基因调控相互作用限制了基因表达的多样性

Orr LevyDepartment of Immunobiology, Yale University School of Medicine, New Haven, CT, USAHoward Hughes Medical Institute, Chevy Chase, MD, USA, Shubham TripathiYale Center for Systems and Engineering Immunology and Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA, Scott D. PopeDepartment of Immunobiology, Yale University School of Medicine, New Haven, CT, USAHoward Hughes Medical Institute, Chevy Chase, MD, USA, Yang Y. LiuChanning Division of Network Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, USACenter for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA, Ruslan MedzhitovDepartment of Immunobiology, Yale University School of Medicine, New Haven, CT, USAHoward Hughes Medical Institute, Chevy Chase, MD, USATananbaum Center for Theoretical and Analytical Human Biology, Yale University School of Medicine, New Haven, CT, USA
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引用次数: 0

摘要

表达基因的多样性在细胞特化、适应环境变化和整体细胞功能中起着至关重要的作用。这种多样性在不同的细胞类型中变化很大,并由复杂的、动态的和细胞类型特异性的基因调节网络(grn)协调。尽管对grn进行了广泛的研究,但它们的支配原理以及形成它们的潜在力量在很大程度上仍然未知。在这里,我们研究了表达基因的多样性和GRN相互作用的强度之间是否存在权衡。我们开发了一个计算框架,从scRNA-seq数据中评估GRN相互作用强度,并使用它来分析从人类、小鼠、果蝇和秀丽隐杆线虫的不同组织中收集的模拟和真实scRNA-seq数据。在稳定性约束的驱动下,我们发现了多样性和相互作用强度之间的重要权衡,其中GRN可以稳定到临界复杂性水平-基因表达多样性和相互作用强度的产物。此外,我们分析了造血干细胞分化数据,发现不稳定过渡状态细胞的总体复杂性高于干细胞和完全分化细胞。我们的研究结果表明,grn是由限制基因表达多样性的稳定性约束形成的。
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Gene regulatory interactions limit the gene expression diversity
The diversity of expressed genes plays a critical role in cellular specialization, adaptation to environmental changes, and overall cell functionality. This diversity varies dramatically across cell types and is orchestrated by intricate, dynamic, and cell type-specific gene regulatory networks (GRNs). Despite extensive research on GRNs, their governing principles, as well as the underlying forces that have shaped them, remain largely unknown. Here, we investigated whether there is a tradeoff between the diversity of expressed genes and the intensity of GRN interactions. We have developed a computational framework that evaluates GRN interaction intensity from scRNA-seq data and used it to analyze simulated and real scRNA-seq data collected from different tissues in humans, mice, fruit flies, and C. elegans. We find a significant tradeoff between diversity and interaction intensity, driven by stability constraints, where the GRN could be stable up to a critical level of complexity - a product of gene expression diversity and interaction intensity. Furthermore, we analyzed hematopoietic stem cell differentiation data and find that the overall complexity of unstable transition states cells is higher than that of stem cells and fully differentiated cells. Our results suggest that GRNs are shaped by stability constraints which limit the diversity of gene expression.
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