ArticleNature communications2018
Single-cell variability in multicellular organisms.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Article
- Role of intercellular interactions on single cell and population level responses: considerations for multicellular bioreporter design.Frontiers in molecular biosciences · 2025Article
- Studying temporal dynamics of single cells: expression, lineage and regulatory networks.Biophysical reviews · 2024Review
- Inferring delays in partially observed gene regulation processes.Bioinformatics (Oxford, England) · 2023Article
- Voices carry.Nature chemical biology · 2023Article
- Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis.PLoS computational biology · 2022Article
- Evidence for close molecular proximity between reverting and undifferentiated cells.BMC biology · 2022Article
- Noise reduction by upstream open reading frames.Nature plants · 2022Article
- The macroscopic limit to synchronization of cellular clocks in single cells of Neurospora crassa.Scientific reports · 2022Article
- Hematopoietic differentiation is characterized by a transient peak of entropy at a single-cell level.BMC biology · 2022Article
- A single-cell resolved cell-cell communication model explains lineage commitment in hematopoiesis.Development (Cambridge, England) · 2021Article
- Single-Cell RNA Sequencing Reveals Cellular Heterogeneity and Stage Transition under Temperature Stress in Synchronized Plasmodium falciparum Cells.Microbiology spectrum · 2021Article
- Plant 3D genomics: the exploration and application of chromatin organization.The New phytologist · 2021Review
- Identifiability analysis for stochastic differential equation models in systems biology.Journal of the Royal Society, Interface · 2020Article
- Stochastic reaction networks in dynamic compartment populations.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Bayesian inference of distributed time delay in transcriptional and translational regulation.Bioinformatics (Oxford, England) · 2020Article
- Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting.PLoS computational biology · 2019Article
- Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.Bulletin of mathematical biology · 2019Review
- Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art.Journal of the Royal Society, Interface · 2019Article
- Application of the Transcriptional Disease Signature (TDSs) to Screen Melanoma-Effective Compounds in a Small Fish Model.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Noisy gene expression is of fundamental importance to single cells, and is therefore widely studied in single-celled organisms. Extending these studies to multicellular organisms is challenging since their cells are generally not isolated, but individuals in a tissue. Cell-cell coupling via signalling, active transport or pure diffusion, ensures that tissue-bound cells are neither fully independent of each other, nor an entirely homogeneous population. In this article, we show that increasing the strength of coupling between cells can either increase or decrease the single-cell variability (and, therefore, the heterogeneity of the tissue), depending on the statistical properties of the underlying genetic network. We confirm these predictions using spatial stochastic simulations of simple genetic networks, and experimental data from animal and plant tissues. The results suggest that cell-cell coupling may be one of several noise-control strategies employed by multicellular organisms, and highlight the need for a deeper understanding of multicellular behaviour.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.