MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices
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Abstract
Sample multiplexing facilitates scRNA-seq by reducing costs and identifying 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. When cells are classified into sample groups using MULTI-seq barcode abundances, data quality is improved through doublet identification and recovery of 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.
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Sample multiplexed scRNA-seq is an efficient method for massively parallel species-mixing experiments.
“Sample multiplexed scRNA-seq is another solution, establishing an efficient method for massively parallel species-mixing experiments [18–22].”
From Single-cell sequencing to multi-omics: technologies and applications (2024) · cites this paper as [21]
The Results section on demultiplexing reports species-specific classification of mixed human and mouse nuclei. The Results section on doublets demonstrates efficient, large-scale multiplexing of 96 human mammary epithelial cell samples, but our copy does not demonstrate a massively parallel species-mixing experiment; the claim combines features shown in separate experiments. Page numbers are unavailable in our copy. (LLM, conf=0.82)
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“Currently, the predominant approach for this technology involves tagging individual samples with DNA oligonucleotides (oligos) barcodes before pooling them together, including lipid-tagged DNA [21], chemical cross-linking reaction [19], and genetic barcodes [20].”
BackgroundAmplification of human interneuron progenitors promotes brain tumors and neurological defects
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Joint single-cell measurements of nuclear proteins and RNA in vivo
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Machine learning for perturbational single-cell omics
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Bacterial induction of B cell senescence promotes age-related changes in the gut microbiota
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Surface antigen-guided CRISPR screens identify regulators of myeloid leukemia differentiation
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Single-cell profiling of proteins and chromatin accessibility using PHAGE-ATAC
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“To identify the transgenic line origin based on fluorescent mRNA counts, we co-opted MULTIseqDemux (McGinnis et al, 2019) to assign donor identities based on the transgenic line–expressed fluorescent gene counts.”
MethodInfluentialImproved ClickTags enable live-cell barcoding for highly multiplexed single cell sequencing
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Order Matters: Ambient RNA correction confounds doublet detection in single-cell RNA sequencing
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- Authors
- McGinnis, C. S., Patterson, D. M., Winkler, J., Conrad, D. N., Hein, M. Y., Srivastava, V., Hu, J. L., Murrow, L. M., Weissman, J. S., Werb, Z., Chow, E. D., & Gartner, Z. J.
- Affiliations
- University of California, San Francisco (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Chow, Eric D.
- Gartner, Zev J.
- ORCID
- Venue
- Nature Methods
- Published
- 2019-06-17
- Volume
- 16
- Issue
- 7
- Pages
- 619-626
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC6837808
- OpenAlex
- W2951068818
- Cited by
- 643
- References
- 68
- Citations by year
- 2026: 69 · 2025: 90 · 2024: 128 · 2023: 106 · 2022: 87 · 2021: 84 · 2020: 52 · 2019: 21 · 2018: 4 · 2013: 1
- FWCI
- 20.08
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature Methods (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (1330864, 1548297)
- U.S. Department of Defense (W81XWH1011023, W81XWH, W81XWH1310221, W81XWH-13)
- Damon Runyon Cancer Research Foundation (DRG-2239-15)
- National Institutes of Health (DBI-1548297, 1s10od021822-01, W81XWH, UL1TR001872)
- University of California, San Francisco (DBI-1548297)
- National Cancer Institute (U01CA199315)
- National Institute of General Medical Sciences (T32GM007810, F32GM128366)
- National Center for Advancing Translational Sciences
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (DP2HD080351)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Keywords
- sample multiplexing, single-cell RNA sequencing, single-nucleus RNA sequencing, T cell activation, mammary epithelial cells, metastatic sites, triple-negative breast cancer, patient-derived xenografts
- MeSH terms
- Animals, Base Sequence, Humans, Lipids, Sequence Analysis, RNA, HEK293 Cells, Single-Cell Analysis, High-Throughput Nucleotide Sequencing
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