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A scalable, low cost, multi-omic interrogation and sample hashing workflow for single-cell analysis using the Seq-Well S3 platform

GSE266385 Homo sapiens Expression profiling by high throughput sequencing; Other 9 samples Submitted 2024/05/02 Platform GPL30173
Summary
Clinical samples promise unparalleled insights into the cellular mechanisms that underlie pathological conditions and therapeutic responses. However, they often can be precious, with few cells available for single-cell analysis, necessitating effort to maximize the amount of information that can be garnered from each. Here, we introduce a low material input, cost-effective protocol for conducting multi-omic analyses and sample hashing on single-cell suspensions using the Seq-Well S3 platform. Our protocol, designed to be both accessible and affordable, leverages readily available reagents and standard laboratory equipment, significantly lowering barriers to entry for researchers in low- and middle-income countries. The method detailed herein offers a streamlined and efficient workflow for: (1) precise staining of single-cell suspensions with antibody-oligo conjugates for accurate cell surface protein identification and effective sample multiplexing; (2) reliable generation of Seq-Well S3 sequencing libraries; (3) optional generation of bulk-RNA sequencing libraries through an optimized SMART-seq2 protocol; and, (4) robust computational pipelines for in-depth multi-omic data analysis. This protocol works with fragile and limited cell inputs (here, outlined for 15,000 cells per 200 µL - a fraction of the input required by most commercial methods). It also offers significant cost and time savings, with the entire process from cell isolation to sequencing taking only 3-6 days, plus an additional 1-2 days for data processing. In sum, this generally applicable pipeline empowers researchers around the globe to apply single-cell multiomics to advance their own research agendas.
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Direct links to NCBI, no account and no request form: the whole study as GSE266385_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 9 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1106889 and SRA study SRP505229. Searching any of these in the dataset finder brings you back here.

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