MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices
| Autor: | Marco Y. Hein, Eric D. Chow, Jennifer L. Hu, Daniel N. Conrad, Lyndsay M. Murrow, Vasudha Srivastava, David M. Patterson, Christopher S. McGinnis, Jonathan S. Weissman, Juliane Winkler, Zev J. Gartner, Zena Werb |
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| Rok vydání: | 2018 |
| Předmět: |
Cell type
Sequence analysis Cell genetic processes Computational biology Biology Barcode Biochemistry Multiplexing Article law.invention 03 medical and health sciences law medicine Animals Humans Multiplex natural sciences Molecular Biology 030304 developmental biology 0303 health sciences Base Sequence Sequence Analysis RNA HEK 293 cells RNA High-Throughput Nucleotide Sequencing Cell Biology Lipids medicine.anatomical_structure HEK293 Cells Single-Cell Analysis Biotechnology |
| Zdroj: | Nature methods. 16(7) |
| ISSN: | 1548-7105 |
| Popis: | Sample multiplexing facilitates scRNA-seq by reducing costs and artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-tagged indices for single-cell and single-nucleus RNA sequencing. MULTI-seq reagents can barcode any cell type or nucleus from any species with an accessible plasma membrane. The method involves minimal sample processing, thereby preserving cell viability and endogenous gene expression patterns. MULTI-seq enables doublet identification, which improves data quality and increases cell throughput by minimizing the negative consequences of Poisson droplet loading. MULTI-seq sample classifications additionally identify cells with low RNA content that would otherwise be discarded by standard quality-control workflows. We use MULTI-seq to track the dynamics of T-cell activation, perform a 96-plex perturbation experiment with primary human mammary epithelial cells, and multiplex cryopreserved tumors and metastatic sites isolated from a patient-derived xenograft mouse model of triple-negative breast cancer. |
| Databáze: | OpenAIRE |
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