MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing
Abstract
Human tissues comprise trillions of cells that populate a complex space of molecular phenotypes and functions and that vary in abundance by 4-9 orders of magnitude. Relying solely on unbiased sampling to characterize cellular niches becomes infeasible, as the marginal utility of collecting more cells diminishes quickly. Furthermore, in many clinical samples, the relevant cell types are scarce and efficient processing is critical. We developed an integrated pipeline for index sorting and massively parallel single-cell RNA sequencing (MARS-seq2.0) that builds on our previously published MARS-seq approach. MARS-seq2.0 is based on >1 million cells sequenced with this pipeline and allows identification of unique cell types across different tissues and diseases, as well as unique model systems and organisms. Here, we present a detailed step-by-step procedure for applying the method. In the improved procedure, we combine sub-microliter reaction volumes, optimization of enzymatic mixtures and an enhanced analytical pipeline to substantially lower the cost, improve reproducibility and reduce well-to-well contamination. Data analysis combines multiple layers of quality assessment and error detection and correction, graphically presenting key statistics for library complexity, noise distribution and sequencing saturation. Importantly, our combined FACS and single-cell RNA sequencing (scRNA-seq) workflow enables intuitive approaches for depletion or enrichment of cell populations in a da…
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Expression libraries were produced with a minimum of three replicates per population.
“developed for scRNA-seq to produce expression libraries with a minimum of three replicates per population.”
From Cross-Species Single-Cell Analysis Reveals Divergence of the Primate Microglia Program (2019) · cites this paper as Keren-Shaul et al., 2019
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- Authors
- Keren-Shaul, H., Kenigsberg, E., Jaitin, D. A., David, E., Paul, F., Tanay, A., & Amit, I.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Weizmann Institute of Science (IL)
- Corresponding author
- Tanay, Amos
- Amit, Ido
- Venue
- Nature Protocols
- Published
- 2019-05-17
- Volume
- 14
- Issue
- 6
- Pages
- 1841-1862
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2945489451
- Cited by
- 292
- References
- 21
- Citations by year
- 2026: 24 · 2025: 38 · 2024: 57 · 2023: 46 · 2022: 44 · 2021: 42 · 2020: 37 · 2019: 4
- FWCI
- 10.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Nature
- 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 › Gene expression and cancer classification
- Keywords
- single-cell RNA sequencing, FACS cell sorting, cell type annotation, rare cell populations, library complexity
- MeSH terms
- Animals, Cell Line, Flow Cytometry, Humans, RNA, Software, Reproducibility of Results, Gene Library, Gene Expression Profiling, Mice, Workflow, Single-Cell Analysis, High-Throughput Nucleotide Sequencing
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