealing metabolic reprogramming in lineage progenitors.
- organism: human
- assay: scRNA-seq
- assay: scATAC-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: perturbation response prediction
- research focus: software / tool
- approach: experimental assay
- Citations
- 0
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