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Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Danio rerio

PROVIDER: GSE215988 | GEO | 2024/02/26

REPOSITORIES: GEO

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Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration [Cut&Tag]

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Project description:Single-cell chromatin landscape of non-myocytes reveals AP-1 as a key transcriptional regulator contributing to highly cooperative networks among non-myocyte subtypes during zebrafish heart regeneration

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Detecting overlapping communities in complex networks using non-cooperative games.

Project description:Detecting communities in complex networks is of paramount importance, and its wide range of real-life applications in various areas has caused a lot of attention to be paid to it, and many efforts have been made to have efficient and accurate algorithms for this purpose. In this paper, we proposed a non-cooperative game theoretic-based algorithm that is able to detect overlapping communities. In this algorithm, nodes are regarded as players, and communities are assumed to be groups of players with similar strategies. Our two-phase algorithm detects communities and the overlapping nodes in separate phases that, while increasing the accuracy, especially in detecting overlapping nodes, brings about higher algorithm speed. Moreover, there is no need for setting parameters regarding the size or number of communities, and the absence of any stochastic process caused this algorithm to be stable. By appropriately adjusting stop criteria, our algorithm can be categorized among those with linear time complexity, making it highly scalable for large networks. Experiments on synthetic and real-world networks demonstrate our algorithm's good performance compared to similar algorithms in terms of detected overlapping nodes, detected communities size distribution, modularity, and normalized mutual information.

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Functional coordination of non-myocytes plays a key role in adult zebrafish heart regeneration.

Project description:Cardiac regeneration occurs primarily through proliferation of existing cardiomyocytes, but also involves complex interactions between distinct cardiac cell types including non-cardiomyocytes (non-CMs). However, the subpopulations, distinguishing molecular features, cellular functions, and intercellular interactions of non-CMs in heart regeneration remain largely unexplored. Using the LIGER algorithm, we assemble an atlas of cell states from 61,977 individual non-CM scRNA-seq profiles isolated at multiple time points during regeneration. This analysis reveals extensive non-CM cell diversity, including multiple macrophage (MC), fibroblast (FB), and endothelial cell (EC) subpopulations with unique spatiotemporal distributions, and suggests an important role for MC in inducing the activated FB and EC subpopulations. Indeed, pharmacological perturbation of MC function compromises the induction of the unique FB and EC subpopulations. Furthermore, we developed computational algorithm Topologizer to map the topological relationships and dynamic transitions between functional states. We uncover dynamic transitions between MC functional states and identify factors involved in mRNA processing and transcriptional regulation associated with the transition. Together, our single-cell transcriptomic analysis of non-CMs during cardiac regeneration provides a blueprint for interrogating the molecular and cellular basis of this process.

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