scholarly journals Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis

2021 ◽  
Author(s):  
T. Lohoff ◽  
S. Ghazanfar ◽  
A. Missarova ◽  
N. Koulena ◽  
N. Pierson ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Target Genes ◽  
Single Cells ◽  
Cell Types ◽  
Spatial Context ◽  
Cell Fate Decisions ◽  
Spatially Resolved ◽  
Regulatory Processes ◽  
Cell Transcriptome

AbstractMolecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8–12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain–hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal–ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.

scholarly journals Highly multiplexed spatially resolved gene expression profiling of mouse organogenesis

2020 ◽  
Author(s):  
T. Lohoff ◽  
S. Ghazanfar ◽  
A. Missarova ◽  
N. Koulena ◽  
N. Pierson ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Single Cell ◽  
Cell Fate ◽  
Target Genes ◽  
Single Cells ◽  
Spatial Context ◽  
Sequencing Data ◽  
Cell Fate Decisions ◽  
Spatially Resolved

AbstractTranscriptional and epigenetic profiling of single-cells has advanced our knowledge of the molecular bases of gastrulation and early organogenesis. However, current approaches rely on dissociating cells from tissues, thereby losing the crucial spatial context that is necessary for understanding cell and tissue interactions during development. Here, we apply an image-based single-cell transcriptomics method, seqFISH, to simultaneously and precisely detect mRNA molecules for 387 selected target genes in 8-12 somite stage mouse embryo tissue sections. By integrating spatial context and highly multiplexed transcriptional measurements with two single-cell transcriptome atlases we accurately characterize cell types across the embryo and demonstrate how spatially-resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary and the developing gut tube. Our spatial atlas uncovers axes of resolution that are not apparent from single-cell RNA sequencing data – for example, in the gut tube we observe early dorsal-ventral separation of esophageal and tracheal progenitor populations. In sum, by computationally integrating high-resolution spatially-resolved gene expression maps with single-cell genomics data, we provide a powerful new approach for studying how and when cell fate decisions are made during early mammalian development.

scholarly journals High-throughput single-cell transcriptomics reveals the female germline differentiation trajectory in Arabidopsis thaliana

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhimin Hou ◽  
Yanhui Liu ◽  
Man Zhang ◽  
Lihua Zhao ◽  
Xingyue Jin ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Single Cell ◽  
Cell Fate ◽  
Single Cells ◽  
Expression Patterns ◽  
Cell Types ◽  
Developmental Time ◽  
Developmental Trajectory ◽  
Germline Differentiation ◽  
Female Germline

AbstractFemale germline cells in flowering plants differentiate from somatic cells to produce specialized reproductive organs, called ovules, embedded deep inside the flowers. We investigated the molecular basis of this distinctive developmental program by performing single-cell RNA sequencing (scRNA-seq) of 16,872 single cells of Arabidopsis thaliana ovule primordia at three developmental time points during female germline differentiation. This allowed us to identify the characteristic expression patterns of the main cell types, including the female germline and its surrounding nucellus. We then reconstructed the continuous trajectory of female germline differentiation and observed dynamic waves of gene expression along the developmental trajectory. A focused analysis revealed transcriptional cascades and identified key transcriptional factors that showed distinct expression patterns along the germline differentiation trajectory. Our study provides a valuable reference dataset of the transcriptional process during female germline differentiation at single-cell resolution, shedding light on the mechanisms underlying germline cell fate determination.

scholarly journals Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1158 ◽  
Author(s):  
Fanny Perraudeau ◽  
Davide Risso ◽  
Kelly Street ◽  
Elizabeth Purdom ◽  
Sandrine Dudoit
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Dimensionality Reduction ◽  
Single Cell ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Stem Cell Differentiation ◽  
Cell Types ◽  
Cell Clustering ◽  
Cell Transcriptome

Novel single-cell transcriptome sequencing assays allow researchers to measure gene expression levels at the resolution of single cells and offer the unprecendented opportunity to investigate at the molecular level fundamental biological questions, such as stem cell differentiation or the discovery and characterization of rare cell types. However, such assays raise challenging statistical and computational questions and require the development of novel methodology and software. Using stem cell differentiation in the mouse olfactory epithelium as a case study, this integrated workflow provides a step-by-step tutorial to the methodology and associated software for the following four main tasks: (1) dimensionality reduction accounting for zero inflation and over dispersion and adjusting for gene and cell-level covariates; (2) cell clustering using resampling-based sequential ensemble clustering; (3) inference of cell lineages and pseudotimes; and (4) differential expression analysis along lineages.

scholarly journals Differential Network Analysis Reveals Regulatory Patterns in Neural Stem Cell Fate Decision

2019 ◽  
Author(s):  
Jiang Xie ◽  
Fuzhang yang ◽  
Jiamin Sun ◽  
Jiao Wang
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Neural Stem Cell ◽  
Integrative Analysis ◽  
Cell Fate Decisions ◽  
Multi Stage ◽  
Gene Regulatory ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Background Neural stem cell (NSC) differentiation is one of many multi-stage lineage systems that require multiple cell fate decisions. Recent single-cell transcriptome datasets became available at individual differentiation, however, a systematic and integrative analysis of multiple datasets at multiple temporal points of NSC differentiation is lacking. Results Here we investigate five NSC differentiation paths by analyzing and comparing four different single-cell transcriptome datasets. By constructing gene regulatory networks for each cell type, we delineate their regulatory patterns via analyses of differential topology and network diffusion. Among the five NSC differentiation paths, we find 12 common differentially expressed genes, with one common three-gene regulatory pattern shared by all paths. The identified regulatory pattern, partly supported by previous experimental evidence, is found to be essential to all differentiation paths, however, plays a different role in each path when regulating other genes. Conclusions Together, our integrative analysis provides both common and specific regulatory mechanisms for each of the five NSC differentiation paths, and the approach can be applied to analyzing other complex multi-stage lineage systems.

scholarly journals Chromatin accessibility dynamics and single cell RNA-Seq reveal new regulators of regeneration in neural progenitors

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Anneke Dixie Kakebeen ◽  
Alexander Daniel Chitsazan ◽  
Madison Corinne Williams ◽  
Lauren M Saunders ◽  
Andrea Elizabeth Wills
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Neural Progenitor Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Rna Seq ◽  
Tail Regeneration ◽  
Cell Fate Decisions ◽  
Transcriptional Regulatory ◽  
Regulatory Dynamics

Vertebrate appendage regeneration requires precisely coordinated remodeling of the transcriptional landscape to enable the growth and differentiation of new tissue, a process executed over multiple days and across dozens of cell types. The heterogeneity of tissues and temporally-sensitive fate decisions involved has made it difficult to articulate the gene regulatory programs enabling regeneration of individual cell types. To better understand how a regenerative program is fulfilled by neural progenitor cells (NPCs) of the spinal cord, we analyzed pax6-expressing NPCs isolated from regenerating Xenopus tropicalis tails. By intersecting chromatin accessibility data with single-cell transcriptomics, we find that NPCs place an early priority on neuronal differentiation. Late in regeneration, the priority returns to proliferation. Our analyses identify Pbx3 and Meis1 as critical regulators of tail regeneration and axon organization. Overall, we use transcriptional regulatory dynamics to present a new model for cell fate decisions and their regulators in NPCs during regeneration.

scholarly journals Multiplexed biochemical imaging reveals caspase activation patterns underlying single cell fate

2018 ◽  
Author(s):  
Maximilian W. Fries ◽  
Kalina T. Haas ◽  
Suzan Ber ◽  
John Saganty ◽  
Emma K. Richardson ◽  
...  
Keyword(s):  
Cell Death ◽  
Single Cell ◽  
Cell Fate ◽  
Genetic Heterogeneity ◽  
Cellular Response ◽  
Single Cells ◽  
Caspase Activation ◽  
Cell Fate Decisions ◽  
Network Activation ◽  
Biochemical Imaging

The biochemical activities underlying cell-fate decisions vary profoundly even in genetically identical cells. But such non-genetic heterogeneity remains refractory to current imaging methods, because their capacity to monitor multiple biochemical activities in single living cells over time remains limited1. Here, we deploy a family of newly designed GFP-like sensors (NyxBits) with fast photon-counting electronics and bespoke analytics (NyxSense) in multiplexed biochemical imaging, to define a network determining the fate of single cells exposed to the DNA-damaging drug cisplatin. By simultaneously imaging a tri-nodal network comprising the cell-death proteases Caspase-2, -3 and -92, we reveal unrecognized single-cell heterogeneities in the dynamics and amplitude of caspase activation that signify survival versus cell death via necrosis or apoptosis. Non-genetic heterogeneity in the pattern of caspase activation recapitulates traits of therapy resistance previously ascribed solely to genetic causes3,4. Chemical inhibitors that alter these patterns can modulate in a predictable manner the phenotypic landscape of the cellular response to cisplatin. Thus, multiplexed biochemical imaging reveals cellular populations and biochemical states, invisible to other methods, underlying therapeutic responses to an anticancer drug. Our work develops widely applicable tools to monitor the dynamic activation of biochemical networks at single-cell resolution. It highlights the necessity to resolve patterns of network activation in single cells, rather than the average state of individual nodes, to define, and potentially control, mechanisms underlying cellular decisions in health and disease.

Space: the final frontier — achieving single-cell, spatially resolved transcriptomics in plants

2021 ◽  
Author(s):  
Sai Guna Ranjan Gurazada ◽  
Kevin L. Cox, ◽  
Kirk J. Czymmek ◽  
Blake C. Meyers
Keyword(s):  
Single Cell ◽  
Spatial Resolution ◽  
Regulatory Networks ◽  
Single Cells ◽  
Cell Types ◽  
Transcriptional Analysis ◽  
Rna Seq ◽  
Tissue Sections ◽  
Spatially Resolved ◽  
Computational Aspects

Single-cell RNA-seq is a tool that generates a high resolution of transcriptional data that can be used to understand regulatory networks in biological systems. In plants, several methods have been established for transcriptional analysis in tissue sections, cell types, and/or single cells. These methods typically require cell sorting, transgenic plants, protoplasting, or other damaging or laborious processes. Additionally, the majority of these technologies lose most or all spatial resolution during implementation. Those that offer a high spatial resolution for RNA lack breadth in the number of transcripts characterized. Here, we briefly review the evolution of spatial transcriptomics methods and we highlight recent advances and current challenges in sequencing, imaging, and computational aspects toward achieving 3D spatial transcriptomics of plant tissues with a resolution approaching single cells. We also provide a perspective on the potential opportunities to advance this novel methodology in plants.

scholarly journals Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation

2019 ◽  
Vol 5 (4) ◽  
pp. eaav7959 ◽  
Author(s):  
Ce Zhang ◽  
Hsiung-Lin Tu ◽  
Gengjie Jia ◽  
Tanzila Mukhtar ◽  
Verdon Taylor ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cell Differentiation ◽  
Single Cell ◽  
Cell Fate ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Critical Role ◽  
Stem Cell Differentiation ◽  
Cell Fate Decisions ◽  
Cellular Microenvironments

Dynamical control of cellular microenvironments is highly desirable to study complex processes such as stem cell differentiation and immune signaling. We present an ultra-multiplexed microfluidic system for high-throughput single-cell analysis in precisely defined dynamic signaling environments. Our system delivers combinatorial and time-varying signals to 1500 independently programmable culture chambers in week-long live-cell experiments by performing nearly 106 pipetting steps, where single cells, two-dimensional (2D) populations, or 3D neurospheres are chemically stimulated and tracked. Using our system and statistical analysis, we investigated the signaling landscape of neural stem cell differentiation and discovered “cellular logic rules” that revealed the critical role of signal timing and sequence in cell fate decisions. We find synergistic and antagonistic signal interactions and show that differentiation pathways are highly redundant. Our system allows dissection of hidden aspects of cellular dynamics and enables accelerated biological discovery.

scholarly journals Single-cell transcriptome profiling reveals dermal and epithelium cell fate decisions during embryonic hair follicle development

2019 ◽  
Author(s):  
Wei Ge ◽  
Shao-Jing Tan ◽  
Shan-He Wang ◽  
Lan Li ◽  
Xiao-Feng Sun ◽  
...  
Keyword(s):  
Single Cell ◽  
Hair Follicle ◽  
Cell Fate ◽  
Cell Lineage ◽  
Follicle Development ◽  
Cell Fate Decisions ◽  
Dermal Cell ◽  
Hair Follicle Development ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractCharacterization of the morphological structure during hair follicle development has been well documented, while the current understanding of the molecular mechanisms involved in follicle development remain limited. Here, using unbiased single-cell RNA sequencing, we analyzed 15,086 single cell transcriptome profiles from E13.5 and E16.5 fetal mice, and newborn mouse (postnatal day 0, P0) dorsal skin cells. Based on t-distributed Stochastic Neighbor Embedding (tSNE) clustering, we identified 14 cell clusters from skin cells and delineated their cell identity gene expression profiles. Pseudotime ordering analysis successfully constructed epithelium/dermal cell lineage differentiation trajectory and revealed sequential activation of key regulons involved during cell fate decisions. Along with this, intercellular communication between different cell populations were inferred based on a priori knowledge of ligand-receptor pairs. Together, our findings here provide a molecular landscape during hair follicle epithelium/dermal cell lineage fate decisions, and more importantly, recapitulate sequential activation of core regulatory transcriptional factors for different cell populations during hair follicle morphogenesis.

scholarly journals Cell-to-cell heterogeneity in p38-mediated cross-inhibition of JNK causes stochastic cell death

2017 ◽  
Author(s):  
Haruko Miura ◽  
Yohei Kondo ◽  
Michiyuki Matsuda ◽  
Kazuhiro Aoki
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Stress Responses ◽  
Imaging System ◽  
Single Cells ◽  
High Specificity ◽  
Cellular Heterogeneity ◽  
Cell Fate Decisions ◽  
Specificity And Sensitivity ◽  
Cross Inhibition

AbstractThe stress activated protein kinases (SAPKs), c-Jun N-terminal kinase (JNK) and p38, are important players in cell fate decisions in response to environmental stress signals. Crosstalk signaling between JNK and p38 is emerging as an important regulatory mechanism in the inflammatory and stress responses. However, it is still unknown how this crosstalk affects signaling dynamics, cell-to-cell variation, and cellular responses at the single-cell level. To address these questions, we established a multiplexed live-cell imaging system based on kinase translocation reporters to simultaneously monitor JNK and p38 activities with high specificity and sensitivity at single-cell resolution. Various stresses, such as anisomycin, osmotic stress, and UV irradiation, and pro-inflammatory cytokines activated JNK and p38 with various dynamics. In all cases, however, p38 suppressed JNK activity in a cross-inhibitory manner. We demonstrate that p38 antagonizes JNK through both transcriptional and post-translational mechanisms. This cross-inhibition of JNK appears to generate cellular heterogeneity in JNK activity after stress exposure. Our data indicate that this heterogeneity in JNK activity plays a role in fractional killing in response to UV stress. Our highly sensitive multiplexed imaging system enables detailed investigation into the p38-JNK interplay in single cells.One Sentence SummaryCross-inhibition by p38 generates cell-to-cell variability in JNK activity.

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