scholarly journals A spatiotemporal steroidogenic regulatory network in human fetal adrenal glands and gonads

2021 ◽  
Author(s):  
Yifu Wang ◽  
Bingqian Guo ◽  
Yajie Guo ◽  
Nana Qi ◽  
Yufang Lv ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Adrenal Glands ◽  
Time Window ◽  
Sex Differentiation ◽  
Steroid Synthesis ◽  
Androgen Synthesis ◽  
Key Enzyme ◽  
Steroidogenic Cells ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Human fetal adrenal glands produce substantial amounts of dehydroepiandrosterone (DHEA), which is one of the most important precursors of sex hormones. However, the underlying biological mechanism remains largely unknown. Herein, we sequenced human fetal adrenal glands and gonads from 7 to 14 GW via the 10× Genomics single-cell transcriptome techniques and reconstructed their location information by Spatial Transcriptome, conducted COOL-seq for the MC2R+ inner zone steroidogenic cells during the time window of sex differentiation (8-12GW). We found that relative to gonads, adrenal glands begin to synthesize steroids early. The coordination among steroidogenic cells and multiple nonsteroidogenic cells promotes adrenal cortex construction and steroid synthesis. Notably, during the time window of sex differentiation (8-12 GW), key enzyme gene expression shifts to accelerate DHEA synthesis in males and cortisol synthesis in females. Furthermore, high SST+ expressions in the adrenal gland and testis amplify androgen synthesis in males. Our research highlights the robustness of the action of fetal adrenal glands on gonads to modify the process of sexual differentiation.

scholarly journals Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Mouse Brain Vasculature

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wei-Wei Lin ◽  
Lin-Tao Xu ◽  
Yi-Sheng Chen ◽  
Ken Go ◽  
Chenyu Sun ◽  
...  
Keyword(s):  
Single Cell ◽  
Mouse Brain ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Transcriptional Regulatory Network ◽  
Rna Seq ◽  
Brain Vasculature ◽  
Transcriptional Regulatory ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Background. The critical role of vascular health on brain function has received much attention in recent years. At the single-cell level, studies on the developmental processes of cerebral vascular growth are still relatively few. Techniques for constructing gene regulatory networks (GRNs) based on single-cell transcriptome expression data have made significant progress in recent years. Herein, we constructed a single-cell transcriptional regulatory network of mouse cerebrovascular cells. Methods. The single-cell RNA-seq dataset of mouse brain vessels was downloaded from GEO (GSE98816). This cell clustering was annotated separately using singleR and CellMarker. We then used a modified version of the SCENIC method to construct GRNs. Next, we used a mouse version of SEEK to assess whether genes in the regulon were coexpressed. Finally, regulatory module analysis was performed to complete the cell type relationship quantification. Results. Single-cell RNA-seq data were used to analyze the heterogeneity of mouse cerebrovascular cells, whereby four cell types including endothelial cells, fibroblasts, microglia, and oligodendrocytes were defined. These subpopulations of cells and marker genes together characterize the molecular profile of mouse cerebrovascular cells. Through these signatures, key transcriptional regulators that maintain cell identity were identified. Our findings identified genes like Lmo2, which play an important role in endothelial cells. The same cell type, for instance, fibroblasts, was found to have different regulatory networks, which may influence the functional characteristics of local tissues. Conclusions. In this study, a transcriptional regulatory network based on single-cell analysis was constructed. Additionally, the study identified and profiled mouse cerebrovascular cells using single-cell transcriptome data as well as defined TFs that affect the regulatory network of the mouse brain vasculature.

scholarly journals Deciphering the autophagy regulatory network via single-cell transcriptome analysis reveals a requirement for autophagy homeostasis in spermatogenesis

Theranostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 5010-5027
Author(s):  
Mei Wang ◽  
Yanwen Xu ◽  
Yuncong Zhang ◽  
Yuhan Chen ◽  
Gang Chang ◽  
...  
Keyword(s):  
Single Cell ◽  
Transcriptome Analysis ◽  
Regulatory Network ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

scholarly journals Diversification of Reprogramming Trajectories Revealed by Parallel Single-cell Transcriptome and Chromatin Accessibility Sequencing

2019 ◽  
Author(s):  
Qiaorui Xing ◽  
Chadi El Farran ◽  
Pradeep Gautam ◽  
Yu Song Chuah ◽  
Tushar Warrier ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Network ◽  
Chromatin Accessibility ◽  
Cellular Reprogramming ◽  
Binary Choice ◽  
Surface Markers ◽  
Part List ◽  
Cell Transcriptome ◽  
Intermediate Cells ◽  
Single Cell Transcriptome

To unravel the mechanism of human cellular reprogramming process at single-cell resolution, we performed parallel scRNA-Seq and scATAC-Seq analysis. Our analysis reveals that the cells undergoing reprogramming proceed in an asynchronous trajectory and diversify into heterogeneous sub-populations. BDD2-C8 fluorescent probe staining and negative staining for CD13, CD44 and CD201 markers, could enrich for the GDF3+ early reprogrammed cells. Combinatory usage of the surface markers enables the fine segregation of the early-intermediate cells with diverse reprogramming propensities. scATAC-Seq analysis further uncovered the genomic partitions and transcription factors responsible for the regulatory phasing of reprogramming process. Binary choice between a FOSL1 or a TEAD4-centric regulatory network determines the outcome of a successful reprogramming. Altogether, our study illuminates the multitude of diverse routes transversed by individual reprogramming cells and presents an integrative roadmap for identifying the mechanistic part-list of the reprogramming machinery.

scholarly journals Tracing co-regulatory network dynamics in noisy, single-cell transcriptome trajectories

2016 ◽  
Author(s):  
Pablo Cordero ◽  
Joshua M. Stuart
Keyword(s):  
Single Cell ◽  
Regulatory Network ◽  
Neural Differentiation ◽  
Expression Patterns ◽  
Simulated Data ◽  
Gene Modules ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Differentiation Pathways ◽  
Network Rewiring

The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression ‘trajectory’ from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolving co-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

scholarly journals Single cell transcriptome atlas of mouse mammary epithelial cells across development

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Bhupinder Pal ◽  
Yunshun Chen ◽  
Michael J. G. Milevskiy ◽  
François Vaillant ◽  
Lexie Prokopuk ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Single Cell ◽  
Developmental Stages ◽  
Mammary Epithelial Cells ◽  
Expression Profiles ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Mammary Epithelial ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Background Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. Methods The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. Results The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. Conclusions This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

Protective action of the microbial metabolite butyrate against cardiomyocyte hypertrophy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Umei ◽  
H Akazawa ◽  
A Saga-Kamo ◽  
H Yagi ◽  
Q Liu ◽  
...  
Keyword(s):  
Heart Failure ◽  
Short Chain Fatty Acid ◽  
Short Chain Fatty Acids ◽  
Chain Fatty Acid ◽  
G Protein Coupled Receptors ◽  
Short Chain ◽  
Cardiomyocyte Hypertrophy ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
G Protein Coupled

Abstract Introduction Short-chain fatty acids are one of the gut microbial metabolites that may influence host physiology. We previously reported that gut dysbiosis was associated with heart failure, and that the proportions of butyrate-producing bacteria diminished prominently in the gut of patients with heart failure. Purpose We investigated the molecular mechanism of butyrate and investigated the protective mechanism against heart failure. Methods We searched for G protein-coupled receptors for short-chain fatty acids using single-cell transcriptome analysis of cardiomyocytes and non-cardiomyocytes isolated from murine hearts. In addition, we examined the effects of butyrate on endothelin-1 (ET1) or isoproterenol-induced hypertrophic responses and histone deacetylase (HDAC) activities in cultured neonatal rat cardiomyocytes. Results Single-cell transcriptome analysis and co-expression network analysis revealed that G protein-coupled receptors for short-chain fatty acid receptors were not expressed in cardiomyocytes and that Olfr78 was expressed in vascular smooth muscle cells in the heart. Treatment with butyrate inhibited ET1-induced hypertrophic growth and up-regulation of the genes such as Nppa, Acta1, and Myh7 in cultured rat neonatal cardiomyocytes. Moreover, butyrate increased the acetylation levels of histone H3, indicating that butyrate has an inhibitory effect on HDAC in cardiomyocytes. In addition, treatment with butyrate caused up-regulation of Inpp5f, encoding inositol polyphosphate-5-phosphatase f, which was associated with a significant decrease in the phosphorylation levels of Akt. These results suggest that butyrate may act as HDAC inhibitor to increase Inpp5f gene expression, leading to the activation of Akt-glycogen synthase kinase 3beta (Gsk3beta) pathway, and thereby protect against hypertrophic responses. Conclusion There was no known GPCR for short-chain fatty acid expressed in cardiomyocytes. However, butyrate suppressed cardiomyocyte hypertrophy through epigenetic modification of gene expression. Our results may uncover a potential role of the dysbiosis of intestinal microbiota in the pathogenesis of cardiac hypertrophy and failure. Funding Acknowledgement Type of funding source: None

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