Next Article in Journal
Leakage Evaluation by Virtual Entropy Generation (VEG) Method
Next Article in Special Issue
Nonequilibrium Entropic Bounds for Darwinian Replicators
Previous Article in Journal / Special Issue
Remarks on the Maximum Entropy Principle with Application to the Maximum Entropy Theory of Ecology
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Entropy 2018, 20(1), 13; https://doi.org/10.3390/e20010013

Self-Organization of Genome Expression from Embryo to Terminal Cell Fate: Single-Cell Statistical Mechanics of Biological Regulation

1
Environment and Health Department, Istituto Superiore di Sanitá, 00161 Rome, Italy
2
SEIKO Life Science Laboratory, SRI, Osaka 540-659, Japan
3
Systems Biology Program, School of Media and Governance, Keio University, Fujisawa 252-0882, Japan
4
Faculty of Life and Medical Sciences, Doshisha University, Kyotanabe 610-0394, Japan
*
Author to whom correspondence should be addressed.
Received: 4 December 2017 / Revised: 19 December 2017 / Accepted: 20 December 2017 / Published: 28 December 2017
(This article belongs to the Special Issue Entropy and Its Applications across Disciplines)
View Full-Text   |   Download PDF [3139 KB, uploaded 2 January 2018]   |  

Abstract

A statistical mechanical mean-field approach to the temporal development of biological regulation provides a phenomenological, but basic description of the dynamical behavior of genome expression in terms of autonomous self-organization with a critical transition (Self-Organized Criticality: SOC). This approach reveals the basis of self-regulation/organization of genome expression, where the extreme complexity of living matter precludes any strict mechanistic approach. The self-organization in SOC involves two critical behaviors: scaling-divergent behavior (genome avalanche) and sandpile-type critical behavior. Genome avalanche patterns—competition between order (scaling) and disorder (divergence) reflect the opposite sequence of events characterizing the self-organization process in embryo development and helper T17 terminal cell differentiation, respectively. On the other hand, the temporal development of sandpile-type criticality (the degree of SOC control) in mouse embryo suggests the existence of an SOC control landscape with a critical transition state (i.e., the erasure of zygote-state criticality). This indicates that a phase transition of the mouse genome before and after reprogramming (immediately after the late 2-cell state) occurs through a dynamical change in a control parameter. This result provides a quantitative open-thermodynamic appreciation of the still largely qualitative notion of the epigenetic landscape. Our results suggest: (i) the existence of coherent waves of condensation/de-condensation in chromatin, which are transmitted across regions of different gene-expression levels along the genome; and (ii) essentially the same critical dynamics we observed for cell-differentiation processes exist in overall RNA expression during embryo development, which is particularly relevant because it gives further proof of SOC control of overall expression as a universal feature. View Full-Text
Keywords: early embryo development; reprogramming; single-cell differentiation; single-cell genome dynamics; self-organization; autonomous self-organized criticality; genome avalanche; statistical thermodynamics; critical transition state early embryo development; reprogramming; single-cell differentiation; single-cell genome dynamics; self-organization; autonomous self-organized criticality; genome avalanche; statistical thermodynamics; critical transition state
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Giuliani, A.; Tsuchiya, M.; Yoshikawa, K. Self-Organization of Genome Expression from Embryo to Terminal Cell Fate: Single-Cell Statistical Mechanics of Biological Regulation. Entropy 2018, 20, 13.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top