five

CLEAR: Coverage-based Limiting-cell Experiment Analysis for RNA-seq (human)

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NIAID Data Ecosystem2026-04-25 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP149203
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Direct cDNA preamplification protocols developed for single-cell RNA-seq (scRNA-seq) have enabled transcriptome profiling of rare cells without having to pool multiple samples or to perform RNA extraction. We term this approach limiting-cell RNA-seq (lcRNA-seq). Unlike scRNA-seq, which focuses on 'cell-atlasing', lcRNA-seq focuses on identifying differentially expressed genes (DEGs) between experimental groups. This requires accounting for systems noise which can obscure biological differences. We present CLEAR, a workflow that identifies robust transcripts in lcRNA-seq data for between-group comparisons. To develop CLEAR, we compared DEGs from FACS-derived CD5+ and CD5- cells from a chronic lymphocytic leukemia patient at different input RNA levels. When using CLEAR transcripts vs. using all available transcripts, downstream analyses reveal more consistent DEGs, improved Principal Component Analysis separation by cell type, and consistency across input RNA amounts. CLEAR also performs well on external sc- and lcRNA-seq data and an internal murine neural cell lcRNA-seq data set. Overall design: Total RNA from human CLL B cells was quantified using the Invitrogen Qubit RNA HS Assay kit (Invitrogen, Carlsbad, CA) and serially diluted to masses characteristic of single- and low cell number RNA-Seq (10-, 100-, and 1000-pg). The Clontech SMARTer v4 kit (Takara Bio USA, Inc., Mountain View, CA) was used for global preamplification in serially diluted CD5+/CD5- RNA prior to library generation at triplicate with the Nextera XT DNA Library Prep kit (Illumina, Inc., San Diego, CA).
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2020-02-21
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