Cell State Dynamics and Tumorigenesis in Boolean Regulatory Networks

Author(s):  
Sui Huang
2021 ◽  
Author(s):  
Khouri Farah-Nagham ◽  
Qiuxia Guo ◽  
Kerry Morgan ◽  
Jihye Shin ◽  
James Y.H. Li

Recent studies using single-cell RNA-seq have revealed cellular heterogeneity in the developing mammalian cerebellum, yet the regulatory logic underlying this cellular diversity remains to be elucidated. Using integrated single-cell RNA and ATAC analyses, we resolved developmental trajectories of cerebellar progenitors and identified putative trans- and cis-elements that control cell state transition. We reverse-engineered gene regulatory networks (GRNs) of each cerebellar cell type. Through in silico simulations and in vivo experiments, we validated the efficacy of GRN analyses and uncovered the molecular control of a newly identified stem zone, the posterior transitory zone (PTZ), which contains multipotent progenitors for granule neurons, Bergmann glia, and choroid plexus epithelium. Importantly, we showed that perturbing cell fate specification of PTZ progenitors causes posterior cerebellar vermis hypoplasia, the most common cerebellar birth defect in humans. Our study provides a foundation for comprehensive studies of developmental programs of the mammalian cerebellum.


2018 ◽  
Author(s):  
P. Tsakanikas ◽  
D. Manatakis ◽  
E. S. Manolakos

ABSTRACTDeciphering the dynamic gene regulatory mechanisms driving cells to make fate decisions remains elusive. We present a novel unsupervised machine learning methodology that can be used to analyze a dataset of heterogeneous single-cell gene expressions profiles, determine the most probable number of states (major cellular phenotypes) represented and extract the corresponding cell sub-populations. Most importantly, for any transition of interest from a source to a destination state, our methodology can zoom in, identify the cells most specific for studying the dynamics of this transition, order them along a trajectory of biological progression in posterior probabilities space, determine the "key-player" genes governing the transition dynamics, partition the trajectory into consecutive phases (transition "micro-states"), and finally reconstruct causal gene regulatory networks for each phase. Application of the end-to-end methodology provides new insights on key-player genes and their dynamic interactions during the important HSC-to-LMPP cell state transition involved in hematopoiesis. Moreover, it allows us to reconstruct a probabilistic representation of the “epigenetic landscape” of transitions and identify correctly the major ones in the hematopoiesis hierarchy of states.


2021 ◽  
Author(s):  
Ruben Boers ◽  
Joachim Boers ◽  
Beatrice Tan ◽  
Evelyne Wassenaar ◽  
Erlantz Gonzalez Sanchez ◽  
...  

AbstractCell state changes in development and disease are controlled by gene regulatory networks, the dynamics of which are difficult to track in real time. Here, we utilize an inducible DCM-RNA-polymerase-subunit-b fusion protein, to label active genes and enhancers with a bacterial methylation mark that does not affect gene transcription and is propagated in S-phase. We applied this DCM-time-machine (DCM-TM) technology to study intestinal homeostasis, following enterocyte differentiation back in time, revealing rapid and simultaneous activation of enhancers and nearby genes during intestinal stem cell (ISC) differentiation. We provide new insights in the absorptive-secretory lineage decision in ISC differentiation, and show that ISCs retain a unique chromatin landscape required to maintain ISC identity and delineate future expression of differentiation associated genes. DCM-TM has wide applicability in tracking cell states, providing new insights in the regulatory networks underlying cell state changes in development and differentiation.


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