scholarly journals Cellular and molecular landscape of mammalian sinoatrial node revealed by single-cell RNA sequencing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dandan Liang ◽  
Jinfeng Xue ◽  
Li Geng ◽  
Liping Zhou ◽  
Bo Lv ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sinoatrial Node ◽  
Induced Pluripotent Stem Cell ◽  
Transcriptome Profiling ◽  
Core Gene ◽  
Cell Cluster ◽  
Critical Function ◽  
Gene Regulation Network ◽  
Single Cell Rna Sequencing

AbstractBioelectrical impulses intrinsically generated within the sinoatrial node (SAN) trigger the contraction of the heart in mammals. Though discovered over a century ago, the molecular and cellular features of the SAN that underpin its critical function in the heart are uncharted territory. Here, we identify four distinct transcriptional clusters by single-cell RNA sequencing in the mouse SAN. Functional analysis of differentially expressed genes identifies a core cell cluster enriched in the electrogenic genes. The similar cellular features are also observed in the SAN from both rabbit and cynomolgus monkey. Notably, Vsnl1, a core cell cluster marker in mouse, is abundantly expressed in SAN, but is barely detectable in atrium or ventricle, suggesting that Vsnl1 is a potential SAN marker. Importantly, deficiency of Vsnl1 not only reduces the beating rate of human induced pluripotent stem cell - derived cardiomyocytes (hiPSC-CMs) but also the heart rate of mice. Furthermore, weighted gene co-expression network analysis (WGCNA) unveiled the core gene regulation network governing the function of the SAN in mice. Overall, these findings reveal the whole transcriptome profiling of the SAN at single-cell resolution, representing an advance toward understanding of both the biology and the pathology of SAN.

scholarly journals Single‐Cell Transcriptomics of Engineered Cardiac Tissues From Patient‐Specific Induced Pluripotent Stem Cell–Derived Cardiomyocytes Reveals Abnormal Developmental Trajectory and Intrinsic Contractile Defects in Hypoplastic Right Heart Syndrome

2020 ◽  
Vol 9 (20) ◽  
Author(s):  
Yin‐Yu Lam ◽  
Wendy Keung ◽  
Chun‐Ho Chan ◽  
Lin Geng ◽  
Nicodemus Wong ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Pluripotent Stem Cell ◽  
Cardiac Tissue ◽  
Induced Pluripotent Stem Cell ◽  
Developmental Trajectory ◽  
Single Cell Rna Sequencing ◽  
Human Cardiac Tissue ◽  
Induced Pluripotent

Background To understand the intrinsic cardiac developmental and functional abnormalities in pulmonary atresia with intact ventricular septum (PAIVS) free from effects secondary to anatomic defects, we performed and compared single‐cell transcriptomic and phenotypic analyses of patient‐ and healthy subject–derived human‐induced pluripotent stem cell–derived cardiomyocytes (hiPSC‐CMs) and engineered tissue models. Methods and Results We derived hiPSC lines from 3 patients with PAIVS and 3 healthy subjects and differentiated them into hiPSC‐CMs, which were then bioengineered into the human cardiac anisotropic sheet and human cardiac tissue strip custom‐designed for electrophysiological and contractile assessments, respectively. Single‐cell RNA sequencing (scRNA‐seq) of hiPSC‐CMs, human cardiac anisotropic sheet, and human cardiac tissue strip was performed to examine the transcriptomic basis for any phenotypic abnormalities using pseudotime and differential expression analyses. Through pseudotime analysis, we demonstrated that bioengineered tissue constructs provide pro‐maturational cues to hiPSC‐CMs, although the maturation and development were attenuated in PAIVS hiPSC‐CMs. Furthermore, reduced contractility and prolonged contractile kinetics were observed with PAIVS human cardiac tissue strips. Consistently, single‐cell RNA sequencing of PAIVS human cardiac tissue strips and hiPSC‐CMs exhibited diminished expression of cardiac contractile apparatus genes. By contrast, electrophysiological aberrancies were absent in PAIVS human cardiac anisotropic sheets. Conclusions Our findings were the first to reveal intrinsic abnormalities of cardiomyocyte development and function in PAIVS free from secondary effects. We conclude that hiPSC‐derived engineered tissues offer a unique method for studying primary cardiac abnormalities and uncovering pathogenic mechanisms that underlie sporadic congenital heart diseases.

scholarly journals MuDCoD: Multi-Subject Community Detection in Personalized Dynamic Gene Networks from Single Cell RNA Sequencing

2021 ◽  
Author(s):  
Ali Osman Berk Sapci ◽  
Shan Lu ◽  
Oznur Tastan ◽  
Sunduz Keles
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Community Detection ◽  
Gene Networks ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Dynamic Community Detection ◽  
Subject Specific ◽  
Single Cell Rna Sequencing ◽  
Gene Modules

Developments in single-cell RNA sequencing (scRNA-seq) advanced our understanding of transcriptional programs of different cell types and cellular stages at the individual cell level. Single-cell RNA-seq datasets across multiple individuals and time points are now routinely generated for different conditions. Analysis of personalized dynamic gene networks constructed from these datasets could unravel subject-specific network-level variation critical for phenotypic differences. While there have been developments in the gene module discovery methods on networks estimated from scRNA-seq data, these have mostly focused on static gene networks. In this work, we develop MuDCoD to cluster genes in personalized dynamic gene networks and identify gene modules that vary not only across time but also among subjects. To this end, MuDCoD extends the global spectral clustering framework of the previously developed method, PisCES, to promote information sharing among the subject as well as the time domain. Our computational experiments across a wide variety of settings indicate that, when present, MuDCoD leverages shared signals among networks of the subjects, and performs robustly when subjects do not share any apparent information. An application to human-induced pluripotent stem cell scRNA-seq data during dopaminergic neuron differentiation indicates that MuDCoD enables robust inference for identifying time-varying personalized gene modules. Our results illustrate how personalized dynamic community detection can aid the exploration of subject-specific biological processes that vary across time.

scholarly journals BingleSeq: a user-friendly R package for bulk and single-cell RNA-Seq data analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10469
Author(s):  
Daniel Dimitrov ◽  
Quan Gu
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Differential Expression Analysis ◽  
Transcriptome Profiling ◽  
R Package ◽  
Rna Seq ◽  
Single Cell Rna Sequencing ◽  
The Individual ◽  
Visualization Techniques ◽  
User Friendly

Background RNA sequencing is an indispensable research tool used in a broad range of transcriptome analysis studies. The most common application of RNA Sequencing is differential expression analysis and it is used to determine genetic loci with distinct expression across different conditions. An emerging field called single-cell RNA sequencing is used for transcriptome profiling at the individual cell level. The standard protocols for both of these approaches include the processing of sequencing libraries and result in the generation of count matrices. An obstacle to these analyses and the acquisition of meaningful results is that they require programing expertise. Although some effort has been directed toward the development of user-friendly RNA-Seq analysis analysis tools, few have the flexibility to explore both Bulk and single-cell RNA sequencing. Implementation BingleSeq was developed as an intuitive application that provides a user-friendly solution for the analysis of count matrices produced by both Bulk and Single-cell RNA-Seq experiments. This was achieved by building an interactive dashboard-like user interface which incorporates three state-of-the-art software packages for each type of the aforementioned analyses. Furthermore, BingleSeq includes additional features such as visualization techniques, extensive functional annotation analysis and rank-based consensus for differential gene analysis results. As a result, BingleSeq puts some of the best reviewed and most widely used packages and tools for RNA-Seq analyses at the fingertips of biologists with no programing experience. Availability BingleSeq is as an easy-to-install R package available on GitHub at https://github.com/dbdimitrov/BingleSeq/.

scholarly journals Single-Cell RNA Sequencing Analysis of Chicken Anterior Pituitary: A Bird’s-Eye View on Vertebrate Pituitary

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiannan Zhang ◽  
Can Lv ◽  
Chunheng Mo ◽  
Meng Liu ◽  
Yiping Wan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Population ◽  
Endocrine Cell ◽  
Anterior Pituitary ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Cluster ◽  
Single Cell Rna Sequencing

It is well-established that anterior pituitary contains multiple endocrine cell populations, and each of them can secrete one/two hormone(s) to regulate vital physiological processes of vertebrates. However, the gene expression profiles of each pituitary cell population remains poorly characterized in most vertebrate groups. Here we analyzed the transcriptome of each cell population in adult chicken anterior pituitaries using single-cell RNA sequencing technology. The results showed that: (1) four out of five known endocrine cell clusters have been identified and designated as the lactotrophs, thyrotrophs, corticotrophs, and gonadotrophs, respectively. Somatotrophs were not analyzed in the current study. Each cell cluster can express at least one known endocrine hormone, and novel marker genes (e.g., CD24 and HSPB1 in lactotrophs, NPBWR2 and NDRG1 in corticotrophs; DIO2 and SOUL in thyrotrophs, C5H11ORF96 and HPGDS in gonadotrophs) are identified. Interestingly, gonadotrophs were shown to abundantly express five peptide hormones: FSH, LH, GRP, CART and RLN3; (2) four non-endocrine/secretory cell types, including endothelial cells (expressing IGFBP7 and CFD) and folliculo-stellate cells (FS-cells, expressing S100A6 and S100A10), were identified in chicken anterior pituitaries. Among them, FS-cells can express many growth factors, peptides (e.g., WNT5A, HBEGF, Activins, VEGFC, NPY, and BMP4), and progenitor/stem cell-associated genes (e.g., Notch signaling components, CDH1), implying that the FS-cell cluster may act as a paracrine/autocrine signaling center and enrich pituitary progenitor/stem cells; (3) sexually dimorphic expression of many genes were identified in most cell clusters, including gonadotrophs and lactotrophs. Taken together, our data provides a bird’s-eye view on the diverse aspects of anterior pituitaries, including cell composition, heterogeneity, cell-to-cell communication, and gene expression profiles, which facilitates our comprehensive understanding of vertebrate pituitary biology.

scholarly journals Human cutaneous neurofibroma matrisome revealed by single-cell RNA sequencing

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jean-Philippe Brosseau ◽  
Adwait A. Sathe ◽  
Yong Wang ◽  
Toan Nguyen ◽  
Donald A. Glass ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Wide Spectrum ◽  
Transcriptome Profiling ◽  
Dry Weight ◽  
Neurofibromatosis Type ◽  
Type I ◽  
Nerve Sheath Tumor ◽  
Genetic Syndrome ◽  
Single Cell Rna Sequencing

AbstractNeurofibromatosis Type I (NF1) is a neurocutaneous genetic syndrome characterized by a wide spectrum of clinical presentations, including benign peripheral nerve sheath tumor called neurofibroma. These tumors originate from the Schwann cell lineage but other cell types as well as extracellular matrix (ECM) in the neurofibroma microenvironment constitute the majority of the tumor mass. In fact, collagen accounts for up to 50% of the neurofibroma’s dry weight. Although the presence of collagens in neurofibroma is indisputable, the exact repertoire of ECM genes and ECM-associated genes (i.e. the matrisome) and their functions are unknown. Here, transcriptome profiling by single-cell RNA sequencing reveals the matrisome of human cutaneous neurofibroma (cNF). We discovered that classic pro-fibrogenic collagen I myofibroblasts are rare in neurofibroma. In contrast, collagen VI, a pro-tumorigenic ECM, is abundant and mainly secreted by neurofibroma fibroblasts. This study also identified potential cell type-specific markers to further elucidate the biology of the cNF microenvironment.

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