scholarly journals Single-cell transcriptome reveals the redifferentiation trajectories of the early stage of de novo shoot regeneration in Arabidopsis thaliana

2022 ◽  
Author(s):  
Guangyu Liu ◽  
Jie Li ◽  
Jiming Li ◽  
Zhiyong Chen ◽  
Peisi Yuan ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Shoot Regeneration ◽  
De Novo ◽  
Developmental Process ◽  
Early Stage ◽  
Cell Populations ◽  
Cell Heterogeneity ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

De novo shoot regeneration from a callus plays a crucial role in both plant biotechnology and the fundamental research of plant cell totipotency. Recent studies have revealed many regulatory factors involved in this developmental process. However. our knowledge of the cell heterogeneity and cell fate transition during de novo shoot regeneration is still limited. Here, we performed time-series single-cell transcriptome experiments to reveal the cell heterogeneity and redifferentiation trajectories during the early stage of de novo shoot regeneration. Based on the single-cell transcriptome data of 35,669 cells at five-time points, we successfully determined seven major cell populations in this developmental process and reconstructed the redifferentiation trajectories. We found that all cell populations resembled root identities and undergone gradual cell-fate transitions. In detail, the totipotent callus cells differentiated into pluripotent QC-like cells and then gradually developed into less differentiated cells that have multiple root-like cell identities, such as pericycle-like cells. According to the reconstructed redifferentiation trajectories, we discovered that the canonical regeneration-related genes were dynamically expressed at certain stages of the redifferentiation process. Moreover, we also explored potential transcription factors and regulatory networks that might be involved in this process. The transcription factors detected at the initial stage, QC-like cells, and the end stage provided a valuable resource for future functional verifications. Overall, this dataset offers a unique glimpse into the early stages of de novo shoot regeneration, providing a foundation for a comprehensive analysis of the mechanism of de novo shoot regeneration.

scholarly journals Super-cells untangle large and complex single-cell transcriptome networks

2021 ◽  
Author(s):  
Mariia Bilous ◽  
Loc Tran ◽  
Chiara Cianciaruso ◽  
Santiago J Carmona ◽  
Mikael J Pittet ◽  
...  
Keyword(s):  
Single Cell ◽  
Coarse Graining ◽  
Cell Populations ◽  
Cell Type ◽  
Large Numbers ◽  
Single Cell Rna Sequencing ◽  
Gene Correlation ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Single-cell RNA sequencing (scRNA-seq) technologies offer unique opportunities for exploring heterogeneous cell populations. However, in-depth single-cell transcriptomic characterization of complex tissues often requires profiling tens to hundreds of thousands of cells. Such large numbers of cells represent an important hurdle for downstream analyses, interpretation and visualization. Here we develop a network-based coarse-graining framework where highly similar cells are merged into super-cells. We demonstrate that super-cells not only preserve but often improve the results of downstream analyses including visualization, clustering, differential expression, cell type annotation, gene correlation, imputation, RNA velocity and data integration. By capitalizing on the redundancy inherent to scRNA-seq data, super-cells significantly facilitate and accelerate the construction and interpretation of single-cell atlases, as demonstrated by the integration of 1.46 million cells from COVID-19 patients in less than two hours on a standard desktop.

scholarly journals Lifelong single-cell profiling of cranial neural crest diversification

2021 ◽  
Author(s):  
Peter Fabian ◽  
Kuo-Chang Tseng ◽  
Mathi Thiruppathy ◽  
Claire Arata ◽  
Hung-Jhen Chen ◽  
...  
Keyword(s):  
Neural Crest ◽  
Single Cell ◽  
Cell Fate ◽  
Intrinsic Property ◽  
Chromatin Accessibility ◽  
Specific Cell ◽  
List Type ◽  
Cranial Neural Crest ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractThe cranial neural crest generates a huge diversity of derivatives, including the bulk of connective and skeletal tissues of the vertebrate head. How neural crest cells acquire such extraordinary lineage potential remains unresolved. By integrating single-cell transcriptome and chromatin accessibility profiles of cranial neural crest-derived cells across the zebrafish lifetime, we observe region-specific establishment of enhancer accessibility for distinct fates. Neural crest-derived cells rapidly diversify into specialized progenitors, including multipotent skeletal progenitors, stromal cells with a regenerative signature, fibroblasts with a unique metabolic signature linked to skeletal integrity, and gill-specific progenitors generating cell types for respiration. By retrogradely mapping the emergence of lineage-specific chromatin accessibility, we identify a wealth of candidate lineage-priming factors, including a Gata3 regulatory circuit for respiratory cell fates. Rather than multilineage potential being an intrinsic property of cranial neural crest, our findings support progressive and region-specific chromatin remodeling underlying acquisition of diverse neural crest lineage potential.HighlightsSingle-cell transcriptome and chromatin atlas of cranial neural crestProgressive emergence of region-specific cell fate competencyChromatin accessibility mapping identifies candidate lineage regulatorsGata3 function linked to gill-specific respiratory programGraphical Abstract

scholarly journals Single-cell transcriptome identifies molecular subtype of autism spectrum disorder impacted by de novo loss-of-function variants regulating glial cells

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Nasna Nassir ◽  
Asma Bankapur ◽  
Bisan Samara ◽  
Abdulrahman Ali ◽  
Awab Ahmed ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
De Novo ◽  
Cell Types ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Loss Of Function ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Variant Genes

Abstract Background In recent years, several hundred autism spectrum disorder (ASD) implicated genes have been discovered impacting a wide range of molecular pathways. However, the molecular underpinning of ASD, particularly from the point of view of ‘brain to behaviour’ pathogenic mechanisms, remains largely unknown. Methods We undertook a study to investigate patterns of spatiotemporal and cell type expression of ASD-implicated genes by integrating large-scale brain single-cell transcriptomes (> million cells) and de novo loss-of-function (LOF) ASD variants (impacting 852 genes from 40,122 cases). Results We identified multiple single-cell clusters from three distinct developmental human brain regions (anterior cingulate cortex, middle temporal gyrus and primary visual cortex) that evidenced high evolutionary constraint through enrichment for brain critical exons and high pLI genes. These clusters also showed significant enrichment with ASD loss-of-function variant genes (p < 5.23 × 10–11) that are transcriptionally highly active in prenatal brain regions (visual cortex and dorsolateral prefrontal cortex). Mapping ASD de novo LOF variant genes into large-scale human and mouse brain single-cell transcriptome analysis demonstrate enrichment of such genes into neuronal subtypes and are also enriched for subtype of non-neuronal glial cell types (astrocyte, p < 6.40 × 10–11, oligodendrocyte, p < 1.31 × 10–09). Conclusion Among the ASD genes enriched with pathogenic de novo LOF variants (i.e. KANK1, PLXNB1), a subgroup has restricted transcriptional regulation in non-neuronal cell types that are evolutionarily conserved. This association strongly suggests the involvement of subtype of non-neuronal glial cells in the pathogenesis of ASD and the need to explore other biological pathways for this disorder.

scholarly journals Contribution of Single-Cell Transcriptomics to the Characterization of Human Spermatogonial Stem Cells: Toward an Application in Male Fertility Regenerative Medicine?

2019 ◽  
Vol 20 (22) ◽  
pp. 5773 ◽  
Author(s):  
Anne-Sophie Gille ◽  
Clémentine Lapoujade ◽  
Jean-Philippe Wolf ◽  
Pierre Fouchet ◽  
Virginie Barraud-Lange
Keyword(s):  
Stem Cells ◽  
Regenerative Medicine ◽  
Single Cell ◽  
Developmental Process ◽  
Expression Patterns ◽  
Spermatogonial Stem Cells ◽  
Genomic Technologies ◽  
Cell Transcriptome ◽  
Definition Of ◽  
Single Cell Transcriptome

Ongoing progress in genomic technologies offers exciting tools that can help to resolve transcriptome and genome-wide DNA modifications at single-cell resolution. These methods can be used to characterize individual cells within complex tissue organizations and to highlight various molecular interactions. Here, we will discuss recent advances in the definition of spermatogonial stem cells (SSC) and their progenitors in humans using the single-cell transcriptome sequencing (scRNAseq) approach. Exploration of gene expression patterns allows one to investigate stem cell heterogeneity. It leads to tracing the spermatogenic developmental process and its underlying biology, which is highly influenced by the microenvironment. scRNAseq already represents a new diagnostic tool for the personalized investigation of male infertility. One may hope that a better understanding of SSC biology could facilitate the use of these cells in the context of fertility preservation of prepubertal children, as a key component of regenerative medicine.

scholarly journals De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data

2016 ◽  
Vol 19 (2) ◽  
pp. 266-277 ◽  
Author(s):  
Dominic Grün ◽  
Mauro J. Muraro ◽  
Jean-Charles Boisset ◽  
Kay Wiebrands ◽  
Anna Lyubimova ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
De Novo ◽  
Transcriptome Data ◽  
Cell Identity ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

scholarly journals Dissecting Transition Cells from Single-cell Transcriptome Data through Multiscale Stochastic Dynamics

2021 ◽  
Author(s):  
Peijie Zhou ◽  
Shuxiong Wang ◽  
Tiejun Li ◽  
Qing Nie
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Stochastic Dynamics ◽  
Multiple Scales ◽  
Coarse Grained ◽  
Rate Theory ◽  
Transcriptome Data ◽  
Stochastic Dynamical Systems ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractAdvances of single-cell technologies allow scrutinizing of heterogeneous cell states, however, analyzing transitions from snap-shot single-cell transcriptome data remains challenging. To investigate cells with transient properties or mixed identities, we present MuTrans, a method based on multiscale reduction technique for the underlying stochastic dynamical systems that prescribes cell-fate transitions. By iteratively unifying transition dynamics across multiple scales, MuTrans constructs the cell-fate dynamical manifold that depicts progression of cell-state transition, and distinguishes meta-stable and transition cells. In addition, MuTrans quantifies the likelihood of all possible transition trajectories between cell states using the coarse-grained transition path theory. Downstream analysis identifies distinct genes that mark the transient states or drive the transitions. Mathematical analysis reveals consistency of the method with the well-established Langevin equation and transition rate theory. Applying MuTrans to datasets collected from five different single-cell experimental platforms and benchmarking with seven existing tools, we show its capability and scalability to robustly unravel complex cell fate dynamics induced by transition cells in systems such as tumor EMT, iPSC differentiation and blood cell differentiation. Overall, our method bridges data-driven and model-based approaches on cell-fate transitions at single-cell resolution.

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.

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