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Droplet-based Single-cell Total RNA-seq Reveals Differential Non-Coding Expression and Splicing Patterns during Mouse Development

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NIAID Data Ecosystem2026-03-14 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176588
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Single-cell RNA-seq is one of the most important and widely used approaches to characterize cell types and to understand major parts of biological systems. As of today, most methods are only able to capture parts of the whole transcriptome, mainly the protein-coding genes, and therefore lack information about non-coding biotypes or full-length transcripts. Here, we present “Vast transcriptome Analysis of Single-cells by dA-tailing (VASA-seq)”, a method for highly-sensitive, full-length and total RNA-seq in single-cells. VASA-seq is compatible with plate-formats for sorting of rare cell populations, and with droplet microfluidics for high-throughput applications and atlasing. We applied VASA-seq to >30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. Our in-depth analysis revealed expression of novel cell-type specific non-coding RNA markers, enhanced cell-cycle characterization and alternative splicing patterns. We believe the method and mouse dataset will serve as a useful tool to further investigate the expression of different RNA biotypes and splicing patterns in large datasets. total RNA sequencing data (VASA-seq) from Hek293T cells, mES cells and E6.5, E7.5, E8.5 and E9.5 mouse embryo
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2023-01-06
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