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Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq]

ABSTRACT: Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq]

PROVIDER: PRJNA1107394 | ENA |

REPOSITORIES: ENA

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Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add]

Project description:Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add]

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Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq]

Project description:During early mammalian development, the endoderm layer undergoes complex patterning to form the foundations of the respiratory and digestive systems. This intricate process, guided by a series of cell fate decisions, remains only partially understood. Our research introduces a pioneering genetic tracing code across 14 distinct endodermal regions by developing a group of mouse strains. By integrating high-throughput and high-precision single-cell RNA sequencing with sophisticated imaging techniques across various mouse models, we comprehensively resolve the spatiotemporal and genetic lineage differentiation processes of the endoderm at a single-cell resolution. Our findings reveal a previously unrecognized multipotentiality within early endodermal regions for differentiation into diverse organ primordia. Furthermore, this research illuminates the complex and underestimated phenomenon of multiple origins in the development of endodermal organs, prompting a reevaluation of differentiation models for these organs. This work not only advances our understanding of developmental biology, but also has significant implications for regenerative medicine and the development of organoid models, providing new insights into the intricate mechanisms that guide organogenesis.

2025-01-16 | GSE266496 | GEO

Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add]

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Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [10X]

Project description:We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow via robotic implementation and established best practices to consistently achieve high cell capture efficiency and data quality. In comparison with the 10X platform, HT Smart-seq3 analysis of primary CD4+ T-cells demonstrated superior sensitivity in gene detection and similar capability to capture major cellular heterogeneity upon sufficient scaling up. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified more productive pairs of alpha and beta chains without additional primer design, enabling more comprehensive profiling of TCRs. Collectively, HT Smart-seq3 provides a cost-effective and scalable method for characterization of single-cell transcriptomes and immune repertoires.

2024-07-02 | GSE270917 | GEO

Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [Bulk]

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Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 [HT SS3]

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Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [10x-v3-RNA-seq]

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K562+mESC Smart-seq3

Project description:Single cell sequencing with Smart-seq3 of K562 and mESC cells

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Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution

Project description:Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution

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Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3

Project description:Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

2020-04-14 | E-MTAB-8735 | biostudies-arrayexpress

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