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
{"title":"基因调控相互作用限制了基因表达的多样性","authors":"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","doi":"arxiv-2311.15503","DOIUrl":null,"url":null,"abstract":"The diversity of expressed genes plays a critical role in cellular\nspecialization, adaptation to environmental changes, and overall cell\nfunctionality. This diversity varies dramatically across cell types and is\norchestrated by intricate, dynamic, and cell type-specific gene regulatory\nnetworks (GRNs). Despite extensive research on GRNs, their governing\nprinciples, as well as the underlying forces that have shaped them, remain\nlargely unknown. Here, we investigated whether there is a tradeoff between the\ndiversity of expressed genes and the intensity of GRN interactions. We have\ndeveloped a computational framework that evaluates GRN interaction intensity\nfrom scRNA-seq data and used it to analyze simulated and real scRNA-seq data\ncollected from different tissues in humans, mice, fruit flies, and C. elegans.\nWe find a significant tradeoff between diversity and interaction intensity,\ndriven by stability constraints, where the GRN could be stable up to a critical\nlevel of complexity - a product of gene expression diversity and interaction\nintensity. Furthermore, we analyzed hematopoietic stem cell differentiation\ndata and find that the overall complexity of unstable transition states cells\nis higher than that of stem cells and fully differentiated cells. Our results\nsuggest that GRNs are shaped by stability constraints which limit the diversity\nof gene expression.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gene regulatory interactions limit the gene expression diversity\",\"authors\":\"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\",\"doi\":\"arxiv-2311.15503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The diversity of expressed genes plays a critical role in cellular\\nspecialization, adaptation to environmental changes, and overall cell\\nfunctionality. This diversity varies dramatically across cell types and is\\norchestrated by intricate, dynamic, and cell type-specific gene regulatory\\nnetworks (GRNs). Despite extensive research on GRNs, their governing\\nprinciples, as well as the underlying forces that have shaped them, remain\\nlargely unknown. Here, we investigated whether there is a tradeoff between the\\ndiversity of expressed genes and the intensity of GRN interactions. We have\\ndeveloped a computational framework that evaluates GRN interaction intensity\\nfrom scRNA-seq data and used it to analyze simulated and real scRNA-seq data\\ncollected from different tissues in humans, mice, fruit flies, and C. elegans.\\nWe find a significant tradeoff between diversity and interaction intensity,\\ndriven by stability constraints, where the GRN could be stable up to a critical\\nlevel of complexity - a product of gene expression diversity and interaction\\nintensity. Furthermore, we analyzed hematopoietic stem cell differentiation\\ndata and find that the overall complexity of unstable transition states cells\\nis higher than that of stem cells and fully differentiated cells. Our results\\nsuggest that GRNs are shaped by stability constraints which limit the diversity\\nof gene expression.\",\"PeriodicalId\":501321,\"journal\":{\"name\":\"arXiv - QuanBio - Cell Behavior\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Cell Behavior\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2311.15503\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Cell Behavior","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.15503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.