Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays

Cell, Journal Year: 2022, Volume and Issue: 185(10), P. 1777 - 1792.e21

Published: May 1, 2022

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view current methodologies precludes their systematic application analyze relatively large three-dimensional mid- late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays in situ RNA capture create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq generate mouse organogenesis spatiotemporal atlas (MOSTA), which maps with single-cell high sensitivity kinetics directionality transcriptional variation during organogenesis. used this information gain insight into molecular basis cell heterogeneity fate specification developing tissues dorsal midbrain. Our panoramic will facilitate in-depth investigation longstanding questions concerning normal abnormal development.

Language: Английский

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Joint probabilistic modeling of single-cell multi-omic data with totalVI

Nature Methods, Journal Year: 2021, Volume and Issue: 18(3), P. 272 - 282

Published: Feb. 15, 2021

Language: Английский

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Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts

Science, Journal Year: 2021, Volume and Issue: 371(6532)

Published: Jan. 21, 2021

Following cancer through the body The heterogeneity of mammalian tumors has been well documented, but it remains unknown how differences between individual cells lead to metastasis and spread throughout body. Quinn et al. created a Cas9-based lineage tracer used single-cell sequencing generate phylogenies follow movement metastatic human implanted in lung mouse xenograph model. Using this model, they found that within same cell line, exhibited diverse phenotypes. These subclones differential gene expression profiles, some which were previously associated with metastasis. Science , issue p. eabc1944

Language: Английский

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Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution

Cell, Journal Year: 2022, Volume and Issue: 185(11), P. 1905 - 1923.e25

Published: May 1, 2022

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth expansion to neighboring distal tissues. The study phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout mouse model Kras;Trp53(KP)-driven lung adenocarcinoma tracked tumor from single-transformed metastatic tumors at unprecedented resolution. We found loss initial, stable alveolar-type2-like state was accompanied transient increase in plasticity. This followed adoption distinct transcriptional programs rapid and, ultimately, clonal sweep subclones capable metastasizing. Finally, develop through stereotypical evolutionary trajectories, perturbing additional suppressors accelerates progression creating novel trajectories. Our elucidates hierarchical nature more broadly, enables in-depth studies progression.

Language: Английский

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The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination

Cell, Journal Year: 2021, Volume and Issue: 184(15), P. 3915 - 3935.e21

Published: June 25, 2021

Language: Английский

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Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution

Cell, Journal Year: 2022, Volume and Issue: 185(23), P. 4428 - 4447.e28

Published: Oct. 31, 2022

Human brain development is underpinned by cellular and molecular reconfigurations continuing into the third decade of life. To reveal cell dynamics orchestrating neural maturation, we profiled human prefrontal cortex gene expression chromatin accessibility at single-cell resolution from gestation to adulthood. Integrative analyses define dynamic trajectories each type, revealing major reconfiguration prenatal-to-postnatal transition in all types followed continuous adulthood identifying regulatory networks guiding developmental programs, states, functions. We uncover links between milestones, characterize diverse timing when cells acquire adult-like identify convergence distinct origins. further their regulators implicated neurological disorders. Finally, using this reference, benchmark identities maturation states organoid models. Together, captures landscape cortical development.

Language: Английский

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Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Feb. 7, 2023

The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal including surgery, radiation therapy, and hormonal therapy. Recurrence development metastatic remains a clinical problem, without clear understanding what drives immune escape tumor progression. Here, we comprehensively describe the microenvironment localized in comparison with adjacent normal samples healthy controls. Single-cell RNA sequencing high-resolution spatial transcriptomic analyses reveal context dependent changes gene expression. Our data indicate that an suppressive associates myeloid populations exhausted T-cells, addition to high stromal angiogenic activity. We infer cell-to-cell relationships from throughput ligand-receptor interaction measurements within undissociated tissue sections. work thus provides highly detailed comprehensive resource as well tumor-stromal cell interactions.

Language: Английский

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High-resolution 3D spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae

Developmental Cell, Journal Year: 2022, Volume and Issue: 57(10), P. 1271 - 1283.e4

Published: May 1, 2022

Drosophila has long been a successful model organism in multiple biomedical fields. Spatial gene expression patterns are critical for the understanding of complex pathways and interactions, whereas temporal changes vital studying highly dynamic physiological activities. Systematic studies still impeded by lack spatiotemporal transcriptomic information. Here, utilizing spatial enhanced resolution omics-sequencing (Stereo-seq), we dissected developing with high sensitivity. We demonstrated that Stereo-seq data can be used 3D reconstruction transcriptomes embryos larvae. With these models, identified functional subregions embryonic larval midguts, uncovered cell state dynamics testis, revealed known potential regulons transcription factors within their topographic background. Our provide research community useful resources organism-wide spatiotemporally resolved information across developmental stages.

Language: Английский

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Spatiotemporal mapping of gene expression landscapes and developmental trajectories during zebrafish embryogenesis

Developmental Cell, Journal Year: 2022, Volume and Issue: 57(10), P. 1284 - 1298.e5

Published: May 1, 2022

A major challenge in understanding vertebrate embryogenesis is the lack of topographical transcriptomic information that can help correlate microenvironmental cues within hierarchy cell-fate decisions. Here, we employed Stereo-seq to profile 91 zebrafish embryo sections covering six critical time points during first 24 h development, obtaining a total 152,977 spots at resolution 10 × 15 μm3 (close cellular size) with spatial coordinates. Meanwhile, identified modules and co-varying genes for specific tissue organizations. By performing integrated analysis scRNA-seq data from each point, reconstructed spatially resolved developmental trajectories transitions molecular changes embryogenesis. We further investigated distribution ligand-receptor pairs potentially important interactions development. Our study constitutes fundamental reference studies aiming understand

Language: Английский

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Computational solutions for spatial transcriptomics

Computational and Structural Biotechnology Journal, Journal Year: 2022, Volume and Issue: 20, P. 4870 - 4884

Published: Jan. 1, 2022

Transcriptome level expression data connected to the spatial organization of cells and molecules would allow a comprehensive understanding how gene is structure function in biological systems. The transcriptomics platforms may soon provide such information. However, current still lack resolution, capture only fraction transcriptome heterogeneity, or throughput for large scale studies. strengths weaknesses ST computational solutions need be taken into account when planning basis analysis developed single-cell RNA-sequencing data, with advancements taking connectedness transcriptomes. scRNA-seq tools are modified new like deep learning-based joint expression, spatial, image extract information spatially resolved can reveal remarkable insights patterns cell signaling, type variations connection type-specific signaling complex tissues. This review covers topics that help choosing platform research. We focus on currently available methods their limitations. Of solutions, we an overview steps used analysis. compatibility types provided by frameworks summarized.

Language: Английский

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